ArticleFrontiers in surgery2025
Predicting the risk of endometriosis in Chinese infertile women: development and assessment of a predictive nomogram.
Article in Frontiers in surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Locking plates versus intramedullary nails for the treatment of two- and three-part proximal humerus fractures in patients older than 60 years: a meta-analysis.European journal of orthopaedic surgery & traumatology : orthopedie traumatologie · 2025Pooled it
- A nomogram integrating a novel uterine isthmus ratio (APTUIR), sonographic signs and clinical symptoms for predicting posterior deep endometriosis.Archives of gynecology and obstetrics · 2026Article
Corrections and comments
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Authors and funding
6 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Purpose: This study aimed to establish a risk prediction model of endometriosis in infertile women and verify the model. Methods: A retrospective study was made of 140 infertile women hospitalized at Henan Provincial People's Hospital between January 2018 and May 2024. They were divided into the Endometriosis group (EMs) and the No Endometriosis group (No-EMs). The baseline characteristics of the two groups were compared. The least absolute shrinkage and selection operator (LASSO) regression model was utilized to optimize feature selection. Subsequently, logistic regression (LR) analysis was utilized to formulate a predictive model that integrated the selected features. The discrimination and calibration of the predictive model were evaluated using the C-index and calibration plot. Internal validation was conducted using bootstrapping methods. Results: The LASSO regression model identified five feature selections: menstrual pattern, menstrual cycle length, severity of dysmenorrhea, duration of infertility, and type of infertility. LR analysis revealed that the severity of dysmenorrhea (OR = 10.278, 95% CI = 2.372-73.400, Conclusion: The development of Nomogram prediction models offers significant clinical predictive utility in evaluating the risk of EMs among infertile women. It equips clinicians with rational treatment strategies and novel perspectives for managing infertile women.
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Registered trials
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 Socratic graph.