A prediction score model for risk factors of mortality in neonate with pulmonary hemorrhage: the experience of single neonatal intensive care unit in Southwest China

Abstract

Aim: To establish a prediction score model for mortality of neonates with pulmonary hemorrhage (PH).

Methods: Mortality risk factors of PH were analyzed by logistic regression analysis in 244 neonates retrospectively. A prediction score model was developed according to regression coefficients of risk factors. The receiver operating characteristic curve (ROC) was also constructed and the cutoff was determined.

Results: The overall mortality rate of PH was 74.59% (182/244). More patients from multiple pregnancies were found in the death group than in the survivor group (20.1% vs. 3.2%, P = 0.023). The survivor group infants had higher birth weight in average than death group infants (2,787 g vs. 2,339 g, P = 0.000). Significant differences were found between survivor and death groups in the rates of intraventricular hemorrhage (IVH) (25.8% vs. 53.8%, P = 0.000), heart failure (22.6% vs. 48.9%, P = 0.000) and sepsis (3.2% vs. 16.5%, P = 0.008). Birth weight, IVH, heart failure and sepsis were identified as independent mortality risk factors by logistic regression analysis. A score model predicting death was developed according to the regression coefficients, with a sensitivity of 0.846, a specificity of 0.661, a positive predictive value of 0.88 and a negative predictive value of 0.594 at a cutoff of 9 points. The low risk group, with a score of 9 or less, had a lower mortality rate as compared with the high risk group (40.6% vs. 88%, P = 0.000).

Conclusions: Low birth weight, IVH, heart failure and sepsis were the risk factors for mortality of PH. Those infants with a predictive score of more than 9 were at high risk for death.