Factors Associated with the Outcome of a Pediatric Patients Admitted to Intensive Care Unit in Resource-Limited Setup: Cross-Sectional Study.

BACKGROUND: Critical care is a multidisciplinary and interprofessional specialty devoted to treating patients who already have or are at danger of developing acute, life-threatening organ dysfunction. Due to the higher disease load and mortality from preventable illness, patient outcomes in intensive care units are challenging in settings with inadequate resources. This study aimed to determine factors associated with outcomes of pediatric patients admitted to intensive care units.

METHODS: A cross-sectional study was conducted at Wolaita Sodo and Hawassa University teaching hospitals in southern Ethiopia. Data were entered and analyzed using SPSS version 25. Normality tests using the Shapiro-Wilk and Kolmogorov-Smirnov data were normally distributed. The frequency, percentage, and cross-tabulation of the different variables were then determined. Finally, the magnitude and associated factors were first analyzed using binary logistic regression and then multivariate logistic regression. Statistical significance was set at P < 0.05.

RESULTS: A total of 396 Pediatric ICU patients were included in this study, and 165 (41.7%) deaths were recorded. The odds of patients from urban areas (AOR = 45%, CI 95%: 8%, 67% p-value = 0.025) were less likely to die than those in rural areas. Patients with co morbidities (AOR = 9.4, CI 95%: 4.5, 19.7, p = 0.000) were more likely to die than pediatric patients with no co-morbidities. Patients admitted with Acute respiratory distress syndrome (AOR = 12.86, CI 95%: 4.3, 39.2, p = 0.000) were more likely to die than those with not. Pediatric patients on mechanical ventilation (AOR = 3, CI 95%: 1.7, 5.9, p = 0.000) more likely to die than not mechanically ventilated.

CONCLUSION: Mortality of paediatric ICU patients was high (40.7%) in this study. Co-morbid disease, residency, the use of inotropes, and the length of ICU stay were all statistically significant predictors of death.