Patterns of dynamic malalignment, muscle activation, joint motion, and patellofemoral-pain syndrome
Context: Dynamic malalignment (DM), abnormal muscle activation, and static malalignments
all might lead to patellofemoral pain (PFP) but have not been examined using a
multifactorial approach. Objective: To determine which measures of static malalignment, DM,
and muscle-onset times best predict PFP. Design and Setting: Between-subjects, laboratory.
Subjects: 2 groups (PFP and uninjured) of 16 subjects each. Interventions: EMG and 3-D
kinematic data were recorded during a step-down. Five static-alignment assessments were …
all might lead to patellofemoral pain (PFP) but have not been examined using a
multifactorial approach. Objective: To determine which measures of static malalignment, DM,
and muscle-onset times best predict PFP. Design and Setting: Between-subjects, laboratory.
Subjects: 2 groups (PFP and uninjured) of 16 subjects each. Interventions: EMG and 3-D
kinematic data were recorded during a step-down. Five static-alignment assessments were …
Context
Dynamic malalignment (DM), abnormal muscle activation, and static malalignments all might lead to patellofemoral pain (PFP) but have not been examined using a multifactorial approach.
Objective
To determine which measures of static malalignment, DM, and muscle-onset times best predict PFP.
Design and Setting
Between-subjects, laboratory.
Subjects
2 groups (PFP and uninjured) of 16 subjects each.
Interventions
EMG and 3-D kinematic data were recorded during a step-down. Five static-alignment assessments were performed.
Measurements
Three discriminant analyses using injury as the grouping variable and static measures, joint angles, and EMG onsets as the predictor variables. A final combined discriminant analysis using the most predictive variables from each set.
Results
The static-alignment discriminant function was most predictive (81.3% correct), followed by the kinematic (69%) and the EMG (67%) functions. The final discriminant function included iliotibial-band flexibility, navicular drop, pronation, knee flexion, hip adduction, gluteus medius, and vastus medialis obliquus onset time and correctly classified 92.3% of PFP subjects.
Conclusions
PFP can most accurately be predicted when multiple measures of lower extremity function are considered together.
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