Abstract
Background
Coma has been considered as a valuable symptom of heatstroke. This study aimed to evaluate the role of the Glasgow Coma Scale (GCS) as an indicator of prognosis of patients with heatstroke.
Material/Methods
From Jan 1st, 2013 to Dec 31st, 2020, the clinical courses of 257 heatstroke patients from 3 medical centers in Guangdong, China, were observed. Diagnosis of heatstroke was made according to Expert Consensus in China. GCSs were calculated on the 1st, 3rd, and 5th days after admission to intensive care units (ICUs). GCS ≤8, as a coma criterion, was employed to predict the outcomes.
Results
Seventy-five patients (29.18%) were comatose at admission. Twenty-seven (10.50%) patients, including 24 (24/75, 32.00%) coma patients and 3 (3/182,1.65%) non-coma patients died during ICU stay (P<0.0001). Patients with GCS ≤8 had a 2-fold higher risk of death as compared with those with GCS >8. The area under curves (AUCs) of GCSs on the 1st, 3rd, and 5th days to predict mortality were 0.81 (0.70–0.91), 0.91 (0.84–0.98), and 0.91 (0.82–0.99), respectively. Each additional 1 year of age, 1/min of respiratory rate (RR), and 1% of hematocrit (HCT) increased the risk of death of coma patients by 3%, 6%, and 4%, respectively (all P≤0.05). Patients with improving GCSs had lower mortality rates than non-improving patients (5.71% vs 55.00%, P<0.0001) within 5 days after admission.
Conclusions
GCS ≤8 at admission predicted worse outcomes in heatstroke patients, which possibly enhanced the risks of death for other factors, including age, RR, and HCT.
Keywords: Glasgow Coma Scale, Heat Stroke, Mortality, Prognosis
Background
Heatstroke has attracted the attention of clinicians for about 100 years. In 1886, 48 heatstroke patients with a 52% mortality rate were reported in the Assouan area of Egypt due to a heatwave [1]. Since clinicians found that brain injury was a common phenomenon in heatstroke in 1888 [2], coma has been considered as a valuable symptom in subsequent studies [3]. Although still controversial, the definition of heatstroke proposed by Dr. Bouchamais, which defined it as a core body temperature over 40°C and which induced multiple organs dysfunction dominated by central nervous system abnormalities such as delirium, convulsion, or coma, is used clinically [4,5]. The impact of an extremely hot environment on health has become a growing concern and a burden on public health [6]. According to the data provided by the largest emergency department (ED) data system from 2009 to 2010 in the USA, the number of emergency visits because of heatstroke was estimated to be 8251, 54.6% of whom needed hospitalization, and 3.5% of whom died in EDs or hospitals [7]. In a recent study, 1152 cases of severe heatstroke with 10% mortality were reported from 2013 to 2017 in Shanghai, China [8]. It is particularly important to explore the high-risk factors for poor outcomes in heatstroke. Central nervous system abnormalities, a common phenomenon, may be a potential risk factor for poor outcomes in heatstroke [9]. A cohort study assessed the prognostic factors of heatstroke, which shows Acute Physiology and Chronic Health Evaluation II (APACHE II) score, Sequential Organ Failure Assessment Score (SOFA), and Japanese Association for Acute Medicine (JAAM) Disseminated intravascular coagulation (DIC) score, but not Glasgow Coma Scale (GCS), can predict in-hospital mortality in heatstroke [10]. However, the severity of the patients was mild or moderate, as their mean APACHE II score was below 15, which possibly masked the potential efficacy of the predictors.
