Values of serum intestinal fatty acid-binding protein, fecal calprotectin, and fecal human β-defensin 2 for predicting necrotizing enterocolitis

Liu, Sujia; Liu, Yongle; Lai, Shuhua; Xie, Yingling; Xiu, Wenlong; Yang, Changyi

doi:10.1186/s12887-024-04667-5

Cited by 1 publication

(1 citation statement)

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“…The incidence of NEC in neonates ranges from 2% to 7%, with mortality rates reaching up to 21.9–38% ( 3 ). Surviving infants often face poor growth, developmental issues, and gastrointestinal disorders like short bowel syndrome ( 4 ), placing a significant burden on families and society.…”

Section: Introductionmentioning

confidence: 99%

Advancing necrotizing enterocolitis prediction through iterative monitoring

Dong,

Yin,

et al. 2024

Transl Pediatr

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Background Necrotizing enterocolitis (NEC) is a severe inflammatory intestinal disease in preterm infants, marked by heightened morbidity and mortality. Timely prediction of NEC is significant in the management of critical neonates. However, it is difficult to predict NEC accurately because of the multi-factorial pathogenesis. This study aimed to develop a prediction model through repeated measurement data to further improve the accuracy of prediction in NEC. Methods We retrospectively collected clinical data of premature infants admitted to the Neonatology Department of the First Affiliated Hospital of Anhui Medical University from January 2016 to December 2023. The infants were categorized into the NEC group (Bell’s stage ≥ II) (n=150) and the non-NEC group (n=150). The clinical baseline data of the NEC and non-NEC groups were matched. Laboratory examination indicators were collected on the 1st day, the 7th day after birth, and the day of NEC onset. Univariate and multivariate logistic regression analyses were conducted to identify independent factors influencing NEC. A nomogram was constructed based on these factors to predict NEC. The concordance index and calibration plot were used to assess the efficiency of the nomogram in the training and validation cohorts. Results This study demonstrated that antenatal steroids, antenatal antibiotics, probiotics treatment before NEC, anion gap (AG, day 7), and mean corpuscular volume (MCV, day 7) were independent risk factors which combined to accurately predict NEC. A nomogram of NEC was created utilizing these five predictors. With an area under the receiver operator characteristic (ROC) curve of 0.835 [95% confidence interval (CI): 0.785–0.884]. Concordance index for the training and validation groups were 0.835 and 0.848, respectively. As the calibration plots indicate, the predicted probability of NEC is highly consistent with the actual observation. Conclusions The risk estimation nomogram for NEC offers clinical value by guiding early prediction, targeted prevention, and early intervention strategies for NEC.

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Section: Introductionmentioning

confidence: 99%