heat stroke research paper

• Open access
• Published: 22 May 2018
• Heat stroke
• Toru Hifumi 1 , 5 ,
• Yutaka Kondo 2 ,
• Keiki Shimizu 3 &
• Yasufumi Miyake 4  

Journal of Intensive Care volume  6 , Article number:  30 ( 2018 ) Cite this article

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Heat stroke is a life-threatening injury requiring neurocritical care; however, heat stroke has not been completely examined due to several possible reasons, such as no universally accepted definition or classification, and the occurrence of heat wave victims every few years. Thus, in this review, we elucidate the definition/classification, pathophysiology, and prognostic factors related to heat stroke and also summarize the results of current studies regarding the management of heat stroke, including the use of intravascular balloon catheter system, blood purification therapy, continuous electroencephalogram monitoring, and anticoagulation therapy.

Two systems for the definition/classification of heat stroke are available, namely Bouchama’s definition and the Japanese Association for Acute Medicine criteria. According to the detailed analysis of risk factors, prevention strategies for heat stroke, such as air conditioner use, are important. Moreover, hematological, cardiovascular, neurological, and renal dysfunctions on admission are associated with high mortality, which thus represent the potential targets for intensive and specific therapies for patients with heat stroke. No prospective, comparable study has confirmed the efficacy of intravascular cooling devices, anticoagulation, or blood purification in heat stroke.

The effectiveness of cooling devices, drugs, and therapies in heat stroke remains inconclusive. Further large studies are required to continue to evaluate these treatment strategies.

Heat stroke is a life-threatening injury requiring neurocritical care, and there have been at least 3332 deaths attributed to heat stroke from 2006 to 2010 in the USA [ 1 ]. Regarding heat stroke, 28-day and 2-year mortality rates have been reported to be 58 and 71%, respectively [ 2 ]. In addition, the number of deaths from heat stroke has been reported to increase due to climate change [ 1 ]. By the 2050s, heat stroke-related deaths are expected to rise by nearly 2.5 times the current annual baseline of approximately 2000 deaths [ 2 ].

Unfortunately, heat stroke has not been comprehensively examined due to several possible reasons. First, while sepsis, acute respiratory distress syndrome (ARDS), and acute kidney injury (AKI) include simple and commonly used definitions, no universally accepted definition of heat stroke exist in the clinical settings. Second, because a large number of heat stroke victims are uncommon in the USA or European countries (ex. 1995, and 1999 in Chicago, 2003 in Paris) [ 2 , 3 , 4 , 5 ], clinical research has not been continuously conducted in these regions.

Several review articles regarding heat stroke focusing on critical care have been published in the early 2000s [ 6 , 7 ]; moreover, additional new devise for cooling, blood purification therapy for renal/hepatic failure, continuous electroencephalogram (cEEG) monitoring, and the use of drugs, such as anticoagulants, for treating heat stroke have become readily available, and substantive clinical research regarding such devises/drugs has been published in the 2010s [ 8 , 9 , 10 , 11 , 12 , 13 ].

Thus, in the current review, we elucidate the definition/classification, pathophysiology, and prognostic factors associated with heat stroke and also summarize the results of current studies regarding the management of heat stroke, including the use of intravascular balloon catheter systems, blood purification therapy, cEEG monitoring, and anticoagulants.

Definition and classification of heat stroke

Historically, heat stroke has been classified into two groups according to the presence or absence of exertion. Exertional heat stroke develops in able-bodied individuals, such as athletes, soldiers, or laborers, and performing rigorous physical activities [ 1 ]. In contrast, nonexertional heat stroke can develop during low-level physical activities among elderly, ambulatory individuals with comorbidities including obesity, diabetes, hypertension, heart disease, renal disease, dementia, and alcoholism [ 1 ].

To date, no universally accepted definition of heat stroke exists. The most commonly used definition of heat stroke worldwide is the Bouchama’s definition [ 6 ]. Bouchama has defined heat stroke as a core body temperature that rises above 40 °C, accompanied by hot dry skin and central nervous system abnormalities, such as delirium, convulsions, or coma. Heat stroke results from exposure to a high environmental temperature or from strenuous exercise [ 6 ]. Bouchama has also proposed an alternative definition of heat stroke on the basis of its pathophysiology, stating that heat stroke is a form of hyperthermia associated with a systemic inflammatory response that leads to a syndrome of multiorgan dysfunction, predominantly encephalopathy [ 6 ].

Pease et al. have reported an unusual heat wave that lasted 9 days in France in 2003 [ 14 ] and referred to the following criteria according to the Bouchama’s definition: the alteration of mental status (coma, delirium, disorientation, or seizures); a body core temperature of > 40.6 °C or a documented evidence of cooling before the first record temperature; a reliable history of compatible environmental exposure; and the presence of hot, dry, or flushed skin. In another study, Misset et al. defined heat stroke as “the presence of hyperthermia of >40.5°C” [ 15 ], but the phrase “core body temperature” was not included in their definition. Consequently, specific body temperature and the use of phrase “core body temperature” vary across studies.

In Japan, the Japanese Association for Acute Medicine (JAAM) has collected data through a nationwide heat-related illness registry of patients diagnosed as having heat-related illnesses (including heat stroke) regardless of the core body temperature since 2006 [ 16 , 17 ]. The JAAM has established and published the criteria for heat-related illnesses, including heat stroke, in 2014 [ 18 ] (Fig.  1 ).

Japanese Association of Acute Medicine Heat-Related Illness criteria. DIC, disseminated intravascular coagulation; JCS, Japan Coma Scale

Heat stroke was defined as patients exposed to high environmental temperature who met one or more of the following criteria:

Central nervous system manifestation (impaired consciousness with a Japan Coma Scale score of ≥ 2 [ 19 ], cerebellar symptoms, convulsions, or seizures);

Hepatic/renal dysfunction (follow-up following admission to hospital, hepatic or renal impairment requiring inpatient hospital care);

Coagulation disorder [diagnosed as disseminated intravascular coagulation (DIC) by the JAAM] [ 20 , 21 ].

Apparently, the body temperature was not included in these diagnostic criteria because of several fatal cases of patients whose body temperatures were below 40 °C that were observed in clinical practice [ 22 ].

In 2016, the JAAM Heat Stroke (JAAM-HS) Committee launched a working group (JAAM-HS-WG) to analyze the collected megadata regarding heat-related illnesses. The JAAM-HS-WG further simplified the heat stroke classification [ 22 ]. The modified JAAM heat stroke definition included patients exposed to high environmental temperature and meeting at least one of the following criteria:

Glasgow Coma Scale (GCS) score of ≤ 14,

Creatinine or total bilirubin levels of ≥ 1.2 mg/dL,

JAAM DIC score of ≥ 4.

The difference between the definitions/classifications of heat stroke among Bouchama’s definition and the JAAM and JAAM-HS-WG criteria is summarized in Table  1 .

Pathogenesis

Thermoregulation.

A normal body temperature is maintained at approximately 37 °C by the anterior hypothalamus through the process of thermoregulation [ 23 , 24 ]. Several mechanisms related to sweating, such as vaporization, radiation, convection, and conduction, function to cool the body surface [ 25 ]. As the body temperature increases, active sympathetic cutaneous vasodilation increases blood flow in the skin and initiates thermal sweating [ 26 , 27 ]. Cutaneous vasodilation causes a relative reduction in intravascular volume, leading to heat syncope [ 28 ]. The loss of salts and water through sweat induces dehydration and salt depletion, which are associated with heat exhaustion and cramps unless appropriate supplementations of water and salt are initiated [ 28 ]. Further loss of salt and water impairs thermoregulation followed by the reduction of visceral perfusion due to shunt from the central circulation to the skin and muscles, resulting in organ failure [ 6 , 28 , 29 ]. Therefore, heat stroke is a condition of multiple organ failure caused by hot environment.

Heat shock response

Heat shock proteins (HSP) are a family of proteins produced by nearly all cells in response to stressful conditions, including heat shock as well as other stresses, such as exposure to cold and ultraviolet light [ 6 , 30 ]. Increased levels of HSPs, such as HSP70, are necessary for acquired heat tolerance. Moreover, the overexpression of HSP70 in response to heat stress can protect against organ dysfunction and reduces mortality in rats [ 30 ].

Pathophysiology

Hyperthermia due to passive heat exposure facilitates the leakage of endotoxin from the intestinal mucosa to the systemic circulation as well as the movement of interleukin (IL)-1 or IL-6 proteins from the muscles to the systemic circulation [ 31 ]. This causes an excess activation of leukocytes and endothelial cells manifested by the release of various cytokines and high-mobility group box 1 protein (HMGB1), which is a prototypic alarmin (endogenous molecules that signal tissue and cellular damage). Together, these processes cause the systemic inflammatory response syndrome [ 6 , 32 , 33 ].

The inflammatory and coagulation responses to heat stroke, together with direct cytotoxic effects of heat, injure the vascular endothelium, causing microthromboses [ 6 ]. Platelet counts decrease because of microthrombosis, the secondary consumption of platelets, and hyperthermia-induced platelet aggregation. Heat stroke also suppresses platelet release from bone marrow due to megakaryocyte susceptibility to high temperature exposures. Heat stroke-induced coagulation activation and fibrin formation clinically manifest DIC.

Prognostic factors

As mentioned above, because the definition of heat stroke varies across studies, detailed examinations, rather than mere results, are required to understand these study findings (Table  2 ).

Patients exposed to the August 2003 heat wave in Paris were examined to identify the prognostic factors, and several studies examining different populations have been published. Hausfater et al. have examined all patients who developed the core temperatures of > 38.5 °C, who were admitted to one of the emergency departments during the August 2003 heat wave in Paris. Previous treatment with diuretics, living in an institution, age > 80 years, the presence of cardiac disease or cancer, core temperature > 40 °C, systolic arterial pressure < 100 mmHg, GSC scale < 12, and transportation to hospital in ambulance were identified as prognostic factors associated with death for nonexertional heatstroke [ 34 ]. Argaud et al. examined long-term outcome in 83 patients with nonexertional heatstroke resulting from the August 2003 heat wave in Paris and having core temperatures > 40 °C. Multivariate cox proportional hazard model analysis revealed an independent contribution to 2-year mortality if patients were staying at an institution (hazard ratio (HR), 1.98; 95% confidence interval (CI), 1.05–3.71), if they used long-term antihypertensive medications (HR, 2.17; 95% CI, 1.17–4.05), or if they presented with anuria (HR, 5.24; 95% CI, 2.29–12.03), coma (HR, 2.95; 95% CI, 1.26–6.91), or cardiovascular failure (HR, 2.43; 95%CI, 1.14–5.17) at admission [ 2 ]. Misset et al. have conducted a questionnaire survey and a multivariate analysis, wherein the occurrence of heatstroke at home or in a healthcare facility (vs. in a public area), high Simplified Acute Physiology Score (SAPS) II score [ 35 ], initial high body temperature, prolonged prothrombin time, the use of vasoactive drugs within the first day in intensive care unit (ICU), and patient management in an ICU without air conditioning were independently associated with an increased risk of hospital death [ 15 ].

Tsuruta et al. have examined 77 mechanically ventilated patients with heat-related illnesses who met the JAAM-HS criteria. Their systolic blood pressure (SBP) and SpO2 at scene and arterial base excess were identified as independent risk factors for poor outcomes (death and with sequelae).

Hifumi et al. have examined 705 patients who met the JAAM-HS-WG criteria for heat stroke and observed that the hospital mortality was 7.1% (50 patients) [ 22 ]. Multiple regression analysis revealed that hospital mortality was significantly associated with SBP (odds ratio (OR), 0.99; 95% CI, 0.98–0.99; p  = 0.026), GCS score (OR, 0.77; 95% CI, 0.69–0.86; p  < 0.01), serum creatinine levels (OR, 1.28; 95% CI, 1.02–1.61; p  = 0.032), and the presence of DIC on admission (OR, 2.16; 95% CI, 1.09–4.27; p  = 0.028) [ 22 ].

According to the detailed analysis of risk factors, careful attention should be paid for the prevention of heat stroke in patients living in a healthcare facility, aged > 80 years, and previously treated with diuretics. Moreover, because hematological, cardiovascular, neurological, and renal dysfunctions on admission are associated with high mortality, these dysfunctions represent potential targets for intensive and specific therapies for patients with heat stroke.

Heat stroke progresses to multiorgan dysfunction syndrome; therefore, rapid, effective cooling followed by close monitoring and specific treatment for injured organs are fundamental to treatment success.

Initial cooling

Target temperature of initial cooling.

There is no evidence to support a specific temperature end point; however, a rectal temperature of 39.4 °C has been used in large series and has been proven to be safe [ 6 ].

