Prognostic model of in-hospital ischemic stroke mortality based on an electronic health record cohort in Indonesia.

Stroke patients rarely have satisfactory survival, which worsens further if comorbidities develop in such patients. Limited data availability from Southeast Asian countries, especially Indonesia, has impeded the disentanglement of post-stroke mortality determinants. This study aimed to investigate predictors of in-hospital mortality in patients with ischemic stroke (IS). This retrospective observational study used IS medical records from the National Brain Centre Hospital, Jakarta, Indonesia. A theoretically driven Cox's regression and Fine-Gray models were established by controlling for age and sex to calculate the hazard ratio of each plausible risk factor for predicting in-hospital stroke mortality and addressing competing risks if they existed. This study finally included 3,278 patients with IS, 917 (28%) of whom had cardiovascular disease and 376 (11.5%) suffered renal disease. Bivariate exploratory analysis revealed lower blood levels of triglycerides, low density lipoprotein, and total cholesterol associated with in-hospital-stroke mortality. The average age of patients with post-stroke mortality was 64.06 ± 11.32 years, with a mean body mass index (BMI) of 23.77 kg/m2 and a median Glasgow Coma Scale (GCS) score of 12 and an IQR of 5. Cardiovascular disease was significantly associated with IS mortality risk. NIHSS score at admission (hazard ratio [HR] = 1.04; 95% confidence interval [CI]: 1.00-1.07), male sex (HR = 1.51[1.01-2.26] and uric acid level (HR = 1.02 [1.00-1.03]) predicted survivability. Comorbidities, such as cardiovascular disease (HR = 2.16 [1.37-3.40], pneumonia (HR = 2.43 [1.42-4.15] and sepsis (HR = 2.07 [1.09-3.94, had higher hazards for post-stroke mortality. Contrarily, the factors contributing to a lower hazard of mortality were BMI (HR = 0.94 [0.89-0.99]) and GCS (HReye = 0.66 [0.48-0.89]. In summary, our study reported that male sex, NIHSS, uric acid level, cardiovascular diseases, pneumonia, sepsis. BMI, and GCS on admission were strong determinants of in-hospital mortality in patients with IS.

High socioeconomic status is associated with stroke severity among stroke patients in the National Brain Centre Hospital, Jakarta, Indonesia.

Rapid economic growth has widened the gap between the rich and the poor, contributing to inequalities in socioeconomic status (SES) in Indonesia and possibly inequalities in health care. Here, we aimed to assess the potential association between SES and stroke severity in Indonesia, one of the largest low- and middle-income countries. Patients diagnosed with stroke at National Brain Centre (NBC) Hospital, Jakarta, Indonesia, in 2020 were included in the study. SES was measured based on marital status, occupation, education level, source of payment, and hospitalized class with smoking status and sex as confounder. Stroke severity was classified based on the National Institutes of Health Stroke Scale score into minor stroke (Adams et al., 1993, Amarenco et al., 2014, Andersen and Olsen, 2018, Austin and Steyerberg, 2017) and moderate to severe stroke (>4). A total of 2,443 patients with moderate to severe stroke (58%) were analyzed. Currently employed patients had a lower adjusted OR (aOR) of 0.65 (95% confidence interval [CI], 0.51-0.83) than unemployed patients. Patients with the highest education level, at least a diploma degree, had a lower aOR of 0.67 (95% CI, 0.49-0.92) than those with an elementary or no education. Our findings showed that patients with a higher SES had a lower risk of more severe stroke than those with a lower SES. Hence, we must focus on improving SES as part of stroke management.