Sex-based Differences in Common Sports Injuries

Carter, Cordelia W.; Ireland, Mary Lloyd; Johnson, Anthony; Levine, William N.; Martin, Scott D.; Bedi, Asheesh; Matzkin, Elizabeth G.

doi:10.5435/jaaos-d-16-00607

Cited by 35 publications

(38 citation statements)

References 58 publications

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“…Gender imbalance within the IKD group (59 males vs 19 females) may also have affected our results. Given that females have an increased relative risk of ACL rupture in non-contact injuries, [22] likely due to an increased TT-TG distance as compared to their male counterparts, it is possible that our data underestimates the true IKD range. In the control group, this was not an issue as gender was equally balanced (34 males and 29 females).…”

Section: Discussionmentioning

confidence: 88%

The relationship between patellar lateralization diagnostic imaging markers and non-contact internal knee derangements

Stumetz¹,

Gothard

Walser³

et al. 2020

J Orthop Surg Res

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Background: To investigate differences in the tibial tubercle-trochlear groove (TT-TG) and patellar tendon-posterior cruciate ligament (PT-PCL) distances in symptomatic patients with non-contact internal knee derangements (IKD) and symptomatic patients with internally intact knees (control). Methods: A retrospective review of MRI studies was completed by comparing 78 patients with meniscal and ligamentous derangements of the knee to 63 internally intact knees (age range, 13 to 50 years). MRI findings were reviewed independently by two board-certified radiologists to assess for agreement. TT-TG and PT-PCL distances were measured on proton density-weighted axial images by two independent observers blinded to the MRI and arthroscopic findings. Independent t tests were used to determine differences in TT-TG distance between the internal derangement and control groups. Chi-square tests were used to compare categorical variables for distributional equality between study groups. Results: The mean TT-TG distance averaged across the two raters in the IKD group was 11.5 mm (95% confidence interval [CI], 10.6-12.4), compared to 8.3 mm (95% CI, 7.6-9.0) in the control group (p < 0.001). The mean PT-PCL distance similarly averaged across both raters was 20.6 mm (95% CI, 19.7-21.5) for the IKD group compared to 18.2 mm (95% CI, 17.2-19.2) for the control group (p < 0.001). Among the IKD group, there were 51 meniscal tears, 12 cruciate ligament tears, and 15 tears with a combination of meniscal and cruciate findings. IKD was significantly correlated with greater TT-TG distance (p < 0.001) and greater PT-PCL distance (p < 0.003) when compared with control. Conclusions: Increased TT-TG distances and PT-PCL distances are associated with both cartilaginous and ligamentous internal knee injuries in the present study, with TT-TG distances greater than the 12 mm representing a new threshold for concern.

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Section: Discussionmentioning

confidence: 88%

The relationship between patellar lateralization diagnostic imaging markers and non-contact internal knee derangements

Stumetz¹,

Gothard

Walser³

et al. 2020

J Orthop Surg Res

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show abstract

“…Impaired glucose and lipid metabolism in addition to energy balance and body fat distribution have a significant impact on overall health and can have a greater effect on women than on men [42]. Also, the general statics and body weight/muscle ratio are important factors for women's high risk of injury [43].…”

Section: Injuries During Training and Weight Lossmentioning

confidence: 99%

Injuries and Rapid Weight Loss in Elite Adolescent Taekwondo Athletes: A Korean Prospective Cohort Study

Kim

Park

2020

Physikalische Medizin, Rehabilitationsmedizin, Kurortmedizin

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Objectives To report injury patterns associated with training activities of elite adolescent Taekwondo athletes who are expected to represent South Korea in the future. Methods Beginning in 2019, we prospectively collected data on elite adolescent Taekwondo athletes at the Korean Training Center. The athletes were assessed by sports medicine doctors, and data were stratified according to sex, weight class, injury location, injuries during the weight loss period, and weight loss method. We used χ2 tests were used to compare groups. Injury rates were expressed as Poisson rates with 95% confidence intervals. Results There were 117 male and 102 female elite adolescent Taekwondo athletes. The mean weight loss among athletes was 3.37 (±1.23) kg, and the mean duration of weight loss was 7.53 (±3.40) days. In general, all athletes used similar weight loss methods. We recorded 846 injuries (annual average, 3.98 injuries/athlete). In general, female athletes had higher injury rates than their male counterparts. Additionally, the athletes had significantly higher injury rates during weight loss periods than during other periods of training. When all athletes were considered, most injuries occurred in the lower extremities (63.2%), followed by the trunk (14.2%), upper extremities (16.3%), and the head and neck area (6.3%). The injury severity significantly influenced the body regions in weight categories. Conclusion Rapid weight loss is related to the incidence of sports damage in athletes. Most injuries occur during weight loss periods in South Korean elite adolescent Taekwondo athletes. Moreover, the injury rate and injury severity depends on weight class.

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“…The brain-computer interface [24] does not need to rely on the composition of muscles and peripheral nerves of the brain, and can communicate with the outside world or control external devices through brain thinking. It is a multi-field interdisciplinary [25] involving neuroscience, computer science, signal processing and other disciplines. BCI provides a way for people to interact with external devices.…”

Section: Introductionmentioning

confidence: 99%

Security Analysis of Sports Injury Medical System Based on Internet of Health Things Technology

Xia

Yun-xiang

2020

IEEE Access

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In the absence of physical movement, the dynamic process of rehearsing specific actions in the mind based on memory is called motor imagination (MI). Motor imaging brain-computer interface (BCI) refers to communicating with a computer or controlling external devices by imagining specific movements in the brain, while the Internet of health things technology helps to convey the rehabilitation of the limbs of patients with paralysis and stroke in time. Studies have shown that with the increase of motor imaging tasks, the classification accuracy rate will also decrease. It is necessary to study the construction and security of sports injury rehabilitation systems under the Internet of health things. Based on the study of the feature extraction algorithm, this paper starts with the infusion monitoring in the clinical medical care work, and through the construction of the Internet of health things smart care management system. It could provide application modules such as "infusion monitoring", "disease call interconnection", and "PDA interconnection" to realize the closed-loop path management of the whole process of basic nursing work in the ward. The sports rehabilitation training system receives the EEG data collected by the UE-16B EEG amplifier through the socket, and calls MATLAB to perform feature extraction and classification of the EEG data, and feedback the processing results to the sports rehabilitation training system and subjects. On this basis, the system has designed and completed a non-feedback training module, a feedback training module and related BCI game modules to promote users to perform sports imagination training and successfully complete sports rehabilitation training.

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Sex-based Differences in Common Sports Injuries

Cited by 35 publications

References 58 publications

The relationship between patellar lateralization diagnostic imaging markers and non-contact internal knee derangements

The relationship between patellar lateralization diagnostic imaging markers and non-contact internal knee derangements

Injuries and Rapid Weight Loss in Elite Adolescent Taekwondo Athletes: A Korean Prospective Cohort Study

Security Analysis of Sports Injury Medical System Based on Internet of Health Things Technology

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