Initial cooling method

To date, several cooling methods are available in the clinical settings, including immersion [ 36 ], evaporation [ 37 ], and the use of cold water bladders, gastric and rectal lavage [ 38 ], and noninvasive cooling systems [ 39 ]. However, there is no evidence supporting the superiority of any one cooling method for patients with heat stroke [ 6 ]. An intravascular balloon catheter system has been approved in the USA for therapeutic core cooling and rewarming in humans during or following cardiac or neurological surgery and following stroke [ 40 ]. However, a few cases have reported the use of intravascular cooling for heat stroke [ 41 , 42 ]. Hamaya et al. have reported for the first time a good recovery in a case of severe heat stroke, followed by multiple organ dysfunction, which was successfully treated through initial intravascular cooling [ 12 ]. In this case, at an average rate of 0.1 °C/min, the core temperature of the patient’s body reached 38.8 °C after just 17 min. Yokobori et al. have conducted a prospective study examining the feasibility and safety of a convection-based intravascular cooling device (IVC) in patients with severe heat stroke. Comparison between IVC plus conventional cooling (CC) and CC was made in patients with severe heat stroke. The IVC group showed a significant decrease in the Sequential Organ Failure Assessment score during the first 24 h (from 5.0 to 2.0, P  = 0.02). Moreover, all patients in the IVC group ( N  = 9) experienced favorable outcomes defined as modified Rankin scale score of 0–2 at discharge and at 30 days after the admission. Their findings indicate that accurate temperature management may prevent organ failure and produce better neurological outcomes. The Fukuoka University Hospital group has used extracorporeal circulation with hemodiafiltration circuits for cooling patients with severe heat stroke and has reported improved cooling efficiency [ 43 ]. To date, there have been no prospective, comparative studies confirming the superiority of the initial cooling method. Intravascular balloon catheter system does not result in cutaneous vasoconstriction as external cooling does, but it requires the placement of cooling balloon.

Management for organ dysfunctions in ICU

Central nervous system dysfunction.

Nakamura et al. have examined central nervous system sequelae of heat-related illnesses and have observed that 22 of 1441 cases (1.5%) exhibited the central nervous system sequelae of heat-related illnesses. Heatstroke patients presenting with lower GCS scores and higher body temperatures at admission were more likely to experience central nervous system sequelae and required longer cooling times to achieve the target body temperature. Therefore, rapid cooling followed by neuromonitoring might be associated with the neurological sequelae of heat stroke.

Recently, Hachiya et al. have reported the usefulness of cEEG in patients with severe heat stroke complicated with multiorgan failure [ 13 ]. The patients developed a persistent disturbance of consciousness; therefore, cEEG monitoring was applied. cEEG monitoring confirmed triphasic waves, which indicated hepatic failure as the cause of the persistent disturbance of consciousness. The patient’s condition improved following an artificial liver support therapy [ 13 ]. Thus, no prospective, comparable study has revealed the adequate neuromonitoring and the effect of temperature control on central nervous system.

Coagulation disorder

Anticoagulation therapy.

Antithrombin: Pachlaner et al. have reported good recovery in a patient with near-fatal heat stroke treated with type III antithrombin (AT-III) [ 44 ]. On admission, although the patient’s AT-III activity was 98%, a treatment with AT-III concentrate was initiated within 24 h due to DIC, which was aimed toward achieving supranormal plasma concentrations. Plasma AT concentrations were maintained at > 120% by continuous intravenous supplementation [ 44 ]. Additionally, in a rat model of heat stroke, AT-III treatment decreased serum cytokines (IL-1 β, tumor necrosis factor-α, and IL-6), and HMGB1 [ 45 ]. Thus, prospective studies will be needed to confirm the efficacy of AT-III supplementation in improving the clinical outcome of heat stroke.

Thrombomodulin (TM): Recombinant soluble thrombomodulin α (rTM), which is currently under phase III clinical trials for use in patients with severe sepsis, could also be a candidate for the treatment of heat stroke-induced DIC [ 46 ] because it serves as a negative feedback regulator of blood coagulation [ 47 ]. In basic research, rTM prevents heat stroke by inhibiting HMGB1 [ 48 ]. Sakurai et al. have reported (in Japanese) two cases of good recovery from heatstroke-induced DIC, which were successfully treated with TM administration [ 49 ]. Prospective studies will be needed to confirm the efficacy of rTM.

Hepatic/renal dysfunction

• Blood purification therapy

Blood purification therapy has not been discussed in the two previously reported review articles; however, good recovery cases have been reported in Japan [ 6 , 7 ].

Ikeda et al. have reported three cases of survival following multiorgan failure secondary to heat stroke that was treated with blood purification therapy, including continuous venovenous hemofiltration and plasma exchange (PE) [ 8 ]. Blood purification therapy removes proinflammatory cytokines related to heat stroke [ 8 ]. Chen et al. have conducted a retrospective study including 33 patients with severe exertional heat stroke and have compared clinical effects of continuous renal replacement therapy (CRRT) and routine therapy in these patients. They reported significantly lower 30-day mortality in the CRRT group than in the control group (15.2% vs.45.5%, p  = 0.029) although initial APACHE II scores in both groups were similar [ 10 ].

Recently, Inoue et al. have reported a case of severe exertional heat stroke with multiple organ failure that was successfully treated with continuous plasma diafiltration (PDF) [ 11 ]. PDF is a blood purification therapy in which PE is performed using a selective membrane plasma separator while the dialysate flows outside the hollow fibers. This separator has a small pore size (0.01 mm) and a sieving coefficient of 0.3 for albumin, which can selectively remove low- or intermediate-molecular weight albumin-bound substances [ 50 , 51 , 52 ].

In the clinical practice, decisions to continue blood purification therapy are difficult because this therapy is time-consuming and costly. Yonemitsu et al. have published a case report and literature review of cases of heat stroke treated with blood purification therapy [ 53 ]. The review includes several survival cases treated more than three times with PE; therefore, withdraw therapy following only a few trials. No prospective, comparable study has confirmed the efficacy of blood purification in heat stroke.

Cardiovascular dysfunction

Hart et al. have observed that supplementary vasoactive agents necessary to elevate blood pressure were associated with both high mortality rates and neurologic disability in patients with heat stroke [ 54 ]. Misset et al. have demonstrated that the use of vasoactive drugs within the first 24 h of admission to ICU was an independent factor associated with mortality. These findings suggest a close association between hypotension and poor outcomes. To date, no prospective, comparable study has confirmed the efficacy of targeted fluid administration or specific vasoactive drugs in heat stroke.

It would be acceptable to consider prevention, rather than the treatment of organ dysfunctions, because therapeutic options for organ dysfunction are rather limited even in the late 2010s, as described above. Nonetheless, heat-related deaths and illnesses are preventable [ 6 , 55 ]. Heat stroke prevention strategies, such as using air conditioner; limiting outdoor activities during the daytime; consuming ample fluids; wearing loose-fitting light-colored clothing, being aware of medication side effects that may cause fluid losses, decrease sweating, or decreased heart rate; and never leaving impaired adults or children in a car unattended, are important [ 55 ]. Centers for Disease Control and Prevention has uploaded a video titled “ How to Stay Cool in Extreme Heat” to YouTube [ 56 ].

Conclusions

In the present review, we elucidated the clinical diagnosis of heat stroke. Regarding the definition/classification of heat stroke, the Bouchama’s definition and the JAAM criteria are the two available systems. Intravascular cooling devises provided rapid cooling in the small number of heat stroke patients. Although few case reports and retrospective case-series for the use of anticoagulation and blood purification therapies have been reported, particularly in Japan, no prospective, comparative study has been conducted to date. Further large studies are warranted to evaluate these treatment strategies among patients with heat stroke.

Abbreviations

Acute Kidney Injury

Acute Respiratory Distress Syndrome

Conventional cooling

Continuous Electroencephalogram

Continuous Renal Replacement Therapy

Disseminated Intravascular Coagulation

Glasgow Coma Scale

High-mobility group box 1

Heat shock proteins

Intensive care unit

Convection-based intravascular cooling device

Japanese Association for Acute Medicine

Japanese Association of Acute Medicine heat stroke committee working group

Japan Coma Scale

Plasma diafiltration

Plasma exchange

Simplified Acute Physiology Score II score

Systolic blood pressure

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How to Stay Cool in Extreme Heat [ https://www.cdc.gov/disasters/extremeheat/how_to_stay_cool_video.html ].

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Emergency Medical Center, Kagawa University Hospital, 1750-1 Ikenobe, Miki, Kita, Kagawa, 761-0793, Japan

Toru Hifumi

Department of Emergency and Critical Care Medicine, Juntendo University, Urayasu Hospital, 2-1-1 Tomioka,Urayasu-shi, Chiba, 279-0021, Japan

Yutaka Kondo

Emergency and Critical Care Center, Tokyo Metropolitan Tama Medical Centre, 2-8-29 Musashidai, Fuchu-shi, Tokyo, 183-8524, Japan

Keiki Shimizu

Department of Emergency Medicine, Teikyo University School of Medicine, 2-11-1 Kaga, Itabashi-Ku, Tokyo, 173-8606, Japan

Yasufumi Miyake

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TH wrote the manuscript. YK, KS, and YM revised and edited the manuscript. All authors read and approved the final manuscript.

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• Anticoagulation
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Research progress of heat stroke during 1989-2019: a bibliometric analysis

Affiliations.

• 1 Department of Emergency, Changhai Hospital, the Naval Medical University, Shanghai, 200433, China.
• 2 Nursing College, The Naval Medical University, Shanghai, 200433, China.
• 3 Department of Clinical Medicine, The Naval Medical University, Shanghai, 200433, China.
• 4 Department of Intensive Care Unit, General Hospital of Southern Theater Command, Guangzhou, 510010, China.
• 5 Department of Emergency, Changhai Hospital, the Naval Medical University, Shanghai, 200433, China. [email protected].
• PMID: 33472705
• PMCID: PMC7818934
• DOI: 10.1186/s40779-021-00300-z

Background: Heat stroke (HS) is an acute physical disorder that is associated with a high risk of organ dysfunction and even death. HS patients are usually treated symptomatically and conservatively; however, there remains a lack of specific and effective drugs in clinical practice. An analysis of publication contributions from institutions, journals and authors in different countries/regions was used to study research progress and trends regarding HS.

Methods: We extracted all relevant publications on HS between 1989 and 2019 from Web of Science. Using the Statistical Package for Social Science (SPSS, version 24) and the software GraphPad Prism 8, graphs were generated and statistical analyses were performed, while VOSviewer software was employed to visualize the research trends in HS from the perspectives of co-occurring keywords.

Results: As of April 14, 2020, we identified 1443 publications with a citation frequency of 5216. The United States accounted for the largest number of publications (36.2%) and the highest number of citations (14,410), as well as the highest H-index at 74. Although the sum of publications from China ranked second, there was a contradiction between the quantity and quality of publications. Furthermore, Medicine & Science in Sports & Exercise published the most papers related to HS, with Lin MT publishing the most papers in this field (112), while the review by Knochel JP received the highest citation frequency at 969. The keyword heat-stress appeared most recently, with an average appearing year of 2015.5. In the clinical research cluster, exertional heat-stroke was determined to be the hotspot, while ambient-temperature and heat waves were the new trends in the epidemiological research cluster.

Conclusions: Corresponding to this important field, while the contributions of the publications from the United States were significant, the mismatch between the quantity and quality of publications from China must be examined. Moreover, it is hypothesized that clinical and epidemiological studies may become hotspots in the near future.

Keywords: Citation frequency; Heat stroke; Publications.

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• Historical Article
• Research Support, Non-U.S. Gov't
• Bibliometrics
• Heat Stroke / history
• Heat Stroke / therapy*
• History, 20th Century
• History, 21st Century

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Heat Stroke

• Medical News & Perspectives Why Farmworkers Need More Than New Laws for Protection From Heat-Related Illness Bridget M. Kuehn, MSJ JAMA

Heat stroke is the most dangerous heat-related illness, and it can be fatal.

Two characteristics define heat stroke: a core body temperature greater than 104°F (40°C) and neurological signs such as confusion, seizures, or loss of consciousness.

Some of the first cells in the body to be affected are in the brain. These cells are sensitive to temperature changes. The heart also must work harder to push blood to the skin. As a person’s temperature gets closer to the air temperature, the rate of heat transferred to the skin decreases. Evaporation of sweat also decreases with higher humidity. Sweating leads to further dehydration and loss of electrolytes and minerals vital for muscle and nerve cell function. As the body is no longer able to cool itself by sweating, heart rate and breathing increase to compensate. This can be aggravated by medications that alter heart function or by chronic diseases.

Classic heat stroke is seen in people who are exposed to a hot environment, especially in young and elderly persons. Those with chronic diseases such as Parkinson disease, heart failure, or diabetes or who take medications can have a decreased response to dehydration. Exertional heat stroke is seen in healthy people who undergo strenuous activity in hot weather, such as marathon runners, military trainees, and football players.

Schedule outdoor activities during cool times of the day.

Drink plenty of fluids. Avoid drinks with too much sugar or alcohol, which can cause dehydration.

Wear loose-fitting, light-colored clothing.

Acclimate to new hot environments, over many days if possible.

Be aware of medication side effects. If taking medications, be aware of those that may cause fluid losses, decrease sweating, or slow the heart rate. Common medications include those used for depression, blood pressure and heart disease, and coughs and colds.

Never leave an impaired adult or a child in a car unattended.

If you see these signs of heat stroke, call 911 immediately: core body temperature over 104°F; rapid heart rate; rapid breathing; flushed, hot skin; nausea and vomiting; or mental status changes (headache, confusion, slurring of words, seizures, or coma).

Follow these steps while waiting for emergency personnel:

Move the individual out of the heat.

Remove clothing to promote cooling.

Position the person on his or her side to minimize aspiration.

