Evidence map›Paper›PMID 42142159›Full record

ArticleInternational urogynecology journal2026

Hidden Preoperative Lower-Extremity Venous Thrombosis in Pelvic Organ Prolapse Surgery: Prevalence and Development of a Clinical Prediction Model.

Qi Wang, Xiaoxiang Jiang, Xiaoyan Li, Chaoqin Lin

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Article in International urogynecology journal, 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 authors.

Qi Wang *Department of Urogynecology and Pelvic Reconstructive Surgery, Fujian Maternity and Child Health Hospital, 18 Dao-Shan Street, Fuzhou, 350000, Gu-Lou District, China.ORCID http://orcid.org/0000-0003-3175-2881
Xiaoxiang Jiang *Department of Urogynecology and Pelvic Reconstructive Surgery, Fujian Maternity and Child Health Hospital, 18 Dao-Shan Street, Fuzhou, 350000, Gu-Lou District, China.
Xiaoyan LiDepartment of Urogynecology and Pelvic Reconstructive Surgery, Fujian Maternity and Child Health Hospital, 18 Dao-Shan Street, Fuzhou, 350000, Gu-Lou District, China. wmbssci@126.com.
Chaoqin LinDepartment of Urogynecology and Pelvic Reconstructive Surgery, Fujian Maternity and Child Health Hospital, 18 Dao-Shan Street, Fuzhou, 350000, Gu-Lou District, China. lcqfjsfy@126.com.ORCID http://orcid.org/0000-0003-4631-0218

Funding

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6 · The paper itself

Abstract

introduction and hypothesisPreoperative lower-extremity venous thrombosis (LEVT) is frequently overlooked in women undergoing pelvic organ prolapse (POP) surgery, despite its potential impact on perioperative outcomes. Conventional risk tools, including the Caprini score and D-dimer, show limited performance in this population, and the true prevalence of occult preoperative LEVT remains uncertain. This study aimed to determine the prevalence of occult preoperative LEVT in women undergoing POP surgery and to develop and validate a clinical prediction model for this condition.

methodsThis retrospective cross-sectional study included consecutive women scheduled for POP surgery between August 2019 and August 2025. All patients underwent routine preoperative compression ultrasonography of lower extremities. Demographic, clinical, and laboratory variables were collected. Patients were randomly divided into training (n = 878) and testing (n = 375) sets. Independent predictors were identified by multivariable logistic regression. Five predictive models-logistic regression, random forest, extreme gradient boosting (XGBoost), adaptive boosting (AdaBoost), and support vector machine (SVM)-were developed. Model performance was assessed using discrimination, calibration, and clinical utility, with comparisons to the Caprini score and D-dimer. A nomogram and web-based calculator were derived from the final model.

resultsAmong 1253 women, 117 (9.3%) had preoperative LEVT. Independent predictors of preoperative LEVT included advanced age, lower-extremity varicose veins, prior venous thromboembolism, elevated cholesterol, and increased D-dimer. Logistic regression achieved the best performance for predicting preoperative LEVT (AUC 0.827; 95% CI 0.770-0.883), significantly exceeding the Caprini score and D-dimer. At the optimal threshold, sensitivity was 0.971 and negative predictive value was 0.995.

conclusionsRoutine screening revealed a higher-than-expected prevalence of preoperative LEVT in POP surgery. A simple logistic model provided clinically useful risk stratification, supporting more selective use of preoperative ultrasonography and improved perioperative thrombosis management.

Indexed as

Machine learningPelvic organ prolapsePrediction modelPreoperative screeningVenous thrombosis

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.