Risk Factors for Poor Prognosis in Neonatal Necrotizing Enterocolitis
Conditions: Necrotizing Enterocolitis
Sponsor: Guangzhou Women and Children's Medical Center

Clinical research protocol
Project name: Risk factors for poor prognosis in neonatal
necrotizing enterocolitis
Leading unit: Guangzhou Women and Children's Medical
Center
Project leader: Wei Zhou
Department: Pediatrics
Research period: July 1, 2024 to June 30, 2025
Project number: EK-NEC20240705
NCT No.: none.
Version No.: V1.0
Version Date: July 01, 2024

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Catalogue
Abstract............................................................................................................................
1. project basis.................................................................................................................
1.1. Research background.........................................................................................
1.2. creativity............................................................................................................
2. goal of study................................................................................................................
3. Research Design and Statistical processing.................................................................
3.1. Research Design................................................................................................
3.2. sample size.........................................................................................................
3.3. data collection....................................................................................................
3.4. Inclusion criteria................................................................................................
3.5. Excluded criteria................................................................................................
3.6. Observation items..............................................................................................
3.7. Statistical............................................................................................................
4. Ethics in clinical research............................................................................................
5. Research progress........................................................................................................
6. References....................................................................................................................

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Abstract
Object name
Analysis of integrated clinical, laboratory and prognostic data of
neonates with necrotizing enterocolitis
Goal of study
This retrospective cohort study aims to enroll patients with
necrotizing enterocolitis (NEC) from July 1, 2017 to December 31,
2022, conduct a comprehensive analysis of their clinical
characteristics, metabolic indicators, laboratory parameters,
prognosis, and outcomes, and identify indicators that may predict the
progression of neonatal NEC and its associated mortality.
Research design
Retrospective cohort study
Research period
July 1, 2024 to June 30, 2025
Leading unit
Guangzhou Women and Children's Medical Center
Research
Consultant
Wei Zhou; Yueju Cai
Research object
Neonates with necrotizing enterocolitis (NEC) from July 1, 2017 to
December 31, 2022, conduct a comprehensive analysis of their
clinical characteristics, metabolic indicators, laboratory parameters,
prognosis, and outcomes.
Inclusion criteria
(1) Diagnosis of NEC
Excluded
criteria
Data that meets any of the following conditions need to be
eliminated:
(1) Congenital gastrointestinal malformations (e.g., intestinal
atresia, Hirschsprung's disease) or spontaneous intestinal perforation;
(2) Hereditary metabolic disorders;
(3) refusal of participation.
Sample size
220 newborns who suffered from necrotizing enterocolitis between

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July 1, 2017 to December 31, 2022
Data collection
Data collection was performed via structured extraction from
electronic medical records. The following variables were
systematically retrieved: (1) Neonatal medical history, including sex,
gestational age, birth weight, and history of birth asphyxia (e.g.,
Apgar scores); (2) Maternal medical history, particularly mode of
delivery, chorioamnionitis, and premature rupture of membranes; (3)
NEC-related clinical parameters: Bell’s staging, clinical
manifestations (abdominal distension, bloody stools,
pneumoperitoneum), complications (patent ductus arteriosus [PDA],
sepsis, shock), therapeutic interventions (mechanical ventilation,
surgical treatment), and mortality; (4) CBC parameters, lactate levels,
and parameters required for calculating the nSOFA score at the onset
of NEC.
Statistical
processing
Statistical analyses and graphic visualization were performed using
SPSS 26.0 (IBM Corp.) and GraphPad Prism 9.0. Data for normally
distributed, skewed distributed, and categorical variables were
expressed as mean ± standard deviation, median (interquartile range),
and frequency (%), respectively. Intergroup comparisons of
categorical variables were conducted using the Chi-square (χ²) test or
Fisher’s exact test, while continuous variables were analyzed using
the Student’s t-test or Mann-Whitney U test. Variables with p < 0.05
in univariate analysis were subsequently included in multivariate
logistic regression analysis.
Mediation analysis was performed using the PROCESS macro 4.1,
with 1000 bootstrap iterations to decompose the total effect into
direct and indirect paths. Receiver operating characteristic (ROC)
curve analysis was conducted using SPSS 26.0 to evaluate the
predictive performance of individual and combined biomarkers. All
analyses adopted two-tailed tests, and p < 0.05 was considered
statistically significant.
Abbreviation
NEC,
necrotizing
enterocolitis;
PNEC,
perforated
necrotizing

