Clinical Profile and Outcome of Heat-Stroke Patients Presenting to the Emergency Department of a Tertiary Care Center in Eastern Part of India

Abstract

Background

Heat stroke represents a growing public health concern, exacerbated by rising temperatures and prolonged heat waves. This study examines the clinical profile, prognostic markers, and outcomes of heat stroke patients presenting to a tertiary care center in India and compares findings with previous global studies.

Objective

To analyze the clinical profile, prognostic markers, and outcomes of heat stroke patients presenting to a tertiary care center in India and to compare findings with previous global studies.

Methods

A retrospective study was conducted between March to July 2024. Data on demographics, clinical parameters, laboratory values, and outcomes were collected and analyzed. Primary outcomes were mortality and functional recovery. Statistical tests included chi-square, Mann-Whitney U test, and multivariate logistic regression.

Results

Among 43 patients, the mean age was 57 years, and 67% were male. The overall mortality rate was 21%. Significant predictors of mortality included hypotension (SBP <100 mm Hg, p = 0.040), tachypnea (RR >20/min, p = 0.001), Glasgow Coma Scale score <9 (p < 0.001), elevated creatinine, and multi-organ dysfunction syndrome (MODS) involving renal and CNS systems (p < 0.01). Middle-aged, active individuals were disproportionately affected due to occupational exposure to high ambient temperatures.

Conclusion

Our findings highlight key clinical and biochemical predictors of poor outcomes in heat stroke. Indian patients who are middle-aged individuals, possibly exposed due to outdoor occupations, may face greater exposure to high ambient temperatures.

Keywords

Introduction

Heat stroke is defined by the World Health Organization (WHO) as a medical emergency characterized by elevated core body temperature above 40 °C, accompanied by central nervous system dysfunction—such as confusion, delirium, seizures, or coma—resulting from exposure to high environmental temperatures or strenuous physical activity. It can lead to multiple organ failure and death if not treated promptly.¹ In eastern India, characterized by high temperatures often exceeding 40–45 °C during summer months and intense humidity, heat stroke has become a significant public health concern.¹

The increasing frequency and intensity of heat waves in India over recent decades have amplified the burden of heat-related illnesses. In 2022, approximately 730 heat stroke–related deaths were reported nationwide, nearly double the fatalities from the previous year and surpassing the decade's annual average of 1100 deaths.² These events highlight the disproportionate impact of extreme heat on specific regions, with eastern India bearing a substantial portion of the burden. In contrast, military populations and athletes have been extensively studied for exertional heat stroke globally, but in India, non-exertional, community-acquired heat stroke remains predominant.

Compounding factors such as rapid urbanization, inadequate housing, and limited public awareness have worsened the situation. Gender disparities also exist, with men disproportionately affected; between 2011 and 2015, 5157 men and 1254 women succumbed to heat-related causes.

Despite the alarming rise in heat-stroke cases, there is limited research on the demographic and clinical profiles of affected individuals in eastern India.^3,4 This study aims to bridge this gap by examining the burden, clinical presentations, and outcomes of heat stroke in the region. By identifying high-risk groups and emphasizing the need for timely interventions, the study provides a region-specific analysis to guide effective preventive and management strategies for mitigating the impact of heat waves in eastern India.

Materials and Methods

This was a retrospective study conducted in the emergency department (ED) of a government-run, publicly funded tertiary care teaching hospital (AIIMS Patna) located in the eastern part of India. The study was approved by the Institutional Ethics Committee (AIIMS/Pat/IEC/2024/1318). The hospital is equipped with an advanced electronic medical record (EMR) system, which was utilized to identify eligible patients.

Study Population

Patients presenting to the ED with a confirmed diagnosis of heat stroke as per WHO criteria,¹ during the period from March 2024 to July 2024, were included. Patients with alternative diagnoses or incomplete medical records were excluded. The study employed a convenient sampling method, where all patients meeting the inclusion criteria during the study period were recruited. A total of 43 patients were included in the final analysis.

Data Collection

Patient data were extracted from the hospital's EMR system using a predefined data extraction form. Cases were identified using ICD-10 codes and keywords, and manual verification was performed to confirm the diagnosis based on clinical records. Recorded variables included demographics such as age, sex, and comorbidities; clinical parameters included initial vital signs (heart rate, blood pressure, respiratory rate, and temperature), Glasgow Coma Scale (GCS) score, and presenting symptoms. The J-ERATO (Japanese Early Risk Assessment Tool for detecting clinical Outcomes) score was calculated for each patient based on initial ED values, using parameters such as respiratory rate (≥22/min), Glasgow Coma Scale (<15), systolic blood pressure (≤100 mm Hg), heart rate (≥100 bpm), body temperature (≥38 °C), and age (≥65 years).⁵ Laboratory investigations included renal function tests (blood urea, serum creatinine), liver enzymes (alanine transaminase, aspartate transaminase), prothrombin time (PT), and international normalized ratio (INR). Outcomes were assessed in terms of mortality, the need for intensive care unit (ICU) admission, and intubation requirements.

