Abstract
The variables identified as predictors of surgical outcome often differ depending on the specific outcome variable chosen to designate "success". A short set of multidimensional core outcome measures was recently developed, in which each of the following domains was addressed with a single question and then combined in an index: pain, function, symptom-specific well-being, general well-being (quality of life), disability (work and social). The present study examined the factors that predicted surgical outcome as measured using the multidimensional core measures. 163 spinal surgery patients (mixed indications) completed questionnaires before and 6 months after surgery enquiring about demographics, medical/clinical history, fear-avoidance beliefs (FABQ), depression (Zung self-rated depression), and the core measures domains. Multiple regression analyses were used to identify predictor variables for each core domain and for the multidimensional combined core-set index. The combination of baseline symptoms, medical variables (pain duration, previous spine operations, number of levels treated, operative procedure) and psychosocial factors (FABQ and Zung depression) explained 34% of the variance in the core measures index (P < 0.001). With regard to the individual domain items, the medical variables were better in predicting the items "pain" and "symptom-specific well-being" (R (2) = 6-7%) than in predicting "function", "general well-being" or "disability" (each R (2) < 4%). The inverse pattern was shown for the psychosocial predictors, which accounted for in each case approximately 20% variance in "function", "general well-being" and "disability" but only 12-14% variance in "pain" and "symptom-specific well-being". Further to previous studies establishing the sensitivity to change of the core-set, we have shown that a large proportion of the variance in its scores after surgery could be predicted by "well-known" medical and psychosocial predictor variables. This substantiates the recommendation for its further use in registry systems, quality management projects, and clinical trials.