Etiology and Short-term Outcome of Pediatric Coma at a Tertiary Hospital in Douala, Cameroon

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Understanding its epidemiology and prognostic factors is essential for improving outcomes. Methods A 28-month cross-sectional study (January 2017-April 2019) was conducted at Gyneco-Obstetric and Pediatric Hospital of Douala, Cameroon. Children aged 1 month to 15 years with Glasgow Coma Scale ≤ 14 were included. Data on demographics, clinical presentation, etiology, and outcomes were collected through retrospective record review and prospective patient enrollment. Statistical analysis used SPSS version 20.0 and CSPro with Chi-square and Fisher's exact tests. Results Among 864 hospitalized children, 109 presented with coma (prevalence 12.6%). The male-to-female ratio was 1.4:1, with mean age 48.8 ± 47.5 months; 64.2% were under 5 years. Infectious causes predominated (62.4%), with cerebral malaria accounting for 42.2% and septicemia for 15.6%. Other etiologies included metabolic/toxic causes (16.5%), post-epileptic coma/status epilepticus (14.7%), and traumatic brain injury (4.6%); 12.8% remained undiagnosed. Clinical features included fever (73.4%) and seizures at admission (68.8%). Overall mortality was 26.6%, with 30.9% of survivors experiencing neurological sequelae, predominantly motor deficits (14.8%). Significant mortality predictors included age under 2 years (6–10 times higher odds), female sex (3.54 times higher odds), direct home admission (3.24 times higher odds), and deeper coma stages (100% mortality in Stage IV versus 3.8% in Stage I). Conclusion Pediatric coma at this tertiary center predominantly affects young children and stems primarily from infectious etiologies, particularly cerebral malaria. The high mortality (26.6%) and substantial neurological morbidity among survivors underscore urgent needs for strengthened malaria prevention programs, improved community awareness, enhanced referral systems, and increased diagnostic and intensive care capabilities. Early recognition and prompt management of preventable causes could significantly reduce mortality and morbidity from pediatric coma in Central Africa. Coma Children Etiology Outcome Cerebral malaria Glasgow Coma Scale Mortality Sub-Saharan Africa Figures Figure 1 Figure 2 1. INTRODUCTION Coma is defined as a prolonged loss of consciousness resulting from dysfunction of the ascending reticular activating formation (ARAF), which is responsible for arousal and maintenance of wakefulness [1–4]. In pediatric practice, coma represents a critical emergency, accounting for 10–15% of all hospitalizations and associated with substantial morbidity and mortality [5–7]. The epidemiology of pediatric coma varies significantly across geographic regions. In England, the incidence of non-traumatic coma has been estimated at 30.8 per 100,000 children under 16 years annually, with etiology-specific mortality rates ranging from 3% to 84% [8]. In Saudi Arabia, Ali et al. reported an incidence of 4.8 per 100,000 children per year for both traumatic and non-traumatic coma, with a mortality rate of 47.2% [9]. African studies have shown variable prevalence rates: 5.4% in Lomé, Togo (mortality 27.6%) [3], and 14.4% in Cairo, Egypt (mortality 50%) [1]. In sub-Saharan Africa and Asia, the predominant etiologies of pediatric coma are infections of the central nervous system, including cerebral malaria, acute bacterial meningitis, and viral encephalitis. Understanding the etiology and predictive factors of coma outcomes is crucial for developing improved management strategies, particularly in resource-limited settings where diagnostic and supportive systems are rarely available [10]. The prognosis of coma depends on both etiology and the rapidity of appropriate management [11–13]. Outcomes range from complete recovery to persistent neurological sequelae or death. Two particular evolutionary aspects deserve attention: brain death and vegetative state. In Douala, Cameroon's largest city, limited data exist on pediatric coma. This study was therefore undertaken to describe the etiologies and determine the short-term outcomes of childhood coma at the Gyneco-Obstetric and Pediatric Hospital of Douala (HGOPED), a major tertiary referral center. 2. MATERIALS AND METHODS 2.1 Study Design, Area, and Population We conducted a cross-sectional study with both retrospective and prospective phases at the Gyneco-Obstetric and Pediatric Hospital of Douala (HGOPED) in Cameroon. The study extended from December 2018 to June 2019, encompassing data collection for children who presented with coma between January 2017 and April 2019, totaling 28 months of patient inclusion. HGOPED is a first-category tertiary hospital located in Douala 3rd district, covering 7 hectares with 11 buildings. The facility serves as a major referral center for the Douala metropolitan area and surrounding regions. The pediatric service at HGOPED comprises three functional units: general pediatrics with 25-bed capacity, neonatology with 20-bed capacity divided into internal and external sectors, and an outpatient consultation unit. The hospital is staffed by 5 pediatricians including 2 neonatologists and 1 child neurologist, 6 general practitioners, and approximately 30 paramedical personnel. Diagnostic facilities available include a clinical laboratory, video-electroencephalography, and computed tomography imaging services, providing comprehensive investigative capabilities for neurological emergencies. The study population comprised children aged 1 month to 15 years hospitalized during the study period who presented with coma. Inclusion criteria encompassed both a retrospective analysis of medical records for children aged 1 month to 15 years presenting with coma and a prospective cohort of children in the same age range for whom parental or guardian informed consent was secured. Children were excluded from the study if their medical records were incomplete in the retrospective phase, or if informed consent from a parent or guardian was not obtained in the prospective phase. Sample size was calculated using Lorenz's formula: n = (t)² × p × (1-p) / e², where n represents expected sample size, t equals confidence level of 1.96 for 95% confidence, p represents estimated population proportion with the characteristic studied, and e equals margin of error of 5%. Using a coma prevalence of 5.4% from Lomé, Togo, the calculated minimum sample size was 79 patients. Our final sample of 109 patients exceeded this requirement, ensuring adequate statistical power. 2.2 Description of Materials After obtaining administrative authorization and ethical clearance from both HGOPED and the University of Douala institutional ethics committees, data collection proceeded through two distinct phases. For the retrospective phase, the pediatric and intensive care unit admission registers were systematically reviewed to identify all children aged 1 month to 15 years hospitalized between January 2017 and April 2019. Medical records were then carefully examined to identify coma cases meeting inclusion criteria, with data extracted using standardized case report forms. For the prospective phase, all children presenting with coma or developing coma during hospitalization whose parents provided informed consent were enrolled consecutively. Standardized case report forms were designed to capture comprehensive information across multiple domains including sociodemographic characteristics, medical history, clinical presentation, investigation results, treatment administered, and outcomes. Each prospectively enrolled child underwent systematic clinical examination at admission, including detailed neurological assessment and Glasgow Coma Scale scoring. Capillary glucose measurement was performed routinely in the emergency room for all patients. Additional investigations including malaria testing, laboratory studies, lumbar puncture when indicated, and neuroimaging were performed based on clinical presentation and suspected etiology. 2.3 Variables and Data Collection Data collection encompassed multiple variable categories to provide comprehensive characterization of pediatric coma cases. Sociodemographic data included age, sex, city of residence, and referral source whether directly from home or referred from another healthcare facility. Personal medical history variables documented psychomotor development status, previous episodes of coma, seizure history, known epilepsy diagnosis, and ongoing antiepileptic treatment at the time of admission. Clinical characteristics at admission were meticulously recorded, including body weight, consciousness level assessed using Glasgow Coma Scale, coma stage classification, presence of respiratory distress, digestive disorders, clinical malnutrition, skin rash, ear-nose-throat infections, severe pallor suggesting anemia, body temperature, and seizure activity including topography and seizure type. The comprehensive clinical assessment ensured capture of all relevant presenting features that might influence diagnosis and prognosis. Complementary investigations performed were systematically documented, including capillary glucose measurement, thick blood smear for malaria parasites, malaria rapid diagnostic test, serum sodium levels, hemoglobin concentration, C-reactive protein, lumbar puncture with cerebrospinal fluid analysis and culture, brain computed tomography, brain magnetic resonance imaging, and electroencephalography. The availability and results of these investigations were recorded, recognizing that resource limitations might affect diagnostic workup completeness. Etiological classification was determined based on clinical presentation, investigation results, and final diagnosis. Categories included infectious causes such as cerebral malaria, septicemia, febrile gastroenteritis with dehydration, herpes encephalitis, and bacterial meningitis; metabolic and toxic causes including hyponatremia, hypoglycemia, various intoxications, and diabetic ketoacidosis; post-epileptic coma and status epilepticus; traumatic brain injury; intracranial hemorrhage; vascular causes; congenital malformations; and unknown etiology when diagnosis could not be established despite investigation. Outcome variables at hospital discharge included death, transfer to another facility, discharge against medical advice, survival without sequelae, and survival with sequelae. For patients with sequelae, the specific types were documented including motor deficit, visual impairment, hearing impairment, psychomotor regression, and behavioral disorders. Hospital stay duration was also recorded, categorized as less than one week, one week to one month, or more than one month. 2.4 Clinical Variables Several operational definitions guided data collection, classification, and analysis. Coma was defined as a Glasgow Coma Scale score ≤ 14 out of 15, using either the standard Glasgow Coma Scale for verbal children or the pediatric Glasgow Coma Scale for pre-verbal children. This threshold was chosen to capture the full spectrum of altered consciousness requiring intensive monitoring and management. Coma severity was stratified into four stages based on Glasgow Coma Scale scores: Stage I representing Vigil Coma with GCS 11–13, Stage II representing Light Coma with GCS 9–10, Stage III representing Deep Coma with GCS 6–8, and Stage IV representing Beyond Coma or Carus with GCS 3–5. This classification system allowed for prognostic stratification and facilitated comparison with other studies. Short-term outcome was defined as patient status at hospital discharge, categorized as death, discharge against medical advice, transfer to another facility, survival without detectable sequelae, or survival with neurological sequelae. Sequelae were specifically defined as new neurological deficits present at discharge that were absent on admission or represented deterioration from baseline function. These included motor deficit affecting limb movement or coordination, visual impairment newly identified or worsened, hearing impairment newly identified or worsened, psychomotor regression representing loss of previously acquired developmental milestones, and behavioral disorders manifesting as new problematic behaviors do not present before the coma episode. Fever was defined as body temperature ≥ 38°C measured by axillary or rectal thermometry, while hypothermia was defined as temperature < 36.5°C. Hypoglycemia was defined as capillary glucose ≤ 0.50 g/L, hyperglycemia as capillary glucose ≥ 1.26 g/L, and normoglycemia as values between these thresholds. Severe pallor was clinically assessed using palmar and conjunctival examination, suggesting significant anemia. Respiratory distress was identified by tachypnea, increased work of breathing, or oxygen desaturation. 