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.

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.