Immerse the individual in cold water or apply cold, wet cloths or ice packs to the skin (neck, armpit, and groin areas, where large blood vessels are located) to lower the body temperature.

Continue cooling the individual until the body temperature reaches 101°F to 102°F (38.4°C to 39°C).

Do not give any fluids to the person because it is not safe to drink during an altered level of consciousness. If the person is alert and requests water, give small sips.

Avoid aspirin and acetaminophen; they do not help with cooling.

Despite aggressive medical care, heat stroke can damage multiple organs in the body, including the brain, liver, kidneys, and muscles (muscle breakdown or rhabdomyolysis ). It can leave affected individuals with permanent neurological damage and, if not treated early, can cause death.

For More Information

Centers for Disease Control and Prevention https://www.cdc.gov/disasters/extremeheat/index.html

MedlinePlus https://medlineplus.gov/ency/article/000056.htm

Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.

Source: Bobb JF, Obermeyer Z, Wang Y, Dominici F. JAMA . 2014;312(24):2659.

Topic: Environmental Health

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Peiris AN , Jaroudi S , Noor R. Heat Stroke. JAMA. 2017;318(24):2503. doi:10.1001/jama.2017.18780

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• Published: 20 October 2016

A bibliometric analysis of exertional heat stroke research in Web of Science

• Zhi Mao 1 ,
• Chao Liu 1 ,
• Shuo Chen 2 ,
• Zheng-Guo Zhu 3 ,
• Hong-Jun Kang 1 &
• Fei-Hu Zhou   ORCID: orcid.org/0000-0001-6154-013X 1  

Military Medical Research volume  3 , Article number:  31 ( 2016 ) Cite this article

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Metrics details

Exertional heat stroke is a fatal condition and remains a health problem. This paper evaluates the publication trend regarding exertional heat stroke research between 1996 and 2015 using a bibliometric method.

Articles regarding exertional heat stroke research published between 1996 and December 2015 were searched for in the SCI-EXPANDED database of Web of Science. The search results were analyzed with regard to publication year; publication quantity regarding countries/regions, and authors; citation frequency; and journal distribution. CiteSpace (v3.6) was used for a document co-citation visualization analysis.

In total, 289 publications on heat stroke were located. After selection, 209 original articles conducted across 28 countries/regions and published in 83 journals were included in the analysis. The USA, Isreal, and France were the most common locations for exertional heat stroke studies. The CiteSpace visualization cluster analysis showed that exertional heat stroke-related mortality and protective measures were constant concerns of research.

Conclusions

Research related to exertional heat stroke has been continuous concerned. USA is still the leading country in this field.

Heat stroke is a severe and fatal condition clinically characterized by a severe rise in core body temperature (often >40 °C), with concomitant central nervous system dysfunctions such as delirium, convulsions, epilepsy, and coma [ 1 ]. Heat stroke is primarily classified into classic heat stroke and exertional heat stroke. The latter is particularly encountered during modern warfare and military training. Over the past few decades, the incidence of exertional heat stroke has significantly increased. According to data from the US Centers for Disease Control and Prevention, 7,000 cases of heat stroke death occurred in the US between 1979 and 1997 [ 2 ]. Along with the change in global climate, the progress of urbanization, and the extension of life expectancy, exertional heat stroke is expected to remain a health problem that cannot be ignored [ 3 ]. The most common treatment for exertional heat stroke is rapid cooling to promptly lower body temperature to normal. This strategy can reduce the risk of organ damage [ 4 ]. Despite effective cooling, numerous patients suffer from multiple organ failure, disability, and even death following active cooling treatment. Several studies related to exertional heat stroke have been published over the last few decades [ 1 – 3 ]. However, many problems remain to be addressed regarding the pathogenesis, prevention, and treatment of exertional heat stroke [ 3 ]. Bibliometric analysis is a wildly used method to evaluate the publication trend on a special topic [ 5 ].

Although many papers investigated exertional heat stroke, reports are still currently lacking regarding the trend of exertional heat stroke publications. We aimed to employ a bibliometric method to analyze the trend of exertional heat stroke publication in the latest twenty years.

This trend analysis was performed using the Web of Science database with regard to publication quantity, country/region, institution, author, journal, and so on. The co-citation patterns were visualized to provide evidence for relevant clinics and research.

Data source and retrieval

The SCI-EXPANDED database of Web of Science was searched, and the last search occurred on June 14, 2016. The search terms “heat stroke” or “heatstroke” and “exertional” were used to create the following search queries: (topic = “heat stroke”) OR (topic = heatstroke)) AND “exertional”. The time span was set to between 1996 and 2015. The publication type was not limited, and “article” was selected for an in-depth analysis.

Statistical analyses

Histcite 12.03.07 (Thomson Reuters) was used for the descriptive analysis. A bibliometric method was used to quantitatively describe the published articles regarding year of publication; publication quantity, including country/region, institution, and author; citation frequency; and journal distribution. A citation map was generated. The co-citation visualization analysis was performed using CiteSpace 3.6.

Selection of articles

Using the search queries, 289 publications were searched, including 209 original articles, 37 reviews, 11 editorials, 10 meeting abstracts, 10 letters, 8 proceedings papers, 4 corrections. Based on the selection criteria, 80 non-original articles were excluded, and 209 original articles related to exertional heat stroke were included in the analysis.

Distribution of articles by publication years

The quantity of published articles on exertional heat stroke showed an overall trend by year, which rose from 12 in 1996 to 31 in 2015 (Table  1 ).

Distribution of articles by countries and regions

The 209 articles originated from 28 countries and regions. The USA, Isreal, France, Mainland China and Taiwan, and UK were the most common locations for publishing articles on exertional heat stroke (Table  2 ). USA is the leading country during the twenty years in publishing articles on exertional heat stroke.

Distribution of articles by authors

The 209 articles were written by 803 authors in total. The top 10 authors publishing articles on exertional heat stroke primarily came from the US and Israel (Table  3 ). Casa DJ from the University Connecticut of USA published the most articles (20 records) and accounted for 9.6 % of all published articles. Casa DJ published the first article on exertional heat stroke in 2005 [ 6 ]; the most recent research on exertional heat stroke was published in 2015 [ 7 ].

Distribution of articles by journals

The 209 articles were published across 105 journals. The top 10 journals published 83 articles on heat stroke and accounted for 32.9 % of all articles included in this study (Table  4 ). The JOURNAL OF ATHLETIC TRAINING published the most articles (16). Ellis A published the most frequently cited article in Gut in 1996 which was referenced 102 times [ 8 ].

Citation map

One of the core documents cited was published by Epstein Y in 1999, titled “Exertional heat stroke: a case series” [ 9 ]. Another core document cited was published by Smith JE in 2005, titled “Cooling methods used in the treatment of exertional heat illness” [ 10 ] (Fig.  1 ).

A citation map, with Ref 9 and Ref 10 as core documents

Analysis of time-frequency of key words

The time frequency of the keywords was obtained via a co-citation analysis using CiteSpace (Fig.  2 ). The core documents co-cited were subject to a cluster analysis (Table  5 ). Fifteen categories were generated in the cluster analysis, with the following nine major categories: “fulminant hepatic failure”, “contribution”, “near-fatal exertional heat stroke”, “plasma beta-endorphin concentration”, “marine corp”, “suspected heat illness”, “distance”, “air force”, and “energy metabolism” et al. In this figure, the timeline of clusters labeled using keywords is shown horizontally. The earliest concern was “marine corp”.

Timeline for the keyword analysis of the document co-citation clustering

According to classical bibliometric theory, increases or decreases in the number of scientific research publications indicate the speed of scientific/technological development. The present study shows that the number of published research articles on exertional heat stroke between 1996 and 2015. These publications indicate several findings. First, heat stroke research has been of continuous concern. Second, environmental heat damage, sports heat damage, and military action training heat damage remain problems that cannot be ignored. Finally, many problems have yet to be solved regarding the diagnosis, treatment, and prognosis of heat stroke.

With regard to distribution by country/region, US and Israel are the two leading countries. Mainland China published the most articles on heat stroke ranking No.4. Previous bibliometric studies in other fields have also found a sharp increase in the number of research articles from Mainland China, exceeding Hong Kong and Taiwan [ 11 – 13 ] and ranking second only to the US [ 14 ]. The continuous research progress in the number of published articles on exertional heat stroke demonstrates the overall improvements in critical care medicine, sports medicine, and military medicine in the output country.

With respect to journal distribution, the top 10 journals publishing articles on exertional heat stroke were all specialist publications, and none were comprehensive. On one hand, this evidence indicates that exertional heat stroke research is relatively esoteric. Most of these top 10 journals were classified as quartile 2 or 3 SCI publications. These journals mainly focus on Sport Science or Military Medicine. Although impact factor has been extensively used to evaluate the quality of research published [ 15 ], its value has always been questioned. Professor Alberts, the editor-in-chief of Science , the top journal in the sciences, recently published an editorial stating that impact factor has led to abnormalities in the research evaluation system [ 16 ]. Moreover, high impact factor journals occasionally publish low-quality research. Therefore, we did not analyze or discuss impact factor in the present study.

Recently, an increasing number of bibliometric analyses have emerged in medicine [ 11 – 13 , 17 – 20 ] and have demonstrated significant value [ 21 ]. Previous analyses have shown that the number of published articles grew rapidly in certain countries that are emerging in scientific research, which reduced the share of articles from traditional research powers in Europe and the US [ 22 ]. A 2010 study showed that 100 classic publications in Bone Science were primarily from the UK and the US [ 23 ]. The authors of that study predicted that China would reverse this situation and establish a new balance in the near future [ 21 ]. As the present study revealed, this trend has begun to show in heat stroke research. Furthermore, we performed a visualization cluster analysis of co-cited documents on heat stroke and listed core documents in these clusters.

The present study has a few limitations. For example, to perform the citation analysis, we only searched the SCI database and not the Medline or Embase databases. However, we are certain that the SCI database generally includes all mainstream documents in the natural sciences.

In summary, the research evidence gained continous attention in exertional heat stroke-related fields. USA is the dominated country in this field.

Abbreviations

Science Citation Index

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All data generated or analyzed during this study are included in this published article [and its supplementary information files].

Authors’ contributions

ZM and CL contributed equally to this work. ZM and CL conceived the study, participated in the design, collected the data, performed statistical analyses, and drafted the manuscript. SC performed statistical analyses, and helped to draft the manuscript. ZGZ and HJK revised the manuscript critically for important intellectual content. FHZ performed statistical analyses, helped to revise the manuscript critically for important intellectual content. All authors read and approved the final manuscript.

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The authors declare that they have no competing interests.

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Department of Critical Care Medicine, Chinese PLA General Hospital, Beijing, 100853, China

Zhi Mao, Chao Liu, Hong-Jun Kang & Fei-Hu Zhou

Department of Medical Information, Chinese PLA General Hospital, Beijing, 100853, China

Department of Orthopedics, Chinese PLA General Hospital, Beijing, 100853, China

Zheng-Guo Zhu

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Correspondence to Fei-Hu Zhou .

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Mao, Z., Liu, C., Chen, S. et al. A bibliometric analysis of exertional heat stroke research in Web of Science. Military Med Res 3 , 31 (2016). https://doi.org/10.1186/s40779-016-0101-6

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Received : 24 March 2016

Accepted : 10 October 2016

Published : 20 October 2016

DOI : https://doi.org/10.1186/s40779-016-0101-6

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• Volume 1, Issue 1
• Exertional heat stroke: pathophysiology and risk factors
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• Christian K Garcia 1 ,
• Liliana I Renteria 2 ,
• Gabriel Leite-Santos 2 ,
• Lisa R Leon 1 and
• http://orcid.org/0000-0003-2768-1427 Orlando Laitano 1
• 1 Department of Applied Physiology and Kinesiology , University of Florida , Gainesville , FL , USA
• 2 Department of Nutrition and Integrative Physiology , Florida State University , Tallahassee , FL , USA
• Correspondence to Dr Orlando Laitano, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA; orlando.laitano{at}UFL.edu

Exertional heat stroke, the third leading cause of mortality in athletes during physical activity, is the most severe manifestation of exertional heat illnesses. Exertional heat stroke is characterised by central nervous system dysfunction in people with hyperthermia during physical activity and can be influenced by environmental factors such as heatwaves, which extend the incidence of exertional heat stroke beyond athletics only. Epidemiological data indicate mortality rates of about 27%, and survivors display long term negative health consequences ranging from neurological to cardiovascular dysfunction. The pathophysiology of exertional heat stroke involves thermoregulatory and cardiovascular overload, resulting in severe hyperthermia and subsequent multiorgan injury due to a systemic inflammatory response syndrome and coagulopathy. Research about risk factors for exertional heat stroke remains limited, but dehydration, sex differences, ageing, body composition, and previous illness are thought to increase risk. Immediate cooling remains the most effective treatment strategy. In this review, we provide an overview of the current literature emphasising the pathophysiology and risk factors of exertional heat stroke, highlighting gaps in knowledge with the objective to stimulate future research.

