Rebecca Avrin Zifchock1, Yatin Kirane, Howard Hillstrom. 1. Leon Root, MD Motion Analysis Laboratory, Department of Rehabilitation, Hospital for Special Surgery, 535 East 70th Street, New York, NY 10021, USA.
Abstract
BACKGROUND: Although the severity of knee osteoarthritis (OA) usually is assessed using different measures of joint structure, function, and pain, the relationships between these measures are unclear. PURPOSE: Therefore, we: (1) examined the relationships between the measures of knee structure (flexion-extension range of motion, radiographic tibiofemoral angle, and medial joint space), function (Knee Osteoarthritis Outcome Scores [KOOS], peak adduction angle, and moment), and pain (visual analog scale [VAS]); and (2) identified variables that best predicted knee pain. METHODS: We assessed 15 patients with medial knee OA using VAS pain, KOOS questionnaire, 3-D gait analysis, and radiographic examination. Parameter relationships were assessed using Pearson correlation, and variables most predictive of knee pain were determined using a stepwise multiple regression. RESULTS: Subjective measurements correlated (|r| ≥ 0.54) with one another, as did most of the objective measurements (|r| ≥ 0.56) except for adduction moment which did not correlate with any variable. All variables correlated (|r| > 0.54) with VAS knee pain except peak adduction moment. Medial joint space and peak adduction angle best predicted knee pain, accounting for approximately three-quarters of the model variance (r(2) = 0.73). CONCLUSIONS: Medial joint space and peak adduction angle may be useful for predicting knee pain in patients with medial knee OA. Therapies that target these structural and functional variables may reduce knee pain in this population. CLINICAL RELEVANCE: Increasing the medial joint space and limiting the peak knee adduction angle may be critical in achieving effective pain relief in patients with varus knee OA.
BACKGROUND: Although the severity of knee osteoarthritis (OA) usually is assessed using different measures of joint structure, function, and pain, the relationships between these measures are unclear. PURPOSE: Therefore, we: (1) examined the relationships between the measures of knee structure (flexion-extension range of motion, radiographic tibiofemoral angle, and medial joint space), function (Knee Osteoarthritis Outcome Scores [KOOS], peak adduction angle, and moment), and pain (visual analog scale [VAS]); and (2) identified variables that best predicted knee pain. METHODS: We assessed 15 patients with medial knee OA using VAS pain, KOOS questionnaire, 3-D gait analysis, and radiographic examination. Parameter relationships were assessed using Pearson correlation, and variables most predictive of knee pain were determined using a stepwise multiple regression. RESULTS: Subjective measurements correlated (|r| ≥ 0.54) with one another, as did most of the objective measurements (|r| ≥ 0.56) except for adduction moment which did not correlate with any variable. All variables correlated (|r| > 0.54) with VAS knee pain except peak adduction moment. Medial joint space and peak adduction angle best predicted knee pain, accounting for approximately three-quarters of the model variance (r(2) = 0.73). CONCLUSIONS: Medial joint space and peak adduction angle may be useful for predicting knee pain in patients with medial knee OA. Therapies that target these structural and functional variables may reduce knee pain in this population. CLINICAL RELEVANCE: Increasing the medial joint space and limiting the peak knee adduction angle may be critical in achieving effective pain relief in patients with varus knee OA.
Authors: W Zhang; G Nuki; R W Moskowitz; S Abramson; R D Altman; N K Arden; S Bierma-Zeinstra; K D Brandt; P Croft; M Doherty; M Dougados; M Hochberg; D J Hunter; K Kwoh; L S Lohmander; P Tugwell Journal: Osteoarthritis Cartilage Date: 2010-02-11 Impact factor: 6.576
Authors: Andrew J Meyer; Darryl D D'Lima; Thor F Besier; David G Lloyd; Clifford W Colwell; Benjamin J Fregly Journal: J Orthop Res Date: 2012-12-31 Impact factor: 3.494