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Background: A comprehensive understanding of the intrinsic risk factors for anterior cruciate ligament (ACL) disruption is important for identifying individuals at increased risk for suffering this trauma and developing interventions to mitigate risk.Hypothesis: A variety of risk factors predispose athletes to first-time, noncontact ACL injury and some of these differ between male and female athletes.Study Design: Prospective cohort study with nested case-control sampling.Level of Evidence: Level 2.Methods: Sport teams at 28 high schools and 8 colleges were monitored prospectively over 4 years, and 109 of 130 athletes who suffered their first noncontact ACL injury participated in the study. At the time of injury, matched control subjects were randomly selected from among the case’s teammates and a total of 227 athletes participated. Demographic characteristics, joint laxity, lower extremity alignment, strength, and personality characteristics were measured. The association of each risk factor with injury risk was assessed by conditional logistic regression.Results: The risk factors that were associated with ACL injury in both male and female athletes included having a parent with prior ACL injury and increases of the following variables: body weight, anterior displacement of the tibia relative to the femur, genu recurvatum, and generalized joint laxity. Risk factors that are unique to female athletes included increased body mass index, increased trunk flexion strength, and prior non-ACL knee injury. The risk factors specific to male athletes were decreased standing quadriceps angle, decreased hip adduction strength, and chronic disease.Conclusion: A diverse set of risk factors predispose both male and female athletes to ACL injury, whereas others appear to be sex-specific.Clinical Relevance: Different approaches for assessing risk and preventing ACL injury are needed for male and female athletes. In addition, personalized prevention strategies may be needed to target the specific characteristics that place an individual at increased risk of suffering this trauma.

Quantitative magnetic resonance imaging (qMRI) parameters such as T1ρ and T2* characterize changes in cartilage matrix composition prior to cartilage loss. However, T1ρ and T2* measurement reliability in phantoms that mimic in vivo knee size and position within the scanner bore (left or right side of isocenter) is unknown. This study aimed to quantify sources of variance, and the systematic differences between left and right positions in T1ρ and T2* in small vials of a commercially available phantom and a knee-sized phantom.

Background: Static and dynamic exercises are performed before activity to decrease injury risk and increase performance. Although evidence supports using dynamic over static stretching and performing Fédération Internationale de Football Association (FIFA) 11+ as a dynamic prepractice routine, we do not know the frequency at which these exercises are utilized in high school populations.Hypothesis: We hypothesize that there is a wide variety of preparticipation exercises performed by high school athletes, and that few high school teams perform FIFA 11+ as an injury prevention program in its entirety.Study Design: Observational study.Level of Evidence: Level 4.Methods: High school prepractice routines were observed for 185 teams (football, soccer, basketball, and lacrosse) over 1 season. The percentages of team warm-up routines that included components of FIFA 11+ were calculated, and the chi-square test was used to compare sex, sport, and level of competition.Results: Of a total 644 warm-up observations, 450 (69.9%) included only non–FIFA 11+ exercises, 56 (8.7%) included at least 1 FIFA 11+ exercise, and 38 (5.9%) included only jogging; 69 (10.6%) consisted only of sport-specific activities. The type of warm-up differed significantly between males and females (P= 0.002), sports (P< 0.001), and level of competition (P< 0.001). Static stretching and athletes stretching on their own were observed in 14% and 15% of all observations. No team performed the FIFA 11+ injury prevention routine in its entirety.Conclusion: The type of warm-up differed by sex, sport, and level of competition. Static stretching was performed more frequently than anticipated, and an entire FIFA 11+ warm-up was never performed.Clinical Relevance: We need to identify the exercises that decrease injury and increase performance and better inform the athletic population about the risks and benefits of static and dynamic warm-up programs.

Objective: To provide athletic trainers with a fundamental understanding of the pathogenesis and risk factors associated with the development of posttraumatic osteoarthritis (PTOA) as well as the best current recommendations for preventing and managing this condition.Background: Posttraumatic osteoarthritis, or osteoarthritis that develops secondary to joint injury, accounts for approximately 5.5 million US cases annually. A young athlete with a joint injury is at high risk for PTOA before the age of 40, which could lead to the patient living more than half of his or her life with a painful and disabling disorder. Given our frequent contact with physically active people who often sustain traumatic joint injuries, athletic trainers are in a unique position to help prevent and manage PTOA. We can, therefore, regularly monitor joint health in at-risk patients and implement early therapies as necessary.Recommendations: The recommendations for preventing and managing PTOA are based on the best available evidence. Primary injury prevention, self-management strategies, maintenance of a healthy body weight, and an appropriate level of physical activity should be encouraged among those at risk for PTOA after acute traumatic joint injury. Education of athletic trainers and patients regarding PTOA is also critical for effective prevention and management of this disease.

Objective.To assess the association between change in walking speed over a 12-month period and risk of developing radiographic knee osteoarthritis (rKOA) over a 24-month period.Methods.We included participants without rKOA from the Osteoarthritis Initiative. Change in walking speed was determined from a 20-m walk assessment, calculated using walking speed at 12-month followup minus baseline speed and/or 24-month followup walking speed minus 12-month speed. Incident rKOA was defined as progressing to Kellgren-Lawrence arthritis grading scale ≥ 2 within 24 months (i.e., incidence between 12 and 36 mos or 24 and 48 mos). Self-reported significant knee injury during the exposure period, age, body mass index (BMI), and Physical Activity Scale for the Elderly (PASE) score were adjusted for analytically.Results.We included 2638 observations among 1460 unique participants (58% women; aged 59 ± 9 yrs, range 45–79). The mean change in walking speed over 12 months was 0.001 ± 0.13 m/s (range −0.6271 to 1.4968). About 5% of the sample (n = 122) developed rKOA over a 24-month period. After controlling for significant knee injury, age, BMI, and PASE score, we found an 8% relative increase in risk of developing rKOA for every 0.1 m/s decrease in walking speed over a 12-month period (risk ratio 1.08, 95% CI 1.00–1.15, p = 0.05).Conclusion.Evaluating change in speed over a 12-month period using a 20-m walk test may be useful in identifying individuals at increased risk of developing rKOA over the subsequent 24 months. Identification of patients at high risk for developing rKOA would allow medical providers to implement early interventions to maximize joint health.

Context: 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.Objective: 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.Design: Descriptive laboratory study.Setting: Research laboratory.Participants: 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.Main Outcome Measure(s): 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.Results: Fourteen participants (45) experienced anovulatory cycles. The algorithm correctly classified MC phase for 23 participants (74): 22 (76) of 29 who were preovulatory/anovulatory and 1 (50) of 2 who were postovulatory. Agreement between expert and algorithm classifications ranged from 80.6 (κ 0.50) to 93 (κ 0.83). Classifications based on same-day saliva sample and optimal P4 threshold were the same as those based on MC history alone (87.1 correct). Algorithm accuracy varied during the MC but at no time were both sensitivity and specificity levels acceptable.Conclusions: These findings raise concerns about the accuracy of previous retrospective MC-phase classification systems, particularly in a population with a high occurrence of anovulatory cycles.