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The multivariate cox regression model for complete enteral nutrition after primary anastomosis in neonates with
Yang Chen1,2, Le-Dao Zhu1, Ling Zhou1
1Shenzhen Children's Hospital, Shenzhen, China.
Insights
This study developed a prediction model for complete enteral nutrition in neonates with intestinal atresia. Key factors like gestational age and feeding time help predict outcomes, aiding clinical decisions.
Area of Science:
- Pediatric Surgery
- Neonatal Nutrition
- Clinical Prediction Modeling
Background:
- Enteral feeding following intestinal atresia repair presents clinical challenges.
- Existing research often focuses on isolated factors, lacking a comprehensive approach.
Purpose of the Study:
- To comprehensively analyze multiple factors influencing complete enteral nutrition after primary intestinal anastomosis.
- To establish a convenient and accurate prediction model for enteral feeding success in neonates.
Main Methods:
- Retrospective analysis of neonatal intestinal atresia cases (January 2010 - June 2022).
- Cox regression analysis to identify independent risk factors.
- Development and validation of a nomogram using ROC, calibration, and decision curves.
Main Results:
- Identified key predictors: gestational age, meconium peritonitis, anastomosis-to-ileocecal region distance, proximal-to-distal bowel diameter ratio, and initial feeding time.
- Nomogram demonstrated strong predictive performance with AUCs of 0.765 (week 2), 0.785 (week 3), and 0.747 (week 4).
- Calibration and decision curves confirmed the model's accuracy and clinical applicability.
Conclusions:
- The developed prediction model holds significant clinical value for managing enteral feeding in neonates with intestinal atresia.
- This tool can assist pediatricians in optimizing patient care, potentially reducing hospital costs and parental anxiety.
Objective:
Enteral feeding after intestinal atresia has always been a concern for clinicians. But the present studies mainly focused on single factors. This research aimed to comprehensively analyze the multiple factors on complete enteral nutrition after primary anastomosis, and establish the convenient prediction model.
Methods:
We retrospectively collected reliable information in neonates with intestinal atresia form January 2010 to June 2022. The cox regression analysis was performed to select independent risk factors and develop nomogram. Subsequently, ROC curve, calibration curve and decision curve were drawn to thoroughly evaluate the accuracy and applicability of the model.
Results:
The predictors finally included in the model were gestational age, meconium peritonitis, distance from the anastomosis to the ileocecal region, diameter ratio of proximal to distal bowels, and time of initial feeding. The nomogram of predicting the probability of week 2, week 3 and week 4 was drawn and their area under the curve were 0.765, 0.785 and 0.747, respectively. Similarly, calibration and decision curve indicated that the prediction model had a great prediction performance.
Conclusion:
The clinical value of predictive models can be recognized. The hope is that the predictive model can help pediatricians reduce hospital costs and parental anxiety.
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