2.5 Data Analysis Data were entered and analyzed using Census and Survey Processing System (CSPro) for data entry and SPSS version 20.0 for statistical analysis. Tables and figures were created using Microsoft Excel and Word 2010 to present results clearly. Descriptive statistics included frequencies and percentages for categorical variables and means with standard deviations for continuous variables. Medians and ranges were also calculated for variables with skewed distributions. Categorical variables were compared using Chi-square tests when expected cell counts were adequate, or Fisher's exact tests when expected cell counts were small. The significance threshold was set at p < 0.05 for all statistical tests. Associations between predictor variables and outcomes, particularly mortality and sequelae, were assessed using odds ratios with 95% confidence intervals. Logistic regression analysis was performed to identify independent predictors of mortality while controlling for potential confounding factors. Variables with p-values < 0.20 in univariate analysis were included in multivariable models. Linear regression analyses were also performed where appropriate to examine relationships between continuous variables and outcomes. Model goodness-of-fit was assessed, and multicollinearity was checked for all regression models. Results were presented in tables showing odds ratios, confidence intervals, and p-values for significant associations. 3. RESULTS 3.1 Study Population and Sociodemographic Characteristics Of 864 children hospitalized during the 28-month study period (January 2017 to April 2019), 109 (12.6%) presented with coma, comprising 88 cases identified retrospectively and 21 prospectively enrolled. Males constituted 57.8% (n = 63) of the cohort, giving a male-to-female ratio of 1.4:1. The mean age was 48.8 ± 47.5 months (range: 1-180 months; median: 36 months), with children under 5 years representing nearly two-thirds (64.2%) of all cases. The largest age group was children aged 3–24 months (43.1%, n = 47), followed by those aged 5–10 years (22.9%, n = 25). Infants under 3 months represented only 3.7% (n = 4) of cases, while children aged 25–59 months accounted for 16.5% (n = 18), and adolescents aged 10–15 years comprised 12.8% (n = 14) of the cohort. Male predominance was most pronounced in older age groups, with males representing 85.7% of adolescent cases compared to only 25% of infants under 3 months. (See Table 1 ) Table 1 Age and Sex Distribution of Children with Coma (N = 109) Age Group Male (%) Female (%) Total (%) 1–3 months 1 (25.0) 3 (75.0) 4 (3.7) 3–24 months 24 (51.1) 23 (48.9) 47 (43.1) 25–59 months 10 (55.6) 8 (44.4) 18 (16.5) 5–10 years 16 (64.0) 9 (36.0) 25 (22.9) 10–15 years 12 (85.7) 2 (14.3) 14 (12.8) Total 63 (57.8) 46 (42.2) 109 (100) Regarding geographic distribution, the vast majority of patients (91.7%, n = 100) resided in Douala, with smaller proportions from Buea (4.6%, n = 5), and other cities including Kribi and Edéa (3.7%, n = 4). Most children (74.3%, n = 81) were referred from other healthcare facilities, while 25.7% (n = 28) were brought directly from home. 3.2 Medical History Normal psychomotor development was documented in 91.3% (n = 100) of patients, indicating that the majority of children had no pre-existing neurological impairment. Previous history of seizures was reported in 17.5% (n = 19) of cases, while only 1.9% (n = 2) had experienced a prior episode of coma. Known epilepsy was present in 5.8% (n = 6) of children, all of whom (5.8%, n = 6) were receiving ongoing antiepileptic treatment at the time of admission. 3.3 Clinical Presentation Assessment of coma severity using the Glasgow Coma Scale revealed that the majority of patients presented with moderate coma: Stage II (GCS 9–10) was most common at 45.0% (n = 49), followed by Stage I (GCS 11–13) at 23.9% (n = 26), and Stage III (GCS 6–8) at 20.2% (n = 22). Severe Stage IV coma (GCS 3–5) was present in 10.1% (n = 11) of cases. (See Table 2 ) Table 2 Clinical Characteristics at Admission (N = 109) Clinical Feature Number, n (%) Coma Severity (Glasgow Coma Scale) Stage I (GCS 11–13) 26 (23.9) Stage II (GCS 9–10) 49 (45.0) Stage III (GCS 6–8) 22 (20.2) Stage IV (GCS 3–5) 11 (10.1) Temperature Fever (≥ 38°C) 80 (73.4) Normothermia (36.5–37.5°C) 20 (18.3) Hypothermia (< 36.5°C) 9 (8.3) Associated Features Seizures at admission 75 (68.8) Respiratory distress 50 (45.9) Digestive disorders 42 (38.5) Severe pallor 25 (22.9) Skin rash 12 (11.0) ENT infection 7 (6.4) Malnutrition 6 (5.5) Fever (temperature ≥ 38°C) was the most frequent associated finding, present in 73.4% (n = 80) of patients at admission. Normothermia (36.5–37.5°C) was documented in 18.3% (n = 20), while hypothermia (< 36.5°C) occurred in 8.3% (n = 9). Seizures at admission were observed in 68.8% (n = 75) of children, predominantly generalized in distribution (85.3%). Respiratory distress was identified in 45.9% (n = 50), and digestive disorders in 38.5% (n = 42) of cases. Severe pallor, suggestive of significant anemia, was noted in 22.9% (n = 25) of children. Less frequent findings included skin rash (11.0%, n = 12), ear-nose-throat infections (6.4%, n = 7), and clinical malnutrition (5.5%, n = 6). 3.4 Laboratory and Imaging Investigations Capillary glucose measurement was performed in 98.2% (n = 107) of patients, revealing hypoglycemia (≤ 0.50 g/L) in 12.1%, hyperglycemia (≥ 1.26 g/L) in 9.3%, and normoglycemia in 78.6%. Malaria diagnostic testing (thick blood smear and/or rapid diagnostic test) was completed in 89.0% of cases, with 47.7% testing positive. Serum sodium was measured in 45.0% of patients, with hyponatremia detected in 11.9% of the total cohort. Mean hemoglobin level was 9.8 ± 3.2 g/dL, indicating prevalent anemia. C-reactive protein was measured in 68.8% of cases and was elevated in the majority. Cerebrospinal fluid examination was performed in only 31.2% (n = 34) of patients. Among these, CSF culture was positive in 2.9%, and bacterial meningitis was confirmed in 0.9% (n = 1) of the total cohort. Neuroimaging was limited: brain computed tomography was performed in 22.0% (n = 24) with abnormal findings in half of these cases, brain magnetic resonance imaging in 4.6% (n = 5), and electroencephalography in 8.3% (n = 9). 3.5 Etiological Distribution Infectious causes predominated, accounting for 62.4% (n = 68) of all cases. Within this category, cerebral malaria was the single most common etiology at 42.2% (n = 46), followed by septicemia at 15.6% (n = 17). Febrile gastroenteritis with dehydration contributed 6.4% (n = 7), herpes encephalitis 2.8% (n = 3), and bacterial meningitis 0.9% (n = 1) of cases. (See Table 3 ) Table 3 Etiological Distribution of Pediatric Coma (N = 109) Etiology Number (%) Deaths (%) Infectious causes 68 (62.4) 19 (27.9) Cerebral malaria 46 (42.2) 9 (19.6) Septicemia 17 (15.6) 8 (47.1) Febrile gastroenteritis with dehydration 7 (6.4) 3 (42.9) Herpes encephalitis 3 (2.8) 2 (66.7) Bacterial meningitis 1 (0.9) 1 (100) Metabolic/Toxic causes 18 (16.5) 4 (22.2) Hyponatremia 13 (11.9) 3 (23.1) Hypoglycemia 3 (2.8) 0 (0) Intoxication 3 (2.8) 1 (33.3) Diabetic ketoacidosis 1 (0.9) 0 (0) Post-epileptic/Status epilepticus 16 (14.7) 2 (12.5) Traumatic brain injury 5 (4.6) 1 (20.0) Other causes 7 (6.4) 2 (28.6) Unknown etiology 14 (12.8) 1 (7.1) Malformations 1 (0.9) 0 (0) Figure 1 illustrates the relative proportions of different etiological categories. Metabolic and toxic causes represented the second largest etiological group at 16.5% (n = 18). Hyponatremia was the predominant metabolic disturbance, affecting 11.9% (n = 13) of all patients. Hypoglycemia and various intoxications (petroleum products, medications) each accounted for 2.8% (n = 3), while diabetic ketoacidosis was identified in 0.9% (n = 1). Post-epileptic coma and status epilepticus collectively comprised 14.7% (n = 16) of cases. Traumatic brain injury was relatively uncommon at 4.6% (n = 5). Other miscellaneous causes accounted for 6.4% (n = 7), while malformations represented only 0.9% (n = 1). Despite thorough investigation, the etiology remained undetermined in 12.8% (n = 14) of cases. No instances of intracranial hemorrhage or primary cerebrovascular causes were identified in this cohort. 3.6 Clinical Outcomes Overall, 74.3% (n = 81) of children survived to hospital discharge, while 26.6% (n = 29) died. Among other outcomes, 2.8% (n = 3) were transferred to other facilities, 5.5% (n = 6) were discharged against medical advice, and 1.8% (n = 2) required intensive care unit admission. Hospital stay duration varied: 52.3% were hospitalized for less than one week, 11.9% for one week to one month, and 7.3% for more than one month. Table 4 demonstrates the strong relationship between coma severity and outcome. Among survivors (n = 81), 69.1% (n = 56) had no detectable sequelae at discharge, while 30.9% (n = 25) experienced neurological sequelae. The specific types of sequelae are detailed in Table 5 , with motor deficits being most common at 14.8% (n = 12), followed by visual impairment, hearing impairment, and psychomotor regression, each occurring in 2.5% (n = 2) of survivors. Behavioral disorders were noted in 1.2% (n = 1). Table 4 Outcome According to Coma Severity (N = 109) Outcome Stage I (GCS 11–13) n = 26 Stage II (GCS 9–10) n = 49 Stage III (GCS 6–8) n = 22 Stage IV (GCS 3–5) n = 11 Total n = 109 Survival without sequelae 21 (80.8%) 33 (67.3%) 13 (59.1%) 0 (0%) 67 (61.5%) Survival with sequelae 5 (19.2%) 16 (32.7%) 9 (40.9%) 0 (0%) 30 (27.5%) Death 1 (3.8%) 12 (24.5%) 6 (27.3%) 11 (100%) 30 (27.5%) Transfer 0 (0%) 1 (2.0%) 0 (0%) 0 (0%) 1 (0.9%) DAMA* 0 (0%) 5 (10.2%) 0 (0%) 1 (9.1%) 6 (5.5%) *DAMA: Discharge against medical advice Table 5 Sequelae Among Survivors (n = 81) Type of Sequelae Number, n (%) No sequelae 56 (69.1) Any sequelae 25 (30.9) Motor deficit 12 (14.8) Visual impairment 2 (2.5) Hearing impairment 2 (2.5) Psychomotor regression 2 (2.5) Behavioral disorders 1 (1.2) Figure 2 illustrates mortality rates stratified by coma stage. A striking gradient was observed, with Stage IV (GCS 3–5) demonstrating 100% mortality (11/11 patients), Stage III (GCS 6–8) showing 27.3% mortality (6/22), Stage II (GCS 9–10) demonstrating 24.5% mortality (12/49), and Stage I (GCS 11–13) having the lowest mortality at 3.8% (1/26). 3.7 Factors Associated with Mortality and Sequelae Age emerged as a powerful protective factor, with mortality decreasing substantially as age increased. Compared to children under 2 years, those aged 2–5 years had an odds ratio of 0.17 (95% CI: 0.05–0.59, p = 0.017), representing an approximately 6-fold reduction in mortality risk. Children over 5 years demonstrated even greater protection with an odds ratio of 0.09 (95% CI: 0.02–0.38, p = 0.001), translating to a 10-fold reduction in mortality risk compared to infants and young toddlers. (See Table 6 ) Table 6 Predictors of Mortality: Logistic Regression Analysis Variable Odds Ratio 95% CI p-value Age group 2–5 years vs. 5 years vs. <2 years 0.09 0.02–0.38 0.001 Sex Female vs. Male 3.54 2.48–4.60 0.019 Provenance Home vs. Referred 3.24 2.07–4.42 0.050 City of residence Outside Douala vs. Douala 0.61 0.16–2.28 0.598 Sex was significantly associated with outcome, with female patients demonstrating 3.54 times higher odds of death compared to males (95% CI: 2.48–4.60, p = 0.019). Referral pattern also proved significant: children admitted directly from home had 3.24 times higher mortality odds compared to those referred from other healthcare facilities (95% CI: 2.07–4.42, p = 0.050). In contrast, city of residence (Douala versus other locations) showed no significant association with mortality (OR 0.61, 95% CI: 0.16–2.28, p = 0.598). Coma severity was strongly associated with mortality (p < 0.001), as demonstrated in Table 4 . Duration of hospitalization exceeding one week was associated with significantly increased odds of developing sequelae among survivors (OR 5.23, p = 0.008). Medical history variables, including previous seizures, known epilepsy, and abnormal psychomotor development, showed no significant associations with mortality in multivariate analysis. Etiology-specific mortality analysis revealed substantial variation across diagnostic categories. Among infectious causes, septicemia carried the highest mortality at 47.1% (8/17 cases), followed by herpes encephalitis at 66.7% (2/3 cases), and cerebral malaria at 19.6% (9/46 cases). Overall infectious etiology mortality was 27.9% (19/68). Metabolic and toxic causes demonstrated 22.2% mortality (4/18), while post-epileptic coma and status epilepticus showed lower mortality at 12.5% (2/16). Traumatic brain injury resulted in 20.0% mortality (1/5 cases). 4. DISCUSSION This study provides important insights into the epidemiology, etiology, and outcomes of pediatric coma in a major tertiary center in Central Africa. The 12.6% prevalence observed in our study is consistent with previous reports suggesting that coma accounts for 10–15% of pediatric hospitalizations [5–7], though it exceeds the 5.4% reported in Lomé, Togo [3] and falls below the 14.4% found in Cairo [1]. These variations may reflect differences in referral patterns, healthcare-seeking behavior, and disease burden across different African settings. 4.1 Demographic Characteristics The male predominance (sex ratio 1.4:1) observed in our cohort is consistent with several previous studies [1,3]. The mean age of 48.8 months and the predominance of children under 5 years (64.2%) align with global patterns showing that younger children are at higher risk for coma, likely reflecting age-related vulnerabilities including immature cerebral physiology, higher susceptibility to infections, and increased risk of metabolic derangements [5,14]. The high proportion of referrals from other healthcare facilities (74.3%) underscores HGOPED's role as a tertiary referral center. Interestingly, direct admission from home was associated with significantly higher mortality (OR 3.24), possibly reflecting delays in care-seeking, more severe disease at presentation, or inadequate initial management. This finding emphasizes the importance of efficient referral systems and community education about recognizing danger signs. 