OBJECTIVES: The aim of the current study was to evaluate the potential efficacy of a presurgical behavioral medicine evaluation (PBME) screening algorithm with patients undergoing evaluation for implantable pain management devices. METHODS: Sixty patients were evaluated for prognostic recommendations regarding outcomes from surgery for spinal cord stimulators and intrathecal pumps. Diagnostic interviews, review of medical charts, and psychosocial and functional measures were used in the initial evaluation. RESULTS: Patients were classified into one of four prognostic groups, from low to increasing risks: Green, Yellow-I, Yellow-II, and Red. The Green group showed the most positive biopsychosocial profile, while the Red groups showed the worst profiles. CONCLUSIONS: This preliminary study suggests that the PBME algorithm may be an effective method for categorizing patients into prognostic groups. Psychological and adverse clinical features appear to have the most power in the classification of such patients.
OBJECTIVES: The aim of the current study was to evaluate the potential efficacy of a presurgical behavioral medicine evaluation (PBME) screening algorithm with patients undergoing evaluation for implantable pain management devices. METHODS: Sixty patients were evaluated for prognostic recommendations regarding outcomes from surgery for spinal cord stimulators and intrathecal pumps. Diagnostic interviews, review of medical charts, and psychosocial and functional measures were used in the initial evaluation. RESULTS: Patients were classified into one of four prognostic groups, from low to increasing risks: Green, Yellow-I, Yellow-II, and Red. The Green group showed the most positive biopsychosocial profile, while the Red groups showed the worst profiles. CONCLUSIONS: This preliminary study suggests that the PBME algorithm may be an effective method for categorizing patients into prognostic groups. Psychological and adverse clinical features appear to have the most power in the classification of such patients.
Authors: M A Kemler; G A Barendse; M van Kleef; H C de Vet; C P Rijks; C A Furnée; F A van den Wildenberg Journal: N Engl J Med Date: 2000-08-31 Impact factor: 91.245
Authors: Laura L Adams; Robert J Gatchel; Richard C Robinson; Peter Polatin; Noor Gajraj; Martin Deschner; Carl Noe Journal: J Pain Symptom Manage Date: 2004-05 Impact factor: 3.612