Women are 2 to 8 times more likely to sustain an anterior cruciate ligament (ACL) injury than men, and previous studies indicated an increased risk for injury during the preovulatory phase of the menstrual cycle (MC). However, investigations of risk rely on retrospective classification of MC phase, and no tools for this have been validated.To evaluate the accuracy of an algorithm for retrospectively classifying MC phase at the time of a mock injury based on MC history and salivary progesterone (P4) concentration.Descriptive laboratory study.Research laboratory.Thirty-one healthy female collegiate athletes (age range, 18-24 years) provided serum or saliva (or both) samples at 8 visits over 1 complete MC.Self-reported MC information was obtained on a randomized date (1-45 days) after mock injury, which is the typical timeframe in which researchers have access to ACL-injured study participants. The MC phase was classified using the algorithm as applied in a stand-alone computational fashion and also by 4 clinical experts using the algorithm and additional subjective hormonal history information to help inform their decision. To assess algorithm accuracy, phase classifications were compared with the actual MC phase at the time of mock injury (ascertained using urinary luteinizing hormone tests and serial serum P4 samples). Clinical expert and computed classifications were compared using κ statistics.Fourteen participants (45

作者：Timothy W, Tourville；Sandra J, Shultz；Pamela M, Vacek；Emily J, Knudsen；Ira M, Bernstein；Kelly J, Tourville；Daniel M, Hardy；Robert J, Johnson；James R, Slauterbeck；Bruce D, Beynnon

来源：Journal of athletic training 2016 年 51卷 1期