4.2 Clinical Presentation and Severity The distribution of coma severity in our study showed that most patients presented with moderate coma (Stages II and III: 65.2%), while 10.1% had very deep coma (Stage IV). This distribution has important prognostic implications, as we observed 100% mortality in Stage IV coma, compared to only 3.8% in Stage I. These findings are consistent with numerous studies demonstrating that GCS score is a powerful predictor of outcome in pediatric coma [11,12]. Seizures at admission were present in 68.8% of patients, predominantly generalized. This high frequency likely reflects both the etiologies prevalent in our setting (particularly cerebral malaria and status epilepticus) and the pathophysiological mechanisms of coma in children, where seizure activity frequently accompanies acute brain dysfunction. 4.3 Etiological Profile The predominance of infectious causes (62.4%) in our study mirrors findings from other sub-Saharan African and Asian countries, where infections remain the leading cause of pediatric coma [1,3,8–10]. However, the specific distribution of infectious etiologies reflects regional epidemiology. Cerebral malaria emerged as the single most common cause (42.2%), consistent with the high malaria endemicity in Cameroon. This finding aligns with studies from other malaria-endemic regions where cerebral malaria accounts for 30–50% of pediatric coma cases. The 19.6% mortality rate for cerebral malaria in our study falls within the reported range of 15–25% for this condition, though it remains unacceptably high given that malaria is preventable and treatable. Septicemia (15.6%) was the second most common infectious cause, with a notably high mortality rate of 47.1%. This high fatality rate likely reflects both the severity of sepsis at presentation and potential limitations in intensive care capabilities. The low frequency of bacterial meningitis (0.9%) may be attributable to several factors: widespread vaccination against Haemophilus influenzae and Streptococcus pneumoniae , empirical antibiotic use before lumbar puncture, or diagnostic limitations (only 31.2% of patients underwent lumbar puncture). Metabolic and toxic causes (16.5%) represented the second most common etiological category. Hyponatremia (11.9%) was the most frequent metabolic disturbance, consistent with reports that children are at higher risk than adults for hyponatremic encephalopathy due to their relatively larger brain-to-intracranial volume ratio [15–17]. Hypoglycemia (2.8%) was less common than expected, possibly due to systematic glucose monitoring and correction in the emergency department before enrollment. Post-epileptic coma and status epilepticus (14.7%) constituted a significant proportion, reflecting the high burden of seizure disorders in African children [18–21]. The fact that only 5.8% of our cohort had known epilepsy suggests that many cases represented first presentations or seizures secondary to acute illnesses. Traumatic brain injury (4.6%) was relatively uncommon in our series, likely because severe trauma cases may be managed at other facilities or because parents delay seeking care for trauma. This low proportion contrasts with data from high-income countries where trauma often accounts for a larger proportion of pediatric coma [22–24]. The 12.8% of cases with unknown etiology despite investigation highlights diagnostic challenges in resource-limited settings, including limited access to advanced neuroimaging, microbiological diagnostics, and metabolic testing. 4.4 Diagnostic Approach The diagnostic workup in our study reflected the resource constraints typical of many African settings. While basic investigations (capillary glucose, malaria testing, hemoglobin) were performed in most patients, more advanced studies were limited: brain imaging in only 26.6%, lumbar puncture in 31.2%, and EEG in 8.3%. These limitations may have contributed to the relatively high proportion of unknown etiologies and could have affected management decisions. The low rate of lumbar puncture is concerning given the need to exclude treatable causes such as bacterial meningitis. Barriers may include concerns about safety in patients with altered consciousness, lack of availability of CT to exclude raised intracranial pressure, or empirical antibiotic treatment initiated before the procedure. 4.5 Outcomes and Prognostic Factors The overall mortality rate of 26.6% in our study falls within the wide range (3–84%) reported globally [8], but exceeds rates from high-income countries and approaches those from other resource-limited settings in Africa [1,3,9]. This mortality reflects both the severity of presenting illnesses and systemic healthcare limitations. 4.6 Several factors emerged as significant predictors of mortality: Age Younger children (< 2 years) had substantially higher mortality, with odds 6–10 times higher than older children. This age-related vulnerability reflects multiple factors including immature cerebral autoregulation, limited physiological reserves, higher susceptibility to hypoglycemia and electrolyte disturbances, and greater vulnerability to infection-related complications. Sex The unexpected finding of higher mortality in females (OR 3.54) contrasts with some previous studies showing male predominance in poor outcomes. This finding requires further investigation but could reflect sex-specific differences in care-seeking behavior, underlying nutritional status, or biological factors. Coma severity The strong relationship between deeper coma stages and mortality has been consistently demonstrated across multiple studies and settings [11–13]. The 100% mortality in Stage IV coma reflects the severity of underlying brain dysfunction and the limited reversibility of such profound depression of consciousness. Referral pattern: The threefold higher mortality in children coming directly from home versus those referred from other facilities is striking and suggests several possible mechanisms: delay in initial care-seeking leading to more advanced disease, lack of stabilization before referral, or more fulminant disease courses. This finding emphasizes the importance of community health education and strengthening primary care capabilities. Among survivors, 30.9% had sequelae at discharge, predominantly motor deficits (14.8%). Hospitalization exceeding one week was associated with fivefold higher odds of sequelae, likely reflecting both greater injury severity and longer disease courses. These findings underscore the substantial burden of neurological morbidity beyond mortality. 4.7 Clinical and Public Health Implications Our findings have important implications for clinical practice and public health policy in similar resource-limited settings: Malaria prevention and control must remain a priority, as cerebral malaria constitutes the largest single preventable cause of pediatric coma. Strategies should include widespread distribution of insecticide-treated bed nets, prompt diagnosis and treatment of malaria, and continued research into vaccines and novel therapeutics. Early recognition and management of pediatric emergencies at the community and primary care levels could reduce mortality, particularly given the association between direct home admission and poor outcomes. Training of community health workers and primary care physicians in recognizing danger signs and providing initial stabilization is critical. Strengthening referral systems and emergency transport capabilities could improve outcomes by ensuring patients receive appropriate care at each level and arrive at tertiary centers in optimally stabilized condition. Systematic diagnostic protocols including routine lumbar puncture (when safe), glucose monitoring, electrolyte assessment, and neuroimaging when indicated should be implemented to improve etiological diagnosis and targeted treatment. Improved intensive care capabilities including mechanical ventilation, hemodynamic monitoring, and neurological support could potentially reduce mortality, particularly in severe cases and those with metabolic derangements. Long-term follow-up programs for survivors are needed to identify and address delayed neurological sequelae, support rehabilitation, and improve functional outcomes. CONCLUSION This study demonstrates that pediatric coma at a tertiary hospital in Douala predominantly affects young children and is primarily attributable to infectious causes, particularly cerebral malaria. The mortality rate of 26.6% remains high, with younger age, female sex, direct admission from home, and deeper coma stages serving as significant predictors of poor outcome. Among survivors, nearly one-third experience neurological sequelae at discharge, predominantly motor deficits. These findings emphasize the urgent need for strengthened malaria prevention and control programs, improved community awareness of pediatric danger signs, enhanced referral systems, and increased diagnostic and intensive care capabilities in resource-limited settings. Early recognition and prompt, appropriate management of preventable causes could substantially reduce both mortality and morbidity from pediatric coma in Central Africa. Future multicenter prospective studies with longer follow-up periods and standardized diagnostic protocols are needed to better characterize the full spectrum and long-term outcomes of pediatric coma in this region. Study Limitations This study has several limitations. First, the single-center design and convenience sampling limit generalizability. Second, the retrospective component of the study was constrained by incomplete medical records for some variables. Third, the relatively short follow-up (to hospital discharge only) does not capture long-term outcomes or delayed neurological sequelae. Fourth, limited access to advanced diagnostics (neuroimaging, comprehensive metabolic panels, extended microbiological testing) likely resulted in missed diagnoses and contributed to the unknown etiology category. Fifth, the absence of standardized protocols for investigation and management may have introduced variability in diagnostic approaches. Finally, we could not assess intensive care interventions systematically, which likely influenced outcomes. Abbreviations • ARAF Ascending Reticular Activating Formation • CI Confidence Interval • CRP C-Reactive Protein • CSF Cerebrospinal Fluid • CSPro Census and Survey Processing System • CT Computed Tomography • DAMA Discharge Against Medical Advice • EEG Electroencephalography • ENT Ear, Nose, and Throat • GCS Glasgow Coma Scale • HGOPED Hôpital Gynéco-Obstétrique et Pédiatrique de Douala (Gyneco-Obstetric and Pediatric Hospital of Douala) • MRI Magnetic Resonance Imaging • OR Odds Ratio • RDT Rapid Diagnostic Test • SD Standard Deviation • SPSS Statistical Package for the Social Sciences • Video-EEG Video-Electroencephalography Declarations Ethics approval and consent to participate. Ethical approval was obtained from the University of Douala: n° 1679/CEI-UDo/02/2019/T and DGOPH: n°2018/0005/HGOPED/DG/CEI institutional ethics committees. The retrospective component received consent waiver; written informed consent was obtained for prospective enrollment. Confidentiality was maintained through data coding and secure storage. The study was observational with no additional costs to participants and was conducted according to the declaration of Helsinki. Data Availability Statement: The datasets used and/or analyzed during the current study are not publicly available due to ethical restrictions and privacy protection requirements for pediatric medical data. However, de-identified datasets are available from the corresponding author on reasonable request and with appropriate ethical approvals. Consent for publication Not applicable Competing interests The authors declare no competing interests. Authors details 1 Faculty of Medicine and Pharmaceutical Sciences, University of Dschang, Dschang, Cameroon 2 Pediatric Department, Douala Gyneco-Obstetric and Pediatric Hospital, Douala, Cameroon 3 Faculty of Medicine and the Biomedical Sciences, University of Garoua, Garoua, Cameroon 4 Faculty of Medicine and Pharmaceutical Sciences, University of Douala, Douala, Cameroon 5 School of Health and Medical Sciences, Catholic University of Cameroon, Bamenda, Cameroon Clinical Trial Number Not applicable Funding This research did not receive a specific grant. Acknowledgements The authors thank all the staff at the pediatric ward at the Douala Gyneco-Obstetric and Pediatric Hospital, as well as the families who agreed to participate in the study. Authors’ Contributions Conception and design : DE, DCKK, YNM. Data collection : DE, CHK, DNN. Data analysis and interpretation : DCKK, DE, CHK. Write-up and revision of the manuscript : DE, SH, FEN, PHA, JANK, PCNM Supervision : DE, DCKK, YNM. Approval of final version of the manuscript : All authors References Fouad H, Haron M, Halawa EF, Nada M. Nontraumatic coma in a tertiary pediatric emergency department in Egypt: etiology and outcome. J Child Neurol. 2011;26(1):136-41. doi:10.1177/0883073810374358. Singhi PD, Bansal A, Ramesh S, Khandelwal N, Singhi SC. Predictive value of electroencephalography and computed tomography in childhood non-traumatic coma. Indian J Pediatr. 