Coma, a state of unarousable unconsciousness due to dysfunction of the brain’s ascending reticular activating system (ARAS), which is responsible for arousal and maintaining wakefulness [11], is a common phenomenon in patients with heatstroke. In the early stage of HS, brain CT usually has no positive results. Diffuse edema of the brain parenchyma may appear after 2–5 days. Most brain edema in HS patients is reversible. When the condition is stable, it can gradually disappear after 7–10 days [4]. In some extreme cases, punctate hemorrhages can be found by susceptibility-weighted imaging [12]. Clinically, although many patients had encephalopathy early, they experienced different trajectories depending on whether they had transient or persistent coma; therefore, the clinical picture and kinetics of encephalopathy need to be elucidated in heatstroke. The Glasgow Coma Scale (GCS), introduced in 1974 to standardize assessment of the level of consciousness in brain-injured patients, has been widely used in monitoring neurological status and predicting patient outcome [13]. The GCS consists of 3 parameters: best eye response (E), best verbal response (V), and best motor response (M). The total Coma Score has values of 3–15, with 3 being the worst and 15 being the best [14]. GCS ≤8, a criterion of coma, is associated with severe brain injury and poor prognosis. Neurological injury markers can predict poor prognosis of exertional heat stroke (EHS) [15]. The GCS was selected as one of the predictors of the mortality rate of EHS patients [16]. The EHSS score involves 12 parameters – T, GCS, potential hydrogen value (pH), lactate (Lac), platelet (PLT), prothrombin time (PT), fibrinogen (Fib), troponin I (TnI), aspartate aminotransferase (AST), total bilirubin (TBIL), serum creatinine (SCr), and acute gastrointestinal injury (AGI) classification – with a predictive value with AUC higher than 0.96 [17]. Another study with 763 patients found that GCS and platelets were independent predictors of poor outcomes [18]. The present retrospective study from 3 medical centers in Guangdong, China focused on the kinetics of GCS and its prognostic value in heatstroke patients, aiming to evaluate the role of the GCS as an indicator of prognosis in 257 patients with heatstroke.
Material and Methods
Ethical Statement
The protocol of the study was approved by the Medical Ethics Review Committee of General Hospital of Southern Theatre Command of PLA (No. NZLLKZ2022047). As a retrospective study, the requirement for informed consent was waived.
Study Population
From Jan 1st, 2013 to Dec 31st, 2020, patients with heatstroke admitted to the 3 intensive care units (ICUs) in Guangdong province of China, were retrospectively enrolled. Heatstroke was diagnosed according to the Expert Consensus on Diagnosis and Treatment of Heatstroke in China published by the Expert Group on Prevention and Treatment of Heatstroke and Critical Care Committee of the General Hospital of Southern Theatre Command of PLA [4]. We excluded patients with chronic liver and kidney diseases, chronic cardiac insufficiency, chronic pulmonary insufficiency, underlying central nervous system (CNS) diseases, metabolic disorders, or those using sedation and analgesia medications. Researchers from the 3 centers were trained by doctors from the General Hospital of Southern Theatre Command of PLA. All patients were treated by cooling, fluid resuscitation, and organ support according to their conditions. Antibiotics were also administered if necessary.
Data Collection
GCSs were calculated on the 1st, 3rd, and 5th days after admission. The patients were divided into survival and non-survival groups. GCS ≤8 was considered to be an indicator of coma. The max body temperature (Tmax) out-of-hospital was recorded. The body temperature at admission (Tadmit), heart rate (HR), respiratory rate (RR), mean artery pressure (MAP), and laboratory indexes at 1st, 3rd, and 5th days were also recorded. APACHE II and SOFA scores were determined to evaluate the disease severity. Baseline demographic characteristics were recorded at admission (day 1). Representative brain computed tomography (CT) from surviving and non-surviving patients was employed to evaluate the severity of brain injury.
Statistical Analysis
Means (M)±standard deviations (SD) of outcome measurements were calculated and compared using R language with EmpowerStats 2.0 software, and forest plots were drawn using Python 3.8. Repeated measurements were analyzed using IBM SPSS Statistics v 20.0 software. Kaplan-Meier (KM) curve and receiver operating characteristic (ROC) curves were employed to assess the prognosing values of GCS. Odds ratio (OR) and 95% confidence interval (CI) were also calculated. P≤0.05 was considered statistically significant.
Results
Characteristics of the Patients
A total of 260 heatstroke patients were admitted to the 3 ICUs during the period covered. Three patients were excluded due to lack of GCS values at admission. The remaining 257 patients (33±15 years old, 90% males) were included. Twenty-seven (10.50%) patients died during ICU stay. GCSs in non-surviving patients (5.67±3.55) were significantly lower than those in surviving patients (12.35±4.05, P<0.0001). Seventy-five patients (29.18%) were comatose (GCS ≤8), of whom 24 (88.89%) died and 51 (22.17%) survived. The rates of mortality in coma and non-coma patients were 32.00% (24/75) and 1.65% (3/182), respectively (P<0.0001). Baseline demographic characteristics of non-surviving and surviving patients are listed in Table 1. HR, MAP, Tmax, and Tadmit at admission in non-surviving patients were all significantly higher than those in surviving patients. Hematocrit (HCT), platelets (PLT), total bilirubin (TBIL), albumin (ALB), serum creatinine (SCr), and creatine kinase isoenzyme (CK-MB) were also significantly worse in non-surviving patients.
