Abstract
Background
A hemorrhagic stroke is a life‐threatening emergency that can lead to disability or death without prompt treatment. However, there is limited evidence on factors associated with mortality in hemorrhagic stroke, particularly in eastern Ethiopia. Therefore, this study is aimed at assessing the factors associated with mortality among adult hemorrhagic stroke patients in the Harari region, eastern Ethiopia.
Methodology
A retrospective cohort study was conducted among 262 patients with hemorrhagic stroke at public hospitals in the Harari region of eastern Ethiopia, from September 1, 2019, to August 31, 2024. Factors associated with mortality were identified using the Gompertz hazards regression model.
Results
Of the 262 patients included in the final analysis, 45 (17.18%; 95% CI: 13.05%–22.26%) died. The mortality rate for hemorrhagic stroke was 10.62 cases per 1000 person‐months (95% CI: 7.93–14.23). Mortality was significantly associated with patients having kidney disease (AHR: 3.04; 95% CI: 1.44–6.44; p value: 0.004) and poor Glasgow Coma Scale (GCS) scores (AHR: 3.92; 95% CI: 1.58–9.71; p value: 0.003). Septic shock and aspiration pneumonia had exploratory associations with mortality.
Conclusion
In‐hospital mortality was observed in approximately one in six hemorrhagic stroke patients treated at public hospitals. Risk factors such as kidney disease, aspiration pneumonia, poor GCS, and septic shock increased mortality risk. Hence, special emphasis should be given to early screening for kidney disease and the management of stroke patients with poor a GCS score.
Keywords: eastern Ethiopia, factors, hemorrhagic stroke patients, mortality
1. Introduction
Hemorrhagic stroke is a life‐threatening neurological emergency that requires immediate medical intervention, as delayed diagnosis and treatment are associated with an increased risk of severe neurological disability and mortality [1]. It occurs due to bleeding into the brain caused by the rupture of a blood vessel and is further subdivided into intracerebral hemorrhage (ICH) and subarachnoid hemorrhage [2, 3]. Acute lobar cerebral hemorrhages present with a different clinical presentation and a more severe early prognosis than deep subcortical ICHs. In addition, nonhypertensive mechanisms are more likely to predominate in the lobar location [4]. Compared with ischemic strokes, hemorrhagic strokes tend to present more severely with higher fatality, requiring different prevention and treatment strategies [5].
Although hemorrhagic stroke accounts for a smaller proportion of stroke cases than ischemic stroke, it contributes disproportionately to stroke‐related mortality and disability worldwide [6]. There were 62.8 million disability adjusted life years (DALYs) lost (86% in low‐ and middle‐income countries [LMICs]) due to hemorrhagic stroke [7]. Globally, ICH represents approximately 28% of all strokes but is associated with the highest mortality, with a case‐fatality rate of 35.5% and minimal improvement in survival over recent decades [6]. Beyond mortality, stroke survivors often face severe physical impairments such as paralysis, loss of speech, and cognitive difficulties, resulting in significant care burdens for families and health systems [8]. The impact is especially profound in LMIC, where healthcare resources for prevention, treatment, and rehabilitation are limited [9]. A recent study reported that hemorrhagic stroke patients in Africa had a pooled mortality rate of 26.1% (95% confidence interval [CI]: 24.0%–28.3%), notably higher than for ischemic stroke [10]. Stroke accounts for 6.23% of deaths in Ethiopia, with an age‐adjusted stroke mortality rate of 89.82 per 100,000 population [11]. A systematic review and meta‐analysis in Ethiopia showed that the percentage of hemorrhagic stroke cases among total stroke patients in Ethiopia is approximately 36.53% [12]. Many studies in Ethiopia have investigated stroke in general rather than focusing on particular types of strokes. Current research often pools both hemorrhagic and ischemic stroke patients or relies heavily on ischemic stroke data because ischemic stroke is the most common type and may dominate it [13, 14]. To the best of our knowledge, the burden of mortality among patients with hemorrhagic stroke has not been comprehensively characterized in Ethiopia. Identifying stroke subtypes is essential for guiding appropriate stroke management [15].
Understanding the factors associated with mortality in hemorrhagic stroke is crucial for improving clinical decision‐making, optimizing resource allocation, and guiding patient and family counseling. Factors such as patient demographics, pre‐existing comorbidities such as hypertension and diabetes, clinical presentation at admission, such as Glasgow Coma Scale (GCS) score, and the development of in‐hospital complications such as aspiration pneumonia and septic shock are known to influence survival [12, 16–19]. In addition, intraventricular extension of ICH and advanced age were determinants of poor outcome [20].
However, the specific risk factors and their magnitude can vary significantly across different populations and healthcare systems. It is important to study hemorrhagic stroke‐specific prognostic factors—such as hematoma volume, intraventricular extension, and initial GCS score—to enable accurate early risk stratification, improve the quality of patient and family counseling, and inform the development of targeted therapies designed to mitigate the high lethality of hemorrhagic events specifically. Given the current data gaps and the severity of hemorrhagic strokes, it is important to separately assess factors associated with mortality among hemorrhagic stroke patients. Therefore, this study is aimed at identifying the factors associated with mortality among adult hemorrhagic stroke patients admitted to public hospitals in the Harari region, eastern Ethiopia, using a retrospective hospital‐based cohort design. The findings will provide valuable, context‐specific evidence to clinicians and health policymakers, enabling them to improve the quality of care and survival outcomes for this critically ill patient group.
2. Methods
2.1. Study Design and Setting
A hospital‐based retrospective cohort study was conducted among patients diagnosed with hemorrhagic stroke at public hospitals in the Harari region, eastern Ethiopia, from September 1, 2019, to August 31, 2024. The Harari region is situated 526 km east of Addis Ababa, the capital city of Ethiopia. The region is currently served by two public hospitals. The two public hospitals in the area—Jugal General Hospital (JGH) and Hiwot Fana Comprehensive Specialized University Hospital (HFCSUH)—deliver medical services to the local population. The data were extracted from September 1 to October 1, 2024.
