Predicting risk of severe neonatal outcomes in preterm infants born from mother with prelabor rupture of membranes

Abstract

Background: Perinatal complications are common burdens for neonates born from mother with pPROM. Physicians and parents sometimes need to make critical decisions about neonatal care with short- and long-term implications on infant's health and families and it is important to predict severe neonatal outcomes with high accuracy.

Methods: The study was based on our prospective study on 1001 preterm infants born from mother with pPROM from August 1, 2017, to March 31, 2018 in three hospitals in China. Multivariable logistic regression analysis was applied to build a predicting model incorporating obstetric and neonatal characteristics available within the first day of NICU admission. We used enhanced bootstrap resampling for internal validation.

Results: One thousand one-hundred pregnancies with PROM at preterm with a single fetus were included in our study. SNO was diagnosed in 180 (17.98%) neonates. On multivariate analysis of the primary cohort, independent factors for SNO were respiratory support on the first day,, surfactant on day 1, and birth weight, which were selected into the nomogram. The model displayed good discrimination with a C-index of 0.838 (95%CI, 0.802-0.874) and good calibration performance. High C-index value of 0.835 could still be reached in the internal validation and the calibration curve showed good agreement. Decision curve analysis showed if the threshold is > 15%, using our model would achieve higher net benefit than model with birthweight as the only one predictor.

Conclusion: Variables available on the first day in NICU including respiratory support on the first day, the use of surfactant on the first day and birthweight could be used to predict the risk of SNO in infants born from mother with pPROM with good discrimination and calibration performance.

Keywords: Preterm prelabor rupture of membranes; Prognostic nomogram; Severe neonatal outcomes.

Fig. 1

The flow chart of selection of study subjects from the 2017–2018 MCPPNC database

Fig. 2

Developed SNO nomogram. The SNO nomogram was developed in the cohort, with Respiratory support on the first day, the use of surfactant on the first day and birthweight incorporated. The level of Respiratory support: 0, No respiratory support; 1 = Oxygen therapy (oxygen inhalation in incubator, oxygen inhalation with facemask, oxygen inhalation in oxygen chamber); 2, Normal frequency ventilation (including the use of continuous positive airway pressure (CPAP) and synchronized intermittent mandatory ventilation (SIMV)); 3 = High-frequency ventilation (HFO)

Fig. 3

Calibration curves. A. Calibration curves of the SNO nomogram. B. Calibration curves of the internal validation. The x-axis represents the predicted SNO risk. The y-axis represents the actual occurrence of SNO. The diagonal dotted line represents a perfect prediction by an ideal model. The solid line represents the performance of the nomogram, of which a closer fit to the diagonal dotted line represents a better prediction

Fig. 4

Decision curve analysis for the SNO nomogram. A Net benefit curves for the SNO nomogram. The y-axis measures the net benefit. The thin solid line represents the assumption that all patients are SNO. The thick solid line represents the assumption that no patients are SNO. The red line represents the SNO risk simple nomogram developed by only one variation “birth weight”. The blue line represents the SNO complex risk nomogram developed by variations “Respiratory support on the first day, the use of surfactant on the first day and birthweight”. B Clinical impact curves for the simple model. Clinical impact curve for the risk model base on variables including only birthweight. Of 1,000 patients, the heavy red solid line shows the total number who would be deemed high risk for each risk threshold. The blue dashed line shows how many of those would be true positives (SNO cases). C Clinical impact curves for the SNO complex model. Clinical impact curve for the risk model base on variables including Respiratory support, the use of surfactant on the first day and birthweight. Of 1,000 patients, the heavy red solid line shows the total number who would be deemed high risk for each risk threshold. The blue dashed line shows how many of those would be true positives (SNO cases)