Table 1.
Baseline demographic characteristics of non-surviving and surviving patients with heatstroke.
| Non-survival group | Survival group | p-value | |
|---|---|---|---|
| Cases | 27 | 230 | |
| Age (y, M±SD) | 32.89±16.97 | 33.45±14.34 | 0.85 |
| Gender | 0.86 | ||
| male (cases, %) | 26 (10.12%) | 220 (85.60%) | |
| female (cases, %) | 1 (0.39%) | 10 (3.89%) | |
| Coma (cases, %) | 24 (88.89%) | 51 (22.17%) | <0.0001 |
| GCS score (M±SD) | 5.67±3.55 | 12.35±4.05 | <0.0001 |
| APACHE II score (M±SD) | 25.00±10.14 | 9.26±7.24 | <0.0001 |
| SOFA score (M±SD) | 9.63±1.51 | 3.84±3.06 | <0.0001 |
| HR (beat/min, M±SD) | 125.33±29.26 | 88.48±25.64 | <0.0001 |
| RR (breath/min, M±SD) | 23.28±7.32 | 20.96±3.33 | 0.006 |
| MAP (mmHg, M±SD) | 79.49±21.55 | 87.73±14.13 | 0.009 |
| Tmax (°C, M±SD) | 40.87±1.19 | 39.89±1.46 | 0.003 |
| Tadmit (°C, M±SD) | 38.64±1.60 | 37.30±1.25 | <0.001 |
| Laboratory indexes | |||
| Leukocyte(×109/L,M±SD) | 12.61±5.23 | 12.03±5.06 | 0.58 |
| HCT (%,M±SD) | 33.82±13.93 | 41.51±9.02 | <0.0001 |
| PLT (×109/L, M±SD) | 89.15±70.76 | 187.22±89.10 | <0.0001 |
| TBIL (umol/L, M±SD) | 83.01±100.87 | 26.05±34.19 | <0.0001 |
| ALB (g/L, M±SD) | 36.72±6.20 | 43.16±6.90 | <0.0001 |
| SCr (umol/L, M±SD) | 215.18±81.03 | 146.60±85.65 | <0.0001 |
| CK-MB (ng/ml, M±SD) | 162.02±190.11 | 45.00±95.89 | <0.0001 |
GCS – Glasgow Coma Scale; APACHE II score – Acute Physiology and Chronic Health Evaluation II score; SOFA score – Sequential Organ Failure Assessment Score; HR – heart rate; RR – respiratory rate; MAP – mean arterial pressure; Tmax – the max body temperature; Tadmit – the body temperature at admission; HCT – hematocrit; PLT – platelet; TBIL – total bilirubin; ALB – albumin; SCr – serum creatinine; CK-MB – creatine kinase isoenzyme.
Univariate Analysis of Death-Associated Risk Factors at Admission
Tachycardia, hyperthermia, Tmax, coma, and higher TBIL, SCr, and CK-MB at admission were risk factors for death (Table 2).
Table 2.
Univariate analysis of mortality-associated risk factors in heatstroke.