2005;72(6):475-9. doi:10.1007/BF02724423. Balaka B, Douti L, Azoumah D, Bakonde B, Agbere AD, Kessie K. Etiologies and prognosis of non-traumatic comas in children at the University Hospital of Lomé. J Rech Sci Univ Lomé. 2012;14(1):33-40. Arciniegas D, Anderson C, Filley C. Behavioral Neurology & Neuropsychiatry [Internet]. Cambridge University Press. [cited 2025 Oct 5]. Available from: https://www.cambridge.org/core/books/behavioral-neurology-neuropsychiatry/1F2A6A40200D29559C258D0C89EA9434 Sofiah A, Hussain IH. 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Emergency and resuscitation management of status epilepticus in adults and children (excluding newborns). Formalized recommendations from experts under the auspices of the French-speaking Resuscitation Society. Réanimation. 2009;18(1):4-12. doi:10.1016/j.reaurg.2008.07.008. Coulter DA, DeLorenzo RJ. Basic mechanisms of status epilepticus. Adv Neurol. 1999;79:725-33. Seif-Eddeine H, Treiman DM. Problems and controversies in status epilepticus: a review and recommendations. Expert Rev Neurother. 2011;11(12):1747-58. doi:10.1586/ern.11.160. Chin RFM, Neville BGR, Peckham C, Bedford H, Wade A, Scott RC, et al. Incidence, cause, and short-term outcome of convulsive status epilepticus in childhood: prospective population-based study. Lancet. 2006;368(9531):222-9. doi:10.1016/S0140-6736(06)69043-0. Nguefack S, Mbassi HD, Kambou Kouam M, Chiabi A, Mah E, Mbonda E, et al. Etiologies and short-term evolution of inaugural status epilepticus in infants and children in two university hospitals in Yaoundé (Cameroon). Health Sci Dis. 2016;17(1). https://doi.org/10.5281/hsd.v17i1.568 Gordon KE. Pediatric minor traumatic brain injury. Semin Pediatr Neurol. 2006;13(4):243-55. doi:10.1016/j.spen.2006.09.005. Sookplung P, Vavilala MS. What is new in pediatric traumatic brain injury? Curr Opin Anaesthesiol. 2009;22(5):572-8. doi:10.1097/ACO.0b013e3283303884. Farrell CA. Care for pediatric patients with acute head trauma. Paediatr Child Health. 2013;18(5):259-64. doi:10.1093/pch/18.5.259. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 30 Dec, 2025 Read the published version in BMC Pediatrics → Version 1 posted Editorial decision: Revision requested 28 Nov, 2025 Reviews received at journal 27 Nov, 2025 Reviews received at journal 22 Nov, 2025 Reviewers agreed at journal 21 Nov, 2025 Reviewers agreed at journal 13 Nov, 2025 Reviewers agreed at journal 13 Nov, 2025 Reviewers invited by journal 11 Nov, 2025 Editor invited by journal 07 Nov, 2025 Editor assigned by journal 07 Nov, 2025 Submission checks completed at journal 07 Nov, 2025 First submitted to journal 03 Nov, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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2","display":"","copyAsset":false,"role":"figure","size":50783,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8017262/v1/a359786c8b09f17002729a66.jpg"},{"id":99545443,"identity":"54b9d8bc-00fc-4df3-b778-c1f360728c1c","added_by":"auto","created_at":"2026-01-05 16:07:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1320191,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8017262/v1/43b40e81-809c-4a3a-8002-3e62e88ac37e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eEtiology and Short-term Outcome of Pediatric Coma at a Tertiary Hospital in Douala, Cameroon\u003c/p\u003e","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eComa is defined as a prolonged loss of consciousness resulting from dysfunction of the ascending reticular activating formation (ARAF), which is responsible for arousal and maintenance of wakefulness [1\u0026ndash;4]. In pediatric practice, coma represents a critical emergency, accounting for 10\u0026ndash;15% of all hospitalizations and associated with substantial morbidity and mortality [5\u0026ndash;7].\u003c/p\u003e\u003cp\u003eThe epidemiology of pediatric coma varies significantly across geographic regions. In England, the incidence of non-traumatic coma has been estimated at 30.8 per 100,000 children under 16 years annually, with etiology-specific mortality rates ranging from 3% to 84% [8]. In Saudi Arabia, Ali et al. reported an incidence of 4.8 per 100,000 children per year for both traumatic and non-traumatic coma, with a mortality rate of 47.2% [9]. African studies have shown variable prevalence rates: 5.4% in Lom\u0026eacute;, Togo (mortality 27.6%) [3], and 14.4% in Cairo, Egypt (mortality 50%) [1].\u003c/p\u003e\u003cp\u003eIn sub-Saharan Africa and Asia, the predominant etiologies of pediatric coma are infections of the central nervous system, including cerebral malaria, acute bacterial meningitis, and viral encephalitis. Understanding the etiology and predictive factors of coma outcomes is crucial for developing improved management strategies, particularly in resource-limited settings where diagnostic and supportive systems are rarely available [10].\u003c/p\u003e\u003cp\u003eThe prognosis of coma depends on both etiology and the rapidity of appropriate management [11\u0026ndash;13]. Outcomes range from complete recovery to persistent neurological sequelae or death. Two particular evolutionary aspects deserve attention: brain death and vegetative state.\u003c/p\u003e\u003cp\u003eIn Douala, Cameroon's largest city, limited data exist on pediatric coma. This study was therefore undertaken to describe the etiologies and determine the short-term outcomes of childhood coma at the Gyneco-Obstetric and Pediatric Hospital of Douala (HGOPED), a major tertiary referral center.\u003c/p\u003e"},{"header":"2. MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study Design, Area, and Population\u003c/h2\u003e\u003cp\u003eWe conducted a cross-sectional study with both retrospective and prospective phases at the Gyneco-Obstetric and Pediatric Hospital of Douala (HGOPED) in Cameroon. The study extended from December 2018 to June 2019, encompassing data collection for children who presented with coma between January 2017 and April 2019, totaling 28 months of patient inclusion. HGOPED is a first-category tertiary hospital located in Douala 3rd district, covering 7 hectares with 11 buildings. The facility serves as a major referral center for the Douala metropolitan area and surrounding regions.\u003c/p\u003e\u003cp\u003eThe pediatric service at HGOPED comprises three functional units: general pediatrics with 25-bed capacity, neonatology with 20-bed capacity divided into internal and external sectors, and an outpatient consultation unit. The hospital is staffed by 5 pediatricians including 2 neonatologists and 1 child neurologist, 6 general practitioners, and approximately 30 paramedical personnel. Diagnostic facilities available include a clinical laboratory, video-electroencephalography, and computed tomography imaging services, providing comprehensive investigative capabilities for neurological emergencies.\u003c/p\u003e\u003cp\u003eThe study population comprised children aged 1 month to 15 years hospitalized during the study period who presented with coma. Inclusion criteria encompassed both a retrospective analysis of medical records for children aged 1 month to 15 years presenting with coma and a prospective cohort of children in the same age range for whom parental or guardian informed consent was secured. Children were excluded from the study if their medical records were incomplete in the retrospective phase, or if informed consent from a parent or guardian was not obtained in the prospective phase.\u003c/p\u003e\u003cp\u003eSample size was calculated using Lorenz's formula: n = (t)\u0026sup2; \u0026times; p \u0026times; (1-p) / e\u0026sup2;, where n represents expected sample size, t equals confidence level of 1.96 for 95% confidence, p represents estimated population proportion with the characteristic studied, and e equals margin of error of 5%. Using a coma prevalence of 5.4% from Lom\u0026eacute;, Togo, the calculated minimum sample size was 79 patients. Our final sample of 109 patients exceeded this requirement, ensuring adequate statistical power.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Description of Materials\u003c/h2\u003e\u003cp\u003eAfter obtaining administrative authorization and ethical clearance from both HGOPED and the University of Douala institutional ethics committees, data collection proceeded through two distinct phases. For the retrospective phase, the pediatric and intensive care unit admission registers were systematically reviewed to identify all children aged 1 month to 15 years hospitalized between January 2017 and April 2019. Medical records were then carefully examined to identify coma cases meeting inclusion criteria, with data extracted using standardized case report forms.\u003c/p\u003e\u003cp\u003e For the prospective phase, all children presenting with coma or developing coma during hospitalization whose parents provided informed consent were enrolled consecutively. Standardized case report forms were designed to capture comprehensive information across multiple domains including sociodemographic characteristics, medical history, clinical presentation, investigation results, treatment administered, and outcomes. Each prospectively enrolled child underwent systematic clinical examination at admission, including detailed neurological assessment and Glasgow Coma Scale scoring. Capillary glucose measurement was performed routinely in the emergency room for all patients. Additional investigations including malaria testing, laboratory studies, lumbar puncture when indicated, and neuroimaging were performed based on clinical presentation and suspected etiology.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Variables and Data Collection\u003c/h2\u003e\u003cp\u003eData collection encompassed multiple variable categories to provide comprehensive characterization of pediatric coma cases. Sociodemographic data included age, sex, city of residence, and referral source whether directly from home or referred from another healthcare facility. Personal medical history variables documented psychomotor development status, previous episodes of coma, seizure history, known epilepsy diagnosis, and ongoing antiepileptic treatment at the time of admission.\u003c/p\u003e\u003cp\u003eClinical characteristics at admission were meticulously recorded, including body weight, consciousness level assessed using Glasgow Coma Scale, coma stage classification, presence of respiratory distress, digestive disorders, clinical malnutrition, skin rash, ear-nose-throat infections, severe pallor suggesting anemia, body temperature, and seizure activity including topography and seizure type. The comprehensive clinical assessment ensured capture of all relevant presenting features that might influence diagnosis and prognosis.\u003c/p\u003e\u003cp\u003eComplementary investigations performed were systematically documented, including capillary glucose measurement, thick blood smear for malaria parasites, malaria rapid diagnostic test, serum sodium levels, hemoglobin concentration, C-reactive protein, lumbar puncture with cerebrospinal fluid analysis and culture, brain computed tomography, brain magnetic resonance imaging, and electroencephalography. The availability and results of these investigations were recorded, recognizing that resource limitations might affect diagnostic workup completeness.\u003c/p\u003e\u003cp\u003eEtiological classification was determined based on clinical presentation, investigation results, and final diagnosis. Categories included infectious causes such as cerebral malaria, septicemia, febrile gastroenteritis with dehydration, herpes encephalitis, and bacterial meningitis; metabolic and toxic causes including hyponatremia, hypoglycemia, various intoxications, and diabetic ketoacidosis; post-epileptic coma and status epilepticus; traumatic brain injury; intracranial hemorrhage; vascular causes; congenital malformations; and unknown etiology when diagnosis could not be established despite investigation.\u003c/p\u003e\u003cp\u003eOutcome variables at hospital discharge included death, transfer to another facility, discharge against medical advice, survival without sequelae, and survival with sequelae. For patients with sequelae, the specific types were documented including motor deficit, visual impairment, hearing impairment, psychomotor regression, and behavioral disorders. Hospital stay duration was also recorded, categorized as less than one week, one week to one month, or more than one month.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Clinical Variables\u003c/h2\u003e\u003cp\u003eSeveral operational definitions guided data collection, classification, and analysis. Coma was defined as a Glasgow Coma Scale score\u0026thinsp;\u0026le;\u0026thinsp;14 out of 15, using either the standard Glasgow Coma Scale for verbal children or the pediatric Glasgow Coma Scale for pre-verbal children. This threshold was chosen to capture the full spectrum of altered consciousness requiring intensive monitoring and management.\u003c/p\u003e\u003cp\u003eComa severity was stratified into four stages based on Glasgow Coma Scale scores: Stage I representing Vigil Coma with GCS 11\u0026ndash;13, Stage II representing Light Coma with GCS 9\u0026ndash;10, Stage III representing Deep Coma with GCS 6\u0026ndash;8, and Stage IV representing Beyond Coma or Carus with GCS 3\u0026ndash;5. This classification system allowed for prognostic stratification and facilitated comparison with other studies.