2.2. Population and Sampling
The source population for this study included all patients aged 15 years and older who were treated for hemorrhagic stroke at public hospitals in the Harari Regional State. The study population specifically consisted of hemorrhagic stroke patients who were admitted and registered in the adult medical wards of these hospitals during the study period. Patients with incomplete medical information on the treatment outcome of hemorrhagic stroke were excluded.
A total of 281 hemorrhagic stroke patients were treated at the medical ward of HFCSUH and JGH in the study period. There were 256 and 25 patients from each hospital, respectively. Of these, 19 patients′ medical records were incomplete. The final analysis included 262 hemorrhagic strokes. (Figure 1).
Figure 1.
Flow diagram of selection for study on the factors associated with mortality among adult hemorrhagic stroke patients in the Harari region, east Ethiopia, 2024.
2.3. Variables
The primary outcome of this study was in‐hospital mortality among hemorrhagic stroke patients. Diagnosis of hemorrhagic stroke was based on clinical assessment in conjunction with neuroimaging. A noncontrast computed tomography (CT) scan was utilized to confirm the diagnosis. Data on mortality were obtained from the death summaries documented in patients′ medical records.
2.4. Operational Definitions
Event: the mortality of hemorrhagic stroke.
Censored: hemorrhagic stroke patients who did not die during the follow‐up study (improved, discharged against medical advice [DAMA], and discharged with complications).
Treatment outcomes: the results or effects of medical intervention on a patient′s health (improved, complications, or death) [21].
Improved: Information about the improvement of patients was obtained from the discharge summary of medical records. Functional outcome was evaluated by the modified Rankin scale (mRS). It was categorized into good (mRS < 3) and poor (mRS ≥ 3) functional recovery [22].
A good GCS indicates a patient with mild brain injury or who is alert (GCS 13–15), a moderate brain injury or who is drowsy (GCS 9–12), and a poor GCS indicates a patient with severe brain injury or who is unconscious (GCS 3–8) [23].
Time to death: time from the date of hemorrhagic stroke diagnosis to the date of death [24].
2.5. Data Collection and Quality Control
Data were collected using a data extraction form adapted from the WHO STEPSwise approach to stroke surveillance [25]. This form included key patient information, including demographic details (age, sex, and residency), clinical data (hypertension, atrial fibrillation, DM, aspiration pneumonia, kidney disease, and raised intracranial pressure [ICP]), treatment outcomes, medications used, and laboratory investigations. Four public health professionals from the university conducted data collection under the supervision of two trained supervisors. Data were extracted from patients′ paper‐based medical records.
Before the actual data collection, a pretest was conducted using 5% (14) of the medical records of stroke patients from both hospitals to assess the reliability and consistency of the data collection tools. Based on the pretest findings, necessary revisions were made to the instruments, and the data were not included in the final analytical sample. Data collectors received training for 2 days on the procedures and tools of data collection. Data collection was closely supervised by the principal investigators, and any inconsistencies identified were promptly addressed. Data collected using the Kobo toolbox were reviewed for consistency and completeness before being uploaded to the server.
2.6. Data Analysis
The dataset was then imported into STATA Version 17.0 for analysis. Descriptive statistics, including means, frequencies, tables, and graphs, were used to summarize and describe the data. To address missing data, a complete case analysis was applied under the assumption that data were missing completely at random (MCAR). The cumulative incidence of mortality was calculated by dividing the number of deaths by the total initial population at risk during follow‐up. Patient‐months at risk were determined from the date of baseline diagnosis to either the date of the event (death) or censoring. Based on this, incidence density was calculated as the number of deaths per patient‐months at risk. The outcome variable was categorized into two groups: death (event) and censored. Kaplan–Meier failure curves were used to estimate mortality probabilities, and the log‐rank test was employed to compare survival functions across explanatory variables. To identify factors associated with mortality, both the Cox proportional hazards (PH) model and three parametric survival models (Weibull, Exponential, and Gompertz) were fitted. The model was selected by the Akaike information criterion (AIC), Bayesian information criterion (BIC), and log‐likelihood criterion, with the Gompertz PH model ultimately chosen as the most parsimonious. In addition, the selection was guided by the suitability of the Gompertz distribution for modeling monotonically changing hazards, which is clinically plausible in hemorrhagic stroke, where the risk of mortality may evolve consistently over time. The direction and magnitude of the effect estimates were broadly consistent across models. The PH assumption was checked using Schoenfeld residuals (both global and scaled) as well as graphical methods, such as the log–log survival plots. Multicollinearity among factors was assessed using the variance inflation factor (VIF). The following variables were selected on clinical and theoretical grounds: age greater than 65 years, atrial fibrillation, kidney diseases, brain edema, and GCS [24, 26–30]. A p value < 0.05 was considered statistically significant in the multivariable model, and the strength of associations was expressed using hazard ratios (HR) with 95% CIs. The goodness of fit of the model was assessed via the Cox–Snell residual technique. The cumulative hazard plot follows a straight line through the origin with slope, indicating that the model fits the data well. (Figure 2).
Figure 2.
Cox–Snell residuals for Gompertz PH models of hemorrhagic stroke patients in the public hospitals in the Harari region, eastern Ethiopia, 2024.
3. Results
3.1. Sociodemographic Characteristics
Out of 281 adult hemorrhagic stroke patient records reviewed, 262 were included in the final analysis. A total of 19 records (6.76%) were excluded due to incomplete information. Among the 262 adults diagnosed with hemorrhagic stroke, 171 (65.27%) were male, with a mean age of 55 years (±15.67 SD). Regarding residence, approximately 65.27% of patients were from rural areas (Table 1).
Table 1.
Sociodemographic characteristics of hemorrhagic stroke patients at public hospitals in the Harari region, east Ethiopia, from 2019 to 2024 (N = 262).
| Characteristics | Category | Frequency (%) |
|---|---|---|
| Sex | Male | 171 (65.27) |
| Female | 91 (34.73) | |
| Age | < 45 | 70 (26.72) |
| 45–65 | 125 (47.71) | |
| > 65 | 67 (25.57) | |
| Residence | Rural | 170 (64.89) |
| Urban | (35.11) |
3.2. Clinical Characteristics
The most frequently observed clinical presentation was hemiparesis (72.90%), followed by loss of consciousness (37.79%). The median time from symptom onset to hospital presentation was 29 h (IQR: 60), and in about 50.38% of cases, the time from symptom onset to admission exceeded 24 h. A large proportion of patients, 195 (74.43%), had at least one comorbid condition. Hypertension was the most common comorbidity (60.31%), followed by diabetes (11.45%) and kidney disease (9.54%). At the time of hospitalization, the mean diastolic and systolic blood pressures were 83.85 ± 19.73 and 140.98 ± 28.55 mmHg, respectively. Elevated body temperature (> 37.5°C) was observed in 9.54% of the patients. The mean total cholesterol level was 149.43 ± 50.81 mg/dL, with 17.57% of patients showing elevated levels. The median length of hospital stay was 5 days (±6 SD) (Table 2).
