Survival of patients in the intensive care units of referral hospitals in Amhara Region: A prospective cohort study

Authors

  • Berhanu Elfu Feleke
  • Teferi Elfu Feleke
  • Meku Damtie
  • Desalegn Achenefe
  • Fantahun Biadglegne

Abstract

Background: An intensive care unit (ICU) is a place where critically ill patients are managed using life-saving interventions. Evidence regarding ICUs like average days of stay, and what caused the patients to delay in the ward were scarce in resource-limited settings such as Ethiopia. The objectives of this study were to assess the survival of patients in ICUs, the incidence density for discharge with prognosis, and the determinants of ICU stay in five referral hospitals in Amhara Region.

Methods and materials: To implement the prospective cohort study design, baseline data were recorded from patients’ charts at the time of admission to the ICUs of the five referral hospitals. Patients’ status was followed every day for a maximum of nine days. Interviews and chart reviews were used to collect the data. A Kaplan–Meier curve was used to estimate the time of patients’ discharge from the ICU. A Cox proportional hazard model (Weibull) was used to identify the predictors of ICU stay.

Results: A total of 2,789 patients were included; the incidence density of discharge with prognosis was 1,962/12,448 person days. The length of ICU stay was determined by patient-to-nurse ratio (AHR = 0.59 [95% CI: 0.56-0.64]), chronic illness (AHR = 0.93 [95% CI: 0.88-0.98]), hemoglobin concentration (AHR = 1.09 [95% CI: 1.05-1.14]), ICU area-to-bed ratio (AHR = 1.14 [95% CI: 1.06-1.22]), nosocomial infection (AHR = 0.47 [95% CI: 0.37-0.59]), tracheotomy (AHR =  1.12 [95% CI: 1.01-1.24]), time of admission (AHR = 0.83 [95% CI: 0.75-0.93]), and formal education (AHR = 0.72 [95% CI: 0.64-0.80]).

Conclusions and recommendations: Decision makers in Ethiopia should give high priority to ICU infrastructure and to increasing the number of nurses in ICU wards. [Ethiop. J. Health Dev. 2020; 34(1):30-34]

Key words: Critical care, Intensive care, predictors, resource-limited setting

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Published

2020-02-18

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Articles