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enterocolitis; VLBW, very low birth weight; SGA, small for
gestational age; NICUs, neonatal intensive care units; PDA, patent
ductus
arteriosus;
RDS,
Respiratory
distress
syndrome;
CRP,
C-reactive protein; WBC, white blood cell; CBC, complete blood
count; NEU, absolute neutrophil count; LYM, absolute lymphocyte
count;
MON,
absolute
monocyte
count;
EOS,
eosinophilic
granulocyte; RBC: red blood cell; PLT, platelet count; MPV, mean
platelet
volume;
PDW,
platelet
distribution
width;
NLR,
neutrophil-to-lymphocyte ratio; NMR, neutrophil-to-monocyte ratio;
MLR, monocyte-to-lymphocyte ratio; SII, systemic inflammatory
index = (NEU*PLT)/LYM; SIRI, systemic inflammatory response
index = (NEU*MON)/LYM; AISI, aggregate inflammatory systemic
index = (NEU*MON*PLT)/LYM; nSOFA, neonatal sequential organ
failure assessment; ROC, receiver operating characteristic; AUC, the
area under the ROC curve; OR, odds ratio; CIs, confidence intervals.

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1. project basis
1.1 Research background
Necrotizing enterocolitis (NEC), a life-threatening gastrointestinal disorder
predominantly, affects 5–12% of very low birth weight (VLBW) neonates, with
20–40% of cases progressing to severe disease requiring surgical intervention, while
survivors often endure lifelong consequences, including short-bowel syndrome and
neurodevelopmental impairments [1-4]. Despite advances in neonatal care, early
identification of high-risk patients remains challenging due to the nonspecificity of
clinical signs (e.g., abdominal distension, feeding intolerance) and radiographic
findings (e.g., pneumatosis intestinalis), which frequently manifest only after
irreversible bowel damage has occurred [5]. Furthermore, current diagnostic tools or
conventional biomarkers
lack
both sensitivity and specificity
for early
risk
stratification of NEC, underscoring an urgent need for biomarkers that integrate
pathophysiological mechanisms to guide preemptive therapeutic strategies.
Emerging evidence underscores the multifactorial pathophysiology of NEC,
where intestinal ischemia-reperfusion injury, exaggerated immune activation, and
microbial dysbiosis converge to drive disease progression [6]. Hypoxic-ischemic
injury constitutes a key pathological mechanism underlying intestinal mucosal
damage in NEC, driving dysregulation of cellular processes including apoptosis,
autophagy, proliferation, and migration within intestinal tissues [7]. In infants with
NEC, persistent hypoxemia and compromised tissue perfusion induce metabolic
reprogramming, marked by a shift toward glycolytic dominance—a compensatory
adaptation to oxygen deprivation. Within this framework, serum lactate, as a
well-established marker of tissue hypoperfusion and anaerobic metabolism, has
garnered attention for its prognostic relevance. Elevated lactate levels correlate with
transmural intestinal necrosis and predict fatal outcomes in NEC, reflecting the
severity of ischemic insult [8,9]. However, lactate alone lacks specificity, as
hyperlactatemia may arise from concurrent sepsis or perinatal asphyxia, limiting its
standalone
utility
[10,11].
Recent
studies
propose
combining
lactate
with