\u003c/p\u003e\u003cp\u003eShort-term outcome was defined as patient status at hospital discharge, categorized as death, discharge against medical advice, transfer to another facility, survival without detectable sequelae, or survival with neurological sequelae. Sequelae were specifically defined as new neurological deficits present at discharge that were absent on admission or represented deterioration from baseline function. These included motor deficit affecting limb movement or coordination, visual impairment newly identified or worsened, hearing impairment newly identified or worsened, psychomotor regression representing loss of previously acquired developmental milestones, and behavioral disorders manifesting as new problematic behaviors do not present before the coma episode.\u003c/p\u003e\u003cp\u003eFever was defined as body temperature\u0026thinsp;\u0026ge;\u0026thinsp;38\u0026deg;C measured by axillary or rectal thermometry, while hypothermia was defined as temperature\u0026thinsp;\u0026lt;\u0026thinsp;36.5\u0026deg;C. Hypoglycemia was defined as capillary glucose\u0026thinsp;\u0026le;\u0026thinsp;0.50 g/L, hyperglycemia as capillary glucose\u0026thinsp;\u0026ge;\u0026thinsp;1.26 g/L, and normoglycemia as values between these thresholds. Severe pallor was clinically assessed using palmar and conjunctival examination, suggesting significant anemia. Respiratory distress was identified by tachypnea, increased work of breathing, or oxygen desaturation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Data Analysis\u003c/h2\u003e\u003cp\u003eData were entered and analyzed using Census and Survey Processing System (CSPro) for data entry and SPSS version 20.0 for statistical analysis. Tables and figures were created using Microsoft Excel and Word 2010 to present results clearly. Descriptive statistics included frequencies and percentages for categorical variables and means with standard deviations for continuous variables. Medians and ranges were also calculated for variables with skewed distributions.\u003c/p\u003e\u003cp\u003eCategorical variables were compared using Chi-square tests when expected cell counts were adequate, or Fisher's exact tests when expected cell counts were small. The significance threshold was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for all statistical tests. Associations between predictor variables and outcomes, particularly mortality and sequelae, were assessed using odds ratios with 95% confidence intervals. Logistic regression analysis was performed to identify independent predictors of mortality while controlling for potential confounding factors. Variables with p-values\u0026thinsp;\u0026lt;\u0026thinsp;0.20 in univariate analysis were included in multivariable models. Linear regression analyses were also performed where appropriate to examine relationships between continuous variables and outcomes. Model goodness-of-fit was assessed, and multicollinearity was checked for all regression models. Results were presented in tables showing odds ratios, confidence intervals, and p-values for significant associations.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. RESULTS","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Study Population and Sociodemographic Characteristics\u003c/h2\u003e\u003cp\u003eOf 864 children hospitalized during the 28-month study period (January 2017 to April 2019), 109 (12.6%) presented with coma, comprising 88 cases identified retrospectively and 21 prospectively enrolled. Males constituted 57.8% (n\u0026thinsp;=\u0026thinsp;63) of the cohort, giving a male-to-female ratio of 1.4:1. The mean age was 48.8\u0026thinsp;\u0026plusmn;\u0026thinsp;47.5 months (range: 1-180 months; median: 36 months), with children under 5 years representing nearly two-thirds (64.2%) of all cases.\u003c/p\u003e\u003cp\u003e The largest age group was children aged 3\u0026ndash;24 months (43.1%, n\u0026thinsp;=\u0026thinsp;47), followed by those aged 5\u0026ndash;10 years (22.9%, n\u0026thinsp;=\u0026thinsp;25). Infants under 3 months represented only 3.7% (n\u0026thinsp;=\u0026thinsp;4) of cases, while children aged 25\u0026ndash;59 months accounted for 16.5% (n\u0026thinsp;=\u0026thinsp;18), and adolescents aged 10\u0026ndash;15 years comprised 12.8% (n\u0026thinsp;=\u0026thinsp;14) of the cohort. Male predominance was most pronounced in older age groups, with males representing 85.7% of adolescent cases compared to only 25% of infants under 3 months. (See Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAge and Sex Distribution of Children with Coma (N\u0026thinsp;=\u0026thinsp;109)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge Group\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eMale (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eFemale (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eTotal (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u0026ndash;3 months\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (25.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e3 (75.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003e4 (3.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u0026ndash;24 months\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24 (51.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e23 (48.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003e47 (43.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25\u0026ndash;59 months\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10 (55.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e8 (44.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003e18 (16.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026ndash;10 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16 (64.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e9 (36.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003e25 (22.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u0026ndash;15 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12 (85.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2 (14.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003e14 (12.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e63 (57.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e46 (42.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003e109 (100)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eRegarding geographic distribution, the vast majority of patients (91.7%, n\u0026thinsp;=\u0026thinsp;100) resided in Douala, with smaller proportions from Buea (4.6%, n\u0026thinsp;=\u0026thinsp;5), and other cities including Kribi and Ed\u0026eacute;a (3.7%, n\u0026thinsp;=\u0026thinsp;4). Most children (74.3%, n\u0026thinsp;=\u0026thinsp;81) were referred from other healthcare facilities, while 25.7% (n\u0026thinsp;=\u0026thinsp;28) were brought directly from home.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Medical History\u003c/h2\u003e\u003cp\u003eNormal psychomotor development was documented in 91.3% (n\u0026thinsp;=\u0026thinsp;100) of patients, indicating that the majority of children had no pre-existing neurological impairment. Previous history of seizures was reported in 17.5% (n\u0026thinsp;=\u0026thinsp;19) of cases, while only 1.9% (n\u0026thinsp;=\u0026thinsp;2) had experienced a prior episode of coma. Known epilepsy was present in 5.8% (n\u0026thinsp;=\u0026thinsp;6) of children, all of whom (5.8%, n\u0026thinsp;=\u0026thinsp;6) were receiving ongoing antiepileptic treatment at the time of admission.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Clinical Presentation\u003c/h2\u003e\u003cp\u003eAssessment of coma severity using the Glasgow Coma Scale revealed that the majority of patients presented with moderate coma: Stage II (GCS 9\u0026ndash;10) was most common at 45.0% (n\u0026thinsp;=\u0026thinsp;49), followed by Stage I (GCS 11\u0026ndash;13) at 23.9% (n\u0026thinsp;=\u0026thinsp;26), and Stage III (GCS 6\u0026ndash;8) at 20.2% (n\u0026thinsp;=\u0026thinsp;22). Severe Stage IV coma (GCS 3\u0026ndash;5) was present in 10.1% (n\u0026thinsp;=\u0026thinsp;11) of cases. (See Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eClinical Characteristics at Admission (N\u0026thinsp;=\u0026thinsp;109)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical Feature\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber, n (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eComa Severity (Glasgow Coma Scale)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStage I (GCS 11\u0026ndash;13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26 (23.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStage II (GCS 9\u0026ndash;10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e49 (45.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStage III (GCS 6\u0026ndash;8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22 (20.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStage IV (GCS 3\u0026ndash;5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11 (10.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTemperature\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFever (\u0026ge;\u0026thinsp;38\u0026deg;C)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e80 (73.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNormothermia (36.5\u0026ndash;37.5\u0026deg;C)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20 (18.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypothermia (\u0026lt;\u0026thinsp;36.5\u0026deg;C)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9 (8.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAssociated Features\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSeizures at admission\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e75 (68.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRespiratory distress\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50 (45.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDigestive disorders\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e42 (38.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSevere pallor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25 (22.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSkin rash\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12 (11.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eENT infection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (6.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMalnutrition\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6 (5.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFever (temperature\u0026thinsp;\u0026ge;\u0026thinsp;38\u0026deg;C) was the most frequent associated finding, present in 73.4% (n\u0026thinsp;=\u0026thinsp;80) of patients at admission. Normothermia (36.5\u0026ndash;37.5\u0026deg;C) was documented in 18.3% (n\u0026thinsp;=\u0026thinsp;20), while hypothermia (\u0026lt;\u0026thinsp;36.5\u0026deg;C) occurred in 8.3% (n\u0026thinsp;=\u0026thinsp;9). Seizures at admission were observed in 68.8% (n\u0026thinsp;=\u0026thinsp;75) of children, predominantly generalized in distribution (85.3%). Respiratory distress was identified in 45.9% (n\u0026thinsp;=\u0026thinsp;50), and digestive disorders in 38.5% (n\u0026thinsp;=\u0026thinsp;42) of cases. Severe pallor, suggestive of significant anemia, was noted in 22.9% (n\u0026thinsp;=\u0026thinsp;25) of children. Less frequent findings included skin rash (11.0%, n\u0026thinsp;=\u0026thinsp;12), ear-nose-throat infections (6.4%, n\u0026thinsp;=\u0026thinsp;7), and clinical malnutrition (5.5%, n\u0026thinsp;=\u0026thinsp;6).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Laboratory and Imaging Investigations\u003c/h2\u003e\u003cp\u003eCapillary glucose measurement was performed in 98.2% (n\u0026thinsp;=\u0026thinsp;107) of patients, revealing hypoglycemia (\u0026le;\u0026thinsp;0.50 g/L) in 12.1%, hyperglycemia (\u0026ge;\u0026thinsp;1.26 g/L) in 9.3%, and normoglycemia in 78.6%. Malaria diagnostic testing (thick blood smear and/or rapid diagnostic test) was completed in 89.0% of cases, with 47.7% testing positive. Serum sodium was measured in 45.0% of patients, with hyponatremia detected in 11.9% of the total cohort. Mean hemoglobin level was 9.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2 g/dL, indicating prevalent anemia. C-reactive protein was measured in 68.8% of cases and was elevated in the majority.\u003c/p\u003e\u003cp\u003eCerebrospinal fluid examination was performed in only 31.2% (n\u0026thinsp;=\u0026thinsp;34) of patients. Among these, CSF culture was positive in 2.9%, and bacterial meningitis was confirmed in 0.9% (n\u0026thinsp;=\u0026thinsp;1) of the total cohort. Neuroimaging was limited: brain computed tomography was performed in 22.0% (n\u0026thinsp;=\u0026thinsp;24) with abnormal findings in half of these cases, brain magnetic resonance imaging in 4.6% (n\u0026thinsp;=\u0026thinsp;5), and electroencephalography in 8.3% (n\u0026thinsp;=\u0026thinsp;9).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.5 Etiological Distribution\u003c/h2\u003e\u003cp\u003eInfectious causes predominated, accounting for 62.4% (n\u0026thinsp;=\u0026thinsp;68) of all cases. Within this category, cerebral malaria was the single most common etiology at 42.2% (n\u0026thinsp;=\u0026thinsp;46), followed by septicemia at 15.6% (n\u0026thinsp;=\u0026thinsp;17). Febrile gastroenteritis with dehydration contributed 6.4% (n\u0026thinsp;=\u0026thinsp;7), herpes encephalitis 2.8% (n\u0026thinsp;=\u0026thinsp;3), and bacterial meningitis 0.9% (n\u0026thinsp;=\u0026thinsp;1) of cases. (See Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEtiological Distribution of Pediatric Coma (N\u0026thinsp;=\u0026thinsp;109)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEtiology\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDeaths (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInfectious causes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e68 (62.