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Table 3 Results of the binomial logistic regression models

From: Patient demographics and MRI-based measurements predict redundant nerve roots in lumbar spinal stenosis: a retrospective database cohort comparison

Model Independent variables included Negelkerke R2 Odds ratio (OR) [95% C.I.] p-value
1 Gender (Female) .00 1.26 [0.78 to 2.03] p = 0.3
2 Age(1) .02 1.06 [1.01 to 1.12] p = 0.01
3 Body height(2) .02 1.09 [1.01 to 1.16] p = 0.01
4 LLS(3) .16 1.36 [1.23 to 1.52] p < 0.001
5 SLLS(4) .13 1.34 [1.20 to 1.50] p < 0.001
6 rLLS(5) .17 2.26 [1.76 to 2.95] p < 0.001
7 rSLLS(6) .14 2.17 [1.63 to 2.90] p < 0.001
8 LSAD .01 1.08 [0.99 to 1.19] p = 0.07
9 LSS-level(7) .05 2.59 [1.48 to 4.55] p = 0.001
10 LSS-grade .11    p < 0.001
  grade C(8)   5.86 [1.30 to 26.42] p = 0.02
  grade D(9)   18.42 [3.82 to 88.8] p < 0.001
  1. OR for group membership in RNR+, LSS Lumbar Spinal Stenosis, LLS Length of Lumbar Spine
  2. (1)OR for a 2 years increase in patients age
  3. (2)OR for a 3 cm decrease in body height
  4. (3)OR for a 5 mm decrease in LLS
  5. (4)OR for a 5 mm decrease in SLLS
  6. (5)OR for a 1% decrease in rLLS
  7. (6)OR for a 1% decrease in rSLLS
  8. (7)OR for patients classified as LSS-level 2 + 3; reference were patients classified as LSS-level 1
  9. (8)OR for patients classified as LSS-grade C; reference were patients classified as LSS-grade A + B
  10. (9)OR for patients classified as LSS-grade D, reference were patients classified as LSS-grade A + B