Table 2.
Clinical characteristics of hemorrhagic stroke patients at public hospitals in the Harari region, east Ethiopia, from 2019 to 2024 (N = 262).
| Characteristics | Category | Frequency (%) |
|---|---|---|
| Clinical presentations | Hemiparesis | 191 (72.90) |
| Loss of consciousness | 99 (37.79) | |
| Slurred speech | 63 (24.05) | |
| Headache | 69 (26.34) | |
| Aphasia | 40 (15.27) | |
| Vomiting | 47 (17.94) | |
| Facial palsy | 35 (13.36) | |
| Previous history of stroke | No | 219 (83.91) |
| Yes | 42 (16.09) | |
| Time from onset to admission (in hours) | Median ± (IQR) = 29 ± 60 | |
| Comorbidity | Yes | 195 (74.43) |
| No | 67 (25.57) | |
| List of comorbidities | Hypertension | 158 (60.31) |
| Heart failure | 20 (7.63) | |
| Diabetes | 30 (11.45) | |
| Kidney disease | 25 (9.54) | |
| Myocardial Infraction | 6 (2.29) | |
| Atrial fibrillation | 11 (4.20) | |
| Systolic blood pressure (in mmHg) | Mean ± (SD) = 140.98 ± 28.55 | |
| Diastolic blood pressure (in mmHg) | Mean ± (SD) = 83.85 ± 19.73 | |
| Respiratory rate (in breaths per minute) | 12–18 | 16 (6.11) |
| > 18 | 246 (93.89) | |
| Pulse rate (in beats per minute) | < 60 | 8 (3.05) |
| 60–100 | 189 (72.14) | |
| > 100 | 65 (24.81) | |
| Body temperature (in °C) | < 36.5 | 109 (41.60) |
| 36.5–37.5 | 128 (48.85) | |
| > 37.5 | 25 (9.54) | |
| Random blood glucose (in mg/dL) | ≤ 200 | 248 (94.66) |
| > 200 | 14 (5.34) | |
| Total cholesterol (mg/dL) | < 200 | 183 (82.43) |
| ≥ 200 | 39 (17.57) | |
| Serum creatinine (in mg/dL) | < 0.5 | 21 (8.08) |
| 0.5–1.2 | 196 (75.38) | |
| > 1.2 | 43 (16.53) | |
| Serum potassium level (in meq/L) | < 3.5 | 58 (22.39) |
| 3.5–5 | 190 (73.36) | |
| > 5 | 11 (4.25) | |
| Glasgow Coma Scale (GCS) | ≤ 8 | 43 (16.41) |
| 9–12 | 95 (36.26) | |
| 13–15 | 124 (47.33) | |
| Length of hospital stays(days) | Median ± (IQR) = 5 ± 6 |
3.3. Treatment Characteristics
Among the 262 patients, 174 (66.41%; 95% CI: 60.43%–71.91%) had improved outcomes, 10 (3.82%; 95% CI: 2.05%–6.97%) were discharged with complications, 45 (17.18%; 95% CI: 13.05%–22.26%) died, and 33 (12.60%; 95% CI: 9.07%–17.22%) were discharged against medical advice on self and family requests. Among the 45 patients who died, aspiration pneumonia (57.78%) and increased ICP (55.56%) were identified as frequently documented contributing causes of death secondary to hemorrhagic stroke in the investigated patients, whereas hypertension (75.56%) was primarily an underlying risk factor that predisposes to the stroke. Of 262 patients, 129 (49.24%) experienced complications. The most common complications were increased ICP/brain edema (24.43%) and aspiration pneumonia (21.76%). Amlodipine (32.06%) and enalapril (29.77%) were frequently used antihypertensive medications. Additionally, antibiotics such as ceftriaxone and metronidazole were prescribed in 31.68% of patients, primarily for the treatment of aspiration pneumonia and sepsis associated with comorbid conditions. (Table 3)
Table 3.
Treatment outcomes for hemorrhagic stroke patients at public hospitals in the Harari region, east Ethiopia, from 2019 to 2024 (N = 262).
| Characteristics | Category | Frequency (%) |
|---|---|---|
| Treatment outcomes | Improved | 174 (66.41) |
| Discharged with complications | 10 (3.82) | |
| Died | 45 (17.18) | |
| DAMA | 33 (12.60) | |
| Complication | Yes | 129 (49.24) |
| No | 133 (50.76) | |
| Lists of complications | Brain edema/ICP | 64 (24.43) |
| Aspiration pneumonia | 57 (21.76) | |
| UTI | 16 (6.11) | |
| HAI | 20 (7.63) | |
| Seizure | 10 (3.82) | |
| Septic shock | 13 (4.96) | |
| Antihypertensive | Enalapril | 78 (29.77) |
| Amlodipine | 84 (32.06) | |
| Nifedipine | 38 (14.50) | |
| Hydrochlorothiazide | 31 (11.83) | |
| Antiulcer drugs | Cimetidine | 43 (16.41) |
| Omeprazole | 13 (4.45) | |
| Antibiotics | Ceftriaxone | 77 (29.39) |
| Metronidazole | 6 (2.29) | |
| Antipyretic | Paracetamol | 79 (30.15) |
| Antidiabetic | Insulin | 14 (5.34) |
| Osmotic diuretics | Mannitol | 63 (24.05) |
Abbreviations: DAMA, discharged against medical advice; HAI, hospital‐acquired infection; ICP, intracranial pressure; UTI, urinary tract infection.
