Evidence map›Paper›PMID 42292627›Full record

ArticleTranslational pediatrics2026

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

Jinwen Meng, Guannan Bai, Jieni Xiong, Yinbing Tang, Ming Liu, Jiabin Cai, Min He, Lifeng Zhang, Weizhong Gu, Jinhu Wang

Abstract read
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Article in Translational pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Jinwen Meng *Department of Surgical Oncology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Children and Adolescents' Health and Diseases, Hangzhou, China.
Guannan Bai *Department of Child Health Care, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Children and Adolescents' Health and Diseases, Hangzhou, China.
Jieni XiongDepartment of Surgical Oncology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Children and Adolescents' Health and Diseases, Hangzhou, China.
Yinbing TangDepartment of Surgical Oncology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Children and Adolescents' Health and Diseases, Hangzhou, China.
Ming LiuDepartment of Surgical Oncology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Children and Adolescents' Health and Diseases, Hangzhou, China.
Jiabin CaiDepartment of Surgical Oncology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Children and Adolescents' Health and Diseases, Hangzhou, China.
Min HeDepartment of Surgical Oncology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Children and Adolescents' Health and Diseases, Hangzhou, China.
Lifeng ZhangDepartment of Surgical Oncology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Children and Adolescents' Health and Diseases, Hangzhou, China.
Weizhong GuDepartment of Pathology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Children and Adolescents' Health and Diseases, Hangzhou, China.
Jinhu WangDepartment of Surgical Oncology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Children and Adolescents' Health and Diseases, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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 validation set. Calibration analysis showed a strong correlation between predicted and actual probabilities. DCA verified that the nomogram offered a higher net benefit across a broad spectrum of threshold probabilities. Conclusions: A novel nomogram has been developed incorporating age, NLR, the whirlpool sign, and ovarian diameter to predict pediatric ovarian torsion. This tool can serve as an intuitive bedside instrument to aid clinicians in rapid risk stratification, thereby improving diagnostic decision-making and potentially increasing rates of ovarian salvage.

Indexed as

diagnosisnomogramPediatric ovarian torsionprediction model

Identifiers

PMID42292627
PMCPMC13263446

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