Retrospective Analysis of Influencing Factors of Intrauterine Adhesions After Hysteroscopic Resection for Endometrial Polyps and Construction of a Nomogram Prediction Model
Background: This study aimed to explore the factors influencing the development of intrauterine adhesions (IUA) in patients with endometrial polyps (EP) following hysteroscopic resection. We also aimed to construct a nomogram model to predict the risk of postoperative IUA and vali...
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IMR Press
2025-06-01
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| Series: | Clinical and Experimental Obstetrics & Gynecology |
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| Online Access: | https://www.imrpress.com/journal/CEOG/52/6/10.31083/CEOG38262 |
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| author | Lanlan Liu Wei Liu Shuaiting Liu Jingzhen Yang |
| author_facet | Lanlan Liu Wei Liu Shuaiting Liu Jingzhen Yang |
| author_sort | Lanlan Liu |
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| description | Background: This study aimed to explore the factors influencing the development of intrauterine adhesions (IUA) in patients with endometrial polyps (EP) following hysteroscopic resection. We also aimed to construct a nomogram model to predict the risk of postoperative IUA and validate its predictive accuracy. Methods: We conducted a retrospective analysis of data from 322 EP patients treated at our hospital between July 2022 and June 2024. The patients were randomly divided into a modeling group (n = 248) and a verification group (n = 74). Based on whether IUA occurred after hysteroscopic resection, the modeling group was further categorized into an IUA group and a non-IUA group. Data from the modeling group were collected and compared between the two subgroups. We used logistic regression to identify the factors contributing to postoperative IUA. The nomogram model was built using R software, and internal validation was conducted using receiver operating characteristic (ROC) curves, calibration curves, and decision curves. Additionally, we performed external validation using the verification group. Results: The incidence of postoperative IUA in the modeling group was 20.56% (51/248). Logistic regression analysis revealed that the use of intrauterine devices, history of pelvic inflammatory disease, previous curettage, history of pregnancy termination, and surgical duration were significant risk factors for the development of postoperative IUA (p < 0.050). The area under the curve (AUC) for both the modeling and verification groups was 0.815 (95% CI: 0.753–0.876) and 0.808 (95% CI: 0.747–0.870), respectively. The calibration curve indicated that the predicted probability of IUA occurrence closely matched the actual observed values. The decision curve analysis demonstrated that the predictive model had strong clinical applicability. Conclusions: The nomogram model, based on five independent risk factors—use of intrauterine devices, history of pelvic inflammatory disease, previous curettage, history of pregnancy termination, and surgical duration—has shown good predictive performance and significant clinical utility in assessing the risk of postoperative IUA in EP patients. |
| format | Article |
| id | doaj-art-a84fb38fc0d94724a0b5e87d6b170988 |
| institution | Matheson Library |
| issn | 0390-6663 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | IMR Press |
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| series | Clinical and Experimental Obstetrics & Gynecology |
| spelling | doaj-art-a84fb38fc0d94724a0b5e87d6b1709882025-07-08T07:03:51ZengIMR PressClinical and Experimental Obstetrics & Gynecology0390-66632025-06-015263826210.31083/CEOG38262S0390-6663(25)02613-2Retrospective Analysis of Influencing Factors of Intrauterine Adhesions After Hysteroscopic Resection for Endometrial Polyps and Construction of a Nomogram Prediction ModelLanlan Liu0Wei Liu1Shuaiting Liu2Jingzhen Yang3Department of Gynecology, Ganzhou Maternal and Child Health Care Hospital, 341000 Ganzhou, Jiangxi, ChinaDepartment of Gynecology, Ganzhou Maternal and Child Health Care Hospital, 341000 Ganzhou, Jiangxi, ChinaDepartment of Gynecology, Ganzhou Maternal and Child Health Care Hospital, 341000 Ganzhou, Jiangxi, ChinaDepartment of Gynecology, Ganzhou Maternal and Child Health Care Hospital, 341000 Ganzhou, Jiangxi, ChinaBackground: This study aimed to explore the factors influencing the development of intrauterine adhesions (IUA) in patients with endometrial polyps (EP) following hysteroscopic resection. We also aimed to construct a nomogram model to predict the risk of postoperative IUA and validate its predictive accuracy. Methods: We conducted a retrospective analysis of data from 322 EP patients treated at our hospital between July 2022 and June 2024. The patients were randomly divided into a modeling group (n = 248) and a verification group (n = 74). Based on whether IUA occurred after hysteroscopic resection, the modeling group was further categorized into an IUA group and a non-IUA group. Data from the modeling group were collected and compared between the two subgroups. We used logistic regression to identify the factors contributing to postoperative IUA. The nomogram model was built using R software, and internal validation was conducted using receiver operating characteristic (ROC) curves, calibration curves, and decision curves. Additionally, we performed external validation using the verification group. Results: The incidence of postoperative IUA in the modeling group was 20.56% (51/248). Logistic regression analysis revealed that the use of intrauterine devices, history of pelvic inflammatory disease, previous curettage, history of pregnancy termination, and surgical duration were significant risk factors for the development of postoperative IUA (p < 0.050). The area under the curve (AUC) for both the modeling and verification groups was 0.815 (95% CI: 0.753–0.876) and 0.808 (95% CI: 0.747–0.870), respectively. The calibration curve indicated that the predicted probability of IUA occurrence closely matched the actual observed values. The decision curve analysis demonstrated that the predictive model had strong clinical applicability. Conclusions: The nomogram model, based on five independent risk factors—use of intrauterine devices, history of pelvic inflammatory disease, previous curettage, history of pregnancy termination, and surgical duration—has shown good predictive performance and significant clinical utility in assessing the risk of postoperative IUA in EP patients.https://www.imrpress.com/journal/CEOG/52/6/10.31083/CEOG38262endometrial polypshysteroscopic resectionintrauterine adhesionsinfluencing factorsnomogram |
| spellingShingle | Lanlan Liu Wei Liu Shuaiting Liu Jingzhen Yang Retrospective Analysis of Influencing Factors of Intrauterine Adhesions After Hysteroscopic Resection for Endometrial Polyps and Construction of a Nomogram Prediction Model Clinical and Experimental Obstetrics & Gynecology endometrial polyps hysteroscopic resection intrauterine adhesions influencing factors nomogram |
| title | Retrospective Analysis of Influencing Factors of Intrauterine Adhesions After Hysteroscopic Resection for Endometrial Polyps and Construction of a Nomogram Prediction Model |
| title_full | Retrospective Analysis of Influencing Factors of Intrauterine Adhesions After Hysteroscopic Resection for Endometrial Polyps and Construction of a Nomogram Prediction Model |
| title_fullStr | Retrospective Analysis of Influencing Factors of Intrauterine Adhesions After Hysteroscopic Resection for Endometrial Polyps and Construction of a Nomogram Prediction Model |
| title_full_unstemmed | Retrospective Analysis of Influencing Factors of Intrauterine Adhesions After Hysteroscopic Resection for Endometrial Polyps and Construction of a Nomogram Prediction Model |
| title_short | Retrospective Analysis of Influencing Factors of Intrauterine Adhesions After Hysteroscopic Resection for Endometrial Polyps and Construction of a Nomogram Prediction Model |
| title_sort | retrospective analysis of influencing factors of intrauterine adhesions after hysteroscopic resection for endometrial polyps and construction of a nomogram prediction model |
| topic | endometrial polyps hysteroscopic resection intrauterine adhesions influencing factors nomogram |
| url | https://www.imrpress.com/journal/CEOG/52/6/10.31083/CEOG38262 |
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