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. 2018 Dec 20;131(24):2960–2967. doi: 10.4103/0366-6999.247207

Table 2.

Binary logistic regression analysis of relationship of the factors with ACL injury (n = 250)

Variable Regression coefficient SD P OR 95% CI
Age (years) 0.730
 20–29 −0.903 2.148 0.674 0.405 0.006–27.292
 30–39 −1.484 2.081 0.476 0.227 0.004–13.405
 40–49 −1.442 2.097 0.492 0.236 0.004–14.418
 50–59 −1.775 2.124 0.403 0.169 0.003–10.896
 60–69 −0.356 2.288 0.876 0.700 0.008–62.022
Sex 0.389 0.389 0.317 1.476 0.689–3.160
Notch shape 0.867
 Notch shape M −0.230 0.432 0.595 0.794 0.340–1.854
 Notch shape U −0.110 0.745 0.883 0.896 0.208–3.857
Notch width index −35.42 7.890 <0.001 4.141E-16 7.960E-23–2.154E-9
Notch height index 0.882 1.006 0.380 2.416 0.337–17.342
α angle (°) −0.038 0.032 0.231 0.963 0.905–1.024
β angle (°) 0.425 0.079 <0.001 1.530 1.311–1.785
Medial tibial slope −0.026 0.095 0.787 0.975 0.809–1.175
Lateral tibial slope 0.352 0.086 <0.001 1.422 1.201–1.683

OR: Odds ratio; CI: Confidence interval; α angle: The notch angle; β angle: The angle formed by the Blumensaat line and the long axis of the femur; n = 250, including 125 injured patients and 125 controls; ACL: Anterior cruciate ligament; SD: Standard deviation.