Predictive factors for the surgical treatment of necrotizing enterocolitis in preterm infants: a single-center retrospective study

Diagnostic and Prognostic Value of Hematological Parameters in Necrotizing Enterocolitis: A Systematic Review

Background/Objectives: Necrotizing enterocolitis (NEC) is a severe, potentially fatal gastrointestinal disease that primarily affects preterm neonates, especially those with very low birth weight (<1500 g). Despite extensive research, its pathophysiology remains unclear, with NEC considered a spectrum of disorders driven by systemic inflammation, microbiota dysregulation, and intestinal hypoxic injury. Diagnosis is challenging due to its subtle presentation and reliance on clinical and radiographic findings, underscoring the urgent need for reliable early biomarkers. Complete blood count (CBC) is one of the most frequently performed laboratory tests in neonatal care, providing valuable insights associated with hematologic alterations associated with NEC. Given its cost-effectiveness, accessibility, and rapid turnaround time, CBC parameters have been increasingly investigated for their diagnostic and prognostic potential in NEC. This systematic review consolidates existing evidence on the diagnostic and prognostic utility of CBC parameters in NEC, examining their association with disease onset, progression, and outcomes. Methods: A systematic review of the literature in PubMed and Scopus databases was conducted, between February 25 and December 2024. Results: Following a PRISMA-compliant search strategy, 77 eligible studies were included, analyzing data from 295,195 neonates, of whom 14,570 had NEC. Among the 77 studies, 17 examined NEC-associated mortality as a primary outcome, while 13 studies focused on the development of predictive models incorporating CBC parameters alongside other clinical and laboratory data to assess NEC severity and prognosis in neonates. The findings highlight the potential of CBC-derived markers to facilitate early NEC detection and risk stratification. However, variations in study design and diagnostic criteria highlight the need for prospective studies to validate their clinical use. Conclusions: Despite advancements in understanding NEC, its diagnosis remains challenging due to the absence of fully reliable biomarkers. CBC parameters show promise in offering early diagnostic and prognostic insights. However, further validation is needed for their routine integration into NICU practice. Given the persistent challenges in NEC diagnosis and management, our findings highlight the necessity for integrated scoring systems that combine hematologic, clinical, and radiologic data to enhance early detection and optimize neonatal care. Further research is essential to refine these predictive models, enabling timely interventions and improving survival rates in NEC-affected neonates.

Value of portal venous gas and a nomogram for predicting severe neonatal necrotizing enterocolitis

BACKGROUND

Whether portal venous gas (PVG) is a sign of severe neonatal necrotizing enterocolitis (NEC) and predicts poor prognosis remains uncertain.

METHODS

Patients from two centres were randomly assigned to a training set or a validation set. A nomogram model for predicting severe NEC was developed on the basis of the independent risk factors selected by least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate logistic regression analysis. The model was evaluated based on the area under the curve (AUC), calibration curve, and decision curve analysis (DCA).

RESULTS

A total of 585 patients met the study criteria, and propensity score matching resulted in 141 matched pairs for further analysis. Patients with PVG had a greater risk of surgical intervention or death compared with patients without PVG. A prediction model for severe NEC was established based on PVG, invasive mechanical ventilation (IMV), serum platelet count (PLT) and pH <7.35 at the onset of NEC. The model had a moderate predictive value with an AUC > 0.8. The calibration curve and DCA suggested that the nomogram model had good performance for clinical application.

CONCLUSION

A prediction nomogram model based on PVG and other risk factors can help physicians identify severe NEC early and develop reasonable treatment plans.

IMPACT

PVG is an important and common imaging manifestation of NEC. Controversy exists regarding whether PVG is an indication for surgical intervention and predicts poor prognosis. Our study suggested that patients with PVG had a greater risk of surgical intervention or death compared with patients without PVG. PVG, IMV, PLT and pH <7.35 at the onset of NEC are independent risk factors for severe NEC. A prediction nomogram model based on PVG and other risk factors may help physicians identify severe NEC early and develop reasonable treatment plans.

Peripheral Lymphocyte Changes Associate With the Progression of Necrotizing Enterocolitis in Infants

INTRODUCTION

Immune factors are important antecedents in the pathophysiology of necrotizing enterocolitis (NEC). However, studies on the peripheral blood lymphocyte subsets changes in NEC patients among different Bell stages and in patients requiring surgery are scarce.

METHODS

34 infants with NEC and 33 age-matched controls were included. Peripheral blood was collected within 48 h after NEC diagnosis. Peripheral blood B and T lymphocytes subsets were detected by 12-color flow cytometry. Cell ratios were calculated, and their relationship to disease severity and their roles as indicators for surgery were assessed.