| Exposure | Statistics | Risk of death (95% CI, p-value) |
|---|---|---|
| Age (y, M±SD) | 33.46±14.62 | 1.01 (1.00, 1.02), 0.13 |
| Coma | ||
| Yes (cases, %) | 74 (29.37%) | 1.0 |
| No (cases, %) | 178 (70.64%) | 3.57 (2.55, 4.99), <0.0001 |
| HR (beat/min, M±SD) | 92.57±28.40 | 0.99 (0.98, 0.99), <0.0001 |
| RR (breath/min, M±SD) | 21.26±4.04 | 0.98 (0.94, 1.01), 0.17 |
| MBP (mmHg, M±SD) | 86.92±15.23 | 1.01 (1.00, 1.01), 0.25 |
| Tmax (°C, M±SD) | 40.03±1.46 | 0.80 (0.71, 0.90), 0.0003 |
| Tadmit (°C, M±SD) | 37.45±1.34 | 0.78 (0.69, 0.88), <0.0001 |
| Leukocyte(×109/L,M±SD) | 12.08±5.07 | 1.02 (1.00, 1.05), 0.10 |
| HCT (%,M±SD) | 40.70±9.88 | 1.05 (1.03, 1.07), <0.0001 |
| PLT (×109/L, M±SD) | 176.45±92.53 | 1.00 (1.00, 1.00), <0.0001 |
| TBIL (umol/L, M±SD) | 32.45±49.56 | 0.99 (0.98, 0.99), <0.0001 |
| ALB (g/L, M±SD) | 42.43±7.11 | 1.06 (1.04, 1.09), <0.0001 |
| SCr (umol/L, M±SD) | 153.79±87.45 | 1.00 (1.00, 1.00), 0.02 |
| CK-MB (ng/ml, M±SD) | 55.92±112.78 | 1.00 (0.99, 1.00), <0.0001 |
HR – heart rate; RR – respiratory rate; MAP – mean arterial pressure; Tmax – the max body temperature; Tadmit – the body temperature at admission; HCT – hematocrit; PLT – platelet; TBIL – total bilirubin; ALB – albumin; SCr – serum creatinine; CK-MB – creatine kinase isoenzyme.
Sub-Group Analysis of Co-Effects of Coma on Other Death-Associated Risk Factors at Admission
Among coma patients (GCS ≤8), an additional 1 year of age, 1/min of RR, 1% of HCT, and 1×109/L of PLT increased the risks of death by 3%, 6%, 4%, and 0.3%, respectively (all P≤0.05) (Figure 1).
Figure 1. Sub-group analysis of co-effects of coma on other mortality-associated risk factors.
All patients were grouped according to whether they were comatose or not. Coma (GCS ≤8) was applied as a stratification factor. Among the coma patients, older age and higher RR, HCT, PLT, and CKMB were all harmful factors (OR≥1, and P value less than 0.05) (all P≤0.05). These results indicated that an additional 1 year of age, 1/min of RR, 1% of HCT, and 1×109/L of PLT increased the risks of death by 3%, 6%, 4%, and 0.3%, respectively (all P≤0.05). GCS – Glasgow Coma Scale; APACHE II score – Acute Physiology and Chronic Health Evaluation II score; SOFA score – Sequential Organ Failure Assessment Score; HR – heart rate; RR – respiratory rate; MAP – mean arterial pressure; Tmax – the max body temperature; Tadmit – the body temperature at admission; HCT – hematocrit; PLT – platelets; TBIL – total bilirubin; ALB – albumin; SCr – serum creatinine; CK-MB – creatine kinase isoenzyme. The data of the figure were calculated and compared using R language with EmpowerStats 2.0 software, and the forest plot was drawn using Python 3.8.
Multiple Regression Analysis of Death-Associated Risk Factors at Admission
If adjusted by coma, age and HR became more important factors than Tmax, and SCr to predict heatstroke mortality (Table 3). Coma was a mortality risk factor for patients with heatstroke [OR=3.57 (2.55, 4.99), P<0.0001]. Importantly, if adjusted by age, HR, RR, MAP, Tmax, Tadmit, leukocyte count, HCT, PLT, TBIL, ALB, CR, and CK-MB, coma still had significant effect on mortality [OR=2.01 (1.09, 3.69), P=0.02].
Table 3.
Multivariate logistic regression analysis of risk factors.