3.4. Incidence Rate of Stroke Patients
The study samples were followed for a minimum of 1 day and a maximum of 60 months, with no median survival time. Among the total cohort of stroke patients, 45 (17.18%; 95% CI: 13.05%–22.26%) died during the follow‐up period. The overall incidence of death was 10.62 cases per 1000 person‐months of observation (95% CI: 7.93–14.23). The survival probability was highest in the first month of follow‐up after hemorrhagic stroke was diagnosed and then decreased as the follow‐up time increased (Figure 3).
Figure 3.
Overall Kaplan–Meier curve for the cumulative probability of mortality of hemorrhagic stroke patients at public hospitals in the Harari region, east Ethiopia, 2024.
3.5. Factors Associated With Mortality
In the multivariable Gompertz regression analysis, two variables—kidney disease and poor GCS scores—were identified as factors associated with mortality. Septic shock and aspiration pneumonia showed exploratory associations with mortality.
Accordingly, patients with kidney disease had a three fold greater hazard of death from hemorrhagic stroke than those without kidney disease (AHR: 3.04; 95% CI: 1.44, 6.44). The hazard of mortality from hemorrhagic stroke was 3.92 times greater among patients with a GCS score < 8 than among those with a GCS score of 13–15 (AHR: 3.92; 95% CI: 1.58, 9.71) (Table 4).
Table 4.
Bivariate and multivariate Gompertz regression analyses of predictors of mortality among hemorrhagic stroke patients at public hospitals in the Harari region, east Ethiopia, 2024.
| Variable | Category | Mortality | CHR (95% CI) | AHR (95% CI) | p | |
|---|---|---|---|---|---|---|
| Censored (n = 217) | Event (n = 45) | |||||
| Age | < 45 | 61 | 9 | 1 | 1 | |
| 45–65 | 111 | 14 | 0.89 (0.38–2.05) | 0.67 (0.27–1.65) | 0.385 | |
| > 65 | 45 | 22 | 2.57 (1.18–5.57) | 0.78 (0.31–1.95) | 0.598 | |
| Atrial fibrillation | No | 211 | 40 | 1 | 1 | |
| Yes | 6 | 5 | 2.69 (1.06–6.83) | 1.26 (0.44–3.60) | 0.657 | |
| Kidney diseases | No | 208 | 29 | 1 | 1 | |
| Yes | 9 | 16 | 6.91 (3.73–12.79) | 3.04 (1.44–6.44) | 0.004 | |
| Brain edema | No | 178 | 20 | 1 | 1 | |
| Yes | 39 | 25 | 4.77 (2.64–8.61) | 1.58 (0.72–3.46) | 0.253 | |
| GCS | < 8 | 23 | 19 | 14.31 (6.30–32.48) | 3.92 (1.58–9.71) | 0.003 |
| 9–12 | 78 | 17 | 2.97 (1.27–6.95) | 1.22 (0.48–3.12) | 0.671 | |
| 13–15 | 159 | 6 | 1 | 1 | ||
Note: Bold values denote significance at p < 0.05.
Similarly, the risk of mortality from hemorrhagic stroke was greater among patients with septic shock than among those without septic shock. Hemorrhagic stroke patients diagnosed with aspiration pneumonia were more likely to die than those without the condition.
4. Discussion
This study included 262 patients with hemorrhagic stroke; among the total number of hemorrhagic stroke patients followed for approximately 60 months, 45 (17.18%; 95% CI: 13.05%–22.26%) died. The incidence of mortality was 10.62 cases per 1000 person‐months of observation, with a 95% CI of 7.93–14.23. In the multivariable Gompertz regression analysis, two variables—kidney disease and poor GCS scores—were identified as factors associated with mortality. Additionally, septic shock and aspiration pneumonia showed exploratory associations with mortality.
The cumulative incidence of mortality observed in this study was consistent with the incidence of mortality of 19.38% reported in Debre Markos Comprehensive Specialized Hospital, Ethiopia [31], 20.64% in Jimma University Medical Center Stroke Unit, Ethiopia [32], 19.10% in Felege Hiwot Hospital, Ethiopia [24], 16.67% in Beirut [33], and 20.40% in Taiwan [34]. However, it was higher than the study done by [35] in the Aseer Region, southwest of Saudi Arabia, 9.7%. On the other hand, the cumulative incidence in this study was lower than the study conducted in Sierra Leone (33.9%) [36], at University of Gondar Teaching Hospital, Tibebe Gion Comprehensive Specialized Hospital, and Felege Hiwot Referral Hospital, Ethiopia (40.91%) [37], at Mettu Karl Referral, Ethiopia (41.43%) [38], at Jimma University Medical Center, Ethiopia (74.87%) [26], and in Tanzania (44.26%) [39]. This variation may be due to differences in socioeconomic status, level of awareness of the population on risk factors of stroke and its mortality, and differences in sample size and follow‐up time. In developing countries such as Ethiopia, deteriorating patients remaining at home against medical advice resulted in out‐of‐hospital mortality and may have contributed to an underestimated mortality rate of stroke patients [31].
Aspiration pneumonia showed an association with mortality among stroke patients. These results are consistent with studies done in Lusaka, Zambia [40], in Sierra Leone [36], in Tanzania [41], at Ayder Comprehensive Specialized Hospital, Mekelle, Ethiopia [28], and at Jimma University Medical Center, Ethiopia [27]. Aspirational pneumonia can lead to several respiratory problems, including acute respiratory distress syndrome and respiratory failure, which can worsen the course of treatment for hemorrhagic stroke patients and raise their chance of dying [42].
Likewise, the level of GCS < 8 score at the time of hospital admission was associated with hemorrhagic stroke patient mortality. This finding was in line with studies conducted in Saudi Arabia [35], Iran [43], South London [44], Ayder Comprehensive Specialized Hospital, Mekelle, Ethiopia [28], Lusaka, Zambia [40], Jimma University Medical Center, Ethiopia [27], and Saint Paul′s Hospital Millennium Medical College, Ethiopia [29]. The possible explanation could be that patients with decreased GCS or comatose patients had a higher probability of developing acute phase neuromedical stroke complications, which possibly predispose them to a high risk of death [31].
