Machine learning for patient selection in corticosteroid decision making in knee osteoarthritis: A feasibility model

Table 1 Baseline characteristics of patients included in final analysis

Characteristics	Frequency	Percentage
Age (year), mean ± SD	63.4 ± 8.3	-
Gender
Male	233	70.6%
Female	97	29.4%
Race
White/caucasian	263	79.7%
Black/afro-caribbean	59	17.9%
Other	8	2.4%
BMI (kg/m2), mean ± SD	32.3 ± 6.2	-
BMI < 30	147	44.5%
BMI ≥ 30	183	55.5%
Number of comorbidities, mean ± SD	0.7 ± 1.2	-
Comorbidities ≤ 3	317	96.1%
Comorbidities > 3	13	3.9%
KLG
KLG < 2	69	20.9%
KLG ≥ 2	261	79.1%
PASE, mean ± SD	163.1 ± 91.6	-
CESD, mean ± SD	9.7 ± 9.1	-
Past steroid use
No	118	35.8%
Yes	38	11.5%
Unknown	174	52.7%
WOMAC pain score, mean ± SD	5.2 ± 4.1	-
Non-significant change	246	74.5%
Significant change	84	25.5%

BMI: Body mass index; PASE: Physical activity scale for the elderly; CESD: Center for epidemiological studies depression; KLG: Kellgren Lawrence grade; WOMAC: Western Ontario and McMaster Universities Osteoarthritis.