Identification of potential risk factors for the poor prognosis of neonatal sepsis

BACKGROUND AND AIM: Risk factor-based approach is one of the best approaches employed by middle income countries which are not well facility driven for any disease management. Thus, through this approach, we aim to identify the potential risk factors responsible for the poor outcome in neonatal sepsis. METHODS: A case control was conducted retrospectively with neonates admitted to Neonatal Intensive Care Unit during January 2012 to December 2016. Cases were identified using ICD-10 Code from inpatient medical records and demographic, maternal and neonatal details were collected from the medical files. Logistic regression was performed to identify the risk factors associated with mortality in neonatal sepsis. RESULTS: A total of 613 neonates were found to have culture positive sepsis from the 4690 neonates admitted in the Neonatal Intensive Care Unit (NICU). There was a total of 831 episodes in the 613 neonates. The mortality rate in neonates with sepsis was found to be 25.4%. Extremely low birth weight (OR 6.171, CI 3.475–10.957), extreme preterm (OR 5.761, CI 2.612–12.708), very preterm (OR 2.548, CI 1.607–4.042), preeclampsia (OR 1.671, CI 1.091–2.562), acute renal failure (OR 4.939, CI-2.588–9.426), coagulopathy (OR 2.211, CI-1.486–3.289), septic shock (OR 173.522, CI-23.642–1273.59), thrombocytopenia (OR 5.231, CI-3.310–8.268), leukopenia (OR 2.422, CI- 1.473–3.984), CRP > 24 (OR 2.099, CI-1.263–3.487) and abnormal absolute neutrophil count (OR 2.108, CI-1.451–3.062) were some of the significant predictors, identified through risk-based approach, in assessing mortality in neonatal sepsis. CONCLUSION: Risk-based approach applied was successful in determining plausible important predictors such like extreme low birth weight, extreme preterm, resistance against gram negative infections, preeclampsia, septic shock, hypotension, leukopenia, neutropenia, thrombocytopenia in predicting mortality in neonatal sepsis. These potential risk factors, identified through risk- based approach, can play a pivotal role in assisting clinician to make appropriate and judicious decision.