Douglas Wix PT, DPT, SCS, OCS, PES, CES, FMS What can I work

7/12/2014
Douglas Wix PT, DPT, SCS,
OCS, PES, CES, FMS
What can I work on now to minimize the risk of
me getting injured during my career?

Military: 2.4 million visits/$548 Million
High School: 2 million injuries per year
Under 14: 3.5 million MD visits
ACL Reconstruction: 200-250,000 ACL/$1.5
billon per year
Ankle sprains: 3.1 million 2002-2006

Increased incidence of ACL after
UCL Reconstruction: 12% increase from 2002 2010

ACL reconstruction
11.3 x more likely to tear the contra or ipsilateral
ACL within the first 12 months
4.4 x more likely to tear the contra or ipsilateral ACL
outside of 12 months

Clinical Sequela
Meniscus Tear
Chondral Lesion
Osteoarthritis

0-13% with ACL only
21-48% with ACL and meniscectomy
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7/12/2014

Reliability of the Functional Movement Screen has been
established between and within raters across multiple studies
examining the 21 point screen (Minick et al., 2010; Frohm et al.,
2011; Onate et al., 2012; Teyhen et al., 2012; Gribble et al., 2013;
Smith et al., 2013, Gulgin et al., 2014)

Normative values on the movement screen have been established
in active adult populations (Schnieders et al., 2011, Bhk et al., in
press, Perry et al., 2013, Teyhen et al., 2014)
20-40 year olds is approximately a 15

Validity of the Functional Movement
Screen as an injury screening tool has been
established through the use of an
evidenced based cut off score as well as
identifying the presence of an asymmetry
during the testing.(Kiesel et al., 2007,
O’Connor et al., 2011, Butler et al., in
press).
Three studies have reported that scores on
the Functional Movement Screen can be
improved with a 6 week training program
(Goss et al., 2009, Cowen et al., 2010, Kiesel
et al., 2010).
FMS & Cardiovascular Condition

Cardiovascular Conditioning
Lisman 2013: Functional movement screen
and aerobic fitness predict injuries in
military training.

Combining slow 3 mile RT and low FMS scores
(≤14) increased the predictive value across all
injury classifications: candidates scoring poorly on
both tests were 4.2 times more likely to experience
an injury. Functional movement screen and aerobic fitness predict injuries in military
59 college football players were measured on the
Lower Quarter Y Balance Test
The researchers found that those players who scored
below 89.6% composite reach on the YBT-LQ were
3.5 times more likely to get injured.

training. Lisman P, O'Connor FG, Deuster PA, Knapik JJ. Med Sci Sports Exerc. 2013 Apr;45(4):63643.

Y- balance and Neuromuscular Training

Plisky 2006

4cm difference right/left with anterior reach

Girls with a composite score less than 94%
Increase injury risk by 2.5 times
Increased injury risk by 6.5 times
J Orthop Sports Phys Ther. 2006 Dec;36(12):9119.Star Excursion Balance Test as a predictor of
lower extremity injury in high school basketball
players.Plisky PJ, Rauh MJ, Kaminski TW,
Underwood FB.
Dynamic Balance Performance and Noncontact
Lower Extremity Injury in College Football
Players.

Butler RJ , Lehr ME, Fink M, Kiesel KB, Plisky PJ. Dynamic Balance
Performance and Noncontact Lower Extremity Injury in College Football
Players. An initial study Sports Health. 2013
Lehr et al. 2011 in review
183 collegiate athletes
Tested with UE Y-balance, FMS and previous injury
report
63 athletes considerate moderate to severe risk
27 athletes were injured in this group (43%)
Result: 3.6 times more likely to get injured

Lehr ME, Plisky PJ, Kiesel KB, Butler RJ, Fink M, Underwood FB. Fieldexpedient screening and injury risk algorithm categories as predictors of
noncontact lower extremity injury.Scan J Med Sci Sport. 2013
2
7/12/2014
Is to determine whether injuries in
college athletes can be predicted using
a combination of the Functional
movement Screen and the Y-balance
testing.

Functional Movement
Screen
184 Athletes from the University
of South Carolina Upstate
Integrated the Functional
Movement Screen, Upper
Extremity and Lower Extremity Ybalance as part of their annual
physical
Approved by the Spartanburg
Regional Medical Center
Institutional Review Board
III – Able to complete task
II – Able to complete task with compensation
I – Unable to complete the task
0 – Pain during test (or clearing exam)
Max Score = 21 points
Lower & Upper
Extremity Y-balance
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7/12/2014

