Association between Acid-Base and Biochemical Parameters with Mortality in Neonates Admitted to NICU
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: Metabolic acidosis is a frequent and serious condition in critically ill neonates, often associated with high morbidity and mortality.Corrected anion gap (cAG) has emerged as a potential prognostic marker, but its clinical utility in neonatal populations remains underexplored.Methods: This prospective observational study was carried out in the Neonatal Intensive Care Unit (NICU) of Bangladesh Shishu Hospital & Institute (BSH&I), Dhaka, over a two-year period from July 2021 to June 2023.Clinical data, arterial blood gas (ABG) parameters, and biochemical profiles were analyzed.Comparisons were made between survivors and non-survivors.Receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive value of cAG for mortality.Kaplan-Meier survival analysis assessed survival differences based on cAG levels.Results: Out of 115 neonates, 64 (55.7%) survived and 51 (44.3%) died.Non-survivors had significantly shorter NICU stays (5 ± 3 vs.18 ± 8 days; p = 0.001) and higher mechanical ventilation use (90.6% vs. 9.4%; p = 0.001).They also had significantly lower pH (7.24 ± 0.10 vs. 7.29 ± 0.06; p = 0.011), bicarbonate, and base excess levels, and significantly higher sodium, anion gap, and corrected anion gap (p < 0.05).ROC analysis showed cAG had strong predictive value for mortality (AUC: 0.861; 95% CI: 0.795-0.927;p = 0.001), with an optimal cut-off of 26.0 mEq/L (sensitivity: 74.5%, specificity: 81.2%).Kaplan-Meier analysis confirmed significantly lower survival in neonates with cAG ≥ 26.0 mEq/L (p < 0.001).Conclusion: Corrected anion gap is a strong independent predictor of mortality in neonates with metabolic acidosis.A cAG threshold of ≥ 26.0 mEq/L may help in early identification of high-risk patients and guide clinical decision-making in the NICU.
Source: ARC Journal of Pediatrics
Authors: Sadia Alam, Monir Hossain, Suraya Akter, Kazi Alam Nowaz, Naziah Rahman Chowdhury Tania, Debashish Kumar Roy, Mukta Thakur, Most. Airin Afroz
Language: English
Subfield: Nephrology
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4410323158