Risk Factors and Prediction Methods for Endometriosis Combined with Ureteral Stricture Based on Logistic-Regression Analysis

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Previous ureter operation history, endometriosis duration, hematuria, flank pain, and lesion invasion depth ≥5mm are risk factors for endometriosis with ureteral stricture.

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The paper investigates risk factors and builds prediction methods for endometriosis complicated by ureteral stricture using logistic-regression analysis. It analyzes clinical data to identify factors associated with the combined condition and then formulates a model intended to predict its presence, reporting model performance as part of the results. A key limitation is that logistic-regression–based prediction relies on the studied dataset and its variables, and the paper’s reported model validity is therefore confined to the context and population from which the data were drawn. This paper is centrally about endometriosis—specifically endometriosis combined with ureteral stricture and prediction of that complication.

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Abstract

OBJECTIVE: This study aimed to explore the risk factors of patients with endometriosis (EMS) and ureteral stricture and to establish a prediction model based on logistic-regression analysis. METHODS: The clinical data of 228 EMS patients in Jiaozhou Central Hospital of Qingdao from May 2019 to May 2022 were selected for a retrospective study. According to the results of ureteroscopic biopsy, they were divided into concurrent (n = 32) and nonconcurrent (n = 196) groups. Univariate analysis was performed on the general data and situations of clinical treatment in both groups. Single factor with statistically significant differences was included in unconditional logistic-regression analysis with multiple factors to explore the risk factors of such patients and establish a prediction model. RESULTS: Overt differences were found in previous history of ureter operation (odds ratio (OR) = 3.711, p = 0.006), course of EMS (OR = 3.987, p = 0.007), presence or absence of haematuria (OR = 3.586, p = 0.009) and lateral abdominal pain (OR = 4.451, p = 0.002), and invasion depth of lesion (OR = 7.271, p < 0.001) between the two groups (p 0.05). Logistic-regression analysis showed that previous history of ureter operation (a1), course of EMS (b2), occurrence of haematuria (c3) and lateral abdominal pain (d4), and invasion depth of lesion ≥5 mm (e5) were risk factors for EMS combined with ureteral stricture (p < 0.05), taking logit (p) = -4.990 + 1.311a1 + 1.383b2 + 1.277c3 + 1.493d4 + 1.984e5 as regression model. The receiver operating characteristic (ROC) curve analysis based on this model showed that the area under the curve (AUC), standard error, and 95% confidence interval (CI) were 0.813, 0.062, and 0.692-0.934, respectively. One hundred EMS patients were re-included, whose values for predictive sensitivity, specificity, and kappa coefficient were 71.40%, 91.10% and 0.615. CONCLUSIONS: Previous history of ureter operation, course of EMS, occurrence of haematuria and lateral abdominal pain, and invasion depth of lesion ≥5 mm were risk factors for EMS combined with ureteral stricture. Therefore, the use of this model has a certain clinical value.
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Risk Factors and Prediction Methods for Endometriosis Combined with Ureteral Stricture Based on Logistic-Regression Analysis Lixian Wang, Yun Shang, Xiujuan Wu, Haijing Zhang PDF(788 KB) Archivos Españoles de Urología ›› 2023, Vol. 76 ›› Issue (3) : 232-237. DOI: 10.56434/j.arch.esp.urol.20237603.26 Risk Factors and Prediction Methods for Endometriosis Combined with Ureteral Stricture Based on Logistic-Regression Analysis - {{javascript:window.custom_author_en_index=0;}} - , {{custom_author.name_en}} {{custom_author.xref}} {{javascript:window.custom_author_en_index++;}} - {{article.zuoZhe_EN}} Author information + History + {{article.keyPoints_en}} | {{custom_ref.label}} | {{custom_citation.content}} {{custom_citation.annotation}} | {{article.reference}} {{custom_fund}} {{article.copyrightStatement_en}} {{article.copyrightLicense_en}} / | 〈 | 〉 |

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Condition tags

endometriosisdysmenorrhea

MeSH descriptors

Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis

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last seen: 2026-06-28T06:08:18.748782+00:00
pubmed
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