Physical, psychological, and social outcomes all improved in a significant proportion of participants following the IPM. High baseline depression was a clinically reliable predictor of individual-level improvement. Individuals with nociceptive pain and those who were older, respectively, showed the largest response across multiple outcomes and domains.
Background: Multidisciplinary pain management programmes (MPMPs) are widely used to treat chronic pain, but little is known about variability in individual responsiveness. Methods: Responsiveness of 129 participants to a multidisciplinary pain management programme was studied by measuring six psychological components of the chronic pain syndrome (depression, anxiety, stress, pain catastrophising, kinesiophobia, and pain acceptance) both on entry to the programme and on discharge two weeks later. Results: Multivariate analyses of variance showed significant group improvements in all measures, with mean improvements ranging from 42% for depression, 33% for catastrophising, 31% for stress, 22% for anxiety, 17% for pain acceptance, to 9% for kinesiophobia. However, the proportion of participants showing reliable improvements on their own baselines (calculated using the Reliable Change Index) ranged from 50% for stress, 44% for depression, 33% for pain catastrophising, 28% for pain acceptance, 26% for kinesiophobia, to 22% for anxiety. The proportion of participants who showed no reliable change ranged from 68% to 85% for different symptoms and 1–4% deteriorated on particular measures. Conclusions: The significant improvements in group measures masked considerable individual variability. The individual determinants of responsiveness to MPMPs warrant investigation.
Evaluation of patients for rehabilitation after musculoskeletal injury involves identifying, grading and assessing the injury and its impact on the patient's normal activities. Management is guided by a multidisciplinary team, comprising the patient, doctor and physical therapist, with other health professionals recruited as required. Parallel interventions involving the various team members are specified in a customised management plan. The key component of the plan is active mobilisation utilising strengthening, flexibility and endurance exercise programs. Passive physical treatments (heat, ice, and manual therapy), as well as drug therapy and psychological interventions, are used as adjunctive therapy. Biomechanical devices or techniques (eg, orthotic devices) may also be helpful. Coexisting conditions such as depression and drug dependence are treated at the same time as the injury. Effective team communication, simulated environmental testing and, for those employed, contact with the employer facilitate a staged return to normal living, sports and occupational activities.
Aim To understand the relationship between scores on two standardized measures of cognition, the Montreal Cognitive Assessment (MoCA) and the cognitive subscale of the Functional Independence Measure (FIMCog), and whether these scores can predict functional outcomes in rehabilitation. Methods Retrospective data analysis was conducted on all inpatients admitted to a general rehabilitation unit within a 6‐month period (N = 477). The average age of patients was 74 years. The Functional Independence Measure (FIM) was completed for all patients on admission and discharge. The MoCA was administered to patients on clinical suspicion of cognitive impairment. The MoCA was completed with 116 patients. Cognitive status was assessed using FIMCog and MoCA. The motor subscale of FIM was used to assess functional status in calculating the motor Rehabilitation Functional Gain (mRFG) and motor Rehabilitation Functional Efficiency (mRFE) scores. Discharge destination was also used as an outcome measure. Results There was a moderate correlation between FIMCog and MoCA scores on admission (r = 0.49, P < 0.001). Higher FIMCog and MoCA scores were associated with higher mRFG and mRFE scores. There was an indication that patients with higher MoCA scores were more likely to be discharged to a private residence (adjusted odds ratio 1.11; 95% confidence interval: 0.99, 1.25, P = 0.072). Cut‐off points of <25 on the MoCA (sensitivity 88.9%, specificity 48.9%), and <29 on the FIMCog (sensitivity 77.8%, specificity 53.3%) predicted those patients who were less likely to discharge to a private residence. Conclusions FIMCog and MoCA scores on admission were moderately correlated, and strongly correlated with functional rehabilitation outcomes. The FIMCog and MoCA had moderately high utility in predicting discharge destination. Geriatr Gerontol Int 2020; 20: 336–342.
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