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immune-inflammatory biomarkers (such as intestinal fatty acid binding protein or
albumin) to address this limitation [12,13]. Peripheral blood cell analysis serves as a
widely accessible and rapid auxiliary diagnostic tool in neonatal intensive care units
(NICUs). Dynamic changes in peripheral white blood cell (WBC) counts and subset
distribution have been validated as biomarkers closely associated with NEC [14].
Accumulating evidence underscores the involvement of lactate metabolism in
immunomodulation and its influence on disease pathogenesis [15]. However, the
combined utility of lactate levels and peripheral WBC profiles for NEC diagnosis and
prognostic stratification remains unexplored.
As NEC progresses, particularly in cases of perforated NEC, it can evolve from a
localized intestinal disease into a systemic illness characterized by a sepsis-like state
and multi-organ dysfunction. The Neonatal Sequential Organ Failure Assessment
(nSOFA) score is a validated tool designed to objectively quantify the degree of organ
dysfunction in critically ill neonates by evaluating the respiratory, cardiovascular, and
hematologic systems [16]. Studies have demonstrated that higher nSOFA scores are
strongly and independently associated with mortality risk in neonates with respiratory
distress syndrome, late-onset sepsis, and NEC [16-18]. However, single nSOFA lacks
sufficient sensitivity for severe NEC subtypes like PNEC-specific risk stratification:
while it predicts overall NEC mortality and the need for surgical intervention [16],
existing studies have not specifically evaluated its performance in distinguishing NEC
from non-perforated NEC or predicting PNEC-related mortality. The Lewis et al. [16]
study included surgical NEC (e.g., laparotomy or peritoneal drain placement) but did
not isolate PNEC as a distinct endpoint, leaving a critical gap in understanding how
nSOFA performs in this highest-risk subgroup.
1.2 Creativity
To address these gaps, the present retrospective cohort study aims to explore the
potential predictive value of integrating metabolic (lactate), hematologic (CBC), and
organ dysfunction (nSOFA) metrics for NEC and its associated mortality in preterm
infants. By combining these complementary markers, we aim to overcome the

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limitations of single biomarkers and fill the knowledge gap regarding risk
stratification for perforated NEC—an outcome that holds profound implications for
clinical decision-making and improving the survival rate of preterm infants.
2. Research objective
This retrospective cohort study aims to enroll patients with necrotizing
enterocolitis (NEC) from July 1, 2017 to December 31, 2022, conduct a
comprehensive analysis
of
their clinical
characteristics,
metabolic indicators,
laboratory parameters, prognosis, and outcomes, and identify indicators that may
predict the progression of neonatal NEC and its associated mortality.
3. Research scheme and technical route
3.1 Research Design
The principal investigator (PI) and project leader of this study are Wei Zhou,
chief physician of pediatrics of the Guangzhou Women and Children's Medical Center.
In this study, a retrospective analysis was conducted on 220 enrolled neonates with
necrotizing enterocolitis (NEC), with data collected from July 1, 2017 to December
31, 2022. Statistical methods including correlation analysis, multivariate logistic
regression, mediation analysis, and receiver operating characteristic (ROC) curve
analysis were employed to perform mutual analysis of the collected clinical data,
laboratory parameters, and prognostic/mortality outcomes. This analysis aimed to
identify meaningful biomarkers and establish a predictive model, thereby providing
evidence for the pathophysiological mechanisms underlying NEC progression. It is
anticipated that this will optimize clinical decision-making for NEC patients and
improve the survival rate and quality of life of these neonates.
3.2 Sample size
220 newborns who suffered from necrotizing enterocolitis between July 1, 2017
to December 31, 2022.
3.3 data collection
Data collection was performed via structured extraction from electronic medical

8
records. The following variables were systematically retrieved: (1) Neonatal medical
history, including sex, gestational age, birth weight, and history of birth asphyxia (e.g.,
Apgar scores); (2) Maternal medical history, particularly mode of delivery,
chorioamnionitis, and premature rupture of membranes; (3) NEC-related clinical
parameters: Bell’s staging, clinical manifestations (abdominal distension, bloody
stools, pneumoperitoneum), complications (patent ductus arteriosus [PDA], sepsis,
shock), therapeutic interventions (mechanical ventilation, surgical treatment), and
mortality; (4) CBC parameters, lactate levels, and parameters required for calculating
the nSOFA score at the onset of NEC.
3.4 Inclusion criteria
(1) Diagnosis of NEC and having undergone surgical treatment, confirmed by
clinical manifestations (e.g., abdominal distension, bloody stools), radiological
evidence (pneumatosis intestinalis, portal venous gas, or pneumoperitoneum), and
pathological examination in accordance with established guidelines;
(2) Availability of complete medical records for data extraction.
3.5 Excluded criteria
Data that meets any of the following conditions need to be eliminated:
(1) Congenital gastrointestinal malformations (e.g., intestinal atresia, Hirschsprung's
disease) or spontaneous intestinal perforation;
(2) Hereditary metabolic disorders;
(3) Incomplete clinical data or refusal of participation.
3.6 Observation items
(1). Baseline Characteristics: Neonatal demographics (sex, gestational age, birth
weight, small for gestational age [SGA] status), maternal factors (mode of delivery,
premature rupture of membranes, chorioamnionitis), neonatal birth history (1-min
Apgar score ≤7, intrauterine distress), and preterm complications (patent ductus
arteriosus [PDA], respiratory distress syndrome [RDS], sepsis, shock), feeding pattern,
and requirement for mechanical ventilation.
(2). Laboratory and Clinical Assessment Indicators: Hepatobiliary function:

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Albumin, albumin/globulin ratio, total bile acid; Hematologic and inflammatory
parameters: White blood cell (WBC), absolute neutrophil (NEU), lymphocyte (LYM),
monocyte (MON), eosinophil (EOS) counts, red blood cell (RBC), platelet (PLT)
count, mean platelet volume (MPV), platelet distribution width (PDW), C-reactive
protein (CRP), neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio
(MLR), neutrophil-to-monocyte ratio (NMR), systemic inflammatory index (SII),
systemic inflammatory response index (SIRI), aggregate inflammatory systemic index
(AISI); Metabolic: Serum lactate, blood glucose; Organ dysfunction assessment:
Neonatal Sequential Organ Failure Assessment (nSOFA) score.
(3). Primary Outcome Indicators:
- Occurrence of perforated necrotizing enterocolitis (PNEC);
- In-hospital mortality.
(4). Secondary Outcome Indicators:
- Bell’s staging of NEC;
- surgical NEC
3.7 Statistical processing
Statistical analyses and graphic visualization were performed using SPSS 26.0
(IBM Corp.) and GraphPad Prism 9.0. Data for normally distributed, skewed
distributed, and categorical variables were expressed as mean ± standard deviation,
median (interquartile range), and frequency (%), respectively. Intergroup comparisons
of categorical variables were conducted using the Chi-square (χ²) test or Fisher’s exact
test, while continuous variables were analyzed using the Student’s t-test or
Mann-Whitney U test. Variables with p < 0.05 in univariate analysis were
subsequently included in multivariate logistic regression analysis.
Mediation analysis was performed using the PROCESS macro 4.1, with 1000
bootstrap iterations to decompose the total effect into direct and indirect paths.
Receiver operating characteristic (ROC) curve analysis was conducted using SPSS
26.0 to evaluate the predictive performance of individual and combined biomarkers.
All analyses adopted two-tailed tests, and p < 0.05 was considered statistically

10
significant.
4. Ethics in clinical research
Clinical research will follow the World Medical Congress ' Helsinki Declaration '
and other relevant provisions. Before the study began, the clinical study was carried
out after the ethics committee approved the test plan. Before each subject is selected
for this study, the researcher has the responsibility to fully and comprehensively
introduce the purpose, procedure and possible risks of this study to the subjects or
their agents, and to sign a written informed consent form. The subjects should be
informed that they have the right to withdraw from the study at any time. Informed
consent should be retained as a clinical research document for review. The personal
privacy and data confidentiality of the subjects will be protected during the study.
5. Research progress
July 2024 - August 2024: Project pre-planning, standardization of data collection, and
training of personnel Training
August 2024 - March 2025: The specific implementation stage of the experiment,
collecting case data
March 2025 - June 2025: Writing scientific research papers and project summary
reports (1) Organizing research data and conducting statistical analysis; (2) Writing
and submitting scientific research papers; (3) Summarizing research results and
writing the project summary report.
6. Reference
1. Jiang S, Yan W, Li S, et al. Mortality and Morbidity in Infants <34 Weeks'
Gestation in 25 NICUs in China: A Prospective Cohort Study. Front Pediatr. 2020;
833. https://doi.org/10.3389/fped.2020.00033.
2. Bazacliu C, Neu J. Necrotizing Enterocolitis: Long Term Complications. Curr
Pediatr Rev. 2019; 15(2):115-124.
https://doi.org/10.2174/1573396315666190312093119.
3. Vaidya R, Yi JX, O'Shea TM, et al. Long-Term Outcome of Necrotizing
Enterocolitis and Spontaneous Intestinal Perforation. Pediatrics. 2022;

