Development and validation of a predictive nomogram for pediatric ovarian torsion: a retrospective cohort study

作者：Jinwen Meng, Guannan Bai, Jieni Xiong, Yinbing Tang, Ming Liu, Jiabin Cai, Min He, L Zhang, Weizhong Gu, Jinhu Wang · 发表于：Translational Pediatrics · 年份：2026 · DOI：10.21037/tp-2026-1-0131 · 研究领域：Ovarian cancer diagnosis and treatment、Ovarian function and disorders、Omental and Epiploic Conditions

Background: Delayed diagnosis of pediatric ovarian torsion, a challenging emergency, can lead to ovarian loss and compromised fertility. This study aimed to develop and validate a predictive nomogram by integrating clinical, laboratory and sonographic features to facilitate the early and accurate identification of ovarian torsion. Methods: We conducted a retrospective analyses of data from 201 pediatric patients who underwent emergency surgery for suspected ovarian torsion between October 2017 and October 2025. The cohort was randomly divided into a training set (n=140) and a validation set (n=61). Using univariate and multivariate logistic regression analysis, independent predictors of ovarian torsion were identified to construct a predictive nomogram. Its performance was rigorously evaluated in three domains: (I) discrimination, assessed by the area under the receiver operating characteristic curve (AUC); (II) calibration, assessed using calibration plots, the Brier score, and the Spiegelhalter test; and (III) clinical utility, measured through decision curve analysis (DCA). Results: The final multivariate model identified four independent predictors: age [odds ratio (OR) =0.67], neutrophil-to-lymphocyte ratio (NLR) (OR =1.23), the whirlpool sign (OR =7.09), and maximum ovarian diameter (OR =1.75). The nomogram demonstrated excellent discrimination, with an AUC of 0.915 [95% confidence interval (CI): 0.865-0.964] in the training set and 0.853 (95% CI: 0.711-0.994) in the va...