• Occupational diseases
• Sports medicine

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/bmjmed-2022-000239

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Introduction

Heat stroke is classified into two separate endotypes, referred to as classic heat stroke and exertional heat stroke (EHS). Classic heat stroke is induced by heat exposure in the absence of physical exertion. 1 EHS is induced by vigorous physical activity performed normally, but not always, 2 in hot or humid environments. 1 3 The term "heat stroke" suggests the presence of stroke-like symptoms associated with warm environments and hyperthermia (normally characterised by increases greater than 2.5°C from resting values). EHS is characterised by central nervous system (CNS) dysfunction (eg, delirium, convulsions, or coma) with the possibility of follow-on organ or tissue damage in people with hyperthermia. The prevention of EHS is currently more effective than any treatment strategy.

Understanding the pathophysiology and the risk factors that lead to EHS is important for the correct diagnosis and the choice of mitigation strategies. Here, we provide an overview of the pathophysiology of the disorder and discuss the potential risk factors that contribute to its incidence.

Sources and selection criteria

The following electronic databases were searched for articles published from the inception of the databases until July 2022: Medline (accessed by PubMed), Cochrane Wiley (Central Register of Controlled Trials), and LILACS. In addition, the reference lists of relevant published studies were searched manually. To identify relevant publications, the combined search term (exploded versions of the medical subject headings) were used: ("heat illness" OR "heat stroke" OR "exertional heat stroke" OR "heat exhaustion") AND ("heat injury" OR "hot temperature" OR "extreme heat" OR "thermoregulation" OR "warm environment" OR "heat stress") AND ("dehydration" OR "water stress" OR "water-electrolyte imbalance" OR "fluid balance"). We prioritised peer reviewed original studies including case series and retrospective studies. In addition, we also included studies using both clinical (eg, human participants) and preclinical models (eg, animal models). We did not include unpublished data from thesis or dissertations.

Incidence of exertional heat stroke

The precise incidence of EHS is underestimated, but large incidence is observed among warfighters, athletes, labourers, and those engaging in recreational exercise. Problems with classification of the disorder contributes to the lack of a clear reported incidence. Most studies include EHS under the umbrella term of exertional heat illness. Exertional heat illness is classified as a spectrum of severity and includes heat exhaustion, heat injury, and heat stroke, 4 which can be severe if untreated and are all characterised by hyperthermia. 5 To differentiate heat injury from heat exhaustion, tissue or organ injury must be present, although it might quickly resolve in patients that are rapidly treated. A recent systematic review performed in a military cohort reported incidence of exertional heat illness ranging from 0.2 to 10.5 per 1000 person years and prevalence ranging from 0.3% to 9.3%. 6 In addition, long distance road races reported an EHS incidence ranging between 1.6 and 2.13 per 1000 finishers without mortality. 7 8

Another factor that interferes with the precise incidence of EHS is the criteria often used to define the disorder clinically. Previous definitions of EHS have used the cut-off core temperature of >40°C. The use of a threshold core temperature to define the disorder is considered inaccurate. 9 Athletes can collapse at a wide range of core temperatures, 2 10 and the measurements can be inaccurate if taken at peripheral body sites or after cooling has already occurred. The use of a threshold core temperature can lead to a misdiagnosis, suggesting that reliance on other pathological manifestations (ie, CNS dysfunction) is warranted and likely more accurate. Immediate cooling, regardless of core temperature, should always be the main priority on collapse because reliance on a specific core temperature could delay (or fail to prescribe) medical intervention and cause long term organ damage. 11 Although less likely, false positive cases are possible because core temperatures >40°C can occur without CNS impairment. 12 13 Thus, CNS dysfunction is likely to define EHS with more sensitivity or specificity.

Pathophysiology

In this article, we will discuss four aspects of EHS pathophysiology: thermoregulatory or cardiovascular limitations, the so-called leaky gut hypothesis and endotoxaemia, inflammation and systemic inflammatory response syndrome, and coagulopathy and disseminated intravascular coagulation ( figure 1 ).

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Summary of the main pathophysiological factors participating in exertional heat stroke. During exercise (before collapse), hyperthermia ensues due to an inability of the cardiovascular system to sustain thermoregulation. Shifts in blood flow leads to increased intestinal permeability, causing leakage of intestinal content into the systemic circulation, a response is known as the leaky gut hypothesis. Intestinal content and hyperthermia lead to the systemic inflammatory response syndrome, which promotes a disseminated intravascular coagulation characterising the coagulopathy. Most of these responses remain after collapse or until the victim is adequately cooled and regains consciousness. The two most common outcomes of exertional heat stroke are death or recovery with long term negative consequences to health. Figure based on original graphical scheme prepared using Servier medical art (smart.servier.com)

Thermoregulatory and cardiovascular limitations

It seems reasonable to hypothesise that EHS is primarily due to impaired thermoregulation, because patients often display severe hyperthermia at the time of collapse. A person's ability to thermoregulate is closely linked to the ability of the cardiovascular system to cope with central and peripheral blood flow demands to support metabolic and thermoregulatory requirements. 14 15 During vigorous exercise, heat is produced by skeletal muscle contractions at rates that are 15-18 times greater than the basal metabolic rate. 16 Most of this heat is transferred from the muscles to the blood and carried to the body core. Theoretically, if no thermoregulatory mechanisms are activated, metabolic heat production of this magnitude would raise core temperature from 37°C to 42°C in only about 25 minutes. 16 This magnitude of endogenous heat production could overcome the thermoregulatory mechanisms of heat dissipation and induce EHS, even in a temperate environment. 2 Given that cellular tolerance to heat is in the range of 40-45°C, 17 this magnitude of heat would result in cellular and organ damage. Effective thermoregulatory pathways must be active to provide means for heat loss to prevent EHS during severe or prolonged physical activity.

The most effective thermoregulatory mechanism, at least during exercise performed on land and in the heat, is the evaporation of sweat. 18 Sweat production is initiated either by the activation of the central temperature receptors or by elevation of skin temperature, 19 both of which trigger the activation of the eccrine sweat glands. Evaporation of sweat depends on the vapour pressure gradient between the skin and air, 20 such that thermoregulation is normally impaired in humid environments. However, evaporation can still occur even if the skin and air are both saturated with water, provided the air is cooler than the skin. A thermoregulatory failure underlying EHS would signify a suppressed ability to dissipate heat coupled with high rates of heat storage, which would result in a marked elevation in core temperature. One argument against the hypothesis of a thermoregulatory failure underlying EHS is that during exercise in hot environments, core body temperature values of 40-42°C are not uncommon in athletes who are fit and acclimatised to heat. 12 13 21–23 These individuals show no signs or symptoms of EHS. Reports indicate that people with EHS might collapse during activities that were previously completed safely. 24 In addition, high grade fever exceeds 40°C without morbidity. 25 26 Therefore, although a thermoregulatory limitation could participate in the EHS pathophysiology to some extent, it does not entirely explain the manifestation. Since thermoregulation and cardiovascular responses are so tightly intertwined, an overwhelmed cardiovascular system might have a key role in EHS pathophysiology.

During muscle contraction, metabolic heat production increases in an intensity dependent manner. 27–29 During exercise in the heat or when wearing encapsulated clothing, individuals gain extra heat from the environment to the body or the trapping of heat within the clothing ensemble. 30 31 To sustain exercise, cardiac output must match the demands for blood flow. Blood flow to active muscles is required to meet the oxygen demands for muscular activity, while blood flow to skin is required to meet the demands of thermoregulation. 14 Vasodilation and increased skin blood flow increase the amount of blood pooled in peripheral vessels, which reduces central blood volume. Splanchnic and renal blood flow are reduced by both vigorous exercise and severe heat stress. Reductions in gut and renal blood flow are generally thought to facilitate shifts in cardiac output to the skin and exercising muscle to maintain blood pressure and allow continued exercise. 32 33 When these adjustments are inadequate during exercise in hot environments at high metabolic rates (>75% of maximal oxygen consumption (VO 2 max)), skin, muscle, and brain blood flow are compromised and contribute to severity of exertional heat illness. 1 34–36 These cardiovascular alterations lead to a diversity of outcomes including altered gut permeability that can have consequences to EHS pathophysiology.

Leaky gut hypothesis and endotoxaemia

Increased intestinal permeability, also known as the leaky gut hypothesis, suggests that bacteria and toxins leak from the gut lumen, where they are normally contained via tight junctions, through the intestinal wall into the portal and general circulation. Several reports have documented increased intestinal permeability during exercise with 37–39 and without heat stress. 40 As blood flow in the splanchnic circulation declines, skin blood flow increases for heat dissipation and gut epithelial membranes undergo nitrosative and oxidative stress, due to ischaemia reperfusion. 41 These processes degrade tight junction integrity and are thought to facilitate endotoxin leakage into the portal circulation.

The leaky gut hypothesis has been linked to EHS pathophysiology because of observations that in patients with extreme EHS, high levels of lipopolysaccharide (a cell wall component of Gram negative bacteria) are observed. Under normal circumstances, the liver reticuloendothelial system clears endotoxin so that it does not reach the general circulation. 42 In extreme heat stress conditions, dysfunction or damage to the liver could compromise the ability of the reticuloendothelial system to function. Only under these catastrophic conditions of liver failure or damage does endotoxaemia occur. Endotoxaemia and liver necrosis were observed in a football player who died of EHS at a body core temperature of 40.6°C. 43 In primates, circulating endotoxin was markedly increased under classic heat stroke conditions once body core temperatures exceeded the fatal level of 43.0°C. 44 Although liver damage was not assessed in this study, it is typically detectable at body core temperatures ranging from about 42°C to 43°C. 45–47

Studies using endotoxin neutralisation in several species have shown protective effects of antibiotics and endotoxin tolerance against heat stroke mortality, but once again these studies looked at catastrophic models with high mortality rates and core temperatures exceeding the threshold where liver injury would be expected. 44 48 49 On the other hand, a murine model of classic heat stroke that induced body core temperature as high as 42.7°C did not show detectable circulating endotoxin despite considerable gut histological injury. 50 51 This lack of endotoxin was most likely due to the absence of liver damage, which supports the hypothesis that liver dysfunction might be required for endotoxaemia. Chung et al 52 failed to show elevated endotoxin in patients with heat stroke. The liver has a critical role in recovery from EHS, as demonstrated in preclinical mouse models owing to the formation and release of acute phase proteins that support the immune system in repairing organ damage. 53 In figure 2 , we summarise the hypothesis for the leaky gut and endotoxaemia contributions to EHS pathophysiology with and without liver dysfunction.

Working hypothesis for the leaky gut response during exertional heat stroke (EHS). In non-lethal EHS, the liver effectively clears endotoxins. In catastrophic EHS, particularly with severe liver damage, endotoxin leaks into the circulation and causes sepsis. LPS=lipopolysaccharide. Figure based on original graphical scheme prepared using Servier medical art (smart.servier.com)

Inflammation and systemic inflammatory response syndrome

Systemic inflammatory response syndrome is a dysregulated defence response of the body to a noxious stressor to localise and eliminate the source of the insult. 54 The syndrome involves the release of acute phase proteins, cytokines, and chemokines, which are direct mediators of widespread autonomic, endocrine, haematological, and immunological alterations in the host. The dysregulated inflammation can lead to a pro-inflammatory cascade resulting in organ dysfunction and even death.

Preclinical models of classic heat stroke and EHS show a robust inflammatory response that ensues after collapse, which mimics mechanisms observed in patients. 55–57 In both male and female mice with EHS, 53 58 59 levels of plasma interleukin 6 peaked at 0.5 hours after loss of consciousness. 58 59 Induction of interleukin 6 in severe hyperthermia is thought to come from either endotoxaemia or hyperthermia and the actions of this cytokine can differ depending on its circulatory concentration. Sustained elevation of circulating interleukin 6 during recovery from classic heat stroke has been correlated with poor outcome in primates and humans. 55–57 Mice with interleukin 6 gene knockout showed increased mortality, indicating protective effects at a basal level. Interleukin 6 injection in mice with classic heat stroke led to protection from organ injury. 60 Whether these possible dual actions of interleukin 6 also exist for EHS remains unknown.

One possibility for induction of the systemic inflammatory response syndrome after EHS (or classic heat stroke) is that the endotoxaemia via the so-called leaky gut triggers an inflammatory response after its binding to toll-like receptors, a class of proteins that have a crucial role in immune signalling by recognising pathogen and damage associated molecular patterns. 61 Evidence of endotoxaemia is only present in catastrophic EHS events ( figure 2 ), the leaky gut is unlikely to explain the inflammatory response observed on collapse in survivors of EHS. A secondary source for the inflammatory response could be hyperthermia. Hyperthermia increases interleukin 6 mRNA content in myofibres, in part by heat shock factors, although the response in other organ levels has not yet been determined. 62 This response is relevant because interleukin 6 regulates the hepatic acute phase response during recovery from EHS. 53 In summary, EHS is accompanied by a strong inflammatory response that leads to systemic inflammatory response syndrome and multi-organ damage. The triggers for these responses are endotoxaemia (in catastrophic EHS) and probably hyperthermia.