Renal dysfunction was defined as serum creatinine ≥1.5 mg/dL or need for dialysis. Hepatic dysfunction was defined as ALT/AST >3 times the upper normal limit. Coagulation dysfunction was defined as INR >1.5 or PT prolongation >5 s above control.

Statistical Analysis

Data were compiled and analyzed using statistical software (SPSS version 24.0, Chicago, IL, USA). Categorical variables, such as sex and comorbidities, were expressed as frequencies and percentages. Comparisons between groups (eg, survivors vs nonsurvivors) were conducted using the chi-square or Fisher's exact test, as appropriate.

Continuous variables, such as age, temperature, and laboratory values, were tested for normality using the Shapiro-Wilk test. Normally distributed data were expressed as mean ± standard deviation (SD) and compared using the Student's t-test, while nonnormally distributed data were presented as median (interquartile range, IQR) and analyzed using the Mann-Whitney U test.

Multivariate logistic regression analysis was performed to identify independent predictors of mortality, including clinically significant variables from univariate analyses and those with p-value <0.2. Odds ratios (OR) with 95% confidence intervals (CI) were reported. A p-value <0.05 was considered statistically significant.

Ethical Considerations

The study adhered to the ethical guidelines. Informed consent was waived due to the retrospective nature of the study. Patient confidentiality was maintained by anonymizing data during collection and analysis.

Results

In this study, 43 patients with heat stroke were analyzed, with a mean age of 57 ± 17 years. Males accounted for 67% of the cohort, and the overall mortality rate was 21% (n = 9). Key clinical parameters strongly associated with mortality included hypotension (SBP <100 mm Hg, p = 0.040), tachypnea (RR >20/min, p = 0.001), and a Glasgow Coma Score (GCS <9 OR 5.8 [CI 1.8–18.4]) at presentation (p < 0.001). Patients with a J-ERATO score ≥4 exhibited markedly increased rates of ICU admission (85%) and mortality (33%) compared to those with scores ≤2 (ICU admission: 15%, mortality: 3%). The baseline characteristics of the participants and the association between GCS and mortality are summarized in Table 1.

Table 1.

Showing baseline characteristics of participants.

Parameters	Nonsurvivors N = 9	Survivors N = 34	p-Value
Age (years)	60 (17)	55 (17)	0.5
Sex			>0.9
Female	3 (33%)	11 (32%)
Male	6 (67%)	23 (68%)
Systolic blood pressure (mm Hg)			0.040
<100	6 (67%)	8 (24%)
>100	3 (33%)	26 (76%)
Diastolic blood pressure (mm Hg)			0.030
<80	7 (78%)	12 (35%)
>80	2 (22%)	22 (65%)
Respiratory rate (per min)			0.001
<20	1 (11%)	25 (74%)
>20	8 (89%)	9 (26%)
Glasgow coma score			<0.001
<9	7 (78%)	3 (8.8%)
9–13	2 (22%)	11 (32%)
>13	0 (0%)	20 (59%)
J-ERATO score	5 (5, 6)	2 (2, 4)	<0.001

Comorbidity analysis revealed significant differences between survivors and nonsurvivors. Diabetes mellitus was present in 78% of those who died compared to 41% of those discharged, though this was not statistically significant (p = 0.069). Hypertension was observed in 33% of deceased patients and 56% of discharged patients (p = 0.3). Chronic kidney disease, however, showed a significant association with mortality, being present in 22% of patients who died and absent among those discharged (p = 0.040). Chronic liver disease was relatively rare, affecting 11% of deceased patients and 8.8% of those discharged, with no significant difference (p > 0.9).

Laboratory parameters of the study participants are detailed in Table 2, while outcomes based on the involvement of multiple organ dysfunction syndrome (MODS) are presented in Table 3. Furthermore, comparisons of ICU admission rates, intubation requirements, and length of hospital stay are summarized in Table 4.

Table 2.

Showing laboratory parameters of Participant.

