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Updated: Sep 29, 2026

Establishment and Evaluation of a Risk Prediction Model for Pathological Escalation of Gastric Low-Grade Intraepithelial Neoplasia
Published on: February 16, 2024
Development and internal validation of a risk-scoring model for gastrointestinal flexible endoscope reprocessing
Liangyu Fang1, Xiaoxuan Zhou1, Meifeng Wu1
1Department of Nursing, The Second Affiliated Hospital of Zhejiang University School of Medicine, China.
Abstract:
ObjectiveTo identify risk factors for flexible gastrointestinal endoscope reprocessing failure and develop a practical risk-scoring model for the early identification of high-risk reprocessing cycles.MethodsThis retrospective observational study, conducted from January to December 2025 at three endoscopy centers, included 2744 reprocessing cycles that adhered to WS 507-2016. Internal validation was performed using a split-sample approach, with 70% of the sample used for model derivation and 30% for validation. Predictors were selected using univariable and multivariable logistic regression and converted into an integer-based scoring system, with the optimal cutoff determined using the Youden index. Reporting followed the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis and Strengthening the Reporting of Observational Studies in Epidemiology guidelines, and the study was conducted in accordance with the Declaration of Helsinki.ResultsAmong the 2744 eligible reprocessing cycles, 682 (24.85%) exhibited reprocessing failure. Six independent predictors were identified: brushing personnel, washer-disinfector type, accessory use frequency, prior repair history, time from removal to reprocessing, and staff age. The scoring system, with a range of -2 to 18, achieved an area under the curve of 0.834 (95% confidence interval: 0.804-0.864) in the validation cohort. At a cutoff of ≥10, sensitivity was 0.725, specificity was 0.808, positive predictive value was 0.554, and negative predictive value was 0.899. Calibration was satisfactory based on the Hosmer-Lemeshow test and bootstrap analysis.ConclusionsThe internally validated scoring system enables the early identification of high-risk reprocessing cycles and may support quality improvement efforts. However, external validation is needed to assess its generalizability.