RESULTS

NEC patients showed elevated percentages of unSwB cells (CD27+IgD+ unswitched memory/activated B cells)/B cells, SwB cells (CD27+IgD-switched memory B cells)/B cells, CD8+ T (CD3+CD8+ T cells)/T cells, Tem (CD45RA-CCR7-effector memory T cells)/CD4+ T cells, Tem/CD8+ T cells and decreased Bn (CD27-IgD+ naïve B cells)/B cells, CD4+T (CD3+CD4+ T cells)/T cells, CD45RA+ CCR7+ naïve T cells (CD45RA+CCR7+ naïve T cells)/CD8+T cells. Compared to NEC patients at BELL stage I + II, patients at BELL stage III showed increased percentages of SwB cells/B cells, antibody secreting cell (ASC, CD3-CD20-CD27high CD38high ASCs)/B cells and Tem/CD4+ T cells, and decreased percentages of CD45RA+CCR7+ naïve T cells/CD4+ T cells. The Receiver Operating Characteristic Curve analysis showed that the sensitivity of ASC/B cells ratio (0.52%) is 86.67% and the specificity of Tem/CD4+T ratio (5.22%) is 100%, indicating that NEC patients required surgery.

CONCLUSIONS

The severity of NEC exhibits codirectional changes with the maturation of B and T lymphocytes, especially CD4+ T cells. The increased ASC/B and Tem/CD4+ T cells could serve as potential indicators for NEC patients requiring surgery.

Surgical necrotizing enterocolitis risk factors in extremely preterm infants: a Korean nationwide cohort study

BACKGROUND

The incidence of necrotizing enterocolitis (NEC) is significantly associated with gestational age (GA). This study aimed to investigate risk factors for surgically treated NEC (sNEC) in extremely preterm infants (EPIs) using nationwide cohort registry.

METHODS

Data were collected from 16,338 very-low-birth-weight infants registered in the Korean neonatal network. Clinical data of 5310 EPIs were retrospectively analyzed. sNEC was defined as infants with diagnosis of NEC requiring surgical treatment, who underwent surgical intervention for NEC or died before surgery. Infants were categorized into three groups based on their NEC status: infants without NEC (control), medically treated NEC (mNEC), and sNEC. These groups were matched based on GA to investigate risk factors for NEC.

RESULTS

In EPIs, small for gestational age (SGA; odds ratio 1.68, 95% confidence interval [CI], 1.17-2.36, p = 0.004), hypotension (1.49, 1.18-1.89, p = 0.001), and IVH (1.63, 1.30-2.05, p < 0.001) were identified as risk factors for sNEC. Complete administration of antenatal steroid reduced the risk of sNEC (0.80, 0.64-0.99, p = 0.044).

CONCLUSION

Our study demonstrated that EPIs who are SGA, and experience hypotension and IVH may be at an increased risk of developing NEC requiring surgery. These groups require close attention and monitoring for any signs of surgical indications of NEC.

IMPACT

This nationwide cohort study aimed to identify characteristics of infants with necrotizing enterocolitis (NEC) among extremely preterm infants (EPIs) and analyze the risk factors associated with NEC requiring surgical intervention. Small for gestational age (SGA), hypotension, and intraventricular hemorrhage (IVH) were identified as significant risk factors for surgically treated NEC (sNEC) in EPIs. The administration of antenatal steroids decreases the risk of sNEC. Close attention and monitoring for EPIs with early identifiable risk factors such as SGA, hypotension, and IVH should be considered to prevent and detect sNEC early, ultimately leading to improved long-term outcomes.

Machine learning-based analysis for prediction of surgical necrotizing enterocolitis in very low birth weight infants using perinatal factors: a nationwide cohort study

Early prediction of surgical necrotizing enterocolitis (sNEC) in preterm infants is important. However, owing to the complexity of the disease, identifying infants with NEC at a high risk for surgical intervention is difficult. We developed a machine learning (ML) algorithm to predict sNEC using perinatal factors obtained from the national cohort registry of very low birth weight (VLBW) infants. Data were collected from the medical records of 16,385 VLBW infants registered in the Korean Neonatal Network (KNN). Infants who underwent surgical intervention were identified with sNEC, and infants who received medical treatment, with medical NEC (mNEC). We used 38 variables, including maternal, prenatal, and postnatal factors that were obtained within 1 week of birth, for training. A total of 1085 patients had NEC (654 with sNEC and 431 with mNEC). VLBW infants showed a higher incidence of sNEC at a lower gestational age (GA) (p < 0.001). Our proposed ensemble model showed an area under the receiver operating characteristic curve of 0.721 for sNEC prediction.    Conclusion: Proposed ensemble model may help predict which infants with NEC are likely to develop sNEC. Through early prediction and prompt intervention, prognosis of sNEC may be improved. What is Known: • Machine learning (ML)-based techniques have been employed in NEC research for prediction, diagnosis, and prognosis, with promising outcomes. • While most studies have utilized abdominal radiographs and clinical manifestations of NEC as data sources, and have demonstrated their usefulness, they may prove weak in terms of early prediction. What is New: • We analyzed the perinatal factors of VLBW infants acquired within 7 days of birth and used ML-based analysis to identify which infants with NEC are vulnerable to clinical deterioration and at high risk for surgical intervention using nationwide cohort data.