LAUSR

Background One of the major factors contributing to newborn morbidity and mortality across the globe is respiratory distress. In resource-constrained developing nations like Ethiopia, it is a significant issue. Depending on the quality of the care provided, the incidence and time to recovery may differ amongst medical facilities. However, Ethiopia still lacks appropriate data on the incidence and time to recovery from respiratory distress. Objective The aim of the study was to assess the incidence, time to recovery, and predictors among neonates admitted with respiratory distress in the neonatal intensive care unit at the University of Gondar Comprehensive Specialized Hospital. Methods An institution-based retrospective follow-up study design was conducted among 452 neonates with respiratory distress. Data were collected using a data extraction checklist from the medical registry. The extracted data were entered into EPI INFO version 7.2.1.0 and then exported to STATA version 14 for analysis. The median time to recovery, the Kaplan Meier curve, and the log-rank test was computed. Both bi-variable and multivariable Cox regression models were applied to analyze the data. p-value ≤ 0.05 was considered statistically significant. Results Of all respiratory distressed neonate,311 were recovered. The overall incidence rate of neonates admitted with from respiratory distress was 11.5 per 100-neonate day (95% CI: 10.30–12. 87) with 2,703-person day observation and the median time to recovery from respiratory distress was 7 days with (IQR = 3–13 days). Predictors of time to recovery from respiratory distress were very low birth weight (AHR = 0.17, 95% CI: 0.08–0.41), low birth weight (AHR = 0.50, 95% CI: 0.31–0.81), very preterm (AHR = 0.42,95% CI:0.20–0.89), sepsis (AHR = 0.50 95% CI: 0.38–0.65), hypothermia (AHR = 0.61, 95% CI: 0.39–0.81), and Apgar scores less than seven at first (AHR = 0.35, 95% CI: 0.15–0.79) and fifth minute (AHR = 0.45, 95% CI: 0.20–0.97). Conclusion The incidence and time to recovery in this study were discreetly acceptable as compared to previous study. The aforementioned predictors could be used to identify neonates with respiratory distress who are at risk of developing a long-term illness and guide prompt referral to hospitals. This will also provide clinicians with prognostic information, as longer recovery times have economic and social implications in resource limited countries like Ethiopia.