1.Analysis of risk factors and establishment of a prediction model for endometrial cancer in postmenopausal bleeding
Jing WANG ; Qiaoyun ZHOU ; Muyu WANG ; Yu XIAO ; Dongmei SONG ; Yan GUO ; Enlan XIA ; Tinchiu LI ; Xiaowu HUANG
Journal of Capital Medical University 2025;46(1):143-149
Objective To establish a method for predicting the risk of endometrial cancer(EC)and endometrial atypical hyperplasia(AH)in women with postmenopausal bleeding(PMB)by collecting clinical data on routine medical history.Methods The clinical data of a total of 408 PMB patients admitted to Fuxing Hospital,Capital Medical University were consecutively collected in this retrospective study from December 2013 to December 2023.According to the results of endometrial pathology,patients were divided into case group and control group.EC and AH were included in the malignant group(case group)and the other endometrial pathologies were included in the non-malignant group(control group).Clinical data,including clinical history,high risk factors,and common gynecological ultrasound measurement indicators,were collected and studied by univariate and multivariate Logistic regression analysis.Results The mean age of 408 patients was(60.4±7.8)years.A total of 74 cases(18.1%)were in case group and 334 cases(81.9%)were in control group.Based on Logistic regression analysis,the best predictors of endometrial malignant lesions were selected to create a"LRDNT"(light bleeding,recurrent bleeding,diabetes,non-uniform echogenicity & thickness)model.LRDNT scores range from 0 to 22.The score of LRDNT ≥15 has the largest Yoden index,and the sensitivity to predict endometrial malignant lesions is 79.73%,the specificity is 80.84%,and the prediction accuracy is 80.64%.Conclusions The risk prediction model LRDNT,which combines clinical information and common gynecological ultrasound measurement indicators of PMB patients,can help clinicians classify patients at high and low risk of endometrial malignant lesions,and optimize the strategy of diagnosis and treatment.
2.Analysis of risk factors and establishment of a prediction model for endometrial cancer in postmenopausal bleeding
Jing WANG ; Qiaoyun ZHOU ; Muyu WANG ; Yu XIAO ; Dongmei SONG ; Yan GUO ; Enlan XIA ; Tinchiu LI ; Xiaowu HUANG
Journal of Capital Medical University 2025;46(1):143-149
Objective To establish a method for predicting the risk of endometrial cancer(EC)and endometrial atypical hyperplasia(AH)in women with postmenopausal bleeding(PMB)by collecting clinical data on routine medical history.Methods The clinical data of a total of 408 PMB patients admitted to Fuxing Hospital,Capital Medical University were consecutively collected in this retrospective study from December 2013 to December 2023.According to the results of endometrial pathology,patients were divided into case group and control group.EC and AH were included in the malignant group(case group)and the other endometrial pathologies were included in the non-malignant group(control group).Clinical data,including clinical history,high risk factors,and common gynecological ultrasound measurement indicators,were collected and studied by univariate and multivariate Logistic regression analysis.Results The mean age of 408 patients was(60.4±7.8)years.A total of 74 cases(18.1%)were in case group and 334 cases(81.9%)were in control group.Based on Logistic regression analysis,the best predictors of endometrial malignant lesions were selected to create a"LRDNT"(light bleeding,recurrent bleeding,diabetes,non-uniform echogenicity & thickness)model.LRDNT scores range from 0 to 22.The score of LRDNT ≥15 has the largest Yoden index,and the sensitivity to predict endometrial malignant lesions is 79.73%,the specificity is 80.84%,and the prediction accuracy is 80.64%.Conclusions The risk prediction model LRDNT,which combines clinical information and common gynecological ultrasound measurement indicators of PMB patients,can help clinicians classify patients at high and low risk of endometrial malignant lesions,and optimize the strategy of diagnosis and treatment.
4.A comparison of implantation, miscarriage and pregnancy rates of single and double day 3 embryo transfer between fresh and frozen thawed transfer cycles: a retrospective study.
Liu LIU ; Xiaomei TONG ; Lingying JIANG ; Tinchiu LI ; Feng ZHOU ; Songying ZHANG
Chinese Medical Journal 2014;127(5):911-915
BACKGROUNDReduced endometrial receptivity in hyperstimulated cycles may lead to a lower implantation rate and a lower clinical pregnancy rate, but it is unclear if it is also associated with an increase in pregnancy loss rate. The aim of this study was to compare the implantation, miscarriage, and pregnancy rates between fresh and frozen thawed transfer of one or two day-3 embryos, with a view to understanding whether or not reduced endometrial receptivity encountered in hyperstimulated cycles is associated with an increase in miscarriage rate.
METHODSThis study involved a consecutive series of 1 551 single day-3 embryo transfer cycles and consecutive 5 919 double day-3 embryo transfer cycles in the Assisted Reproductive Unit of the Sir Run Run Shaw Hospital, Hangzhou, China, between January 2010 and December 2012.
RESULTSThe implantation and clinical pregnancy rates (single embryo 30.7% and double embryos 33.4% and 51.4%) using fresh cycle were both significantly lower than that of frozen-thawed cycles (single embryo 35.8% and double embryos 38.1% and 57.8%). There was no difference in biochemical loss or clinical miscarriage rates between the two groups.
CONCLUSIONSImpairment of endometrial receptivity associated with ovarian hyperstimulation leads to implantation failure at a very early stage, resulting in an increased number of non-pregnancy. It does not lead to increase in biochemical or clinical losses. The significantly reduced ongoing pregnancy rates in both fresh single and double embryo transfer are therefore due to failure to achieve a pregnancy, rather than pregnancy loss after conception.
Adult ; Cryopreservation ; Embryo Implantation ; physiology ; Embryo Transfer ; methods ; statistics & numerical data ; Female ; Fertilization in Vitro ; methods ; statistics & numerical data ; Humans ; Male ; Pregnancy ; Pregnancy Rate ; Retrospective Studies

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