Construction and evaluation of a risk model for adverse outcomes of necrotizing enterocolitis based on LASSO-Cox regression.

OBJECTIVE

This study aimed to develop a nomogram to predict adverse outcomes in neonates with necrotizing enterocolitis (NEC).

METHODS

In this retrospective study on neonates with NEC, data on perinatal characteristics, clinical features, laboratory findings, and x-ray examinations were collected for the included patients. A risk model and its nomogram were developed using the least absolute shrinkage and selection operator (LASSO) Cox regression analyses.

RESULTS

A total of 182 cases of NEC were included and divided into a training set (148 cases) and a temporal validation set (34 cases). Eight features, including weight [ = 0.471, HR = 0.99 (95% CI: 0.98-1.00)], history of congenital heart disease [ < 0.001, HR = 3.13 (95% CI:1.75-5.61)], blood transfusion before onset [ = 0.757, HR = 0.85 (95%CI:0.29-2.45)], antibiotic exposure before onset [ = 0.003, HR = 5.52 (95% CI:1.81-16.83)], C-reactive protein (CRP) at onset [ = 0.757, HR = 1.01 (95%CI:1.00-1.02)], plasma sodium at onset [ < 0.001, HR = 4.73 (95%CI:2.61-8.59)], dynamic abdominal x-ray score change [ = 0.001, HR = 4.90 (95%CI:2.69-8.93)], and antibiotic treatment regimen [ = 0.250, HR = 1.83 (0.65-5.15)], were ultimately selected for model building. The C-index for the predictive model was 0.850 (95% CI: 0.804-0.897) for the training set and 0.7880.788 (95% CI: 0.656-0.921) for the validation set. The area under the ROC curve (AUC) at 8-, 10-, and 12-days were 0.889 (95% CI: 0.822-0.956), 0.891 (95% CI: 0.829-0.953), and 0.893 (95% CI:0.832-0.954) in the training group, and 0.812 (95% CI: 0.633-0.991), 0.846 (95% CI: 0.695-0.998), and 0.798 (95%CI: 0.623-0.973) in the validation group, respectively. Calibration curves showed good concordance between the predicted and observed outcomes, and DCA demonstrated adequate clinical benefit.

CONCLUSIONS

The LASSO-Cox model effectively identifies NEC neonates at high risk of adverse outcomes across all time points. Notably, at earlier time points (such as the 8-day mark), the model also demonstrates strong predictive performance, facilitating the early prediction of adverse outcomes in infants with NEC. This early prediction can contribute to timely clinical decision-making and ultimately improve patient prognosis.