Lab Parameters	Nonsurvivors N = 9	Survivors N = 34	p-value
Hemoglobin(gm%)			0.3
<10	4 (44%)	7 (21%)
>13	1 (11%)	5 (15%)
10–13	4 (44%)	22 (65%)
WBC(1000/cc)	22 (17, 26)	11 (7, 14)	0.001
Platelet(lac/cc)			0.065
<1.5 lac	8 (89%)	18 (53%)
1.5–4 lac	1 (11%)	16 (47%)
Urea (mg/dl)	91 (64, 214)	32 (21, 46)	<0.001
Creatinine (mg/dl)	3.00 (3.00, 5.64)	0.90 (0.63, 1.00)	<0.001
Na(meq/l)	134 (7)	130 (11)	0.2
K (meq/l)	4.47 (0.92)	3.43 (0.70)	0.010
AST (U/l)	270 (172, 385)	58 (31, 219)	0.018
ALT (U/l)	103 (98, 117)	54 (23, 121)	0.041
ALP (IU/l)	111 (48, 139)	89 (58, 135)	0.7
PT (sec)	25.0 (20.4, 28.0)	17.0 (15.0, 19.7)	<0.001
INR	2.00 (1.60, 2.20)	1.30 (1.00, 1.60)	<0.001

Table 3.

Outcome in participants based on MODS involving system.

Organ Systems	Nonsurvivors N = 9	Survivors N = 34	p-Value
Renal	8 (89%)	3 (21%)	0.003
CNS	7 (78%)	2 (14%)	0.007
Coagulation system	9 (100%)	12 (86%)	0.5
Hepatic	6 (67%)	6 (43%)	0.4
CVS	1 (11%)	3 (21%)	>0.9
Respiratory	6 (67%)	5 (36%)	0.2

Table 4.

Elements of hospital course in Participants.

Variables	Nonsurvivors N = 9	Survivors N = 34	p-Value
Admitted to ICU	9 (100%)	4 (12%)	<0.001
Intubated	9 (100%)	4 (12%)	<0.001
Length of hospital stay (days)	2 (1)	6 (5)	<0.001
External cold sponging given	9 (100%)	33 (97%)	>0.9

The monthly distribution of heat-stroke admissions showed a peak in May and June, with the highest number of cases in May (n = 18), correlating with extreme temperatures recorded during this period. Cooling measures included external cold sponging, ice packs, and cold saline gastric lavage. Cold-water immersion was not feasible due to infrastructural limitations.

Discussion

Heat stroke remains a significant medical emergency with high mortality and morbidity, particularly in tropical regions like Eastern India, where extreme summer temperatures prevail. This study highlights the clinical and biochemical predictors of mortality among heat stroke patients, emphasizing the unique demographic and environmental characteristics of the region. Also, wet bulb temperatures, which combine humidity and heat, are better predictors of heat stroke risk than dry temperatures alone. Their integration into public health early warning systems is warranted to reduce heat stroke morbidity and mortality.

Study Rationale and Sampling Period

The study's sample collection was limited to March through July 2024, coinciding with the peak summer season in Patna, Bihar (recorded a maximum temperature of 46.8 °C on May 28, 2024). These months are characterized by high temperatures often exceeding 40 °C and intense humidity, conditions that significantly increase the risk of heat stroke. Literature indicates that the highest incidence of heat stroke occurs during summer months due to prolonged exposure to elevated temperatures and reduced cooling efficacy of the body's thermoregulatory mechanisms.^5,6

Demographics and Clinical Features

The mean age in our study (57 years) was considerably lower compared to Argaud et al (79.6 years)⁴ and Misset et al (67.2 years),³ where elderly populations with functional limitations were primarily affected. However, a study conducted by Mahavar et al in 2024, which was conducted in the Indian population, had a mean age of 54.6 years. Both studies reported a male predominance (67% vs 74%), consistent with occupational exposure trends in India. This reflects occupational vulnerability among younger, active individuals in India exposed to high ambient temperatures.⁶

Neurological Dysfunction

CNS involvement (GCS <9) was a significant predictor of mortality (78%, p < 0.001). This aligns with previous findings by Dematte et al⁷ and Argaud et al,⁴ who reported neurological impairment in 33% of survivors. Compared to the study on the Indian population, both studies emphasize CNS dysfunction as a hallmark of severe heat stroke. While Mahavar et al highlight leukocytosis and elevated ALT as prognostic markers, our study focuses on systemic predictors like MODS and hypotension.