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 (27.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCerebral malaria\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46 (42.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9 (19.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSepticemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17 (15.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8 (47.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFebrile gastroenteritis with dehydration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (6.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (42.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHerpes encephalitis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (2.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (66.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBacterial meningitis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (100)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMetabolic/Toxic causes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18 (16.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (22.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHyponatremia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13 (11.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (23.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypoglycemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (2.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntoxication\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (2.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (33.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetic ketoacidosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePost-epileptic/Status epilepticus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16 (14.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (12.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTraumatic brain injury\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (4.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (20.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther causes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (6.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (28.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnknown etiology\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14 (12.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (7.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMalformations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the relative proportions of different etiological categories. Metabolic and toxic causes represented the second largest etiological group at 16.5% (n\u0026thinsp;=\u0026thinsp;18). Hyponatremia was the predominant metabolic disturbance, affecting 11.9% (n\u0026thinsp;=\u0026thinsp;13) of all patients. Hypoglycemia and various intoxications (petroleum products, medications) each accounted for 2.8% (n\u0026thinsp;=\u0026thinsp;3), while diabetic ketoacidosis was identified in 0.9% (n\u0026thinsp;=\u0026thinsp;1). Post-epileptic coma and status epilepticus collectively comprised 14.7% (n\u0026thinsp;=\u0026thinsp;16) of cases. Traumatic brain injury was relatively uncommon at 4.6% (n\u0026thinsp;=\u0026thinsp;5). Other miscellaneous causes accounted for 6.4% (n\u0026thinsp;=\u0026thinsp;7), while malformations represented only 0.9% (n\u0026thinsp;=\u0026thinsp;1). Despite thorough investigation, the etiology remained undetermined in 12.8% (n\u0026thinsp;=\u0026thinsp;14) of cases. No instances of intracranial hemorrhage or primary cerebrovascular causes were identified in this cohort.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.6 Clinical Outcomes\u003c/h2\u003e\u003cp\u003eOverall, 74.3% (n\u0026thinsp;=\u0026thinsp;81) of children survived to hospital discharge, while 26.6% (n\u0026thinsp;=\u0026thinsp;29) died. Among other outcomes, 2.8% (n\u0026thinsp;=\u0026thinsp;3) were transferred to other facilities, 5.5% (n\u0026thinsp;=\u0026thinsp;6) were discharged against medical advice, and 1.8% (n\u0026thinsp;=\u0026thinsp;2) required intensive care unit admission. Hospital stay duration varied: 52.3% were hospitalized for less than one week, 11.9% for one week to one month, and 7.3% for more than one month.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e demonstrates the strong relationship between coma severity and outcome. Among survivors (n\u0026thinsp;=\u0026thinsp;81), 69.1% (n\u0026thinsp;=\u0026thinsp;56) had no detectable sequelae at discharge, while 30.9% (n\u0026thinsp;=\u0026thinsp;25) experienced neurological sequelae. The specific types of sequelae are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, with motor deficits being most common at 14.8% (n\u0026thinsp;=\u0026thinsp;12), followed by visual impairment, hearing impairment, and psychomotor regression, each occurring in 2.5% (n\u0026thinsp;=\u0026thinsp;2) of survivors. Behavioral disorders were noted in 1.2% (n\u0026thinsp;=\u0026thinsp;1).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eOutcome According to Coma Severity (N\u0026thinsp;=\u0026thinsp;109)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutcome\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStage I\u003c/p\u003e\u003cp\u003e(GCS 11\u0026ndash;13)\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;26\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStage II\u003c/p\u003e\u003cp\u003e(GCS 9\u0026ndash;10)\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;49\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eStage III\u003c/p\u003e\u003cp\u003e(GCS 6\u0026ndash;8)\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;22\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eStage IV\u003c/p\u003e\u003cp\u003e(GCS 3\u0026ndash;5)\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;11\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eTotal n\u0026thinsp;=\u0026thinsp;109\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSurvival without sequelae\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21 (80.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33 (67.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13 (59.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e67 (61.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSurvival with sequelae\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (19.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16 (32.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (40.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e30 (27.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDeath\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (3.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12 (24.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (27.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e30 (27.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTransfer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (2.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (0.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDAMA*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (10.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 (9.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6 (5.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003e*DAMA: Discharge against medical advice\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSequelae Among Survivors (n\u0026thinsp;=\u0026thinsp;81)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eType of Sequelae\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber, n (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo sequelae\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e56 (69.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c3\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAny sequelae\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25 (30.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c3\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMotor deficit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12 (14.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c3\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVisual impairment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c3\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHearing impairment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c3\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePsychomotor regression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c3\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBehavioral disorders\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c3\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates mortality rates stratified by coma stage. A striking gradient was observed, with Stage IV (GCS 3\u0026ndash;5) demonstrating 100% mortality (11/11 patients), Stage III (GCS 6\u0026ndash;8) showing 27.3% mortality (6/22), Stage II (GCS 9\u0026ndash;10) demonstrating 24.5% mortality (12/49), and Stage I (GCS 11\u0026ndash;13) having the lowest mortality at 3.8% (1/26).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.7 Factors Associated with Mortality and Sequelae\u003c/h2\u003e\u003cp\u003eAge emerged as a powerful protective factor, with mortality decreasing substantially as age increased. Compared to children under 2 years, those aged 2\u0026ndash;5 years had an odds ratio of 0.17 (95% CI: 0.05\u0026ndash;0.59, p\u0026thinsp;=\u0026thinsp;0.017), representing an approximately 6-fold reduction in mortality risk. Children over 5 years demonstrated even greater protection with an odds ratio of 0.09 (95% CI: 0.02\u0026ndash;0.38, p\u0026thinsp;=\u0026thinsp;0.001), translating to a 10-fold reduction in mortality risk compared to infants and young toddlers. (See Table \u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePredictors of Mortality: Logistic Regression Analysis\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOdds Ratio\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u0026ndash;5 years vs. \u0026lt;2 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.05\u0026ndash;0.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.017\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;5 years vs. \u0026lt;2 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.02\u0026ndash;0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale vs. Male\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.48\u0026ndash;4.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.019\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProvenance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHome vs. Referred\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.07\u0026ndash;4.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.050\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCity of residence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutside Douala vs. Douala\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.16\u0026ndash;2.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.598\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eSex was significantly associated with outcome, with female patients demonstrating 3.54 times higher odds of death compared to males (95% CI: 2.48\u0026ndash;4.60, p\u0026thinsp;=\u0026thinsp;0.019). Referral pattern also proved significant: children admitted directly from home had 3.24 times higher mortality odds compared to those referred from other healthcare facilities (95% CI: 2.07\u0026ndash;4.42, p\u0026thinsp;=\u0026thinsp;0.050). In contrast, city of residence (Douala versus other locations) showed no significant association with mortality (OR 0.61, 95% CI: 0.16\u0026ndash;2.28, p\u0026thinsp;=\u0026thinsp;0.598).\u003c/p\u003e\u003cp\u003eComa severity was strongly associated with mortality (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), as demonstrated in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Duration of hospitalization exceeding one week was associated with significantly increased odds of developing sequelae among survivors (OR 5.23, p\u0026thinsp;=\u0026thinsp;0.008). Medical history variables, including previous seizures, known epilepsy, and abnormal psychomotor development, showed no significant associations with mortality in multivariate analysis.\u003c/p\u003e\u003cp\u003eEtiology-specific mortality analysis revealed substantial variation across diagnostic categories. Among infectious causes, septicemia carried the highest mortality at 47.1% (8/17 cases), followed by herpes encephalitis at 66.7% (2/3 cases), and cerebral malaria at 19.6% (9/46 cases). Overall infectious etiology mortality was 27.9% (19/68). Metabolic and toxic causes demonstrated 22.2% mortality (4/18), while post-epileptic coma and status epilepticus showed lower mortality at 12.5% (2/16). Traumatic brain injury resulted in 20.0% mortality (1/5 cases).\u003c/p\u003e\u003c/div\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eThis study provides important insights into the epidemiology, etiology, and outcomes of pediatric coma in a major tertiary center in Central Africa. The 12.6% prevalence observed in our study is consistent with previous reports suggesting that coma accounts for 10\u0026ndash;15% of pediatric hospitalizations [5\u0026ndash;7], though it exceeds the 5.4% reported in Lom\u0026eacute;, Togo [3] and falls below the 14.4% found in Cairo [1]. These variations may reflect differences in referral patterns, healthcare-seeking behavior, and disease burden across different African settings.