Coagulopathy and disseminated Intravascular coagulation

Coagulation is the process of changing the physical state of the blood from liquid to semi-solid. In vertebrates, coagulation is an evolutionary conserved mechanism that maintains haemostasis, in cases of blood vessel damage, by preventing bleeding. 63 Overall, coagulation has four stages of clot formation, including constriction of the blood vessel, formation of a temporary platelet plug, activation of the coagulation cascade, and formation of the final clot. The system is tightly regulated by the complex interaction of 20 pro-coagulation factors, including fibrinogen, thrombin, prothrombin, von Willebrand factors, among others. 64 When the system is under equilibrium, the clotting formation process is balanced by fibrinolysis, which is the enzymatic breakdown of the fibrin in blood clots. 65 Once vascular repair is achieved, the fibrinolytic factors plasminogen and tissue plasminogen activator are attracted by the clot through lysine residues of fibrin and start clot digestion. Disturbances in these haemostatic processes lead to several problems, including thrombosis and disseminated intravascular coagulation. 66

Disseminated intravascular coagulation can be classified into hyperfibrinolytic coagulation, which will lead to thrombotic events, or hypofibrinolytic coagulation, which leads to excessive bleeding. 67 Disseminated intravascular coagulation has been reported in patients with EHS. For example, a 38-year-old male recreational athlete presented in the emergency room with a history of sudden loss of consciousness during a 10 km run. He did not have a history of cardiovascular or respiratory disease and did not have similar loss of consciousness episodes previously. His level of fibrin degradation product, small pieces of protein that stay in the circulation when a blood clot dissolves, was substantially elevated at 0.8 mg/L (normal <0.05 mg/L). Prothrombin time and activated partial thromboplastin time, indicators of the time required for clot formation in a blood sample, were 29.7 seconds (normal time 12.3 seconds) and 33.5 seconds (control time 26.38 seconds), respectively. 68 He also presented bilateral intracerebral bleeding, consistent with hypofibrinolytic disseminated intravascular coagulation.

Treatment strategies for disseminated intravascular coagulation in EHS have not been established, and the time course changes in coagulofibrinolytic markers have not been thoroughly evaluated. The triggers of disseminated intravascular coagulation during heat stroke events are difficult to determine. In a baboon model of classic heat stroke, inhibition of tissue factor/factor VIIa, which has an activating role in the clotting formation cascade, attenuated disseminated intravascular coagulation. 69 The authors concluded that a pathway dependent on tissue factor/factor VIIa initiates coagulation activation in this model. Whether the same factor is responsible for the initiation of disseminated intravascular coagulation in EHS or whether the response holds true in other mammals remains unknown.

Risk factors

No sound evidence indicates which risk factors increase EHS predisposition, but several factors have been implicated. In figure 3 , we highlight the risk factors discussed in this review.

Potential risk factors affecting exertional heat stroke. Arrow colours represent level of evidence for each risk factor: green=strong; yellow=moderate; red=anecdotal

Dehydration

No direct evidence indicates that dehydration has a causative role in EHS. But to hypothesise that it will be a risk factor is logical, given the known impact of dehydration on human physiology. 70 71 Blood plasma consists of about 90% water. During exercise, because of increased metabolic demand and sweat production, plasma volume decreases, which increases plasma osmolality and blood viscosity, which are associated with increased reactive oxygen species production. 72 The increased osmolality induces a pull of water from intracellular stores to extracellular stores to overcome the impact from exercise. The greater viscosity from decreased plasma volume causes cardiac drift, leading to greater cardiac strain. 73 When decreases in plasma volume are drastic enough to decrease blood pressure, it can diminish cerebral blood flow and cause syncope. 74 By exercising in the heat, sweat rates escalate to increase evaporative heat loss from the paired metabolic heat produced from exercise and the external environmental heat. The detriments of dehydration are exacerbated when individuals begin exercise in a hypohydrated state, 75 which is frequent in athletes. 76–78 In a crossover study of 17 male soldiers, Sawka et al compared heat strain between euhydrated and hypohydrated individuals with about 8% dehydration after walking for 180 minutes at 49°C and 20% humidity. 79 The hypohydrated state was more responsible for heat intolerance than aerobic fitness. In the hypohydrated condition, the heart rate was higher, sweat rate was lower, and participants showed lower tolerance for temperature change (observed through exhaustion occurring at lower rectal temperature) even after heat acclimation. 79 Therefore, dehydration could potentially enhance the risk of EHS via hyperthermia. While the role of dehydration in increased intestinal permeability has been hypothesised, 80 more studies are needed to support this idea with EHS.

Body composition

Obesity is associated with decreased cardiovascular fitness and impaired microvascular function at the skin, potentially leading to impaired thermoregulatory responses. 81 Impaired skin microvascular function could lead to a diminished ability to produce sweat that matches evaporative heat loss demands. However, an association between skin blood flow and overall thermoregulation is absent. 82 In a clinical trial involving independent groups (n=9 per group), Dervis et al reported that individuals with higher fat mass have impaired sudomotor responses leading to a decreased ability to thermoregulate. 83 When heat production induced by exercise was fixed, individuals with low body fat had a higher sweat rate than those with high body fat. The fact that both groups exercised at the same heat production relative to lean body mass could explain these findings. The lower lean body mass in the high fat group resulted in a lower absolute heat production and thus a lower evaporative requirement. This diminished sudomotor response could have contributed to the measured core temperature in the Dervis study being greater in the high body fat group after 60 minutes of activity than the low body fat group. Overall, the main message of Dervis study was that, once the effects of heat production and mass were accounted for, a lower average specific heat capacity of body tissues in the high fat group led to a disproportionate mean elevation in core temperature. The findings also reinforce that the thermoregulatory responses of groups with different adiposity levels should not be compared using a fixed heat production.

Adipose tissue itself is an insulator under cool conditions (about 21°C) such that high adiposity might result in decreased ability to dissipate heat and heightened risk of hyperthermia. 84 Sweat evaporation is partially determined by skin temperature and varies across the body. 85–87 In a clinical trial with independent groups (n=20 per group), Chudecka et al observed a statistically significant difference in skin temperature between obese and normal weight women at the thighs and abdomen—locations where excess adipose tissue is typically found in women. These findings support the concept of adipose tissue acting as an insulator, making heat dissipation in those areas less likely and causing heat retention. 84 Yokota et al used a simulated heat model with six compartments (muscle, fat, vascular skin, avascular skin, core, and central blood in passive and active heat) that was based on human physiology and biophysics in male soldiers. 88 The simulated model suggested that short and lean men have the greatest thermoregulatory response while tall and fat men have disadvantage in hyperthermic environments. Therefore, short and lean men were expected to wear their body armour and perform their tasks in a hyperthermic environment for 18 minutes longer than tall and fat men before reaching a core temperature of 38.5°C—a temperature in which 25% of heat casualties occur. 89 This study was simply a predictive model based off collected physiological and anthropometric data in male soldiers. Yokota et al validated this same model in women. Similar to the male data, female soldiers who were short and lean were expected to cope better with required activities in hyperthermic conditions than tall-fat women. 90 The researchers then had the women do the previously simulated situation and found the measured results to be consistent with the predicted results. Both Yokota studies support the idea that increased adipose tissue increases insulation, although the anatomical location of these extra fat stores and the properties of the clothing worn might also be factors.

One aspect to consider is that cutaneous blood vessels pass through the subcutaneous fat layer, thus vasodilated skin allows warm blood to bypass the subcutaneous fat layer, regardless of its thickness. 91 92 The lower density of fat tissue can alter the surface area for heat dissipation, although this effect is likely small. Ultimately, regardless of the mechanism, greater body surface area probably contributes to an increased core temperature and decreased heat loss, making exertional heat illness and EHS more probable. Finally, another factor associated with obesity that might explain a greater susceptibility to EHS is inflammation. Increased adiposity is well known to cause chronic inflammation and metabolic disease, 93 which are thought to be predisposing EHS risk factors.

Sex differences

Thermoregulatory differences exist between male and female individuals at high ambient temperatures in active conditions. 94 95 In military populations, heat illnesses are more prevalent in women, but EHS is most common in men. 96 Behavioural, hormonal, morphological, and physiological differences can be difficult to dissociate between the sexes. From a morphological perspective, variations in surface area and body composition affect thermoregulatory efficiency. Overall, male and female mammals differ in size. Absolute mass and surface area tend to be greater in male mammals whereas surface area-to-mass ratio and body fat tend to be greater in female mammals. The implications of these morphological differences between sexes to EHS responses remain unclear. 97 In a preclinical model of EHS, 98 female mice outperformed male mice by about 40%. 59 This finding was unexpected given that this preclinical model consists of forced wheel running in uncompensable heat (37.5°C environmental temperature and 40% relative humidity) and the greater surface area-to-mass ratio in female mice.

Behavioural responses driven by endocrine stimuli could account for the higher incidence of EHS in men. Testosterone has a role in certain behaviours, including aggression and dominance, 99 which could justify men’s tendency to ignore the protective physical signs and symptoms of heat illness. A clinical trial of 10 men and 10 women confirmed that, during exercise, women use thermal behaviour to a greater extent than men. 100 When looking at sex specific differences, menstrual cycle fluctuations in oestrogen, progesterone, and the ratio between the two result in oscillating core temperatures, 101 although the influence of menstrual cycle in thermoregulation has been limited. At least during hot and dry conditions, the menstrual cycle phase does not appear to modulate whole body heat loss during exercise. 102 Oral contraceptives could affect the core temperature due to the manipulation of these sex hormones, 103 however, the effect of these drugs on EHS has not been studied.

Responses to thermal stress between the sexes are primarily a result of decreased rates of metabolic heat production in female individuals. 95 This decrease in metabolic heat production is presumably associated with cutaneous vascular conductance and sudomotor activity. 104 105 Female individuals tend to show lower sudomotor activity at a similar heat load than male individuals, resulting in differences in temperature regulation and sweat production. 94 However, in a clinical trial, Kazman et al 104 compared men’s (n=55) and women’s (n=20) responses to a heat tolerance test. All women were in the follicular phase of the menstrual cycle (ie, the longest step in the menstrual cycle, lasting from the first day of a period to ovulation, when oestrogen levels are high and progesterone levels are low). In this study, women were more heat intolerant than men, as defined by a core temperature over 38.5°C, failure to plateau in body temperature, or a heart rate over 150 bpm. Thus, sex was thought to predict heat intolerance. However, a linear regression analysis found body fat percentage and VO 2 max were more accurate predictors and negated the effect of sex. These findings also suggested thermal strain is less important than cardiovascular strain regarding performance in the heat. 104 However, the heat tolerance test lacks sensitivity and specificity owing to its stringent terminal criteria and cannot account for fluctuations in temperature above 38.5°C 106 107 and it is associated with a high fail rate of false positives. 107

Oestrogen and progesterone fluctuations in the oestrous cycle result in variations in core temperature with women in the luteal phase (eg, high progesterone, lower oestrogen) showing 0.3-0.5 ◦ C increase in core temperature compared with the follicular phase (eg, high oestrogen, low progesterone). Even with this variation in temperature, thermoregulatory responses did not differ throughout the estrous cycle phases. On the other hand, In a clinical trial of four women aged 20-35 years, Horvath et al observed differences in core temperature at rest that were attenuated during combined heat and exercise. 108 More studies are warranted to determine the influence of sex hormones on EHS susceptibility.

Although EHS is more prevalent in young cohorts, ageing can be considered a risk factor because it is known to hinder several thermoregulatory and cardiovascular responses. Ageing in humans is accompanied by a decrease in sudomotor function, cardiovascular function, immune function, and behavioural thermoregulation. 15 These factors contribute to the increased risk of heat related morbidity and mortality. 109 Elderly people typically have a higher incidence of classic heat stroke than EHS because of decreased activity levels, and many older individuals also have pre-existing cardiovascular insufficiencies, as observed by a lower VO 2 max, which has a negative effect on the ability to adequately respond to heat. 110

Increased levels of physical activity on ageing mitigates the negative physiological alterations associated with ageing. Many factors might contribute to this impact of increased levels of physical activity, such as improved cardiovascular fitness, reduced weight, and improved immunity. The sudomotor system begins to decline considerably at age 40 years, beginning with the lower limbs and followed by the back, abdomen, upper limbs, and then head. 111 The resultant decline in sweat rate is due to decreased functionality of sweat glands, and not the number of sweat glands. An age related decline in sweating limits the ability to dissipate internal (metabolic) and external (ambient) sources of heat gain causing hyperthermia and potentially collapse. With the increasing incidence of EHS beyond athletics, it is likely that humans performing daily tasks, such as lawn mowing and gardening, might be at risk of developing EHS and the impact of ageing must be taken into consideration.

