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. 2019 Nov 22;11(6):1149–1162. doi: 10.1111/os.12577

Table 7.

Logistic regression analyses to identify PTOA as a predictor of clinical outcomes

Kellgren–Lawrence Coefficient Standard error Wald P OR 95% CI
Full model
ROM −0.16 0.10 2.86 0.0910 0.85 0.70 to 1.03
VAS −0.33 0.33 1.03 0.3108 0.72 0.38 to 1.37
AKSS −0.09 0.05 3.40 0.0651 0.91 0.82 to 1.01
KOOS ADL 0.15 0.07 4.74 0.0295 1.16 1.02 to 1.33
KOOS Pain −0.05 0.06 0.73 0.3920 0.95 0.85 to 1.07
KOOS QoL 0.00 0.03 0.00 0.9851 1.01 0.95 to 1.06
KOOS Sport Rec −0.01 0.02 0.57 0.4505 0.99 0.95 to 1.02
SF 36 MCS −0.01 0.04 0.02 0.8916 0.99 0.91 to 1.08
SF 36 PCS −0.07 0.06 1.32 0.2503 0.94 0.83 to 1.05
Constant 22.89 10.52 4.74 0.0295
Reduce model
AKSS −0.06 0.02 7.88 0.0050 0.94 0.90 to 0.98
Constant 5.13 1.86 7.63 0.0058

AKSS, American Knee Society score; KOOS, knee injury and osteoarthritis outcome score; ROM, range of motion in degrees; SD, standard deviation; SF‐36, 36‐Item Short Form Survey; VAS, visual analog score.