\u003c/p\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Demographic Characteristics\u003c/h2\u003e\u003cp\u003eThe male predominance (sex ratio 1.4:1) observed in our cohort is consistent with several previous studies [1,3]. The mean age of 48.8 months and the predominance of children under 5 years (64.2%) align with global patterns showing that younger children are at higher risk for coma, likely reflecting age-related vulnerabilities including immature cerebral physiology, higher susceptibility to infections, and increased risk of metabolic derangements [5,14].\u003c/p\u003e\u003cp\u003eThe high proportion of referrals from other healthcare facilities (74.3%) underscores HGOPED's role as a tertiary referral center. Interestingly, direct admission from home was associated with significantly higher mortality (OR 3.24), possibly reflecting delays in care-seeking, more severe disease at presentation, or inadequate initial management. This finding emphasizes the importance of efficient referral systems and community education about recognizing danger signs.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Clinical Presentation and Severity\u003c/h2\u003e\u003cp\u003eThe distribution of coma severity in our study showed that most patients presented with moderate coma (Stages II and III: 65.2%), while 10.1% had very deep coma (Stage IV). This distribution has important prognostic implications, as we observed 100% mortality in Stage IV coma, compared to only 3.8% in Stage I. These findings are consistent with numerous studies demonstrating that GCS score is a powerful predictor of outcome in pediatric coma [11,12].\u003c/p\u003e\u003cp\u003eSeizures at admission were present in 68.8% of patients, predominantly generalized. This high frequency likely reflects both the etiologies prevalent in our setting (particularly cerebral malaria and status epilepticus) and the pathophysiological mechanisms of coma in children, where seizure activity frequently accompanies acute brain dysfunction.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e4.3 Etiological Profile\u003c/h2\u003e\u003cp\u003eThe predominance of infectious causes (62.4%) in our study mirrors findings from other sub-Saharan African and Asian countries, where infections remain the leading cause of pediatric coma [1,3,8\u0026ndash;10]. However, the specific distribution of infectious etiologies reflects regional epidemiology.\u003c/p\u003e\u003cp\u003eCerebral malaria emerged as the single most common cause (42.2%), consistent with the high malaria endemicity in Cameroon. This finding aligns with studies from other malaria-endemic regions where cerebral malaria accounts for 30\u0026ndash;50% of pediatric coma cases. The 19.6% mortality rate for cerebral malaria in our study falls within the reported range of 15\u0026ndash;25% for this condition, though it remains unacceptably high given that malaria is preventable and treatable.\u003c/p\u003e\u003cp\u003eSepticemia (15.6%) was the second most common infectious cause, with a notably high mortality rate of 47.1%. This high fatality rate likely reflects both the severity of sepsis at presentation and potential limitations in intensive care capabilities. The low frequency of bacterial meningitis (0.9%) may be attributable to several factors: widespread vaccination against \u003cem\u003eHaemophilus influenzae\u003c/em\u003e and \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e, empirical antibiotic use before lumbar puncture, or diagnostic limitations (only 31.2% of patients underwent lumbar puncture).\u003c/p\u003e\u003cp\u003eMetabolic and toxic causes (16.5%) represented the second most common etiological category. Hyponatremia (11.9%) was the most frequent metabolic disturbance, consistent with reports that children are at higher risk than adults for hyponatremic encephalopathy due to their relatively larger brain-to-intracranial volume ratio [15\u0026ndash;17]. Hypoglycemia (2.8%) was less common than expected, possibly due to systematic glucose monitoring and correction in the emergency department before enrollment.\u003c/p\u003e\u003cp\u003ePost-epileptic coma and status epilepticus (14.7%) constituted a significant proportion, reflecting the high burden of seizure disorders in African children [18\u0026ndash;21]. The fact that only 5.8% of our cohort had known epilepsy suggests that many cases represented first presentations or seizures secondary to acute illnesses.\u003c/p\u003e\u003cp\u003eTraumatic brain injury (4.6%) was relatively uncommon in our series, likely because severe trauma cases may be managed at other facilities or because parents delay seeking care for trauma. This low proportion contrasts with data from high-income countries where trauma often accounts for a larger proportion of pediatric coma [22\u0026ndash;24].\u003c/p\u003e\u003cp\u003eThe 12.8% of cases with unknown etiology despite investigation highlights diagnostic challenges in resource-limited settings, including limited access to advanced neuroimaging, microbiological diagnostics, and metabolic testing.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e4.4 Diagnostic Approach\u003c/h2\u003e\u003cp\u003eThe diagnostic workup in our study reflected the resource constraints typical of many African settings. While basic investigations (capillary glucose, malaria testing, hemoglobin) were performed in most patients, more advanced studies were limited: brain imaging in only 26.6%, lumbar puncture in 31.2%, and EEG in 8.3%. These limitations may have contributed to the relatively high proportion of unknown etiologies and could have affected management decisions.\u003c/p\u003e\u003cp\u003eThe low rate of lumbar puncture is concerning given the need to exclude treatable causes such as bacterial meningitis. Barriers may include concerns about safety in patients with altered consciousness, lack of availability of CT to exclude raised intracranial pressure, or empirical antibiotic treatment initiated before the procedure.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003e4.5 Outcomes and Prognostic Factors\u003c/h2\u003e\u003cp\u003eThe overall mortality rate of 26.6% in our study falls within the wide range (3\u0026ndash;84%) reported globally [8], but exceeds rates from high-income countries and approaches those from other resource-limited settings in Africa [1,3,9]. This mortality reflects both the severity of presenting illnesses and systemic healthcare limitations.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003e4.6 Several factors emerged as significant predictors of mortality:\u003c/h2\u003e\u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003cp\u003eYounger children (\u0026lt;\u0026thinsp;2 years) had substantially higher mortality, with odds 6\u0026ndash;10 times higher than older children. This age-related vulnerability reflects multiple factors including immature cerebral autoregulation, limited physiological reserves, higher susceptibility to hypoglycemia and electrolyte disturbances, and greater vulnerability to infection-related complications.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003cp\u003eThe unexpected finding of higher mortality in females (OR 3.54) contrasts with some previous studies showing male predominance in poor outcomes. This finding requires further investigation but could reflect sex-specific differences in care-seeking behavior, underlying nutritional status, or biological factors.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eComa severity\u003c/strong\u003e\u003cp\u003eThe strong relationship between deeper coma stages and mortality has been consistently demonstrated across multiple studies and settings [11\u0026ndash;13]. The 100% mortality in Stage IV coma reflects the severity of underlying brain dysfunction and the limited reversibility of such profound depression of consciousness.\u003c/p\u003e\u003c/p\u003e\u003cp\u003eReferral pattern: The threefold higher mortality in children coming directly from home versus those referred from other facilities is striking and suggests several possible mechanisms: delay in initial care-seeking leading to more advanced disease, lack of stabilization before referral, or more fulminant disease courses. This finding emphasizes the importance of community health education and strengthening primary care capabilities.\u003c/p\u003e\u003cp\u003eAmong survivors, 30.9% had sequelae at discharge, predominantly motor deficits (14.8%). Hospitalization exceeding one week was associated with fivefold higher odds of sequelae, likely reflecting both greater injury severity and longer disease courses. These findings underscore the substantial burden of neurological morbidity beyond mortality.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e\u003ch2\u003e4.7 Clinical and Public Health Implications\u003c/h2\u003e\u003cp\u003eOur findings have important implications for clinical practice and public health policy in similar resource-limited settings:\u003c/p\u003e\u003cp\u003eMalaria prevention and control must remain a priority, as cerebral malaria constitutes the largest single preventable cause of pediatric coma. Strategies should include widespread distribution of insecticide-treated bed nets, prompt diagnosis and treatment of malaria, and continued research into vaccines and novel therapeutics.\u003c/p\u003e\u003cp\u003eEarly recognition and management of pediatric emergencies at the community and primary care levels could reduce mortality, particularly given the association between direct home admission and poor outcomes. Training of community health workers and primary care physicians in recognizing danger signs and providing initial stabilization is critical.\u003c/p\u003e\u003cp\u003eStrengthening referral systems and emergency transport capabilities could improve outcomes by ensuring patients receive appropriate care at each level and arrive at tertiary centers in optimally stabilized condition.\u003c/p\u003e\u003cp\u003eSystematic diagnostic protocols including routine lumbar puncture (when safe), glucose monitoring, electrolyte assessment, and neuroimaging when indicated should be implemented to improve etiological diagnosis and targeted treatment.\u003c/p\u003e\u003cp\u003eImproved intensive care capabilities including mechanical ventilation, hemodynamic monitoring, and neurological support could potentially reduce mortality, particularly in severe cases and those with metabolic derangements.\u003c/p\u003e\u003cp\u003eLong-term follow-up programs for survivors are needed to identify and address delayed neurological sequelae, support rehabilitation, and improve functional outcomes.\u003c/p\u003e\u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study demonstrates that pediatric coma at a tertiary hospital in Douala predominantly affects young children and is primarily attributable to infectious causes, particularly cerebral malaria. The mortality rate of 26.6% remains high, with younger age, female sex, direct admission from home, and deeper coma stages serving as significant predictors of poor outcome. Among survivors, nearly one-third experience neurological sequelae at discharge, predominantly motor deficits.\u003c/p\u003e\u003cp\u003eThese findings emphasize the urgent need for strengthened malaria prevention and control programs, improved community awareness of pediatric danger signs, enhanced referral systems, and increased diagnostic and intensive care capabilities in resource-limited settings. Early recognition and prompt, appropriate management of preventable causes could substantially reduce both mortality and morbidity from pediatric coma in Central Africa.\u003c/p\u003e\u003cp\u003eFuture multicenter prospective studies with longer follow-up periods and standardized diagnostic protocols are needed to better characterize the full spectrum and long-term outcomes of pediatric coma in this region.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudy Limitations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study has several limitations. First, the single-center design and convenience sampling limit generalizability. Second, the retrospective component of the study was constrained by incomplete medical records for some variables. Third, the relatively short follow-up (to hospital discharge only) does not capture long-term outcomes or delayed neurological sequelae. Fourth, limited access to advanced diagnostics (neuroimaging, comprehensive metabolic panels, extended microbiological testing) likely resulted in missed diagnoses and contributed to the unknown etiology category. Fifth, the absence of standardized protocols for investigation and management may have introduced variability in diagnostic approaches. Finally, we could not assess intensive care interventions systematically, which likely influenced outcomes.