biostudies-literatureLiu XThe 345 Talent Project of Shengjing Hospital11https://www.ebi.ac.uk/biostudies/studies/S-EPMC9865251biostudies-literatureUnknown13(1)<h4>Objectives</h4>Information on the prediction of improved semen parameters following varicocelectomy is scarce and mostly contradictory. Therefore, we developed and validated a nomogram to predict whether abnormal semen parameters in infertile men could improve following microscopic varicocelectomy (MSV).<h4>Methods</h4>From January 2018 to December 2021, 460 consecutive patients who underwent MSV were included. Of them, 336 patients as a development cohort at the Xiang Hua institution. As a validation cohort, Hu Nan Center (124 patients) was used. Clinicopathologic patient information was recorded. The likelihood ratio test using Akaike's information criteria was employed as the stopping rule, and multivariate logistic regression was utilized to create a prediction model with regressioJournal of personalized medicineNomogram for Predicting Semen Parameters Improvement after Microscopic Varicocelectomy in Infertile Men with Abnormal Semen Parameters.PMC9865251345Liu XPan CLiu DSu HfalseNomogram for Predicting Semen Parameters Improvement after Microscopic Varicocelectomy in Infertile Men with Abnormal Semen Parameters.<h4>Objectives</h4>Information on the prediction of improved semen parameters following varicocelectomy is scarce and mostly contradictory. Therefore, we developed and validated a nomogram to predict whether abnormal semen parameters in infertile men could improve following microscopic varicocelectomy (MSV).<h4>Methods</h4>From January 2018 to December 2021, 460 consecutive patients who underwent MSV were included. Of them, 336 patients as a development cohort at the Xiang Hua institution. As a validation cohort, Hu Nan Center (124 patients) was used. Clinicopathologic patient information was recorded. The likelihood ratio test using Akaike's information criteria was employed as the stopping rule, and multivariate logistic regression was utilized to create a prediction model with regressio2022-01-01T00:00:00Z2022 Dec2025-04-04T11:33:16.376Z2025-04-04T11:33:16.376ZS-EPMC98652513667567310.3390/jpm13010011