Incidence and Predictors of Cardiac Arrest Among Patients Admitted to the Intensive Care Units of a Comprehensive Specialized Hospital in Central Ethiopia

Background: Cardiac arrest (CA) is a common public health problem. Worldwide, cardiac arrest ranks highly among hospitalised patients' public health concerns, particularly in low-income nations. Data on cardiac arrest in intensive care units in low-income countries are relatively scarce. Determining the incidence and predictors of cardiac arrest among ICU patients will be a very crucial and fruitful clinical practice in resource-limited areas like Ethiopia. Methods: A retrospective cohort study was conducted by reviewing charts of 422 systematically selected patients admitted to the ICU from 2018 to 2022 in Wachemo University Comprehensive Specialized Hospital. The extraction tool was used for the data collection, Epi-data version 4.6.0 for data entry, and STATA version 14 for data cleaning and analysis. Kaplan-Meier, log rank test, and life table were used to describe the data. The Cox proportional hazard regression model was used for analysis. Results: The findings of this study revealed that the overall occurrence of cardiac arrest among critically ill ICU patients was 27% (95% CI: 23, 32). The incidence density rate of cardiac arrest among intensive care unit patients was 19.6 per 1000 person-days of observation. In a multivariable analysis, patients with chronic kidney disease, oxygen saturation <90%, delirium, intubation, and patients admitted to the ICU with cardiovascular disease were found to be independent predictors of cardiac arrest in the Intensive Care Unit. Conclusion: The incidence density rate of cardiac arrest among intensive care unit patients was high. This study also revealed that chronic kidney disease, delirium, intubation, oxygen saturation level below 90% and patients admitted with cardiovascular disease were independent predictors of the occurrence of cardiac arrest among intensive care unit patients. Finally, we recommend that clinician pays attention to those identified as preventable risk factors for early interventions to improve the recovery process of patients in the ICU.