Descriptive Data
Performance Measure
Injuries
N
FMS Component Score
Age
(Years)
Total
184
19.1
Female
91
19
Male
93
19.2
Soccer M/F
30/23
19.3
Softball
10
20
Volleyball
12
19.3
Baseball
31
19.2
Tennis M/F
3/3
20.8
Track M/F
25/25
19.3
Golf
2
20.1
Basketball M/F
3/17
19.8
FMS Component Score
Test
0
1
2
3
Mean
Test
0
1
2
3
Mean
Trunk Stability Push-up
3
59
60
62
2.02
Soccer
4
40
225
102
2.17
Rotary Stability
9
4
171
0
1.97
Softball
0
9
45
16
2.1
Shoulder Mobility
3
15
50
116
2.56
Volleyball
4
16
47
17
2.01
Active Straight Leg Raise
3
16
88
77
2.33
Baseball
4
21
152
40
2.09
Deep Squat
3
63
105
13
1.72
Tennis
1
6
23
12
2.15
Hurdle Step
1
5
159
19
2.08
Track
3
55
193
99
2.13
In-line Lunge
0
6
139
39
2.18
Golf
0
1
8
5
2.29
Total
22
168
772
326
2.12
Basketball
6
20
79
35
2.11
Number
FMS
Avg.YBT_LU
Q
Avg. YBTRUQ
Avg.YBT_LL
Q
Avg.YBT_RL
Q
Total
184
14.34
94.04
94.90
89.44
90.09
Female
91
14.35
91.10
91.63
87.72
87.65
Male
93
14.24
96.91
98.10
91.13
92.47
Soccer
53
14.36
90.71
93.53
89.92
95.50
Softball
10
14.50
83.08
83.28
88.86
90.04
Volleyball
12
13.00
88.23
91.27
90.32
89.12
Baseball
31
13.87
97.36
97.85
91.87
Tennis
6
14.50
94.83
98.25
Track
50
14.73
91.32
91.34
Sport
Avg. FMS
Score
Injuries
FMS ≤ 15
FMS >15
Total
14.34
100
96
88
Female
14.35
55
41
50
Male
14.24
45
55
38
Soccer
14.36
25
27
26
Softball
14.50
1
5
5
91.95
Volleyball
13.00
6
8
4
95.57
90.98
Baseball
13.87
20
20
11
90.23
90.41
Tennis
14.50
4
4
2
Track
14.73
29
20
19
Golf
16.00
0
1
1
Basketball
13.56
3
8
12
Golf
2
16.00
81.10
86
91.65
100.10
Basketball
20
13.56
85.04
86.54
85.34
86.91
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7/12/2014
Injured
Not Injured

FMS: Not found to be predictive of injury
Sport
FMS ≤ 14
FMS ≥ 15
FMS ≤ 14
FMS ≥ 15
Total
49
51
47
37

Female
23
32
18
18

Male
26
19
29
19
Soccer
12
16
15
10
Softball
1
0
4
5
Volleyball
4
2
4
2
Baseball
14
6
6
5
Tennis
2
2
2
0
Track
11
14
9
5
Golf
0
0
1
1
Basketball
2
10
6
2
Sport
Avg.YBT_LUQ
Avg. YBT-RUQ
Avg.YBT_LLQ
Avg.YBT_RLQ
Group
Individual Sport
Injuries
Injured
Sport
Not Injured
YBT-LQ≤ 90% YBT-LQ≥ 90% YBT-LQ≤ 90% YBT-LQ≥ 90%
Total
94.04
94.90
89.44
90.09
100
Total
100
100
144
56
Female
91.10
91.63
87.72
87.65
55
Female
Male
96.91
98.10
91.13
92.47
45
43
67
66
44
Male
57
33
78
12
Soccer
90.71
93.53
89.92
95.50
25
Soccer
32
24
47
9
Softball
83.08
83.28
88.86
90.04
1
Softball
Volleyball
88.23
91.27
90.32
89.12
6
Volleyball
2
6
0
6
0
4
2
8
7
Baseball
97.36
97.85
91.87
91.95
20
Baseball
27
13
33
Tennis
94.83
98.25
95.57
90.98
4
Tennis
5
3
6
2
Track
91.32
91.34
90.23
90.41
29
Track
17
33
38
12
Golf
81.10
86
91.65
100.10
0
Golf
0
0
0
0
Basketball
85.04
86.54
85.34
86.91
3
Basketball
7
17
14
10
Injured
Not Injured
Sport
YBT-UQ≤ 90%
YBT-UQ≥ 90%
YBT-UQ≤ 90%
YBT-UQ≥ 90%
Total
89
79
109
59
Female
33
39
33
39
Male
56
40
76
20
Soccer
28
22
39
11
Softball
9
9
7
11
Volleyball
6
6
7
5
Baseball
10
12
19
3
Tennis
2
2
3
1
Track
11
17
19
9
Golf
4
0
0
4
Basketball
6
10
10
6

Upper Extremity Y-balance:

Lower Extremity Y-balance:

Upper and Lower extremity Y-balance:

FMS, Upper and Lower extremity Y-balance:

Not predictive
Not predictive
Not predictive
Not predictive
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7/12/2014

All screens found not to be predictive of injury
Potential limits of the Study
Video Analysis
Scoring criteria

Change Scoring System

Define Injury Criteria

Point system for each movement
Major verse Minor
Wide range for 2

Injury reporting
Recorded all injuries

FMS and Y-balance Screens
Great for looking at dynamic movement
Identifying asymmetries
Create a game plan for improving movement
patterns
Reduce acute and chronic injuries
Establish a baseline for post injury (Concussion)

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