Evaluation of an Algorithm to Predict Menstrual-Cycle Phase at the Time of Injury

Follicular phase of menstrual cycle is related to higher tendency to suffer from severe injuries among elite female futsal players

OBJECTIVE

To describe the injury incidence according to each phase of menstrual cycle (MC) in professional futsal players along two consecutive season and, secondly, to compare the injury incidence and frequency between different phases of the MC.

DESIGN

Prospective cohort study.

SETTINGS

Elite futsal players.

PARTICIPANTS

179 players.

MAIN OUTCOME MEASURE

Players were registered along two consecutive seasons.

RESULTS

191 injuries were reported throughout both seasons. The injury incidence was 30.63 days-off during the follicular phase, 23.6 during ovulatory phase and 17.59 days-off in luteal phase, showing higher incidence during the follicular phase. No statistical differences (p > 0.05) were reported for any variable comparing among the three phases of MC.

CONCLUSIONS

This study suggests the relevance to track the MC, but reduces its possible relationship or influence on the injury distribution during each phase of the MC. The knowledge of injury incidence, burden and etiology is a key factor to design injury prevention programs with the focus on the most common injuries, where MC could be included as a complementary factor.

Ovulation Induction for the General Gynecologist

The practice of ovulation induction often falls to the reproductive endocrinology and infertility specialist. However, attitudes toward the evaluation and treatment of infertility has shifted among general obstetrician-gynecologists (OB-GYN). This review discusses the underlying scientific basis of anovulation and clinical guidelines regarding the use of different medications for the purpose of promoting follicular recruitment and ovulation for the general OB-GYN.

Multivariate Analysis of the Risk Factors for First-Time Noncontact ACL Injury in High School and College Athletes: A Prospective Cohort Study With a Nested, Matched Case-Control Analysis

BACKGROUND

Multivariate analysis that identifies the combination of risk factors associated with anterior cruciate ligament (ACL) trauma is important because it provides insight into whether a variable has a direct causal effect on risk or an indirect effect that is mediated by other variables. It can also reveal risk factors that might not be evident in univariate analyses; if a variable's effect is moderated by other variables, its association with risk may be apparent only after adjustment for the other variables. Most important, multivariate analyses can identify combinations of risk factors that are more predictive of risk than individual risk factors.

HYPOTHESIS

A diverse combination of risk factors predispose athletes to first-time noncontact ACL injury, and these relationships are different for male and female athletes.

STUDY DESIGN

Case-control study; Level of evidence, 3.

METHODS

Athletes competing in organized sports at the high school and college levels participated in this study. Data from injured subjects (109 suffering an ACL injury) and matched controls (227 subjects) from the same athletic team were analyzed with multivariate conditional logistic regression to examine the effects of combinations of variables (demographic characteristics, joint laxity, lower extremity alignment, strength, and personality traits) on the risk of suffering their first ACL injury and to construct risk models.

RESULTS

For male athletes, increases in anterior-posterior displacement of the tibia relative to the femur (knee laxity), posterior knee stiffness, navicular drop, and a decrease in standing quadriceps angle were jointly predictive of suffering an ACL injury. For female athletes the combined effects of having a parent who had suffered an ACL injury and increases in anterior-posterior knee laxity and body mass index were predictive of ACL injury.

CONCLUSION

Multivariate models provided more information about ACL injury risk than individual risk factors. Both male and female risk models included increased anterior-posterior knee laxity as a predictor of ACL injury but were otherwise dissimilar.