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; ARAF\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAscending Reticular Activating Formation\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; CI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eConfidence Interval\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; CRP\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eC-Reactive Protein\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; CSF\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCerebrospinal Fluid\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; CSPro\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCensus and Survey Processing System\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; CT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eComputed Tomography\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; DAMA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDischarge Against Medical Advice\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; EEG\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eElectroencephalography\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; ENT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEar, Nose, and Throat\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; GCS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eGlasgow Coma Scale\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; HGOPED\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eH\u0026ocirc;pital Gyn\u0026eacute;co-Obst\u0026eacute;trique et P\u0026eacute;diatrique de Douala (Gyneco-Obstetric and Pediatric Hospital of Douala)\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; MRI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMagnetic Resonance Imaging\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; OR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eOdds Ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; RDT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eRapid Diagnostic Test\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; SD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eStandard Deviation\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; SPSS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eStatistical Package for the Social Sciences\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u0026bull; Video-EEG\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eVideo-Electroencephalography\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from the University of Douala: n° 1679/CEI-UDo/02/2019/T and DGOPH: n°2018/0005/HGOPED/DG/CEI institutional ethics committees. The retrospective component received consent waiver; written informed consent was obtained for prospective enrollment. Confidentiality was maintained through data coding and secure storage. The study was observational with no additional costs to participants and was conducted according to the declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are not publicly available due to ethical restrictions and privacy protection requirements for pediatric medical data. However, de-identified datasets are available from the corresponding author on reasonable request and with appropriate ethical approvals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u0026nbsp;\u003c/sup\u003eFaculty of Medicine and Pharmaceutical Sciences, University of Dschang, Dschang, Cameroon\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u0026nbsp;\u003c/sup\u003ePediatric Department, Douala Gyneco-Obstetric and Pediatric Hospital, Douala, Cameroon\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003e Faculty of Medicine and the Biomedical Sciences, University of Garoua, Garoua, Cameroon\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e4\u003c/sup\u003e Faculty of Medicine and Pharmaceutical Sciences, University of Douala, Douala, Cameroon\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e5\u003c/sup\u003e School of Health and Medical Sciences, Catholic University of Cameroon, Bamenda, Cameroon\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive a specific grant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank all the staff at the pediatric ward at the Douala Gyneco-Obstetric and Pediatric Hospital, as well as the families who agreed to participate in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConception and design\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e DE, DCKK, YNM.\u0026nbsp;\u003cstrong\u003eData collection\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e DE, CHK, DNN.\u0026nbsp;\u003cstrong\u003eData analysis and interpretation\u003c/strong\u003e:\u0026nbsp;DCKK, DE, CHK.\u0026nbsp;\u003cstrong\u003eWrite-up and revision of the manuscript\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e DE, SH, FEN, PHA, JANK, PCNM\u0026nbsp;\u003cstrong\u003eSupervision\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e DE, DCKK, YNM.\u0026nbsp;\u003cstrong\u003eApproval of final version of the manuscript\u003c/strong\u003e: All authors\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFouad H, Haron M, Halawa EF, Nada M. 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Available from: https://www.cambridge.org/core/books/behavioral-neurology-neuropsychiatry/1F2A6A40200D29559C258D0C89EA9434\u003c/li\u003e\n\u003cli\u003eSofiah A, Hussain IH. Childhood non-traumatic coma in Kuala Lumpur, Malaysia. Ann Trop Paediatr. 1997;17(4):327-31. doi:10.1080/02724936.1997.11747906.\u003c/li\u003e\n\u003cli\u003eNayana Prabha PC, Nalini P, Tiroumourougane Serane V. Role of Glasgow Coma Scale in pediatric nontraumatic coma. Indian Pediatr. 2003;40(7):620-5.\u003c/li\u003e\n\u003cli\u003eKhodapanahandeh F, Najarkalayee N. Etiology and Outcome of Non-traumatic Coma in Children Admitted to Pediatric Intensive Care Unit. Iran J Pediatr. 2009;19(4):393-8.\u003c/li\u003e\n\u003cli\u003eWong CP, Forsyth RJ, Kelly TP, Eyre JA. Incidence, aetiology, and outcome of non-traumatic coma: a population-based study. Arch Dis Child. 2001;84(3):193-9. doi:10.1136/adc.84.3.193.\u003c/li\u003e\n\u003cli\u003eAli AM, Al-Abdulgader A, Kamal HM, Al-Wehedy A. Traumatic and non-traumatic coma in children in the referral hospital, Al-Hasa, Saudi Arabia. East Mediterr Health J. 2007;13(3):608-14.\u003c/li\u003e\n\u003cli\u003eIbekwe RC, Ibekwe MU, Onwe OE, Nnebe-Agumadu UH, Ibe BC. Non-traumatic childhood coma in Ebonyi State University Teaching Hospital, Abakaliki, South Eastern Nigeria. Niger J Clin Pract. 2011;14(1):43-6. doi:10.4103/1119-3077.79239.\u003c/li\u003e\n\u003cli\u003eKornbluth J, Bhardwaj A. Evaluation of coma: a critical appraisal of popular scoring systems. Neurocrit Care. 2011;14(1):134-43. doi:10.1007/s12028-010-9409-3.\u003c/li\u003e\n\u003cli\u003eMatis GK, Birbilis TA. Poor relation between Glasgow coma scale and survival after head injury. Med Sci Monit. 2009;15(2):CR62-5.\u003c/li\u003e\n\u003cli\u003ePeng Y, Jiang L. Analysis of Prognostic Factors of Children with Intracranial Infection Coma. World J Neurosci. 2015;5(2):131-6. doi:10.4236/wjns.2015.52015.\u003c/li\u003e\n\u003cli\u003eBrown EN, Lydic R, Schiff ND. General anesthesia, sleep, and coma. N Engl J Med. 2010;363(27):2638-50. doi:10.1056/NEJMra0808281.\u003c/li\u003e\n\u003cli\u003eDinis-Oliveira RJ, Magalh\u0026atilde;es T. Children intoxications: what is abuse and what is not abuse. Trauma Violence Abuse. 2013;14(2):113-32. doi:10.1177/1524838012470033.\u003c/li\u003e\n\u003cli\u003eFetveit A. Assessment of febrile seizures in children. Eur J Pediatr. 2008;167(1):17-27. doi:10.1007/s00431-007-0577-x.\u003c/li\u003e\n\u003cli\u003eOutin H, Blanc T, Vinatier I. Emergency and resuscitation management of status epilepticus in adults and children (excluding newborns). Formalized recommendations from experts under the auspices of the French-speaking Resuscitation Society. R\u0026eacute;animation. 2009;18(1):4-12. doi:10.1016/j.reaurg.2008.07.008.\u003c/li\u003e\n\u003cli\u003eCoulter DA, DeLorenzo RJ. Basic mechanisms of status epilepticus. Adv Neurol. 1999;79:725-33.\u003c/li\u003e\n\u003cli\u003eSeif-Eddeine H, Treiman DM. Problems and controversies in status epilepticus: a review and recommendations. Expert Rev Neurother. 2011;11(12):1747-58. doi:10.1586/ern.11.160.\u003c/li\u003e\n\u003cli\u003eChin RFM, Neville BGR, Peckham C, Bedford H, Wade A, Scott RC, et al. Incidence, cause, and short-term outcome of convulsive status epilepticus in childhood: prospective population-based study. Lancet. 2006;368(9531):222-9. doi:10.1016/S0140-6736(06)69043-0.\u003c/li\u003e\n\u003cli\u003eNguefack S, Mbassi HD, Kambou Kouam M, Chiabi A, Mah E, Mbonda E, et al. Etiologies and short-term evolution of inaugural status epilepticus in infants and children in two university hospitals in Yaound\u0026eacute; (Cameroon). Health Sci Dis. 2016;17(1). https://doi.org/10.5281/hsd.v17i1.568\u003c/li\u003e\n\u003cli\u003eGordon KE. Pediatric minor traumatic brain injury. Semin Pediatr Neurol. 2006;13(4):243-55. doi:10.1016/j.spen.2006.09.005.\u003c/li\u003e\n\u003cli\u003eSookplung P, Vavilala MS. What is new in pediatric traumatic brain injury? Curr Opin Anaesthesiol. 2009;22(5):572-8. doi:10.1097/ACO.0b013e3283303884.\u003c/li\u003e\n\u003cli\u003eFarrell CA. Care for pediatric patients with acute head trauma. Paediatr Child Health. 2013;18(5):259-64. doi:10.1093/pch/18.5.259.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Coma, Children, Etiology, Outcome, Cerebral malaria, Glasgow Coma Scale, Mortality, Sub-Saharan Africa","lastPublishedDoi":"10.21203/rs.3.rs-8017262/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8017262/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003ePediatric coma is a critical emergency with high morbidity and mortality in sub-Saharan Africa, where limited data hinders effective management strategies. Understanding its epidemiology and prognostic factors is essential for improving outcomes.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA 28-month cross-sectional study (January 2017-April 2019) was conducted at Gyneco-Obstetric and Pediatric Hospital of Douala, Cameroon. Children aged 1 month to 15 years with Glasgow Coma Scale\u0026thinsp;\u0026le;\u0026thinsp;14 were included. Data on demographics, clinical presentation, etiology, and outcomes were collected through retrospective record review and prospective patient enrollment. Statistical analysis used SPSS version 20.0 and CSPro with Chi-square and Fisher's exact tests.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eAmong 864 hospitalized children, 109 presented with coma (prevalence 12.6%). The male-to-female ratio was 1.4:1, with mean age 48.8\u0026thinsp;\u0026plusmn;\u0026thinsp;47.5 months; 64.2% were under 5 years. Infectious causes predominated (62.4%), with cerebral malaria accounting for 42.2% and septicemia for 15.6%. Other etiologies included metabolic/toxic causes (16.5%), post-epileptic coma/status epilepticus (14.7%), and traumatic brain injury (4.6%); 12.8% remained undiagnosed. Clinical features included fever (73.4%) and seizures at admission (68.8%). Overall mortality was 26.6%, with 30.9% of survivors experiencing neurological sequelae, predominantly motor deficits (14.8%). Significant mortality predictors included age under 2 years (6\u0026ndash;10 times higher odds), female sex (3.54 times higher odds), direct home admission (3.24 times higher odds), and deeper coma stages (100% mortality in Stage IV versus 3.8% in Stage I).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003ePediatric coma at this tertiary center predominantly affects young children and stems primarily from infectious etiologies, particularly cerebral malaria. The high mortality (26.6%) and substantial neurological morbidity among survivors underscore urgent needs for strengthened malaria prevention programs, improved community awareness, enhanced referral systems, and increased diagnostic and intensive care capabilities. Early recognition and prompt management of preventable causes could significantly reduce mortality and morbidity from pediatric coma in Central Africa.\u003c/p\u003e","manuscriptTitle":"Etiology and Short-term Outcome of Pediatric Coma at a Tertiary Hospital in Douala, Cameroon","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-21 18:06:31","doi":"10.21203/rs.3.rs-8017262/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-28T13:06:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-27T17:16:26+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-22T08:25:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"150266487692993192641203869803816278401","date":"2025-11-21T12:35:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"2926373274344840812771430670851838125","date":"2025-11-13T12:05:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"127754780236954250718427888102276547064","date":"2025-11-13T06:48:02+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-11T08:43:52+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-07T13:54:39+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-07T07:38:02+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-07T07:36:27+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pediatrics","date":"2025-11-03T09:13:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5ae66d42-b428-491c-8c6f-6953d787bf48","owner":[],"postedDate":"November 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-05T16:03:59+00:00","versionOfRecord":{"articleIdentity":"rs-8017262","link":"https://doi.org/10.1186/s12887-025-06466-y","journal":{"identity":"bmc-pediatrics","isVorOnly":false,"title":"BMC Pediatrics"},"publishedOn":"2025-12-30 15:58:08","publishedOnDateReadable":"December 30th, 2025"},"versionCreatedAt":"2025-11-21 18:06:31","video":"","vorDoi":"10.1186/s12887-025-06466-y","vorDoiUrl":"https://doi.org/10.1186/s12887-025-06466-y","workflowStages":[]},"version":"v1","identity":"rs-8017262","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8017262","identity":"rs-8017262","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}