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Table 2

Final multivariate pretreatment pain-prediction models and performance metricsa

Responders (N = 297/94)b Future pain intensity (N = 289/94)b
Independent variablesOR(95 % CI) P-valueβ(95 % CI) P-value
Dose (per 6 spinal manipulation visits)1.27(1.08, 1.49)0.004−1.86(−3.35, −0.38)0.014
 Pain intensity4.77(1.85, 7.70)0.001
 Pain unpleasantness3.29(0.35, 6.24)0.028
General Health
 Comorbidities0.81(0.67, 0.97)0.025
 EuroQol – VAS−2.20(−4.00, −0.39)0.017
 EuroQol 5D – self-care (1–3)0.64(0.41, 0.99)0.044
Objective Physical Exam
 LBP: sum for 4 lumbar ROM pain scores0.81(0.67, 0.97)0.0242.89(0.61, 5.16)0.013
Performance metricsc AUC(95 % CI)RMSE(95 % CI)R2 (95 % CI)
 Training set0.62417.4.268
 Test set0.479(0.387, 0.575)19.4(17.0, 21.6).065(−10.5, 21.9)
OR Odds ratio, PC part correlation, β regression coefficient, VAS visual analogue scale, AUC Area under the curve (receiver operating characteristic curve), RMSE root mean squared error (SD of prediction error), R 2 coefficient of determination, LBP low back pain

aVariables were selected into the regression models using forward selection among variables with p  < .05 in the univariate analysis; dose was forced into the models. Independent variables were standardized except for dose (scale unit = 6 visits) and self-care (scale unit = 1 on a 1–3 scale). Lower scores were favorable for pain and self-care; higher scores for EuroQol VAS

bThe first number is the sample size for the model in the training set and the second number is the N for the test set

cChance performance is indicated by 0.5 for AUC. RMSE is the standard deviation of the error in prediction of future pain intensity evaluated on the 0 – 100 pain scale. R 2 is the proportion of the variance in pain intensity explained by the independent variables in the model. Confidence intervals for the performance metrics are given for the test set only