functional movement screen and prior disclosures …ortho.emory.edu/documents/symposium 2016...
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Functional Movement Screen and Prior Injury in National Football League
Combine Athletes
Harris S. Slone, M.D., Spero G. Karas, M.D., Raj Shani, M.D., Megan East, M.A., L.A.T, O.T.C.,
William R. Barfield, Ph.D., Marty Lauzon AT-C, PT
Disclosures HS › Arthrex- Paid Instructor
SGK › DJO Surgical- Consultant, Royalties, Research Support, Institutional
Support › Arthrex- Consultant, Institutional Support, Research Support › Conmed Linvatec- Consultant, Institutional Support › Synthes- Research Support › Wright Medical- Consultant, Research Support › Ossur- Institutional Support › Smith Nephew- Institutional Support › Mimedx- Consultant
Others › None
Background: FMS
Functional Movement Screen (FMS) is an objective screening system intended to rank and categorize fundamental movement patterns and determine side-to-side asymmetries › Used in pre-participation physicals › Currently used at NFL combine › Used by some teams for objective return to play evaluation › Multiple studies have demonstrated good inter- and intrarater
reliability
Cook, NAJSPT 2006
FMS
Overhead Squat Hurdle Step
Active SLR
Trunk Stability
In-line Lunge Shoulder Mobility
Rotary Stability
Scored: 0-3 Total Possible Score: 21
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FMS and Injury Risk
In NFL Athletes › One NFL team for one season › Average FMS score = 16.9 › Difference in scores between those who were injured vs.
not injured (14.3 vs. 17.4) › Players with scores below 14 were >11x more likely to be
injured (placed on IR)
Kiesel, NAJSPT 2007
FMS and Injury Risk
In NFL Athletes › 238 scores obtained before training camp › Players with scores ≤14 were >1.8x more likely to be injured (any
time lost from practice or games) › Any asymmetry, regardless of total score, had 1.8 x greater risk of
injury › Combination of total FMS score ≤14 and ≥1 asymmetry was specific
(0.87) for injury
Kiesel J Sport Rehab 2014
FMS and Injury Risk
In Soldiers › Prospective study of over 2476 men (ages 18-57) › Soldiers who scored ≤ 14 were at higher risk of injury
compared to those with FMS > 14 › Concluded that poor FMS performance was associated with
injury risk, but with low sensitivity, specificity, and PPV › FMS use “not recommended” due to “miscalculation of injury
risk”
Bushman AJSM 2015
Background: Prior Injury
Previous history of injury has been shown in multiple studies as the most significant risk factor for future injury
Hagglund, Br J Sport Med, 2006; Van Mechelen, Med Sci Sport Exercise, 1996
Is there a relationship between previous injury
and FMS score?
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Purpose
The purpose of this study was to determine whether the results of the FMS performed at the NFL Combine were associated with a history of previous injury in the elite collegiate athlete.
Our Study
Retrospective review of 1293 combine participants from 2009-2013 Recorded demographic data, position, injury history, the need for surgery, and number of games missed due to injury
Our Study › By Injury Type
› Stinger › AC sprain › Mechanical low
back pain › Hamstring strain › Groin Strain › MCL sprain › Patellar Tendonitis › Lateral Ankle
Sprain › High Ankle Sprain › Turf Toe
› By Body Part › Neck › Shoulder › Forearm/Hand › Lumbar Spine › Hip/Pelvis › Knee/Leg › Ankle/Foot/
Lower leg
› By Surgery Type › ACL › Meniscus repair/
meniscectomy › Sports Hernia › Shoulder labral
repair › Ankle/Foot fx
ORIFs
Statistics A one-way analysis of variance was performed with Tukey post-hoc comparisons to compare FMS score and position. Chi-square was used for all categorical and dichotomous variable comparisons. › Also used previously established “cut-off” score of 14
Spearman correlation was also used to assess the relationship between FMS, number of asymmetries, number of games missed and number of injuries recorded. The a priori alpha level was established at p ≤0.05
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Results
Overall Injuries and FMS
Mean Range
Total FMS Score 13.8 ± 2.4 5-21
Total # of Injuries 3.5 ± 1.9 0-15
Games Missed 2.3 ± 3.6 0-24
Total # of Asymmetries 0.9 ± 0.9 0-4
Results
35 118
252 309
224 165
89 40 14 9 2 3 1 1 0 1 0
50
100
150
200
250
300
350
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
# of
Pla
yers
# of Injuries
Number of Injuries Reported Per Player
Results
46 88 111 136
178
0 20 40 60 80
100 120 140 160 180 200
Sports Hernia
ACL Tear Ankle or Foot
Fracture
Shoulder Labral Tear
Meniscal Tear
# of
Inju
ries
Injury Type
Number of Injuries Requiring Surgery
Results
64 86 89 130 134 168 221
315 376
474
0
50
100
150
200
250
300
350
