Neurodevelopmental impairment following surgical necrotizing enterocolitis with gestational age ≥ 28 weeks: who is at risk?

PURPOSE: Surgical necrotizing enterocolitis (NEC) is a severe medical condition that, even after surgery, a portion of the survival infants may still have neurological sequelae. The objective of this study was to identify the risk factors associated with the development of permanent neurodevelopmental impairment (NDI) in neonates with surgical NEC. METHODS: Between January 2016 and June 2022, a retrospective data collection was conducted on 98 individuals who experienced surgical NEC with gestational age ≥ 28 weeks. Among these patients, 27 patients were diagnosed with NDI, while the remaining 71 patients did not have NDI. Based on this division, the patients were categorized into the NDI group and the Non-NDI group. Demographics, comorbidities, and admission lab results were analyzed using univariate and logistic regression analyses. RESULTS: Of the 98 neonates following surgical NEC, 27(27.6%) developed permanent neurodevelopmental impairment (NDI). Predictors of NDI were identified through the final multivariable logistic regression analysis, which revealed that gestational age ≤ 32 weeks (p = 0.032; odds ratio [OR], 5.673), assisted mechanical ventilation after NEC onset (p = 0.047; OR, 5.299), postoperative acute kidney injury (p = 0.040; OR, 5.106), CRP day 3 after NEC onset (p = 0.049; OR, 1.037), time from presentation to surgery (p = 0.003; OR, 1.047) were significant risk factors. CONCLUSIONS: Our study identified gestational age ≤ 32 weeks, assisted mechanical ventilation after NEC onset, postoperative acute kidney injury, CRP day 3 after NEC onset, and time from presentation to surgery as significant risk factors for NDI in neonates with surgical NEC. These factors would be helpful to refine treatment modalities for better disease outcomes. We also determined the cut-off values of CRP day 3 after NEC onset and time from presentation to surgery, allowing for the individualized evaluation of NDI risk and the implementation of earlier targeted laparotomy.

A new classification for surgical NEC during exploratory laparotomy: introduction and reproducibility assessment.

PURPOSE: Variability in necrosis patterns and operative techniques in surgical necrotizing enterocolitis (NEC) necessitates a standardized classification system for consistent assessment and comparison. This study introduces a novel intraoperative reporting system for surgical NEC, focusing on reliability and reproducibility. METHODS: Analyzing surgical NEC cases from January 2018 to June 2023 at two tertiary neonatal and pediatric surgery units, a new classification system incorporating anatomical details and intestinal involvement extent was developed. Its reproducibility was quantified using kappa coefficients (κ) for interobserver and intraobserver reliability, assessed by four specialists. Furthermore, following surgery, the occurrence of mortality and enteric autonomy were evaluated on the basis of surgical decision-making of the novel intraoperative classification system for surgical NEC. RESULTS: In total, 95 patients with surgical NEC were included in this analysis. The mean κ value of the intra-observer reliability was 0.889 (range, 0.790-0.941) for the new classification, indicating excellent agreement and the inter-observer reliability was 0.806 (range, 0.718-0.883), indicating substantial agreement. CONCLUSION: The introduced classification system for surgical NEC shows high reliability, deepening the understanding of NEC's intraoperative exploration aspects. It promises to indicate operative strategies, enhance prognosis prediction, and substantially facilitate scholarly communication in pediatric surgery. Importantly, it explores the potential for a standardized report and may represent a step forward in classifying surgical NEC, if pediatric surgeons are open to change.

The Effects of Rso2 and PI Monitoring Images on the Treatment of Premature Infants Based on Deep Learning.

In recent years, due to the combined effects of individual behavior, psychological factors, environmental exposure, medical conditions, biological factors, etc., the incidence of preterm birth has gradually increased, so the incidence of various complications of preterm infants has also become higher and higher. This article is aimed at studying the therapeutic effects of preterm infants and proposing the application of rSO2 and PI image monitoring based on deep learning to the treatment of preterm infants. This article introduces deep learning, blood perfusion index, preterm infants, and other related content in detail and conducts experiments on the treatment of rSO2 and PI monitoring images based on deep learning in preterm infants. The experimental results show that the rSO2 and PI monitoring images based on deep learning can provide great help for the treatment of preterm infants and greatly improve the treatment efficiency of preterm infants by at least 15%.