Previous illness

When an organism has an immunological challenge, the innate and adaptive immune systems are activated. Innate immunity represents non-specific immunological defenses that are activated immediately after antigens appear. Adaptive immunity is an antigen specific immune response that requires recognition of the antigen and development of immune cells specific to destroying that antigen. Heat stress and EHS have been shown to degrade gut integrity and stimulate the immune system. 112 113 The degradation in gut integrity is implicated in a catastrophic immune response known as systemic inflammatory response syndrome. 114 Heat exposure induces a set of proteins that modulate the immune response to resolve systemic inflammatory response syndrome. Cytokines are immune modulators that have a dynamic nature and have been associated with fatalities from heat stroke. However, as previously mentioned with interleukin 6, some cytokines have been implicated in both proinflammatory and anti-inflammatory functions, which could be a function of their concentration or the surrounding milieu in which they are functioning. 115 Because of the vast array of cytokines and their diverse functions, understanding which specific set of cytokines can reduce or accentuate the effects of EHS has been difficult, and is likely to involve a coordinated response among several different cytokines. 62 116 Another important set of immunological cells involved in heat stroke are lymphocytes. 117 118 In classic heat stroke, T regulatory cells have been shown decrease in number and in immunosuppressive function. 117 When lymphocyte production is compromised, heat stroke severity is exacerbated. 118 Other factors might also come into play when determining how EHS or heat stress modulate the immune response, such as thermosensors, pre-existing conditions, previous illnesses, 119 and epigenetic consequences. 120 121

Innate immunity is altered in individuals with comorbidities and pre-existing conditions, thus increasing the potential for exertional heat illness and, if left untreated, death. Diabetes mellitus has been shown to disrupt immune responses that are critical to staving off fungi, toxins, parasites, viruses, and bacteria. The mechanisms that are suppressed in patients with diabetes mellitus include dysfunction of immune cells, decreases in cytokine production, dysfunction in phagocytosis, and a decreased ability to eliminate microbials. 122 These effects are prevalent owing to the hyperglycaemic environment in patients with diabetes mellitus. 123 In terms of heat stress, hyperglycaemic environments are strongly associated with reductions in skin blood flow and sudomotor function, potentially incapacitating evaporative heat loss. 124 125 Another deleterious effect of hyperglycaemic is the loss of nitric oxide availability, contributing to vascular complications. 126 Based on the available evidence, a possible interplay could exist between the cardiovascular system, immune system, and diabetes—which complicates how to treat this condition and determine who is most vulnerable and why.

Emerging treatments and studies

Despite all the progress in our understanding of EHS, effective treatment strategies are still limited. Whole body cooling remains the most effective treatment to manage EHS victims on collapse. 127 A recent review of the literature highlighted the most effective forms of cooling which include immersion in iced or cold water, cold water dousing, tarp assisted immersion in ice or cold water, towels or sheets soaked in iced or cold water, cold water immersion in portable water impermeable bags, and water spray or mister or high powered fan with water spray. 127 Effective drug strategies to treat patients with EHS do not exist and common drugs, such as dantrolene sodium (primarily used to treat disorders related with skeletal muscle spasticity and malignant hyperthermia 128 ) have failed. 129 130 Future studies of potential drug interventions to treat EHS are necessary.

This review highlights gaps in our knowledge to stimulate future research in the field of EHS. Important gaps in knowledge include the contributions of sex hormones to EHS susceptibility, whether dehydration is a risk factor for EHS, the role of endotoxemia in non-lethal EHS pathophysiology, the time course of changes in coagulofibrinolytic markers in EHS, and the impact of oral contraceptives on EHS risk. Research studies partitioning the contributions of different physiological systems 131 and risk factors to EHS are required to advance knowledge on the precise sequence of events leading to EHS and the underlying mechanisms mediating organ damage.

Conclusions

EHS pathophysiology is complex and involves an interaction of thermoregulatory and cardiovascular factors that lead to systemic inflammatory response syndrome. In catastrophic EHS events, systemic inflammatory response syndrome is likely initiated by endotoxaemia when the hepatic system fails to clear bacteria effectively. Coagulopathy is also present in the pathophysiology and manifests through disseminated intravascular coagulation, resulting in thrombosis or bleeding (or both). Risk factors discussed in this review include dehydration, sex differences, ageing, body composition, and previous illness. The reason why some people are more susceptible to EHS than others warrants further research.

Questions for future research

What are the contributions of sex hormones to susceptibility exertional heat stroke (EHS)?

Is dehydration a risk factor for EHS?

Can endotoxaemia be involved in non-lethal EHS pathophysiology?

What is the time course of changes in coagulofibrinolytic markers in EHS?

What is the impact of oral contraceptives on EHS risk?

Patient involvement

No patients were asked for input in the creation of this article.

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Twitter @olaitano

Contributors OL and LRL prepared the figures; CKG, LIR, GL-S, and OL drafted the manuscript; OL and LRL edited and revised the manuscript; CKG, LIR, GL-S, LRL, and OL approved final version of the manuscript. OL is the guarantor.

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial, or not-for-profit sectors.

Competing interests We have read and understood the BMJ policy on declaration of interests and declare the following interests: none.

Provenance and peer review Commissioned; externally peer reviewed.

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Damaging impact of heat waves on vital organs

Heat stress affects brain, gut and liver function via a complex network of molecular mediators.

Researchers from the University of California, Irvine have found evidence of the molecular causes of the damaging impact heat stress causes on the gut, liver and brain in the elderly. These findings point to the potential of developing precise prognostic and therapeutic interventions.

These organs have a complex and multidirectional communication system that touches everything from our gastrointestinal tract to the nervous system. Whether it is our brain affecting hunger or the liver influencing mental health, understanding the gut-liver-brain communication or "axis" is crucial to protecting human health.

Their study, which was conducted on mouse models, is published in thejournal Scientific Reports , a Nature Portfolio journal. It is one of the first to fill the knowledge gap on the effects of heat stress on a molecular level of this crucial biological conversation.

"Inflammation in the brain and spine contributes to cognitive decline, compromises the ability to form new neurons and exacerbates age-related diseases," said corresponding author, Saurabh Chatterjee, a professor of environmental & occupational health at the UC Irvine Program in Public Health. "By investigating the effects of heat stress on the gut-liver-brain crosstalk, we can better protect our increasingly vulnerable aging population."

Using RNA analysis and bioinformatics to analyze elderly, heat-stressed mice, Chatterjee and his team found evidence of heat stress-affected genes in the brain and liver. A significant increase in the production of ORM2, a liver-produced protein, was observed in the heat-stressed mice. The control group of unstressed mice did not show a change, providing proof of organ dysfunction in the heat-stressed mice.

Researchers believe that increased secretion of ORM2 is a coping mechanism that may be due to gut inflammation and imbalance. In addition, ORM2 may impact the brain through a leaky blood-brain barrier, emphasizing intricate multi-organ crosstalk.

Additionally, the study shows the potential to use ORM2 for targeted biomarker interventions to prevent liver disease in heat exposure. This observation advances molecular insights into the pathophysiology of adverse heat events and will serve as a foundation for future research.

"Our findings have the potential to be used for the development of prognostic and therapeutic markers for precise interventions," said Chatterjee. "In a dynamically changing global landscape, the imminent threat of climate change is evident in rising temperatures, raising concerns about intermittent heat waves. Our heating planet is undoubtedly leading to acute and chronic heat stress that harms the health of our aging population."

Additional authors from UCI Public Health include members of the Environmental Health and Disease Laboratory: doctoral students Subhajit Roy (the first author), Punnag Saha, Dipro Bose, Ayushi Trivedi and Madhura More; and Christina Lin, Jie Wu and Melanie Oakes with the UCI genomics high-throughput facility.

A grant from the National Institute of Environmental Health Sciences and a Veterans Affairs Merit award provided study support.

• Liver Disease
• Chronic Illness
• Diseases and Conditions
• Workplace Health
• Severe Weather
• Global Warming
• Encephalopathy
• Molecular biology
• Liver transplantation
• Adult stem cell
• False morel fungus

Story Source:

Materials provided by University of California - Irvine . Note: Content may be edited for style and length.

Journal Reference :

• Subhajit Roy, Punnag Saha, Dipro Bose, Ayushi Trivedi, Madhura More, Christina Lin, Jie Wu, Melanie Oakes, Saurabh Chatterjee. Periodic heat waves-induced neuronal etiology in the elderly is mediated by gut-liver-brain axis: a transcriptome profiling approach . Scientific Reports , 2024; 14 (1) DOI: 10.1038/s41598-024-60664-9

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Data Analytics of a Wearable Device for Heat Stroke Detection

When exercising in a high-temperature environment, heat stroke can cause great harm to the human body. However, runners may ignore important physiological warnings and are not usually aware that a heat stroke is occurring. To solve this problem, this study evaluates a runner’s risk of heat stroke injury by using a wearable heat stroke detection device (WHDD), which we developed previously. Furthermore, some filtering algorithms are designed to correct the physiological parameters acquired by the WHDD. To verify the effectiveness of the WHDD and investigate the features of these physiological parameters, several people were chosen to wear the WHDD while conducting the exercise experiment. The experimental results show that the WHDD can identify high-risk trends for heat stroke successfully from runner feedback of the uncomfortable statute and can effectively predict the occurrence of a heat stroke, thus ensuring safety.

1. Introduction

According to the 2017 global climate report published by the National Oceanic and Atmospheric Administration of the United States [ 1 ], the global temperature in 2017 reached the third highest recorded in history. Moreover, the global temperature was also found to increase 0.07 °C every ten years. These findings indicate an evident trend of global warming occurring in recent decades. This trend has had a significant impact on Taiwan as well. The main island of Taiwan is located on the Tropic of Cancer. The northern part of Taiwan falls within the subtropical zone whereas the southern part is within the tropical climate zone. Nevertheless, both parts of Taiwan are surrounded by a hot and humid climate. Affected by global warming, heat waves are now becoming increasingly frequent and intense in Taiwan, which has led to an increasing number of heat-related illnesses, including heat cramps, heat exhaustion, and heat stroke. Among these illnesses, heat stroke is the most severe, which often occurs in a high temperature and calm weather.

As sports are becoming a more popular component of daily life, many wearable devices capable of detecting physiological information, automatically recording physical data, and tracking the user’s location have been developed to offer convenience and improve safety in sport activities. The improvement in safety is particularly important because the detection of physiological information enabled by these wearable devices can monitor the physical condition and predict potential safety risks for the user, thereby effectively reducing the possibility of getting injured in sports. Table 1 summarizes the pathological features and the corresponding physiological risk factors of heat stroke, obtained from relevant literature studies [ 2 , 3 ]. These findings can be used to increase the chance of early detection of heat stroke.

Pathological features and the corresponding physiological risk factors of heat stroke.

In their heat stroke prevention studies, Naoya Mizota et al. [ 4 ] proposed the concept of showing a heat stroke alert on users’ smartphones based on the environmental temperature—humidity index. Other studies have also suggested that the change in body temperature for individuals of different ages is also an indicator of potential heat stroke [ 5 , 6 , 7 ]. Many other wearable devices equipped with physiological information sensors can monitor changes in a patient’s condition using physiological information signals, such as electrocardiogram, electromyography, and electroencephalogram signals [ 8 , 9 ]. However, a simple device for assessing heat stroke risk based on pathological features and their physiological information that can be carried easily by individuals is still lacking. Such a device can advise the users to take appropriate precautions in case of potential heat stroke risk, and therefore, prevent heat injury.

Wearable devices have been used widely in everyday life with substantial impact on the way that we live. By integrating physiological sensors in wearable devices, the physiological information of an individual exercising (e.g., running) can now be monitored automatically and instantaneously. This information can be combined with recorded environmental conditions to predict the risk of heat stroke and further advise the user to take proper precautions. Because ordinary wearable devices have limited computational power, the physiological information collected by the sensors is usually first sent back to a paired smartphone through Bluetooth wireless communication and then processed by the smartphone [ 10 ]. Bluetooth wireless communication embedded in smart handheld devices has the advantage of low power consumption and easy connection [ 11 ]. While the operating range of Bluetooth communication is officially claimed to be 100 m, experiments have shown that the practical communication range is between 5 and 10 m [ 12 ]. Although such a distance can satisfy the requirements in most conditions [ 13 , 14 , 15 , 16 , 17 , 18 ], the ultimate distance between the sensor and the smart handheld device is still limited by the maximum available wireless communication distance if one wishes to monitor the physiological information of an outdoor runner instantaneously. For individuals performing outdoor sports activities, increasing the wireless communication distance of the wearable device can offer more convenience. A summary of the technical specifications of different wireless communication systems [ 19 ] is provided in Table 2 . As shown in the table, LoRa is a promising wireless technology that can resolve the aforementioned issue owing to its advantageous transmission distance, transmission power consumption, and standby current. Specifically, it has a longer range of wireless signal transmission, a lower sensitivity, and a lower power consumption [ 12 ] than other wireless communication technologies. Therefore, it is an ideal candidate for use as a communication module in wearable devices.

Comparison of the technical specifications of different low-power wireless communication systems.

In addition, fuzzy logic is different from the traditional binary logic, in which the state can be only described by 0 or 1. In fuzzy logic, a membership function with output values changing continuously between 0 and 1 is used to describe the state of a phenomenon [ 20 ]. Using binary logic to describe heat stroke can result in potential danger because heat injury has already occurred when a heat stroke is detected. Using fuzzy logic to describe the heat stroke can prevent potential heat injury based on the level of heat stroke derived by the fuzzy rule. Thus, fuzzy logic is suitable for use in heat stroke prevention.

In our previous work [ 21 ], we developed a wearable heat stroke detection device (WHDD) and demonstrated its heat stroke prediction capability for running. It should be noted that the usage of WHDDs is not limited to running alone. The WHDDs can be used to monitor body temperature and prevent the occurrence of heat stroke in any activity or exercise that carries the risk of heat stroke. In this study, we perform a more detailed analysis and experimental investigation from the perspective of information analysis and experimental subjects. Our results further demonstrate the superior applicability of the WHDD.

2. Materials and Methods

2.1. system description.