MRI studies have demonstrated ischemic changes in the cerebellum, basal ganglia, and hippocampus, consistent with patterns observed globally. Argaud et al.⁴ reported higher mortality (40%) in older, comorbid patients with more profound neurological impairment. In contrast, our patients, though younger, faced substantial CNS dysfunction due to direct heat exposure.

The findings of this study reinforce the prognostic utility of the J-ERATO score in heat-stroke management. The strong correlation between higher J-ERATO scores and adverse outcomes in this study aligns with the findings of Hayashida et al, who validated the score in a Japanese cohort. In our cohort, parameters such as low Glasgow Coma Scale, tachypnea, and hypotension were significant predictors of mortality. The J-ERATO score's simplicity allows for its integration into prehospital and ED settings, enabling early identification of high-risk patients who may benefit from intensive monitoring and intervention.

Renal Dysfunction

Renal injury occurred in 89% of nonsurvivors, significantly higher than the 30%–35% reported by Kalaiselvan et al.⁸ Volume depletion, renal artery vasoconstriction, and rhabdomyolysis were likely contributors to acute kidney injury (AKI). In a study by Bouchama et al,⁹ rhabdomyolysis with myoglobinuria was identified as a primary mechanism for AKI in HRI patients. In our cohort, 3 of 5 dialysis-requiring patients demonstrated myoglobinuria.

Liver Dysfunction and Coagulation Abnormalities

Our study revealed elevated liver enzymes (AST/ALT) and prolonged PT/INR in nonsurvivors. This finding mirrors reports by Argaud et al, who observed 40% ALT elevation during the French heat wave.⁴ Hepatic injury likely resulted from splanchnic ischemia and direct thermal injury.¹⁰ Coagulation abnormalities, though mild in our study, were more severe in Misset et al, where 65% required vasopressor support due to systemic vasoplegia.³

Mortality Rates and Predictors

The mortality rate in our study (21%) lies within the reported range of 20%–62% seen in prior studies.^10,11 Key predictors of mortality include:

Hypotension (SBP <100 mm Hg)

Tachypnea (RR >20/min)

CNS dysfunction (GCS <9)

MODS involving renal and CNS systems

Compared to studies by Misset et al, our patients demonstrated better outcomes with a lower mechanical ventilation rate (64% vs 99%) and shorter ICU stay.

Comparative Analysis

While studies from developed countries highlight the impact of comorbidities and advanced age on heat-stroke outcomes, this study reveals a different risk profile driven by environmental and occupational factors. Younger patients in India experience substantial organ dysfunction directly attributable to extreme heat exposure, reflecting the socioeconomic and climatic disparities between regions.^3,4,12

Implications for Practice and Policy

This study underscores the importance of early identification of clinical and biochemical predictors of mortality in heat-stroke patients. Public health strategies should focus on:

Raising awareness about heat stroke among vulnerable populations.

Establishing early warning systems during peak summer months.

Implementing rapid cooling protocols and adequate hydration strategies in emergency settings.

Strengths and Limitations

This study provides region-specific insights into the clinical and laboratory predictors of heat stroke outcomes in Eastern India. However, it is limited by its retrospective nature, small sample size, single-center design, lack of environmental data such as wet bulb temperatures, and missing documentation on clothing, hydration, and occupational exposure. Longer, multicenter observational studies are needed for broader generalizability.

Conclusion

Our study demonstrates that heat stroke primarily affects middle-aged individuals in India, with significant morbidity and mortality driven by renal and CNS dysfunction. Early recognition of predictors such as hypotension, tachypnea, and GCS <9 can enable prompt interventions. Preventive strategies targeting occupational heat exposure and improved cooling measures are essential.

Footnotes

Author Contribution(s)

Divendu Bhushan: Conceptualization; Data curation; Formal analysis; Formal analysis; Investigation; Methodology; Project administration; Resources; Software; Supervision; Validation; Visualization; Writing – original draft; Writing – review & editing.

Muskan Dogney: Conceptualization; Methodology; Resources; Writing – original draft.

Deepak Kumar: Conceptualization; Data curation; Formal analysis; Formal analysis; Investigation; Methodology; Project administration; Resources; Software; Supervision; Validation; Visualization; Writing – original draft; Writing – review & editing.

Mohammed Iqbal AN: Data curation; Methodology; Visualization; Writing – original draft; Writing – review & editing.

Vishal Vaibhaw: Conceptualization; Data curation; Visualization; Writing – original draft.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Deepak Kumar

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National Health Mission, Ministry of Health and Family Welfare, Government of India. Climate and Health Profile for India: Heat Wave Impact Assessment. Ministry of Health and Family Welfare; 2024.

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