Prediction of the risk of developing endometrial polyp based on lipid metabolism , vaginal microecology combined with uterine volume line graph modeling
10.19405/j.cnki.issn1000-1492.2025.08.025
- VernacularTitle:基于脂质代谢 、阴道微生态联合子宫体积列线图模型 预测发生子宫内膜息肉的风险
- Author:
Ya Li
1
;
Yun Zhang
2
;
Lei Yang
2
;
Nan Min
2
;
Liling Ge
2
;
Shiying Sun
3
;
Bing Wei
3
Author Information
1. Dept of Obstetrics and Gynecology , The Second Afiliated Hospital of Anhui Medical University , Hefei 230031；Dept of Obstetrics and Gynecology , Bengbu First People ′s Hospital , Bengbu 233000
2. Dept of Obstetrics and Gynecology , Bengbu First People ′s Hospital , Bengbu 233000
3. Dept of Obstetrics and Gynecology , The Second Afiliated Hospital of Anhui Medical University , Hefei 230031
- Publication Type:Journal Article
- Keywords:
endometrial polyp;
lipid metabolism;
uterine volume;
vaginal microecology;
line drawing
- From:
Acta Universitatis Medicinalis Anhui
2025;60(8):1541-1547
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the risk of endometrial polyp (EP) based on lipid metabolism and vaginal micro- ecology combined with uterine volume line drawing model.
Methods:143 EP patients treated by hysteroscopic sur- gery were selected as the experimental group , and 113 healthy women were selected as the control group at the same time. The data were randomly divided into training set and validation set according to the ratio of 7 : 3. The clinical data of the two groups were collected and recorded , and t/χ2 test , LASSO regression and multifactorial lo- gistic regression analysis were used to screen the independent risk factors , construct the prediction model , and draw the column line graph. The performance of the model was evaluated by applying subject operating characteristic (ROC) curves , calibration curves , Hosmer-Lemeshow test and clinical decision-making (DCA) curves.
Results:Multifactorial logistic regression analysis showed that total cholesterol ( TC) , low-density lipoprotein cholesterol (LDL-C) , vaginal microecological balance , and uterine volume were independent risk factors for the development of EP. ROC curve analysis showed that the AUC values of the training and validation sets of the column line graph model were 0. 935 and 0. 887 , respectively , and its sensitivity and specificity were 90. 21% , 83. 46% and 86. 29% , 80. 66% respectively , The Hosmer-Lemeshow test showed that the model fits well ( training set : χ2 = 2. 261 , P = 0. 840 ; validation set : χ2 = 4. 837 , P = 0. 441) and the calibration curves of the training and validation sets were close to the ideal curves , which indicated that the model had good prediction accuracy; the analysis of DCA curves of the training and validation sets both showed that the column-line graph model had a good clinical benefit rate in predicting EP.
Conclusion :TC , LDL-C , vaginal microecological balance and uterine volume are independent risk factors for EP , and the column-line diagram model constructed by the model has high clinical ben- efit , calibration and accuracy in predicting the risk of EP.
- Full text:2026041115573711914基于脂质代谢、阴道微生态联合子宫体积列线图模型预测发生子宫内膜息肉的风险_李亚.pdf