| Factors | Non-adjusted OR (95% CI), p-value | Adjust with coma* OR (95% CI), p-value |
|---|---|---|
| Age | 1.01 (1.00, 1.02), 0.13 | 1.02 (1.01, 1.03), <0.0001 |
| HR | 0.99 (0.98, 0.99), <0.0001 | 0.99 (0.99, 1.00), 0.02 |
| RR | 0.98 (0.94, 1.01), 0.17 | 1.00 (0.97, 1.04), 0.86 |
| MAP | 1.01 (1.00, 1.01), 0.25 | 1.01 (1.00, 1.02), 0.07 |
| Tmax | 0.80 (0.71, 0.90), 0.0003 | 0.91 (0.80, 1.04), 0.16 |
| Tadmit | 0.78 (0.69, 0.88), <0.0001 | 0.89 (0.78, 1.01), 0.08 |
| Leukocyte | 1.02 (1.00, 1.05), 0.10 | 1.01 (0.98, 1.04), 0.53 |
| HCT | 1.05 (1.03, 1.07), <0.0001 | 1.04 (1.02, 1.06), <0.0001 |
| PLT | 1.00 (1.00, 1.00), <0.0001 | 1.00 (1.00, 1.00), <0.0001 |
| TBIL | 0.99 (0.98, 0.99), <0.0001 | 0.99 (0.99, 1.00), 0.0010 |
| ALB | 1.06 (1.04, 1.09), <0.0001 | 1.04 (1.02, 1.07), 0.0004 |
| SCr | 1.00 (1.00, 1.00), 0.02 | 1.00 (1.00, 1.00), 0.57 |
| CK-MB | 1.00 (0.99, 1.00), <0.0001 | 1.00 (0.99, 1.00), <0.0001 |
The ORs were adjusted with coma.
HR – heart rate; RR – respiratory rate; MAP – mean arterial pressure; Tmax – the max body temperature; Tadmit – the body temperature at admission; HCT – hematocrit; PLT – platelet; TBIL – total bilirubin; ALB – albumin; SCr – serum creatinine; CK-MB – creatine kinase isoenzyme.
GCS ≤8 on 1st, 3rd and 5th Days After Admission in Predicting Outcomes in Heatstroke
Kaplan-Meier curve analysis indicated significantly different length of ICU stay between patients with GCS ≤8 and those with GCS >8 at admission [log rank (Mantel-Cox) (P=0.002), Breslow (generalized Wilcoxon) (P=0.002), and Tarone-Ware (P=0.001)] (Figure 2A). GCSs were analyzed kinetically, which showed GCSs on the 1st, 3rd, and 5th in non-surviving patients were significantly lower than those in surviving patients (P<0.0001) (Figure 2B). Receiver operating characteristic (ROC) curves indicated GCSs on the 1st, 3rd, and 5th day could predict mortality, with areas under the curve (AUCs) of 0.81 [95% confidence interval (CI) 0.70–0.91], 0.91 (95% CI 0.84–0.98), and 0.91 (95% CI 0.82–0.99) (Figure 2C) and the corresponding cut-off values of 8.5, 9, and 9, respectively. As the AUCs of GCSs on the 3rd and 5th days were greater than that of GCSs on the 1st day, we hypothesized that persistent coma indicates a worsen outcome in heatstroke. Dynamic analysis of the impact of GCS on predicting mortality may have greater clinical significance.
Figurre 2. Association of Glasgow Coma Scale (GCS) with outcomes in heatstroke.
(A). Kaplan-Meier Curve. Patients with GCS ≤8 at admission had poorer clinical outcomes. (B). Kinetics of GCS. GCSs in non-surviving patients were significantly lower than those in surviving patients. (C). Receiver operating characteristic curve (ROCs). GCSs on the 1st, 3rd, and 5th days after admission predicted mortality. (D). Improved GCS predicted better clinical outcomes. The figures were drawn using the SPSS 20.0 for windows and EmpowerStats 2.0 software.
Among the 75 patients with GCS ≤8 at admission, 35 (46.67%) presented GCSs increasing to more than 8 on the 3rd (25) or 5th day (10). The rate of mortality in patients with GCS that did not non-improve (55.00%, 22/40) was significantly higher than that in patients with GCS that improved (5.71%, 2/35) (P<0.0001). The length of ICU stays in GCS non-improving patients (14.44±13.14 days) was significantly shorter than that in patients with improving GCS (7.43±5.64 days, P=0.005). The survival time of patients in the non-improving GCS group was shorter than that in the improving GCS group.
Kaplan-Meier (KM) curve analysis showed improving GCS predicted better outcomes, which was verified by log rank test (Mantel-Cox) (P=0.01), Breslow test (generalized Wilcoxon) (P=0.01), and Tarone-Ware test (P=0.01) (Figure 2D).