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150(5):https://doi.org/10.1542/peds.2022-056445.
4. Butler V, Treluyer L, Patkai J, et al. Mortality and neurodevelopmental outcomes
at 2 years' corrected age of very preterm infants with necrotising enterocolitis or
spontaneous intestinal perforation: The EPIPAGE-2 cohort study. Eur J Pediatr. 2024;
183(9):4019-4028. https://doi.org/10.1007/s00431-024-05675-4.
5. Imren C, Vlug LE, de Koning B, et al. Necrotizing Enterocolitis in a Dutch Cohort
of Very Preterm Infants: Prevalence, Mortality, and Long-Term Outcomes. Eur J
Pediatr Surg. 2022; 32(1):111-119. https://doi.org/10.1055/s-0041-1741544.
6. Chen M, Feng W, Hou J, et al. Effect of gestational age on clinical features in
necrotizing enterocolitis-associated intestinal perforation. Front Pediatr. 2024;
121452207. https://doi.org/10.3389/fped.2024.1452207.
7. Sakellaris G, Partalis N, Dede O, et al. Gastrointestinal perforations in neonatal
period: experience over 10 years. Pediatr Emerg Care. 2012; 28(9):886-888.
https://doi.org/10.1097/PEC.0b013e31826beb0c.
8. Fitzgibbons SC, Ching Y, Yu D, et al. Mortality of necrotizing enterocolitis
expressed by birth weight categories. J Pediatr Surg. 2009; 44(6):1072-1075,
1075-1076. https://doi.org/10.1016/j.jpedsurg.2009.02.013.
9. Clyman RI, Jin C, Hills NK. A role for neonatal bacteremia in deaths due to
intestinal perforation: spontaneous intestinal perforation compared with perforated
necrotizing enterocolitis. J Perinatol. 2020; 40(11):1662-1670.
https://doi.org/10.1038/s41372-020-0691-4.
10. Kim JH, Sampath V, Canvasser J. Challenges in diagnosing necrotizing
enterocolitis. Pediatr Res. 2020; 88(Suppl 1):16-20.
https://doi.org/10.1038/s41390-020-1090-4.
11. Roberts AG, Younge N, Greenberg RG. Neonatal Necrotizing Enterocolitis: An
Update on Pathophysiology, Treatment, and Prevention. Pediatr Drugs. 2024;
26(3):259-275. https://doi.org/10.1007/s40272-024-00626-w.
12. Wang Y, Lai L, Zhang Q, et al. Lactate acid level and prognosis of neonatal
necrotizing enterocolitis: a retrospective cohort study based on pediatric-specific
critical care database. J Pediat-Brazil. 2023; 99(3):278-283.

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https://doi.org/10.1016/j.jped.2022.11.005.
13. Kislal FM, Polat CC, Ergul E, et al. Can lactate be valuable in early diagnosis and
prognosis of neonatal sepsis? Niger J Clin Pract. 2023; 26(9):1319-1325.
https://doi.org/10.4103/njcp.njcp_54_23.
14. El-Abd AA, Hassan MH, Abo-Halawa N, et al. Lactate and intestinal fatty acid
binding protein as essential biomarkers in neonates with necrotizing enterocolitis:
ultrasonographic and surgical considerations. Pediatr Neonatol. 2020; 61(5):481-489.
https://doi.org/10.1016/j.pedneo.2020.03.015.
15. Li B, Chen Y, Yang Z, et al. Lactate/albumin ratio as a prognostic biomarker for
in-hospital mortality in pediatric patients with necrotizing enterocolitis. Bmc Pediatr.
2025; 25(1):93. https://doi.org/10.1186/s12887-025-05439-5.
16. Lewis AN, de la Cruz D, Wynn JL, et al. Evaluation of the Neonatal Sequential
Organ Failure Assessment and Mortality Risk in Preterm Infants with Necrotizing
Enterocolitis. Neonatology. 2022; 119(3):334-344.
https://doi.org/10.1159/000522560.