Table 5.
Multivariate logistic regression model by glenoid type based on Walch classificationa
| Variable | ||||||
| B1 | B2 | B3 | ||||
| OR (95% CI) | p value | OR (95% CI) | p value | OR (95% CI) | p value | |
| Ageb | 0.96 (0.90-1.03) | 0.27 | 0.93 (0.86-1.01) | 0.08 | 0.93 (0.86-1.02) | 0.12 |
| Sex (men) | 0.83 (0.23-3.01) | 0.78 | 4.47 (1.11-18.01) | 0.04 | 12.17 (2.40-61.65) | 0.003 |
| Fatty infiltrationc | ||||||
| Supraspinatus | 1.62 (0.44-5.78) | 0.47 | 1.20 (0.32-4.58) | 0.79 | 2.47 (0.53-11.44) | 0.25 |
| Infraspinatus | 3.31 (0.33-33.37) | 0.31 | 66.1 (7.55-577.88) | < 0.001 | 59.53 (5.36-661.31) | < 0.001 |
| Teres minor | 0.08 (0.01-1.00) | 0.05 | 2.04 (0.35-11.80) | 0.42 | 2.96 (0.46-19.23) | 0.26 |
| Subscapularis | 2.18 (0.23-17.07) | 0.46 | 0.17 (0.02-1.61) | 0.12 | 0.20 (0.02-2.24) | 0.19 |
a
Walch Type B glenoids were compared with Type A glenoids as the reference group.
b
Age was analyzed as a continuous variable, with presented odds ratios representing the change in odds per year.
c
For each of the four rotator cuff muscles, odds ratios represent the increase in odds for the specified Walch type with each increasing grade of fatty infiltration according to the Goutallier classification.