A nomogram prediction model for early death in patients with persistent pulmonary hypertension of the newborn

Abstract

BackgroundPersistent pulmonary hypertension of the newborn (PPHN) is a major lethal disorder in neonates that leads to an extremely high mortality rate. Thus, the early identification of adverse outcomes in PPHN is critical for clinical practice. This research attempted to develop a nomogram prediction system for assessing the mortality of newborns with PPHN.MethodsTwo hundred and three newborns with PPHN diagnosed from January 2015 to March 2022 were involved in the study. The clinical features of these newborns and pregnancy details were compared between newborns in the survival and lethal groups. Univariable and multivariate analyses were established in sequence to demonstrate the essential risk factors. The nomogram prediction model was built.ResultsA total of 203 newborns were included in the analysis. 136 (67.0%) newborns represented the hospital survival group. Plasma pH value (OR = 0.606, p = 0.000, 95% CI 0.45715–0.80315), septicemia (OR = 3.544, p = 0.000, 95% CI 1.85160–6.78300), and abnormal pregnancy history (OR = 3.331, p = 0.008, 95% CI 1.37550–8.06680) were identified as independent risk factors for neonatal death in newborns associated with PPHN. Finally, the nomogram predictive model was established based on multivariate analysis results, indicating the efficacies of prediction and calibration.ConclusionThis study generated an applicable risk score formula using the plasma pH value, septicemia, and abnormal pregnancy history to recognize neonatal death in newborns with PPHN, presenting a sufficient predictive value and calibration.