As shown in Figure 1 , the architecture of the WHDD comprises three main parts: a wearable device, a wireless transmission module, and a back-end monitoring system. The complete WHDD is shown in Figure 2 . Detailed descriptions of the different components of the device can be found in our previous work [ 21 ].

Architecture of the system.

Photograph of the wearable heat stroke detection device (WHDD) on a human body.

2.1.1. Wearable Device

The wearable device is further composed of three parts: the microcontroller, the sensor module, and the alert module. The microcontroller, based on an Arduino Nano board, is responsible for performing basic processing of the front-end data collected by the sensors, data filtering, and signal filtering. Subsequently, the microcontroller packs the data and passes them to the LoRa wireless transmission module, from where they are transmitted to the back-end monitoring system. The sensor module comprises four individual sensors that measure heart rate (World Famous Electronic), body temperature (MLX90614), environmental temperature and humidity (SHT75), and skin resistance (Grove-GSR) separately. The sensor module captures the main physiological information from the user’s body. This information is then transmitted to the back-end monitoring system by the wireless transmission module. Once the back-end system evaluates the risk of heatstroke from the received data, based on the risk level, the control buzzer warns the runner as follows: no alert means Safe situation, the LED turns on without the buzzer in Attention mode, the LED blinks and the buzzer beeps smoothly in Warning status, and the LED blinks and the buzzer beeps rapidly in Interdiction mode. The system suggests to the runner to ensure that appropriate measures are immediately taken in a dangerous situation to avoid heat stroke. The details of these procedures can be found in our previous work [ 21 ].

2.1.2. Wireless Transmission Module

To achieve a large-distance, low-power, and low-cost design target, the LoRa module developed by iFrogLab is used in the wireless transmission module of our device. The LoRa transmission module enables transmission of the information collected by the sensors from the wearable device to a terminal device. The wireless transmission module employs universal asynchronous receiver/transmitter (UART) for signal communication. Control of the data transmission is achieved using the attention (AT) command system. These approaches facilitate the integration of different components to construct the device.

2.1.3. Back-End Monitoring System

After collecting and transmitting the physiological information using the sensors and LoRa, respectively, this information is received by the back-end monitoring system, where the heat stroke risk is analyzed. The primary functions of the back-end monitoring system include recording the user’s physiological information, physical status, and environmental information, as well as setting the parameters for LoRa.

2.2. Planning and Design of Heat Stroke Detection Workflow

After introducing the system architecture of the WHDD, we define the desired operation of the device as well as the associated techniques and hardware required. In this section, we discuss the design of the workflow for heat stroke detection and for the specific functions associated with each of the three architectures (the wearable device, the wireless transmission module, and the back-end monitoring system). Figure 3 shows the workflow of the entire system.

Workflow of the WHDD.

2.2.1. Wearable Device

This section describes the workflow for the target function of the WHDD. The overall workflow can be divided into two stages, namely, the stage before running and during running. The workflow for each section is described in detail below.

During the first stage (before running), the physiological information of the user is recorded. This information will be compared with the physiological information of the user during running. The change in the physiological information before and during running is an important factor for predicting heat stroke risk. Two physiological features, the heart rate and the skin resistance, of the user are recorded by the sensors during this stage. The overall workflow is shown in Figure 4 .

Workflow for collecting physiological information before running.

This workflow comprises the following steps:

• Initialization of all the sensors.
• The heart rate sensor monitors the user’s heart rate for 1 min with a sampling frequency of 2 Hz (one sample every 0.5 s). After 1 min, a total of 120 measurement points are obtained, whose average value is considered as the user’s heart rate before running.
• Determine whether the heart rate is normal. The heart rate of a normal adult ranges from 50 to 90 bpm [ 22 ]. If the heart rate cannot be detected by the sensor, equals zero, or falls within the range associated with an adult in a non-resting condition, then an abnormal phenomenon is identified, and the heart rate is measured again.
• The user’s skin resistance is measured through the galvanic skin response for 1 min with a sampling frequency of 2 Hz (one sample every 0.5 s). A total of 120 measurement points are obtained and the average value is used as the user’s skin resistance before running.
• Determine whether the user’s skin resistance falls within the normal range. The skin resistance of an adult under resting conditions is approximately 10–50 μS [ 23 ]. If the skin resistance cannot be measured, equals zero, or falls within the range associated with an adult in non-resting conditions, then an abnormal phenomenon is identified and the skin resistance is measured again.

In the second stage (during running), the wearable device mainly captures information about the surrounding environment and the user’s physiological condition. Subsequently, this information is packaged and transmitted to the monitoring end by the LoRa wireless transmission module. The main workflow is shown in Figure 5 .

Workflow for extracting information on the surrounding environment and the user’s physiological condition (main program).

• Initial timer interruption program and external interruption program. The timer interruption program allows the wearable device to receive the heat stroke risk level from the monitoring system on a regular basis. The external interruption program enables the user to ask for help by pressing a button on the device. In this case, the device immediately sends the physiological and environmental information back to the monitoring end.
• Determine whether the device must be turned off, namely, by removing the battery from the device and shutting down the program.
• Collection of the user’s physiological and environmental information by the sensors (e.g., temperature and humidity sensor). The information is collected in the following order: environmental temperature and humidity, skin resistance, heart rate, and body temperature. This information is collected at intervals of 3 ms. Therefore, 15 ms are required to complete an entire cycle of information collection.
• The heart rate and body temperature signals are preprocessed, first by a threshold-filtering algorithm, then by an error-filtering algorithm, and finally by a moving-average algorithm. When the number of samples reaches 60, all the filtered information is packaged and transmitted to the monitoring system by LoRa. The interval between each data transmission is approximately 15 ms × 60 = 900 ms (approximately 1 s)
• When the number of samples is less than 60 or the data transmission is finished, the device continues executing the workflow from step 2.

The detailed signal processing workflows for the two most important indices for evaluating the heat stroke risk, i.e., the heart rate and body temperature, are discussed below.

Because the heart rate sensor is designed to be positioned on the user’s wrist, the movement of the arms while running can potentially induce errors in the heart rate measurements. To resolve this issue, a threshold-filtering, error-filtering, and moving-average strategy is adopted to preprocess the heart rate signal and mitigate measurement errors. The code of the program is shown in Algorithm 1.

In the heart rate threshold-filtering program, heart rate signals falling outside the range of 50 to 190 bpm are filtered out. This is because the heart rate of an adult at rest ranges between 50 and 90 bpm [ 22 ]. Therefore, 50 bpm is selected as the lower limit of the heart rate. The upper limit is selected based on the study by Tanaka et al. [ 24 ], who proposed in 2001 that the maximum heart rate ( H R M a x ) of an individual during exercise should be calculated based on the age instead of the gender. Roy et al. [ 25 ] in 2015 reviewed all the existing equations for calculating the maximum heart rate during exercise. They found that the equation proposed by Tanaka is rather accurate. This equation is given by

Here, we assume the age to be 26 and derive the maximum heart rate to be approximately 190. Therefore, the upper limit of the heart rate is selected to be 190.

In the heart rate error-filtering program, each measured heart rate ( H R t ) is compared with the heart rate recorded in the previous cycle. The error between neighboring measurements is given by

This difference is used to revise the heart rate measurement based on a comparison between the performance of the heart rate sensor used in this study and that of a commercial heart rate belt. A fixed equation is derived to convert the measured heart rate to the actual value based on the difference between neighboring heart rate measurements. The revised heart rate is given by the following equation

Finally, when the number of heart rate measurements reaches 60, a heart rate moving-average program is executed to obtain the average value of the heart rate measurements obtained over 60 cycles. The final value is used as the anticipated heart rate ( H R T r u e ), which is given by

The sensor used for measuring body temperature in this study is a non-intrusive sensor. First, it measures the human skin temperature using an infrared sensor and then it converts that to the adult body temperature using a conversion equation. This temperature sensor is placed on the inner side of the user’s wrist. Owing to the low thickness of the skin, this location is the most suitable place for measuring body temperature. According to a study by John Gammel [ 26 ], the following equation, together with the parameters ( α ) listed in Table 3 , are used to convert skin temperature to core temperature.

Parameter α for different body parts.

However, we found that the sweat generated during exercise reduces the surface temperature of the skin, and therefore, results in a lower body temperature. This impact also varies significantly with different levels of sweating for different people. Specifically, the measured skin temperature is increasingly smaller than the actual skin temperature for those generating a larger amount of sweat during exercise and vice versa. Therefore, the error of the core temperature obtained using the conversion equation is greater with increasing exercise time. To reduce the error induced by this physical phenomenon, the temperature data are filtered and processed using the program code shown in Algorithm 2.

After converting the skin temperature to the core temperature ( T C o r e ), the core temperature is processed by a temperature-threshold filter to yield a reasonable body temperature. This revision is based on a comparison between the body temperature measured using the system developed in this study and the value measured using an ear thermometer. A compensation equation is derived from this comparison to revise the core temperature measured by our device. The equation and the applicable temperature ranges are given by

When the measured core temperature ( T C o r e ) is in the range 31–35 °C, the real body temperature is obtained by compensating the difference between the core temperature and 35 °C proportionally. When the measured core temperature is 35–40 °C, no further revision is required. If the measured core temperature is outside the above ranges, it is assigned with a constant value of 36.0 °C, as explained below. According to Reference [ 27 ], humans are warm-blooded animals, and the normal body temperature (no disease) of an adult human range between 35.0 and 37.0 °C based on forehead temperature measured by an infrared temperature gun. Therefore, all abnormal body temperatures were converted to the average human body temperature of 36.0 °C in this study.

Finally, similar to the process used for the heart rate and skin resistance signals, the body temperature data are also processed by a moving-average program that calculates the average value of 60 temperature measurements. Equations (3) and (4) are used to yield the final body temperature of the user ( T B o d y ).

2.2.2. Monitoring System End

After the user’s information is transmitted from the wearable device to the monitoring system, it is imported by the monitoring system to the fuzzy controller designed in this study. The physiological information measured by the sensors and collected by the microcontroller, such as skin resistance, safety factor, human body temperature, and heart rates, is used as input variables for performing fuzzy inference based on a fuzzy rule database, after these input variables are fuzzified. The final results are defuzzified to yield the instantaneous risk level of the user automatically. The details of this process can be found in our previous work [ 21 ]. Additionally, a human–machine user interface (UI) was developed by combining the back-end monitoring system with a C# program. This UI is used to display the physiological information of the user.

2.3. Experiment

This section discusses the experimental process and compares data measured in static conditions (before exercising) and dynamic conditions (during exercise) to confirm the applicability of the WHDD.

2.3.1. Static Experiment

Heart rate and body temperature are the two most important indices for detecting heat stroke [ 28 , 29 ]. To validate the accuracy of these two indices, as measured using the proposed device, we performed a 90-s static experiment. The original heart rate and body temperature measured by the sensors were compared with the results obtained after applying the numerical-filtering algorithm and the conversion formula proposed in this paper. Such a comparison allows us to evaluate the stability of the sensor and the performance of the filtering algorithm. Additionally, the values recorded by the heart rate and body temperature sensors every 10 s were also compared with measurements obtained with existing commercial products to verify the accuracy of our device. Specifically, the CK-102S [ 30 ] instrument, purchased from CHANG KUN, was used to measure the heart rate with a ±5% accuracy. The UE-0042 [ 31 ] instrument, purchased from nac nac, was used to measure the ear temperature with a ±0.2% accuracy. The deviation between the raw values detected by each sensor and those obtained from the commercial instruments were explored by experiments.

2.3.2. Dynamic Experiment

Four adults between the ages of 25–37 participated in the dynamic experiment, as shown in Table 4 . The participants were required to wear the WHDDs and run on a treadmill for 15 min in an indoor environment with a temperature of 28.9 °C and a humidity of 68.2%. The participants performed the exercise at different intensities. The entire test comprised three stages, including warm-up (running at 8 km/h for 10 min), accelerating (running at 10 km/h for 2 min), and intense exercise (running at 12 km/h for 3 min). Increases in running intensities will increase the discomfort of the runners, but the amount of discomfort felt by each individual will be different because they have different levels of fitness. Therefore, the users could press the button on the device to send feedback when they felt uncomfortable while running. This feedback was used for experimental data analysis and validation.

Physiological differences between users.

Additionally, when the user was running, the movement of the arm caused the wearable device to loosen, which resulted in errors in the sensor measurements. Although such a scenario was inevitable, the filtering algorithm could detect and remove these abnormal signals. Particularly, because the heart rate and body temperature were measured by non-intrusive methods, their values suffered from the greatest errors. Furthermore, because the heart rate and temperature sensors were only fixed on the skin surface, they could be affected substantially by the user’s motion. Therefore, the commercial product HRM-Ru [ 32 ] was used to obtain the heart rate under exercise conditions, as shown in Figure 6 . A FLIR ONE [ 33 ] thermal camera was used together with a smartphone application to obtain the instantaneous body temperature, as shown in Figure 7 . These measurements were compared with those obtained by the WHDD.

Heart rate data measured with the commercial heart rate belt.

Thermal camera and measured dynamic body temperature map.

To probe the effectiveness of the WHDD in outdoor exercises, an outdoor running test was conducted with five adults in the evening. The test environment was a standard 400 m track, and the ambient temperature and humidity were 23.5 °C and 80%, respectively, which is equivalent to an environmental danger coefficient of 31.5. The test was carried out by having the test subjects run five continuous laps (2 km) around this track within their individual limits. The physiological differences between the test subjects are shown in Table 5 .