Having kidney disease was significantly associated with mortality among stroke patients, with affected patients demonstrating a 3.04‐fold higher hazard of death from hemorrhagic stroke than those without kidney disease (AHR: 3.04; 95% CI: 1.44, 6.44). This finding was in line with studies conducted in South Ethiopia [30], in India [45], and a review study [46]. Hemorrhagic stroke is the leading cause of death in the chronic kidney disease (CKD) population. Uremic patients are susceptible to hemorrhagic complications due to several factors, namely platelet dysfunction, low platelet number, use of heparin during hemodialysis, and use of anticoagulants for thromboembolic risk [47, 48].
Septic shock showed an association with mortality among stroke patients. This finding was in line with studies conducted in the California State Inpatient Database of the Healthcare Cost and Utilization Project data set [49]. The risk of stroke is high after sepsis, and this risk persists for up to a year. Younger sepsis patients have a particularly increased risk of stroke after sepsis [50].
A potential line for future research in hemorrhagic stroke could be the prediction and prevention of hematoma expansion and rebleeding in ICH through the development and validation of multimodal, precision risk models that combine dynamic imaging biomarkers, serial clinical data, and coagulation biomarkers. This is important because hematoma expansion (≥ 30 mL) is associated with poor ICH outcome [1, 51, 52]. Accordingly, prospective multicenter studies should evaluate whether model‐guided treatment reduces hematoma growth and improves outcomes.
5. The Limitations of the Study
Due to the retrospective design, incomplete or missing data were encountered, including instances of lost patient medical information. Consequently, several clinically important variables that may have a significant association with hemorrhagic stroke mortality could not be ascertained from the medical records and were not assessed. This limitation may have led to an underestimation of the observed effects. The absence of important clinical and neuroimaging severity indicators (e.g., hematoma volume, location, IVH, and stroke severity scores) may have led to incomplete adjustment for baseline risk. As a result, the observed effect size estimates may be biased. Moreover, because the study was hospital‐based and assumed hemorrhagic stroke to be the exclusive cause of all mortality events, the stroke‐specific mortality rate may have been overestimated.
6. Conclusion
In this study, the in‐hospital mortality rate among patients with hemorrhagic stroke was high. Risk factors such as kidney disease, aspiration pneumonia, poor GCS, and septic shock increased mortality risk. We recommend that priority be given to the management of hemorrhagic stroke patients presenting with kidney disease and poor GCS scores. Additionally, researchers are encouraged to conduct further prospective studies to clarify the temporal and causal relationships between these factors and mortality in hemorrhagic stroke patients.
Nomenclature
- AHR
adjusted hazard ratio
- CT
computed tomography
- DALYs
disability adjusted life years
- GCS
Glasgow Coma Scale
- HFCSUH
Hiwot Fana Comprehensive Specialized University Hospital
- HICs
high‐income countries
- ICP
intracranial pressure
- ICU
intensive care unit
- IV‐tPA
intravenous tissue plasminogen activator
- JGH
Jugal General Hospital
- LMICs
low‐ and middle‐income countries
- mRS
modified Rankin score
- SSA
sub‐Saharan Africa
- TIA
transient ischemic attack
- WHO
World Health Organization
Author Contributions
A.T., B.S., A.G.N., and A.S. were involved in the conception and design, acquisition of data, or analysis and interpretation of data. O.K. contributed to data analysis, writing, and editing the document. D.F. gave valuable ideas for the manuscript and revised it critically for important intellectual content.
Funding
No funding was received for this manuscript.
Disclosure
All authors read and approved the final version of the manuscript.
Ethics Statement
The study was carried out under consideration of the Helsinki Declaration of Medical Research Ethics [52]. This work was approved by the Institutional Health Research Ethical Review Committee of Haramaya University College of Health and Medical Sciences (Ref. No. IHRERC/175/2024). Permission was obtained from the Haramaya University College of Health and Medical Sciences administration. The names of patients were not registered in the checklist, and their unique MRN numbers were locked for confidentiality. The need for written informed consent to participate was waived by the Institutional Health Research Ethical Review Committee of the Haramaya University College of Health and Medical Sciences because of the retrospective nature of the study. Data were accessed from September 1 to October 1, 2024. The authors had no access to information that could identify individual participants during or after data collection. Patient data were anonymized, and data access was restricted during extraction.
Consent
The authors have nothing to report.
Conflicts of Interest
The authors declare no conflicts of interest.
Acknowledgments
We acknowledge the Haramaya University Colleges of Health and Medical Sciences Institutional Health Research Ethical Review Committee for providing ethical clearance. We would like to thank Hiwot Fana Comprehensive Specialized University Hospital and Jugal General Hospital administrative bodies and card room workers for their cooperation and permission to conduct the study. We would also like to thank the data collectors and supervisors for their commitment during data collection.
Tesfaye, Alemayehu , Shegene, Birhanu , Negasa, Abdi Gari , Sime, Akewok , Kassa, Obsan , Firdisa, Dawit , Factors Associated With Mortality Among Adult Hemorrhagic Stroke Patients in Public Hospitals in the Harari Region, Eastern Ethiopia: A Retrospective Hospital‐Based Cohort Study, Stroke Research and Treatment, 2026, 9554811, 11 pages, 2026. 10.1155/srat/9554811
Academic Editor: Suraiya Saleem
Contributor Information
Alemayehu Tesfaye, Email: alextesfu3597@gmail.com.