Representative Images Features
A 22-year-old male heatstroke patient with APACHE II score of 31 and GCS of 3 at admission was persistently comatose and died 5 days after admission. A brain computed tomography (CT) scan showed diffuse encephalic swelling, compressed or occluded ventricles, sulci, and cisterna, and extensive subarachnoid hemorrhage on the 3rd day after admission (Figure 3A). His GCS remained less than 5 during ICU stay. Another 27-year-old male heatstroke patient admitted with APACHE II score of 20 and GCS of 5 survived. Although his brain CT scan did not show swelling or edema at admission (Figure 3B1), a light encephalic swelling was shown by a CT scan 6 days later (Figure 3B2). The patient’s brain CT scan images returned to normal on the 17th day. Accordingly, his GCS improved to 10 and 15 on the 5th and 9th day after admission, respectively.
Figure 3. Representative Images of brain CT scan.
Brain computed tomography (CT) scan of a 22-year-old male heatstroke patient admitted with persistent coma showed diffuse encephalic swelling, compressed or occluded ventricles, sulci, and cisterna, and extensive subarachnoid hemorrhage on the 3rd day after admission (A). Another 27-year-old male heatstroke patient admitted with GCS of 5 survived; although his brain CT scan did not show swelling or edema at admission (B1), and a light encephalic swelling was shown by a CT scan 6 days later (B2), his GCS improved after admission and he survived.
Discussion
In the present study, we tried to elucidate the characteristics of GCS kinetics and their prognostic value in heatstroke. Our main findings were: (1) GCS ≤8 at admission could ideally predict the outcomes in heatstroke, which possibly enhanced the risks of mortality for other factors, including age, RR, HCT, and PLT; (2) nearly half of patients with GCS ≤8 persistently within 5 days after admission showed poorer clinical outcomes. Although it is preventable, heatstroke causes huge social and economic burdens due to its high rates of mortality and disability. Exploring the prognostic risk factors is particularly important for disease control.
As neurologic deficit and hyperthermia are the earliest characteristics, we explored whether GCS ≤8 was a risk factor of poor outcomes in heatstroke [19]. A total of 257 HS patients were included in the study, among whom 75 (29.18%) were comatose at admission and 27 (10.50%) patients died. The rate of coma in non-surviving patients (88.89%) was significantly higher than that in surviving patients (22.17%, P<0.0001). The non-surviving patients had a mean GCS of 5.67 vs 12.35 in surviving patients. Coma was thought to add to the mortality risk of other indicators. In our study, it was indicated higher HR, hyperthermia especially Tmax, TBIL, Cr, and CK-MB, and lower MAP, HCT, and PLT at admission in non-surviving patients vs surviving patients. We also found that coma at admission as a prognostic indicator worsened the mortality risks of other factors such as age, HCT, and PLT. We hypothesized that coagulopathy can affect the prediction of mortality. GCS ≤8 at admission was an ideal predictor of mortality in heatstroke patients, which indicated a 2-fold increase in risk of mortality compared to GCS >8.
Kinetically, among the 75 coma patients at admission, 40 patients were persistently comatose on the 3rd and 5th days, among whom 22 (55%) died. However, only 2 (5.71%) of the patients with an improving GCS died. The mean length of ICU stays in patients with improving GCS (7.43 days) was much shorter than that in the non-improving GCS patients (14.44 days, P=0.005). Taken together, the results showed that persistent coma might be a better prognostic factor in heatstroke patients.
The etiology of brain injury in heatstroke is unclear. Brain injuries in rats exposed to 43°C involved hypotension, intracranial hypertension, cerebral hypoperfusion, hypoxia, and ischemia [20]. Recent studies have found that exosomes are involved in the process of ischemia-reperfusion injuries in heatstroke, resulting in neuroinflammation and negative effects on brain tissue [21]. Inflammation can also induce autophagy, but it can also have a protective effect by reducing cell death [22,23]. Although diffuse cerebral cortex injury is rare [24], brain edema can be observed clinically [25]. It is unlikely that a single biomarker could predict clinical outcomes.
