Evidence map›Paper›PMID 42169045›Full record

ArticleBMC women's health2026

Development and validation of a nomogram for predicting the likelihood of undergoing surgical intervention in ruptured corpus luteum.

Liang Chen, Fang Liang, Wanhong Xu, Shijie Zhao, Xuehui Zhong

Abstract readValidation Study
In one paragraph

Article in BMC women's health, 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Liang ChenDepartment of Gynecology, The Fourth Hospital of Changsha (Changsha Hospital of Integrated Traditional Chinese and Western Medicine), No. 70, Luyuan Road, Yuelu District, Changsha, Hunan Province, 410006, China.
Fang LiangDepartment of Gynecology, The Fourth Hospital of Changsha (Changsha Hospital of Integrated Traditional Chinese and Western Medicine), No. 70, Luyuan Road, Yuelu District, Changsha, Hunan Province, 410006, China.
Wanhong XuDepartment of Gynecology, The Fourth Hospital of Changsha (Changsha Hospital of Integrated Traditional Chinese and Western Medicine), No. 70, Luyuan Road, Yuelu District, Changsha, Hunan Province, 410006, China.
Shijie ZhaoDepartment of Gynecology, The Fourth Hospital of Changsha (Changsha Hospital of Integrated Traditional Chinese and Western Medicine), No. 70, Luyuan Road, Yuelu District, Changsha, Hunan Province, 410006, China.
Xuehui ZhongDepartment of Gynecology, The Fourth Hospital of Changsha (Changsha Hospital of Integrated Traditional Chinese and Western Medicine), No. 70, Luyuan Road, Yuelu District, Changsha, Hunan Province, 410006, China. 13467551630@163.com.

Funding

Natural Science Foundation of Hunan Province No. 2026JJ82308
6 · The paper itself

Abstract

objectiveTo investigate clinical factors associated with surgical intervention in patients with ruptured corpus luteum (CL) and to develop a prediction model for estimating the likelihood of undergoing surgical intervention.

methodsThis retrospective study enrolled 341 patients with ruptured CL, who were allocated to surgical (n = 106) or conservative (n = 235) group. Baseline demographic, laboratory, and imaging data were collected and compared. Multivariable logistic regression analysis was employed to identify independently associated factors, which were subsequently used to develop a nomogram prediction model. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) for discriminative ability, calibration curves for accuracy, and decision curve analysis (DCA) for clinical utility.

resultsAbdominal rebound tenderness (OR = 1.363, 95% CI: 1.078-1.724), lower admission hemoglobin level (OR = 0.891, 95% CI: 0.862-0.921), longer prothrombin time (OR = 1.445, 95% CI: 1.019-2.048), larger maximum CL cyst diameter (OR = 2.340, 95% CI: 1.821-3.006), and greater pelvic fluid depth (OR = 1.482, 95% CI: 1.154-1.903) were independent factors associated with undergoing surgical intervention. The nomogram demonstrated good discriminative ability (AUC = 0.884, 95% CI: 0.847-0.921), with a bias-corrected AUC of 0.876 after Bootstrap validation. The calibration curve indicated good agreement between predicted probabilities and actual observations. DCA showed a favorable net clinical benefit across a wide range of threshold probabilities.

conclusionThis study developed a nomogram incorporating five independent predictors: abdominal rebound tenderness, admission hemoglobin, prothrombin time, maximum corpus luteum cyst diameter, and pelvic fluid depth. Although internal validation demonstrated good discrimination (AUC = 0.884) and potential clinical utility, inherent treatment-selection bias renders this model strictly exploratory. Pending prospective external validation, it serves merely as a preliminary decision-support reference.

Indexed as

Corpus LuteumNomogramsOvarian CystsAdultFemaleHumansLogistic ModelsMiddle AgedRetrospective StudiesROC CurveRupture, SpontaneousPrediction modelRisk factorsRuptured corpus luteumSurgical intervention

Identifiers

PMID42169045
PMCPMC13371719

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