Suraiya Saleem, Email: ssaleem@wiley.com.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
References
- 1. Greenberg S. M., Ziai W. C., Cordonnier C., Dowlatshahi D., Francis B., Goldstein J. N., Hemphill JC 3rd, Johnson R., Keigher K. M., Mack W. J., Mocco J., Newton E. J., Ruff I. M., Sansing L. H., Schulman S., Selim M. H., Sheth K. N., Sprigg N., Sunnerhagen K. S., and American Heart Association/American Stroke Association, 2022 Guideline for the Management of Patients With Spontaneous Intracerebral Hemorrhage: A Guideline From the American Heart Association/American Stroke Association, Stroke. (2022) 53, no. 7, e282–e361, 10.1161/STR.0000000000000407, 35579034. [DOI] [PubMed] [Google Scholar]
- 2. Magid-Bernstein J., Girard R., Polster S., Srinath A., Romanos S., Awad I. A., and Sansing L. H., Cerebral Hemorrhage: Pathophysiology, Treatment, and Future Directions, Circulation Research. (2022) 130, no. 8, 1204–1229, 10.1161/CIRCRESAHA.121.319949, 35420918. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Unnithan A. K. A., Das J. M., and Mehta P., Hemorrhagic Stroke Overview, 2023, StatPearls Publishing. [PubMed] [Google Scholar]
- 4. Mendiola J. M. F.-P., Arboix A., García-Eroles L., and Sánchez-López M. J., Acute Spontaneous Lobar Cerebral Hemorrhages Present a Different Clinical Profile and a More Severe Early Prognosis Than Deep Subcortical Intracerebral Hemorrhages—A Hospital-Based Stroke Registry Study, Biomedicines. (2023) 11, no. 1, 10.3390/biomedicines11010223, 36672731. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Salvadori E., Papi G., Insalata G., Rinnoci V., Donnini I., Martini M., Falsini C., Hakiki B., Romoli A., Barbato C., Polcaro P., Casamorata F., Macchi C., Cecchi F., and Poggesi A., Comparison Between Ischemic and Hemorrhagic Strokes in Functional Outcome at Discharge From an Intensive Rehabilitation Hospital, Diagnostics. (2021) 11, no. 1, 10.3390/diagnostics11010038. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Feigin V. L., Abate M. D., Abate Y. H., Abd ElHafeez S., Abd-Allah F., Abdelalim A., Abdelkader A., Abdelmasseh M., Abd-Elsalam S., Abdi P., and Abdollahi A., Global, Regional, and National Burden of Stroke and Its Risk Factors, 1990-2021: A Systematic Analysis for the Global Burden of Disease Study 2021, Lancet Neurology. (2024) 23, no. 10, 973–1003, 10.1016/S1474-4422(24)00369-7, 39304265. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Krishnamurthi R. V., Moran A. E., Forouzanfar M. H., Bennett D. A., Mensah G. A., Lawes C. M., Barker-Collo S., Connor M., Roth G. A., Sacco R., Ezzati M., Naghavi M., Murray C. J. L., Feigin V. L., and Study Stroke Expert Group G. B. D., The Global Burden of Hemorrhagic Stroke: A Summary of Findings From the GBD 2010 Study, Global Heart. (2014) 9, no. 1, 101–106, 10.1016/j.gheart.2014.01.003, 25432119. [DOI] [PubMed] [Google Scholar]
- 8. Kalavina R., Chisati E., Mlenzana N., and Wazakili M., The Challenges and Experiences of Stroke Patients and Their Spouses in Blantyre, Malawi, Malawi Medical Journal. (2019) 31, no. 2, 112–117, 10.4314/mmj.v31i2.2, 31452843. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Abissegue G., Yakubu S. I., Ajay A. S., and Niyi-Odumosu F., A Systematic Review of the Epidemiology and the Public Health Implications of Stroke in Sub-Saharan Africa, Journal of Stroke and Cerebrovascular Diseases. (2024) 33, no. 8, 107733, 10.1016/j.jstrokecerebrovasdis.2024.107733, 38663647. [DOI] [PubMed] [Google Scholar]
- 10. Getie A., Gedfew M., Kitaw T. A., Yilak G., and Bimerew M., Mortality Rate of Stroke and Its Determinants in Africa: An Umbrella Review of Systematic Review and Meta-Analysis, Global Epidemiology. (2025) 10, 100225, 10.1016/j.gloepi.2025.100225, 41112821. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. BeLue R., Okoror T. A., Iwelunmor J., Taylor K. D., Degboe A. N., Agyemang C., and Ogedegbe G., An Overview of Cardiovascular Risk Factor Burden in Sub-Saharan African Countries: A Socio-Cultural Perspective, Global Health. (2009) 5, no. 1, 10.1186/1744-8603-5-10, 19772644. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Getie A., Mumu S. J., and Arora A., Treatment Outcomes and Associated Factors of Stroke in Ethiopia: A Systematic Review and Meta-Analysis, BMC Cardiovascular Disorders. (2025) 25, no. 1, 10.1186/s12872-025-04905-3, 40618060. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Ahmed Z., Chaudhary F., and Agrawal D. K., Epidemiology, Pathophysiology, and Current Treatment Strategies in Stroke, Cardiology and Cardiovascular Medicine. (2024) 8, no. 4, 389–404, 10.26502/fccm.92920399, 39301121. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Tesfaye A., Regassa L. D., Shegene B., Areda N. B., and Tola A., Mortality Rate and Predictors Among Stroke Patients in the Public Hospitals in Harari Region, Eastern Ethiopia, PLOS Global Public Health. (2025) 5, no. 9, e0004414, 10.1371/journal.pgph.0004414, 40911573. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Abdu H., Tadese F., and Seyoum G., Comparison of Ischemic and Hemorrhagic Stroke in the Medical Ward of Dessie Referral Hospital, Northeast Ethiopia: A Retrospective Study, Neurology Research International. (2021) 2021, no. 1, 9996958, 10.1155/2021/9996958. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Abay Kassie S. A., Survival Time of Adult Ischemic Stroke Patients and Associated Risk Factors: A Retrospective Cohort Study at Felege Hiwot Referral Hospital, Asian Journal of Medical Research. (2019) 8, no. 4, ME29–ME35, 10.21276/ajmr.2019.8.4.ME5. [DOI] [Google Scholar]
