Table 5.

Results of the multivariate ordinal logistic regression analysis

Covariable	Odds ratio	95% confidence interval	P value
No change and deterioration versus improvement
Age (continuous, per decade)	1.33	1.07–1.68	0.01
Body weight (continuous, per 10 kg)	0.85	0.63–1.15	0.29
Presence of meniscal lesion on initial MRI	0.30	0.12–0.72	0.01
Presence of total ACL rupture on initial MRI	2.35	1.14–4.82	0.02
Location in posterior horn medial meniscus	0.74	0.16–3.46	0.70
Deterioration versus no change and improvement
Age (continuous, per decade)	1.33	1.07–1.68	0.01
Body weight (continuous, per 10 kg)	1.22	1.01–1.49	0.04
Presence of meniscal lesion on initial MRI	0.30	0.12–0.72	0.01
Presence of total ACL rupture on initial MRI	2.35	1.14–4.82	0.02
Location in posterior horn medial meniscus	2.98	1.20–7.40	0.02

For each independent variable, we first evaluated the applicability of the proportional odds assumption by using Gologit2’s ‘autofit’ option and subsequently specified per variable whether or not the proportional odds assumption was to be applied. This resulted in a partial proportional odds model, with two identical regression coefficients for variables meeting the proportional odds assumption and two different coefficients for those that violated the assumption