Physiological differences between users for outdoor experiment.

3.1. Static Experiment

3.1.1. heart rate.

As shown in Figure 8 , all the original heart rate values fall within the normal range (50–90 bpm) [ 22 ] when the user is at rest. The data obtained after filtering by the microcontroller were found to overlap with the original data. This finding suggests that the sensor can measure the heart rate accurately when the user is at rest. Additionally, no significant measurement fluctuation was observed during the test and there was almost no difference between the original data and the filtered data.

Comparison between original and filtered heart rate when the user was at rest.

Additionally, the average heart rate measured using the commercial wrist sphygmomanometer was approximately 56 bpm. The differences between the data measured using the commercial instrument and the data measured using the WHDD after filtering are summarized in Table 6 . These results show that the average difference between the measurement obtained using the commercially available sphygmomanometer and the device developed in this study is approximately 0.1. Therefore, the sensor integrated in the WHDD can be used to measure the heart rate.

Errors of the heart rates measured in this experiment with respect to data measured using a commercially available sphygmomanometer.

3.1.2. Body Temperature

As shown in Figure 9 , no significant difference was observed between the original data measured by the sensor and the filtered data when the user was at rest. This is primarily because all of the body temperatures obtained after conversion are within a reasonable range (between 35 °C and 40 °C), with an average value of approximately 36.5 °C. Additionally, we see in the figure that the sensor measurement is rather stable when the user is at rest. The maximum error was less than 1 °C, which confirms that the sensor integrated in our device can be used to measure body temperature.

Comparison between the original and filtered body temperature when the user was at rest.

Next, a commercial infrared ear thermometer was used to measure the body temperature when the user was at rest. The average body temperature measured by the commercial instrument varied by 0.14 °C from the temperature measured by the proposed device. The error comparison is shown in Table 7 .

Difference between the body temperature measured in this experiment and that measured using a commercially available infrared temperature gun.

3.2. Dynamic Experiment

3.2.1. heart rate and body temperature.

The heart rate and body temperature exhibited the greatest errors among all the physiological information indices by the sensors. Therefore, the dynamic experiment was focused on investigating these two indices. The heart rates measured by the WHDD during running were compared with those measured using a commercially available commercial heart rate belt and the associated smartphone application. This comparison is shown in Table 8 .

Comparison between heart rates measured with the WHDD and with a commercially available heart rate belt during running.

Next, the dynamic temperature data obtained during running were compared with the instantaneous body temperature measured using a commercial thermal camera in combination with a smartphone application, as shown in Table 9 .

Comparison between body temperatures measured with WHDD and with a commercially available infrared temperature gun during running.

3.2.2. Heat Stroke Risk Indicator

Figure 10 shows a comparison between the physiological data and the feedback signals of the four users during running. Here, user 5 and user 1 are the same participant. Because the change in environmental temperature and humidity were negligible and all of the users exercised under suitable temperature and humidity conditions, the relationship between the environmental temperature/humidity and heat stroke risk are not discussed in this paper.

Comparison between the physiological data and the feedback signals of the four users during running. ( a ) Galvanic skin response (GSR); ( b ) body temperature; ( c ) heartbeat; and ( d ) heatstroke risk level.

First, we found that the data associated with user 5 was very different from those associated with the other four users because they did not undergo the filtering process developed in this study. Instead, these data were extracted directly from the raw measurements to predict the heat stroke risk level. Particularly, the body temperature and heart rate of user 5 varied more significantly from those of the other four users. Although the data still exhibited a reasonable trend, in accordance with the model of an individual performing exercise, the large data fluctuations in a continuous time period resulted in large fluctuations in the heat stroke risk indicator. Therefore, very different heat stroke risk predictions are provided by the device in a short time. Such a high instability issue could cause the user and the system to make wrong assessments. In contrast, the data associated with the other four users were very stable. Therefore, the heat stroke risk levels were also found to be stable for these users.

Next, a detailed analysis was performed on the conditions of the remaining four users. As shown in Figure 11 and Figure 12 , both user 3 and user 4 provided “uncomfortable” feedback to the system, while user 1 and user 2 did not provide any uncomfortable feedback during the exercise. The results were divided into two groups based on the feature of “uncomfortable” and analyzed by comparing the numerical values. With respect to the change in skin inductance (skin resistance), both data groups showed a stable condition in the measurements. This finding indicates that all four users experienced continuous sweating while running. Therefore, the skin resistance changed accordingly during the process. However, the skin inductance of individual was determined by the reference value of the static skin resistance. In other words, the skin resistance is always different for different individuals. Therefore, we infer that the occurrence of uncomfortable conditions in this group was apparently not caused by the lack of sweating but by other physiological factors.

Comparison of skin inductance values in the testing group that did not report uncomfortable conditions (user 1 and 2). ( a ) Galvanic skin response (GSR); ( b ) body temperature; ( c ) heartbeat; and ( d ) heatstroke risk level.

Comparison of skin inductance values in the testing group that reported uncomfortable conditions (user 3 and 4). ( a ) Galvanic skin response (GSR); ( b ) body temperature; ( c ) heartbeat; and ( d ) heatstroke risk level.

Figure 13 shows the results of the outdoor WHDD experiment. Because the physical condition of each test subject was different, the durations in which they completed the 2-km run were all different. User 1, who exercises regularly, completed the 2-km run in the shortest amount of time, whereas User 5, who had the worst physical condition, required the longest duration of time to complete the run. Furthermore, because the environmental danger coefficient of this experiment was lower than that of the indoor experiment (31.5 versus 35.72), it was observed that the risk of heat stroke in this low-risk environment, as evaluated by the WHDD system, was generally lower than that of the indoor experiment.

Comparison between the physiological data and the feedback signals of the five users during running outdoors. ( a ) Galvanic skin response (GSR); ( b ) body temperature; ( c ) heartbeat; and ( d ) heatstroke risk level.

4. Discussion

The rise of body temperature is a common phenomenon for humans when running. Additionally, the highest temperature of all four users never reached a dangerous level (40 °C). This finding suggests that the central control of the human body functions properly to maintain a normal body temperature. However, close examination reveals that the body temperatures of the users in the first group were higher than those in the second group. Although their body temperatures were still within a normal range, a high body temperature can still significantly increase the risk of heat stroke in the calculation. Nevertheless, no substantial difference in body temperature was observed between different users. Therefore, the body temperature is unlikely to be the factor causing an uncomfortable feeling. However, a reasonable guess is that if all four users keep running continuously, there is a high possibility that the body temperature of some users will eventually exceed 40 °C. This could result in a significant increase in heat stroke risk and to a dangerous situation.

The last physiological factor, the “individual heart beat,” is presumed to be the main factor causing an uncomfortable feeling. It can be seen in the Figure 10 that the conditions of all four users are rather normal during the initial stage—particularly, in the first 10 min, when the users were jogging at 8 km/h. When the users started running at 10 km/h, a significant increase in heart rate was observed for users 2, 3, and 4. This phenomenon is consistent with the physiological changes that occur in the human body when performing exercise. No uncomfortable condition was observed during this stage, which indicates that the heart rate of each user was within a reasonable range associated with exercise. When the users started running at 12 km/h, the heart rate of user 3 was found to increase greatly and to be considerably higher than that of the other three users. Next, an uncomfortable signal was sent from user 4 when the total exercise time approached 800 s. Afterwards, the heart rate of user 4 increased suddenly as well. Although the increased heart rate of user 4 was still lower than that of user 3, it was still much higher than those of the other two users. Although the heart rate of user 2 was also rather high, it only increased slightly and remained mostly stable during the stage in which the users were running at 12 km/h. This indicates that the high heart rate associated with the exercise load was still acceptable for the user.

By combining the physiological information and the feedback signals of each user, three conclusions can be drawn from the study:

First, from the perspective of individual data, it can be seen that the heat stroke risk indicator of the users who gave uncomfortable feedback falls within the alert (21–30) and dangerous (31–40) zone. For the users that did not give uncomfortable feedback, however, the highest heat stroke risk indicator falls only within the alert zone (21–30). Therefore, we conclude that the heat stroke risk indicator obtained by the fuzzy controller can be used as a reference for predicting the danger of heat stroke. However, the actual body condition of an individual with a heat stroke risk indicator in a fuzzy area (e.g., the alert zone) can only be known by questioning the person. Only by doing so can we determine the possibility of heat stroke for this individual.

Second, from the perspective of individual data, the physiological factor and the actual physiological reaction of each individual are found to be in good agreement. We can infer with confidence that the heart rate is the major reason causing the uncomfortable feeling to the user. A second factor is the body temperature, which incurs a reaction slightly later than the reaction induced by the heart rate. This is because the rise of body temperature is a normal phenomenon for humans performing exercise. A body temperature reaching 39 °C can still be considered as normal. However, if the individual keeps running with a high heart rate (high load), the body temperature will inevitably rise to a dangerous level. The last factor related to heat stroke is the skin resistance. The reaction induced by skin resistance occurs even later than that induced by body temperature. This is because the human body must dissipate excessive heat by sweating to maintain a constant temperature. The skin resistance starts changing significantly (decrease from large to small, accompanied by a reduction in sweat) only when the body temperature becomes too high. This scenario indicates a shift from normal sweating to a no-sweating condition. Therefore, the heat cannot be dissipated effectively from the human body. At this stage, the user is most likely already affected by heat stroke. Therefore, it is necessary to use the WHDD to predict the possibility of heat stroke and the associated uncomfortable symptoms for a particular user. In this case, an appropriate reminder can be provided to the user to avoid suffering a heat stroke.

A systematic assessment of the relationship between the heart rate, body temperature, and heat stroke risk value was performed. The heat stroke risk value was calculated by the fuzzy controller. Fuzzy theory is mainly based on expert systems—i.e., the experience of the user—whereas the fuzzy rules are obtained from the literature, users’ feedback, and repetitive tests. In the previous section, an analysis of the numerical values obtained from the actual experiments was performed based on Figure 10 . From this analysis, we can obtain the order of reaction to each physiological factor associated with heat stroke, which is: heart rate > body temperature > skin resistance. Therefore, a similar result is expected when analyzing the relationship between heart rate and temperature with heat stroke risk using the heat stroke fuzzy controller designed in this study. Figure 14 shows the relationship between these three factors, obtained by analyzing the results in MATLAB, as the figure clearly shows that the slope associated with the relationship between heart rate and heat stroke is much larger than that associated with the relationship between body temperature and heat stroke risk. This finding also confirms that the device developed in this study can truly reflect the possibility of suffering heat stroke during exercise for an individual with certain physiological characteristics.

Three-dimensional relationship map between heart rate, temperature, and heat stroke risk level.

Subsequently, the feedback of the users who reported an uncomfortable feeling was compared and validated against the predictions of our system. The analysis of the comparison shown in Figure 15 yields the results shown in Table 10 and Table 11 . Based on the data of user 3, the system indicates a “dangerous” condition after 816 s. This prediction is 84 s (1 min 24 s) later than the first feedback provided from the user (732 s). For user 4, however, the system indicates a “dangerous” condition starting at 814 s. This prediction is only 2 s earlier than the first feedback provided by user 4 (816 s). Based on the analysis results on these two individuals, we can first conclude that the heat stroke detection function of our system can be affected by the physiological differences between different individuals and their distinct exercising habits. However, the system developed in this study is capable of detecting potential heat strokes. If the time factor is excluded, our system can effectively reflect the physiological condition of a user, predict the possibility of suffering heat stroke, and assist in cases of danger. To resolve the issue of the differences between different individuals, we can modify the parameters of the fuzzy controller according to the characteristics of the individual. Thus, the system can be revised to better match the condition of a particular individual. In the future, we expect to introduce the concept of machine learning to our system, which can automatically correct the associated parameters and therefore resolve this issue.

Comparison of heat stroke risk indicators for users feeling uncomfortable during the experimental tests (users 3 and 4).

Comparison between feedback data and system prediction results for user 3.

Comparison between feedback data and system prediction results for user 4.

5. Conclusions

Based on our previous work of a designed and implemented WHDD, this study performs further static and dynamic experiments to verify the availability and effectiveness of WHDD. In the static experiment, the heart rate and body temperature parameters are corrected by applying the proposed filtering algorithm. In addition, various intensity running experiments are conducted on several runners who wore the WHDD. The experimental results show that the WHDD can successfully identify the high-risk trends of heat stroke when the runners respond to discomfort information, so the device can effectively predict the occurrence of heat stroke and ensure the safety of runners.

Acknowledgments

The authors thank the financial support from Ministry of Science and Technology of Taiwan, R.O.C. with Grant number. MOST-107-2221-E-606-012.

Author Contributions

All the authors work at the design and realization of the work. S.-S.L. developed the idea of the proposed plan and directed the experiments. C.-W.L. supervised both the technical and experimental activities. H.-Y.H. integrated the electronic measurement devices with the wearable sensors and performed the experiments. S.-T.C. wrote the paper and made all revisions.

This research was funded by Ministry of Science and Technology of Taiwan, R.O.C. with Grant number MOST-107-2221-E-606-012.

Conflicts of Interest

The authors declare no conflict of interest.