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Development and validation of a nomogram for predicting hospitalization longer than 14 days in pediatric patients
Jia-Liang Zhu1,2, Xiao-Mei Xu1,2, Hai-Yan Yin1
1Department of Intensive Care Unit, The First Affiliated Hospital of Jinan University, Guangzhou, China.
Insights
This study developed a nomogram to predict prolonged hospital stays in pediatric ventricular septal defect patients. The tool effectively identifies at-risk children, aiding early intervention and reducing complications.
Area of Science:
- Pediatric Cardiology
- Medical Informatics
- Clinical Prediction Modeling
Background:
- Ventricular septal defect (VSD) is a common congenital heart defect associated with increased risks of lung infection, heart failure, and prolonged hospitalization.
- Identifying pediatric VSD patients at risk for extended hospital stays is crucial for timely intervention and complication management.
- Current management strategies lack precise tools for predicting prolonged hospital stays in this vulnerable population.
Purpose of the Study:
- To develop and validate a predictive nomogram for hospital stays exceeding 14 days in pediatric patients diagnosed with VSD.
- To provide clinicians with a practical tool for early identification of high-risk VSD patients.
- To potentially reduce hospital stay duration and associated complications through targeted interventions.
Main Methods:
- A retrospective analysis of 705 pediatric VSD patients from the Pediatric Intensive Care Database.
- Development of a logistic regression nomogram using variables selected via Variance Inflation Factor (VIF) and Least Absolute Shrinkage and Selection Operator (Lasso) regression.
- Performance evaluation using Area Under the Curve (AUC), Decision Curve Analysis (DCA), and calibration curves, with variable importance assessed by XGboost.
Main Results:
- The final nomogram incorporated Brain Natriuretic Peptide, bicarbonate, fibrinogen, urea, alanine aminotransferase, blood oxygen saturation, systolic blood pressure, respiratory rate, and heart rate.
- The nomogram demonstrated good predictive performance with AUC values of 0.812 in the training cohort and 0.736 in the validation cohort.
- Calibration curves and DCA confirmed the nomogram's robust performance and clinical utility.
Conclusions:
- A validated nomogram utilizing clinical and laboratory parameters effectively predicts prolonged hospital stays in pediatric VSD patients.
- The nomogram offers significant clinical applicability for identifying at-risk populations and guiding early therapeutic strategies.
- This tool can aid in optimizing resource allocation and improving patient outcomes by facilitating timely interventions.
Abstract:
Background: Ventricular septal defect is a common congenital heart disease. As the disease progresses, the likelihood of lung infection and heart failure increases, leading to prolonged hospital stays and an increased likelihood of complications such as nosocomial infections. We aimed to develop a nomogram for predicting hospital stays over 14 days in pediatric patients with ventricular septal defect and to evaluate the predictive power of the nomogram. We hope that nomogram can provide clinicians with more information to identify high-risk groups as soon as possible and give early treatment to reduce hospital stay and complications. Methods: The population of this study was pediatric patients with ventricular septal defect, and data were obtained from the Pediatric Intensive Care Database. The resulting event was a hospital stay longer than 14 days. Variables with a variance inflation factor (VIF) greater than 5 were excluded. Variables were selected using the least absolute shrinkage and selection operator (Lasso), and the selected variables were incorporated into logistic regression to construct a nomogram. The performance of the nomogram was assessed by using the area under the receiver operating characteristic curve (AUC), Decision Curve Analysis (DCA) and calibration curve. Finally, the importance of variables in the model is calculated based on the XGboost method. Results: A total of 705 patients with ventricular septal defect were included in the study. After screening with VIF and Lasso, the variables finally included in the statistical analysis include: Brain Natriuretic Peptide, bicarbonate, fibrinogen, urea, alanine aminotransferase, blood oxygen saturation, systolic blood pressure, respiratory rate, heart rate. The AUC values of nomogram in the training cohort and validation cohort were 0.812 and 0.736, respectively. The results of the calibration curve and DCA also indicated that the nomogram had good performance and good clinical application value. Conclusion: The nomogram established by BNP, bicarbonate, fibrinogen, urea, alanine aminotransferase, blood oxygen saturation, systolic blood pressure, respiratory rate, heart rate has good predictive performance and clinical applicability. The nomogram can effectively identify specific populations at risk for adverse outcomes.
