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Contribution Of Male Age To Outcomes In Assisted Reproductive Technologies—Addressing Methodological Challenges, Brian W. Whitcomb, Eric D. Levens, Renée Turzanski-Fortner, Kevin S. Richter, Simon Kipersztok, Robert J. Stillman, Michael J. Levy
Contribution Of Male Age To Outcomes In Assisted Reproductive Technologies—Addressing Methodological Challenges, Brian W. Whitcomb, Eric D. Levens, Renée Turzanski-Fortner, Kevin S. Richter, Simon Kipersztok, Robert J. Stillman, Michael J. Levy
Brian W. Whitcomb
Objective—To evaluate the relation between male age and pregnancy outcome in donor oocyte assisted reproductive technology cycles Design—Retrospective cohort Setting—Private IVF center. Patients—1392 donor cycles from 1083 female recipients and their male partners Interventions—Oocyte donor cycles Main outcome measure(s)—Live birth Results—Increasing male age was associated with semen parameters including volume and motility; however, male age was not observed to have a statistically significant association with likelihood of live birth in donor cycles after adjustment for female recipient age. Conclusions—When treatment cycle number and female recipient age were taken into account, male age had no significant association with pregnancy outcomes in …
Realignment And Multiple Imputation Of Longitudinal Data: An Application To Menstrual Cycle Data, Sunni L. Mumford, Enrique F. Schisterman, Audrey J. Gaskinsa, Anna Z. Pollack, Neil J. Perkins, Brian W. Whitcomb, Aijun Ye, Jean Wactawski-Wende
Realignment And Multiple Imputation Of Longitudinal Data: An Application To Menstrual Cycle Data, Sunni L. Mumford, Enrique F. Schisterman, Audrey J. Gaskinsa, Anna Z. Pollack, Neil J. Perkins, Brian W. Whitcomb, Aijun Ye, Jean Wactawski-Wende
Brian W. Whitcomb
Reproductive hormone levels are highly variable among premenopausal women during the menstrual cycle. Accurate timing of hormone measurement is essential, especially when investigating day- or phase-specific effects. The BioCycle Study used daily urine home fertility monitors to help detect the luteinising hormone (LH) surge in order to schedule visits with biologically relevant windows of hormonal variability. However, as the LH surge is brief and cycles vary in length, relevant hormonal changes may not align with scheduled visits even when fertility monitors are used. Using monitor data, measurements were reclassified according to biological phase of the menstrual cycle to more accurate …