Effectiveness of multidisciplinary care for Parkinson's disease: A randomized, controlled trial
Bibliographic record
Abstract
Multidisciplinary care is considered an optimal model to manage Parkinson's disease (PD), but supporting evidence is limited. We performed a randomized, controlled trial (RCT) to establish whether a multidisciplinary/specialist team offers better outcomes, compared to stand-alone care from a general neurologist. Patients with PD were randomly allocated to an intervention group (care from a movement disorders specialist, PD nurses, and social worker) or a control group (care from general neurologists). Both interventions lasted 8 months. Clinicians and researchers were blinded for group allocation. The primary outcome was the change in quality of life (Parkinson's Disease Questionnaire; PDQ-39) from baseline to 8 months. Other outcomes were the UPDRS, depression (Montgomery-Asberg Depression Scale; MADRS), psychosocial functioning (Scales for Outcomes in Parkinson's disease-Psychosocial; SCOPA-PS), and caregiver strain (Caregiver Strain Index; CSI). Group differences were analyzed using analysis of covariance adjusted for baseline values and presence of response fluctuations. A total of 122 patients were randomized and 100 completed the study (intervention, n = 51; control, n = 49). Compared to controls, the intervention group improved significantly on PDQ-39 (difference, 3.4; 95% confidence interval [CI]: 0.5-6.2) and UPDRS motor scores (4.1; 95% CI: 0.8-7.3). UPDRS total score (5.6; 95% CI: 0.9-10.3), MADRS (3.7; 95% CI: 1.4-5.9), and SCOPA-PS (2.1; 95% CI: 0.5-3.7) also improved significantly. This RCT gives credence to a multidisciplinary/specialist team approach. We interpret these positive findings cautiously because of the limitations in study design. Further research is required to assess teams involving additional disciplines and to evaluate cost-effectiveness of integrated approaches. © 2012 Movement Disorder Society.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".