Role of the Functional Movement Screen in the Evaluation of Neuromuscular Deficits Associated with Chronic Ankle Instability
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Context: In the United States, lateral ankle sprains account for an annual healthcare cost that has been estimated at $3.8 billion. The term “chronic ankle instability” (CAI) is used to identify insufficiencies in the ankle following an ankle sprain as well as recurring ankle sprains or “giving way”. Chronic ankle instability has been observed in 54% to 72% of first-time ankle sprain patients. The risk factors for developing CAI are not well understood. Previous research identified CAI risk factors such as diminished postural control, decreased range of motion (ROM), increased ligament laxity, muscle weakness, delayed neuromuscular reaction, and decreased functional ability. Objective: To determine the extent to which the Functional Movement ScreenTM (FMS) is an effective tool for discriminating between healthy individuals and patients with CAI with neuromuscular deficits. A secondary aim was to identify risk factors that predispose individuals to CAI. Design: Case-Control. Setting: Laboratory setting. Participants or Other Patients: 60 physically active individuals (age range, 18-35 yrs; mean age, 21.9 + 3.11 yrs) participated in this study. Of our 60 participants, 20 met our operational definition of having CAI. Interventions: We employed a 2:1 ratio of persons without a previous history of ankle injury to those with CAI, and triple matched them on sex, age (+ 5 years) and BMI category (underweight, normal, overweight, obese). Main Outcome Measure(s): Foot and Ankle Disability Index (FADI-Sport), Overall FMS Score, Lower Extremity (LE) and Core Stabilization FMS sub-scores, ankle plantar flexion and dorsiflexion active range of motion (AROM), subtalar eversion and inversion AROM, Y-Balance Test, Athlete Single Leg Stability Test (ASLST). Statistical Analyses: A Group (2) x Limb (2) ANOVA approach was used to identify differences on 8 outcome measures between the Case and Control groups, and the involved/uninvolved limbs of the participants with CAI ( < 0.05). To investigate the extent to which the risk factors played a role in increasing risk for CAI, we calculated odds ratios using conditional logistic regression in an effort to identify independent risk factors for chronic ankle instability. We used paired t-tests to differentiate possible risk factors between involved and uninvolved sides. Results: The FADI-S scores were significantly different between the case and control groups (F = 43.4, p = 0.001, η 2 = 0.428). The average score for the case group for the FADI-S (78.3 + 17.9) was significantly less than the mean score for the control group (97.8 + 4.3). While the overall logistic regression analysis result was statistically significant (p = 0.001), none of the 5 variables was a significant predictor of the risk of developing CAI. Conclusion: The FMS did not identify risk pertaining to this specific injury, but for injury risk overall. The FADI-S may assist in determining risk for CAI. Future studies should be prospective in nature, involve larger sample sizes, and employ multifactorial statistical approaches (MANOVA) in effort to identify risk factors for developing chronic ankle instability.