ArticlePloS one2025
Analysis of risk factors for postoperative complications in hypospadias and construction and validation of a nomogram predictive model.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Machine Learning for Predicting Postoperative Complications After Hypospadias Surgery: A 10-Year Single-Center Retrospective Cohort Study.Children (Basel, Switzerland) · 2026Article
- Do Perioperative Antibiotics Improve Outcomes After Hypospadias Repair? A Systematic Review and Meta-Analysis of Pediatric Literature.Children (Basel, Switzerland) · 2026Review
- Preoperative cystourethroscopic evaluation of children with posterior hypospadias.Bioinformation · 2025Article
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9 authors.
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Abstract
backgroundThe incidence of postoperative complications in children with hypospadias is notably high; however, research on predictive models for these complications remains limited. This study aims to analyze the factors associated with postoperative complications following hypospadias surgery and to develop a nomogram predictive model for such complications.
methodsThis study included 553 hypospadias patients who underwent surgery at Zunyi Medical University Affiliated Hospital from 1/1/2016-1/1/2023.The patients were randomly divided into training (n = 389) and validation (n = 164) cohorts in a 7:3 ratio. Univariate and multivariate logistic regression analyses were performed on the training cohort to identify risk factors for postoperative complications, which were then used to develop a nomogram prediction model. Finally, the internal validation cohort was used to assess the model's prognostic accuracy and clinical utility. All statistical analyses were performed using R software(Version 4.2.2).
resultsMultivariate logistic regression analysis of the training cohort identified six independent risk factors for postoperative complications in hypospadias surgery: age (OR=1.02, 95% CI: 1.01-1.03, P < 0.001), surgeon's experience (OR=0.44, 95% CI: 0.26-0.75, P = 0.0026), glans width (OR=0.70, 95% CI: 0.59-0.82, P < 0.001), length of reconstructed urethra (OR=1.03, 95% CI: 1.01-1.06, P = 0.003), hypospadias classification (OR=4.26, 95% CI: 1.96-9.26, P < 0.001), and urethral stent retention time (OR=0.25, 95% CI: 0.12-0.52, P < 0.001). Based on these factors, a nomogram was constructed. The area under the curve of the nomogram model was 0.800, and after internal validation it was 0.821, indicating good discriminative ability. Furthermore, the model exhibited excellent calibration and high clinical utility.
conclusionThis study developed and validated a nomogram prediction model for postoperative complications in hypospadias surgery based on six factors: age, surgeon's experience, glans width, length of reconstructed urethra, hypospadias classification, and urethral stent retention time. It provides a scientific basis for implementing personalized medicine in hypospadias patients in the future.
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