400
450
500
Patella
r Ten
donit
is
Low B
ack P
ain
Groin S
train
High Ank
le Spra
in
Turf t
oe
Stinge
r
MCL Spra
in
AC Spra
in
Hamstr
ing S
train
Low Ank
le Apra
in
# of
Inju
ries
Injury Type
Number of Non-Surgical Injuries
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FMS by Position
Offensive and Defensive Linemen were significantly more likely to score lower on the FMS (p<0.001)
FMS Test Score By Position Position Number Mean OL 210 12.8 ± 2.5** DL 233 12.9 ± 2.6** LB 123 14.4 ± 2.3 DB 217 14.2 ± 2.4 RB 120 14.1 ± 2.1 WO 178 14.1 ± 2.1 QB 64 14.6 ± 2.4 TE 82 14.4 ± 2.1 ST 36 15.2 ± 1.9
0
5
10
15
20
25
0 2 4 6 8 10 12 14 16
Tota
l FM
S Sc
ore
# of Injuries
FMS vs. Injury History
Total FMS and # of Injuries
No significance
FMS – Total Score
No significance
FMS Score and Injuries/Games Missed FMS Injuries/Games Missed p-value Total FMS score Total # of Injuries 0.806
Total FMS Score Total # of Games Missed 0.714
FMS Score ≤ 14 vs > 14 Total # of Injuries 0.513 FMS Score ≤ 14 vs > 14 Total # of Games Missed 0.074
FMS Asymmetry
The # of FMS asymmetries was associated with total number of games missed
FMS Asymmetries and Injuries/Games Missed
FMS Injuries/Games Missed p-value
# of Asymmetries Total # of Injuries 0.362
# of Asymmetries Total # of Games Missed 0.002**
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Results: Summary
FMS Total Score › Offensive and defensive lineman were more likely to
score lower on the FMS (p<.001)
› No significant difference was seen between total FMS score and # of injuries (p=.806) or # of games missed due to injury (p=.714)
› FMS score did not correlate with # of games missed (r=.006; p=.845) or total # of injuries (r =-.008; p=.778)
Results: Summary
FMS Asymmetries › No significant difference between FMS asymmetries
and # of injuries (p=.362)
› A statistical relationship was noted between the # of asymmetries and # of games missed (p=.002) › Large range of games missed (0-24)
› The # of asymmetries did not correlate with games missed due to injury (r=.016; p=.574) or total # of injuries (r=.001; p=.982)
Limitations
Retrospective study Players may specifically “train” for the FMS prior to the NFL combine Injury history is based on collegiate medial records and volunteered information by the player The number of games missed due to injury may be dependent on the time of year at which the injury occurred
Conclusion The results of this study suggest that within elite athletes at the NFL Combine, no relationship exists between prior injury history and FMS score Caution should be exercised when attempting to evaluate an athlete’s FMS performance perceived to be reflective of past injury.
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Bibliography
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2. Cook G, Burton L, Hoogeboom B. Pre-Participation Screening: The Use of Fundamental Movements as an Assessment of Function – Part 2. N Am J Sports Phys Ther. 2006b; 1: 132-139.
3. Frohm A, Heijne A, Kowalski J, et. al. A nine-test screening battery for athletes: a reliability study. Scand J Med Sci Sports. 2012 Jun;22(3):306-15.
4. Onate JA, Dewey T, Kollock RO, et. al. Real-time intersession and interrater reliability of the functional movement screen. J Strength Cond Res. 2012 Feb;26(2):408-15.
5. Shultz R, Anderson SC, Matheson GO, et. al. Test-retest and interrater reliability of the functional movement screen. J Athl Train. 2013 May-Jun;48(3):331-6
6. Kiesel K, Plisky PJ, Voight M. Can serious injury in professional football be predicted by a preseason Functional Movement Screen? N Am J Sports Phys Ther. 2007; 2(3):76-81.
7. Kiesel KB, Butler RJ, Plisky PJ. Prediction of injury by limited and asymmetrical fundamental movement patterns in american football players. J Sport Rehabil. 2014 May;23(2):88-94.
8. Chorba RS, Chorba DJ, Bouillon LE, et. al. Use of a functional movement screening tool to determine injury risk in female collegiate athletes. N Am J Sports Phys Ther. 2010 Jun;5(2):47-54.
9. O'Connor FG, Deuster PA, Davis J, et. al. Functional movement screening: predicting injuries in officer candidates. Med Sci Sports Exerc. 2011 Dec;43(12):2224-30.
10. Hagglund M. Previous injury as a risk factor for injury in elite football: a prospective study over two consecutive seasons Br J Sports Med 2006;40:767–772
11. Van Mechelen W. Subject-related risk factors for sports injuries: a 1-yr prospective study in young adults. Medicine & Science in Sports & Exercise. 1996: 28(9): 1171-1179
12. Duncan MJ, Stanley M. Functional movement is negatively associated with weight status and positively associated with physical activity in British primary school children. J Obes. 2012.
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