The Medical Meathead
Performance and Prevention
The intersection between injury prevention and performance has unsurprisingly become a major part of my clinical practice. My latest project has been to collect pre and post-season vertical leap, speed/agility/quickness (SAQ) and Functional Movement Screen (FMS) data for our volleyball team. Coupled with last years basketball project and my patient case records regarding injury type, prevalence, and time loss, these data have, among other things, allowed me to draw some inferences regarding my methods as a strength and conditioning coach, how these methods might affect my patient-athletes performance, and if there is any reasonable effect with regard to injury prevention. The movement heirarchy and some of the ideas behind our strength and conditioning programming were outlined previously in a blog titled: Athletic Trainer.... What IS in a name? A preliminary analysis of the volleyball data suggests that our dead lift and kettlebell swing based posterior chain focused training program has been successful in not only limiting incidence of time loss injury but also significantly increasing sport specific performance metrics.
Pre-season descriptive statistics: n=18
mean Age = 189.61mo ± 12.61mo
mean Height = 65.20in ± 2.37in
mean Weight = 139.11lbs ± 29.94lbs
mean BMI = 22.71 ± 5.22
Paired Sample T-Test Correlation: n=18
Weight = .948; p=.000
BMI = .947; p=.000
FMS Composite = .724; p=.001
SAQ = .687; p=.002
Vert = .537; p=.022
Paired Sample T-Test: n=18
mean change Weight = -2.97lbs ± 9.72lbs; p = .210; d = .30
mean change BMI = -.49 ± 1.72; p = .234; d = .29
mean change FMS Composite = .78 ± 1.31; p = .022. d = .59
mean change SAQ = -.54sec ± .43sec; p = .000; d = 1.26
mean change Vert = 1.21in ± 2.32; p = .041; d = .52
It is likely that more robust statistical analysis will reveal more information regarding these changes, however, I have only just finished data collection. A more in depth look at FMS individual task scores regarding changes in asymmetry on paired movements in the FMS and alterations to scores of 1 will likely be done in the future.
Injury Prevalence
As fall sports come to an end, and I reflect on my patient care over the course of the season, I am pleased to announce that our injury reports are rather unremarkable regarding non concussion related time loss injury.
Volleyball: 2018
Patient 001:Missed 7 days with lateral ankle sprain and physician diagnosed avulsion fracture. Immobilized for 3 days. Began using cycle ergometer on day 4. Was treated with modified Mulligan LAS, Fibular Repositioning Tape application, and A-P Talus joint mobilizations beginning on day 6-10. Returned to practice on day 7. Discharged from care on day 14.
Patient 002: Season ending patellar dislocation. When rehabilitation was scheduled to begin the patient was out of town. Upon her return she suffered a concussion. When RTP was scheduled to begin the patient was out of town. It should be noted that this patient had the lowest FMS score (10) and 2nd highest BMI (30) and was excluded from the above analysis due to the inability to collect post season data.
Football: 2018
Patient 003: Missed first 4 weeks of season with back spasms related to a motorcycle accident. This patients case was referred due to the traumatic nautre of the MOI. Symptoms spontaneously cleared after use of prednisone for strep related tonsilitis.
Cross Country 2018:
Patient 004: Modified practice for 2 weeks due to suspected trochanteric bursitis. Finished the season successfully.
Lessons Learned
While the information presented above is interesting and represents increased performance and low injury and time loss prevalence, there is still much to learn from this type of data collection. For example, over two seasons of data collection I have found almost no change in the trunk stability push-up portion of the FMS, particularly among female participants, as they are fairly consistently at the lowest score pre and post season. New information = change = growth. It is time for more experimentation.