- 17. Gebreyohannes E. A., Bhagavathula A. S., Abebe T. B., Seid M. A., and Haile K. T., In-Hospital Mortality Among Ischemic Stroke Patients in Gondar University Hospital: A Retrospective Cohort Study, Stroke Research and Treatment. (2019) 2019, 7275063, 10.1155/2019/7275063. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Chukwudelunzu F. E. and Mbonde A. A., Stroke Care in Sub-Saharan Africa: Evaluating the Present Landscape and Proposing Strategies for Improving Outcomes, Advanced Neurology. (2024) 3, no. 2, 10.36922/an.2804. [DOI] [Google Scholar]
- 19. Legese Y. G., Akmel F., Abajebal K., Wayessa D. I., Deme S., Mekonnen Y., and Yitbarek T., Post stroke Fall and Associated Factors Among Stroke Survivors at Hospitals in Jimma town, Oromia Regional State, Southwest Ethiopia, 2025: A cross sectional Study, BMC Neurology. (2025) 25, no. 1, 10.1186/s12883-025-04320-3, 40783749. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Arboix A., Rodríguez-Aguilar R., Oliveres M., Comes E., García-Eroles L., and Massons J., Thalamic Haemorrhage vs Internal Capsule-Basal Ganglia Haemorrhage: Clinical Profile and Predictors of In-Hospital Mortality, BMC Neurology. (2007) 7, no. 1, 10.1186/1471-2377-7-32, 17919332. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Daswani Bharti R., Mishra D. N., and Phate S. D., Study of Drug Utilization and Outcomes in Stroke Patients in a Tertiary Care Hospital, 2021, Journal of Medical, Pharmaceutical, and Allied Sciences. [Google Scholar]
- 22. Zewde Y., Alem A., and Seeger S. K., Magnitude and Predictors of Post-Stroke Cognitive Impairment Among Ethiopian Stroke Survivors: A Facility-Based Cross-Sectional Study, preprint bioRxiv, May 23, 2023 10.21203/rs.3.rs-2852302/v1. [DOI]
- 23. Zewudie A. Z., Regasa T., Hambisa S., Nureye D., Mamo Y., Aferu T., Feyissa D., and Yosef T., Treatment Outcome and Its Determinants Among Patients Admitted to Stroke Unit of Jimma University Medical Center, Southwest Ethiopia, Stroke Research and Treatment. (2020) 2020, no. 1, 8817948, 10.1155/2020/8817948. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Walelgn N., Abyu G. Y., Seyoum Y., Habtegiorgis S. D., and Birhanu M. Y., The Survival Status and Predictors of Mortality Among Stroke Patients at North West Ethiopia, Risk Management and Healthcare Policy. (2021) 14, 2983–2994, 10.2147/RMHP.S322001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Goulart A. C., Bustos I. R., Abe I. M., Pereira A. C., Fedeli L. M., Bensenor I. M., and Lotufo P. A., A Stepwise Approach to Stroke Surveillance in Brazil: The EMMA (Estudo de Mortalidade e Morbidade do Acidente Vascular Cerebral) Study, International Journal of Stroke. (2010) 5, no. 4, 284–289, 10.1111/j.1747-4949.2010.00441.x, 20636711. [DOI] [PubMed] [Google Scholar]
- 26. Negasa B. W., Wotale T. W., Lelisho M. E., Debusho L. K., Sisay K., and Gezimu W., Modeling Survival Time to Death Among Stroke Patients at Jimma University Medical Center, Southwest Ethiopia: A Retrospective Cohort Study, Stroke Research and Treatment. (2023) 2023, no. 1, 1557133, 10.1155/2023/1557133. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Mosisa W., Gezehagn Y., Kune G., Chego M., Yigezu H. F., and Getnet M., Survival Status and Predictors of Mortality Among Adult Stroke Patients Admitted to Jimma University Medical Center, South west Ethiopia: A Retrospective Cohort Study, Vascular Health and Risk Management. (2023) 19, 527–541, 10.2147/VHRM.S399815, 37649671. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Hagos Gufue Z., Gizaw N. F., Ayele W., Yifru Y. M., Hailu N. A., Welesemayat E. T., Tsegay E. W., Atsbaha A. H., and Gebru H. T., Survival of Stroke Patients According to Hypertension Status in Northern Ethiopia: Seven Years Retrospective Cohort Study, Vascular Health and Risk Management. (2020) 16, 389–401, 10.2147/VHRM.S247667, 33061400. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Sahle T., Mekonen H., Alemu T., Alate T., and Melis T., Survival Status and predictor of Mortality Among Adult Stroke Patients in Saint Paul′s Hospital Millennium Medical College, Addis Ababa, Ethiopia, SAGE Open Medicine. (2022) 10, 20503121221112483, 10.1177/20503121221112483, 35924142. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. Dad T. and Weiner D. E., Stroke and Chronic Kidney Disease: Epidemiology, Pathogenesis, and Management Across Kidney Disease Stages, Seminars in Nephrology. (2015) 35, no. 4, 311–322, 10.1016/j.semnephrol.2015.06.003, 26355250. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Admas M., Teshome M., Petrucka P., Telayneh A. T., and Alamirew N. M., In-Hospital Mortality and Its Predictors Among Adult Stroke Patients Admitted in Debre Markos Comprehensive Specialized Hospital, Northwest Ethiopia, SAGE Open Medicine. (2022) 10, 20503121221122465, 10.1177/20503121221122465, 36093420. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32. Mosisa W., Gezehagn Y., Kune G., Chego M., Yigezu H. F., and Getnet M., Survival Status and Predictors of Mortality Among Adult Stroke Patients Admitted to Jimma University Medical Center, Southwest Ethiopia: A Retrospective Cohort Study, Vascular Health and Risk Management. (2023) 19, 527–541, 10.2147/VHRM.S399815. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33. Abdo R., Abboud H., Salameh P., El Hajj T., and Hosseini H., Mortality and Predictors of Death Poststroke: Data From a Multicenter Prospective Cohort of Lebanese Stroke Patients, Journal of Stroke and Cerebrovascular Diseases. (2019) 28, no. 4, 859–868, 10.1016/j.jstrokecerebrovasdis.2018.11.033, 30638943. [DOI] [PubMed] [Google Scholar]