GCS is often used as a tool to evaluate neurological function after acute or traumatic brain injury [26,27]. In a recent study, GCS was applied to evaluate the prognosis of 64 patients with acute cerebral infarction, clearly showing its ability to predict clinical outcomes [28]. GCS can also be used to predict the long-term outcomes of primary decompressive craniectomy after acute subdural hematoma [29]. Combined with CT scan or other measurements, GCS can better predict clinical outcomes of patients with brain injury [30]. GCS is also widely used to assess critically ill patients. However, GCS is rarely used to assess outcomes in heatstroke. A cohort study, included 117 patients with exertional heatstroke, showed a worsened clinical outcome in patients with GCS less than 8 [31]. Another study, which included 170 exertional heatstroke patients and conducted in multiple centers, assessed the predictive effectiveness of exertional heatstroke score (EHSS), in which GCS was an important component marker. The sensitivity and specificity of GCS in predicting prognosis were 72.5% and 81.0%, respectively [32]. As opposed to some studies which used GCS as a marker of EHSS [16–18], we applied it as an independent risk factor to assess the prognosis. Furthermore, we also classified other factors by GCS, and found that GCS ≤8 added to the mortality risks of other factors, including age, HCT, and PLT. Taken together, the evidence suggests that early brain boosts the acute-phase pathological response in heatstroke [33]. Brain injury is a target organ damaged in the early stage of heatstroke and can enhance sympathetic excitement, increase catecholamine release, and promote inflammation and coagulation, which are the key pathological processes in heatstroke [33].
Clinically, we observed that, although many patients with heatstroke suffered encephalopathy early, they experienced different kinetics with transient vs persistent coma. We presumed that different kinetics of coma possibly indicated different outcomes. Indeed, our study found that kinetics of GCS upon admission on the 3rd and 5th days was a good index to predict mortality in heatstroke. Among 75 patients (29.18%) with GCS ≤8 at admission, 35 patients (46.67%) who had improved GCSs on the 3rd or 5th day had lower mortality (5.71%) than those with persistent GCS ≤8 (55%). The rate of mortality in persistent coma patients was about 2 times higher than in transient coma patients. ROCs showed the AUC of GCSs was 0.91 on the 3rd and 5th days, indicating that dynamic changes of patients’ mental state could be a good predictor for prognosing outcomes in heatstroke. This finding is a highlight of the present study and differentiates it from others.
To further verify our results, we analyzed representative brain radiography of patients with heatstroke. A heatstroke patient with a persistent GCS score of 3 and coma within 5 days after admission died. His brain injury was verified by CT scan images, which showed severe edema of tissue with bilateral compressed lateral ventricles, and subarachnoid hemorrhage in the early stage.
In contrast, another patient who survived, with GCS of 5 at admission but rising to 10 and 15 on the 5th and 9th days, respectively, showed mild brain injury early and later had a normal brain CT scan result. These representative images were consistent with the kinetics of GCS for predicting outcomes in heatstroke patients.
Limitations
The present study has certain limitations. Firstly, although it was demonstrated that persistent coma from admission onwards (GCS ≤8) was valuable in predicting outcomes in heatstroke, due to lack of relative indexes, we could not explain the mechanism of coma. Secondly, indexes used to assess brain injury are limited. Attention should be focused on multiple brain injury-related indicators, including clinical signs, radiography, electroencephalogram, and biomarkers, all of which together can comprehensively evaluate the changes of brain after injury. Thirdly, even though there were no sex differences between the non-survival and survival groups, males accounted for 92% of the total. This added bias to the study and needs to be improved in future research. Finally, this was a retrospective observational study, and we can only analyze existing data to find risk factors.
Conclusions
GCS ≤8 at admission could be an ideal predictor of clinical outcomes in heatstroke patients with GCS ≤8 at admission, which may have enhanced the risks of mortality due to other factors, including age, RR, and HCT.
Footnotes
Conflict of interest: None declared
Publisher’s note: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher
Declaration of Figures’ Authenticity
All figures submitted have been created by the authors, who confirm that the images are original with no duplication and have not been previously published in whole or in part.
Financial support: This work was supported by the PLA Logistics Research Project of China (18CXZ032); the Natural Science Foundation of Guangdong Province (Grant No. 2021A1515012119); Shenzhen Key Laboratory of Prevention and Treatment of Severe Infections (No. ZDSYS20200811142804014), and Shenzhen Key Medical Discipline Construction Fund (No. SZXK045)
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