Table 6.
Logistic regression analyses to identify alignment as predictor of clinical outcomes
| Alignment | Coefficient | Std. Error | Wald | P | OR | 95% CI |
|---|---|---|---|---|---|---|
| Full model | ||||||
| VAS | −0.08 | 0.23 | 0.12 | 0.7273 | 0.92 | 0.59 to 1.44 |
| AKSS | −0.02 | 0.04 | 0.22 | 0.6372 | 0.98 | 0.91 to 1.06 |
| KOOS Pain | 0.05 | 0.04 | 1.36 | 0.2428 | 1.05 | 0.97 to 1.13 |
| KOOS Symptom | 0.01 | 0.02 | 0.38 | 0.5357 | 1.01 | 0.97 to 1.06 |
| KOOS QoL | 0.00 | 0.02 | 0.02 | 0.8994 | 1.00 | 0.96 to 1.04 |
| KOOS Sport Rec | 0.00 | 0.01 | 0.00 | 0.9487 | 1.00 | 0.97 to 1.03 |
| Constant | −2.77 | 3.49 | 0.63 | 0.4276 | ||
| Reduced model | ||||||
| KOOS Pain | 0.05 | 0.02 | 5.43 | 0.0198 | 1.05 | 1.01 to 1.10 |
| Constant | −3.75 | 1.81 | 4.28 | 0.0385 | ||
AKSS, American Knee Society Score; KOOS, Knee injury and Osteoarthritis Outcome Score; ROM, range of motion in degrees; SD, standard deviation; VAS, visual analog score; SF‐36, 36‐Item Short Form Survey.