- 34. Ho W. M., Lin J. R., Wang H. H., Liou C. W., Chang K. C., Lee J. D., Peng T. Y., Yang J. T., Chang Y. J., Chang C. H., and Lee T. H., Prediction of in-Hospital Stroke Mortality in Critical Care Unit, Springerplus. (2016) 5, no. 1, 10.1186/s40064-016-2687-2, 27462499. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Alhazzani A. A., Mahfouz A. A., Abolyazid A. Y., Awadalla N. J., Katramiz K., Faraheen A., Khalil S. N., and Aftab R., In Hospital Stroke Mortality: Rates and Determinants in Southwestern Saudi Arabia, International Journal of Environmental Research and Public Health. (2018) 15, no. 5, 10.3390/ijerph15050927, 29735898. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. Russell J. B., Charles E., Conteh V., and Lisk D. R., Risk Factors, Clinical Outcomes and Predictors of Stroke Mortality in Sierra Leoneans: A Retrospective Hospital Cohort Study, Annals of Medicine and Surgery. (2020) 60, 293–300, 10.1016/j.amsu.2020.10.060, 33204420. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37. Ayehu G. W., Yitbarek G. Y., Jemere T., Chanie E. S., Feleke D. G., Abebaw S., Zewde E., Atlaw D., Agegnehu A., Mamo A., Degno S., and Azanaw M. M., Case Fatality Rate and Its Determinants Among Admitted Stroke Patients in Public Referral Hospitals, Northwest, Ethiopia: A Prospective Cohort Study, PLOS One. (2022) 17, no. 9, e0273947, 10.1371/journal.pone.0273947, 36108071. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38. Ababu D. G. and Getahun A. M., Determinants of Stroke Mortality Through Survival Models: The Case of Mettu Karl Referral Hospital, Mettu, Ethiopia, Stroke Research and Treatment. (2022) 2022, no. 1, 9985127, 10.1155/2022/9985127. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39. Okeng′o K., Chillo P., Gray W. K., Walker R. W., and Matuja W., Early Mortality and Associated Factors Among Patients With Stroke Admitted to a Large Teaching Hospital in Tanzania, Journal of Stroke and Cerebrovascular Diseases. (2017) 26, no. 4, 871–878, 10.1016/j.jstrokecerebrovasdis.2016.10.037, 27913201. [DOI] [PubMed] [Google Scholar]
- 40. Nutakki A., Saylor D., Chishimba L., Chomba M., Mataa M., and Zimba S., Predictors of Stroke Mortality at University Teaching Hospital in Lusaka, Zambia, Journal of Stroke and Cerebrovascular Diseases. (2022) 31, no. 4, 106359, 10.1016/j.jstrokecerebrovasdis.2022.106359. [DOI] [Google Scholar]
- 41. Matuja S. S., Mlay G., Kalokola F., Ngoya P., Shindika J., Andrew L., Ngimbwa J., Ahmed R. A., Tumaini B., Khanbhai K., Mutagaywa R., Manji M., Sheriff F., and Mahawish K., Predictors of 30-Day Mortality Among Patients With Stroke Admitted at a Tertiary Teaching Hospital in Northwestern Tanzania: A Prospective Cohort Study, Frontiers in Neurology. (2023) 13, 1100477, 10.3389/fneur.2022.1100477. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42. Feng M.-C., Lin Y.-C., Chang Y.-H., Chen C.-H., Chiang H.-C., Huang L.-C., Yang Y. H., and Hung C. H., The Mortality and the Risk of Aspiration Pneumonia Related with Dysphagia in Stroke Patients, Journal of Stroke and Cerebrovascular Diseases. (2019) 28, no. 5, 1381–1387, 10.1016/j.jstrokecerebrovasdis.2019.02.011, 30857927. [DOI] [PubMed] [Google Scholar]
- 43. Wang Y., Rudd A. G., and Wolfe C. D., Trends and Survival Between Ethnic Groups After Stroke: The South London Stroke Register, Stroke. (2013) 44, no. 2, 380–387, 10.1161/STROKEAHA.112.680843. [DOI] [PubMed] [Google Scholar]
- 44. Jha V. K., Sharda V., Mirza S. A., Shashibhushan B. K. K., and Bhol K. K., Hemorrhagic Stroke in Chronic Kidney Disease, Journal of Association of Physicians of India. (2018) 66, no. 12, 61–64, 31313552. [PubMed] [Google Scholar]
- 45. Kourtidou C. and Tziomalos K., Epidemiology and Risk Factors for Stroke in Chronic Kidney Disease: A Narrative Review, Biomedicines. (2023) 11, no. 9, 10.3390/biomedicines11092398, 37760839. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46. Pai M. F., Hsu S. P., Peng Y. S., Hung K. Y., and Tsai T. J., Hemorrhagic Stroke in Chronic Dialysis Patients, Renal Failure. (2004) 26, no. 2, 165–170, 10.1081/JDI-120038504. [DOI] [PubMed] [Google Scholar]
- 47. Pavord S. and Myers B., Bleeding and Thrombotic Complications of Kidney Disease, Blood Reviews. (2011) 25, no. 6, 271–278, 10.1016/j.blre.2011.07.001. [DOI] [PubMed] [Google Scholar]
- 48. Shao I. Y., Elkind M. S., and Boehme A. K., Risk Factors for Stroke in Patients With Sepsis and Bloodstream Infections, Stroke. (2019) 50, no. 5, 1046–1051, 10.1161/STROKEAHA.118.023443, 30896327. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49. Boehme A. K., Ranawat P., Luna J., Kamel H., and Elkind M. S., Risk of Acute Stroke After Hospitalization for Sepsis: A Case-Crossover Study, Stroke. (2017) 48, no. 3, 574–580, 10.1161/STROKEAHA.116.016162, 28196938. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50. Kuohn L. R., Witsch J., Steiner T., Sheth K. N., Kamel H., Navi B. B., Merkler A. E., Murthy S. B., and Mayer S. A., Early Deterioration, Hematoma Expansion, and Outcomes in Deep Versus Lobar Intracerebral Hemorrhage: The FAST Trial, Stroke. (2022) 53, no. 2448, 2441–2448, 10.1161/STROKEAHA.121.037974, 35360929. [DOI] [PubMed] [Google Scholar]
- 51. Hemphill J. C., Bonovich D. C., Besmertis L., Manley G. T., and Johnston S. C., The ICH Score: A Simple, Reliable Grading Scale for Intracerebral Hemorrhage, Stroke. (2001) 32, no. 4, 891–897, 10.1161/01.STR.32.4.891. [DOI] [PubMed] [Google Scholar]
- 52. Shrestha B. and Dunn L., The Declaration of Helsinki on Medical Research Involving Human Subjects: A Review of Seventh Revision, Journal of Nepal Health Research Council. (2020) 17, no. 4, 548–552, 10.33314/jnhrc.v17i4.1042, 32001865. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.