Effectiveness of case management interventions in reducing common and potentially preventable complications associated with Parkinson’s disease:A systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Objective We sought to systematically examine the effectiveness of case management interventions on common and potentially preventable complications associated with Parkinson’s disease, both in persons with Parkinson’s disease and in persons with other chronic health conditions. We specifically focused on falls, depression, anxiety, hallucinations, urinary tract infections and swallowing impairments. Background There is no systematic insight in the effect of case management on common complications associated with Parkinson’s disease. This is an important knowledge gap given that people living with Parkinson's have identified care coordination as one of their highest priorities. Furthermore, it remains unclear whether the putative beneficial effects of case management would vary by key patient characteristics, such as their age, gender or disease characteristics. Such insights would contribute to a shift from “one size fits all” healthcare resource allocation to personalized medicine. Methods Using predefined inclusion criteria, we identified studies published up till February 2021 from PubMed and Embase databases. For each study, data were extracted independently by two researchers. Narrative analysis, and when possible also meta-analysis and random-effects analyses were undertaken. Results 23 randomized controlled trials and four non-randomized studies reported data on the effect of case management on feelings of anxiety (8 studies) or symptoms of depression (26 studies). Only one study was conducted in people with Parkinson’s disease. No study were identified that reported on how case management affected falls, hallucinations, urinary tract infections or swallowing impairments. Across meta-analyses, we observed a statistically significant effect of case management on reducing anxiety (Standardized Mean Difference [SMD] = − 0.47; 95% confidence interval [CI]: -0.69, -0.32) and depression (SMD = − 0.48; CI: -0.71, -0.25). We found a large heterogeneity in effect estimates across studies, but this was not explained by patient population or intervention characteristics. Conclusions Among people with chronic health conditions, case management has beneficial effects on symptoms of depression and feelings of anxiety, which are two common complications of Parkinson’s disease. However, these findings were based almost exclusively on interventions in people with other diseases. Future studies should assess the utility of case management for preventing complications in people with Parkinson’s disease, with a particular focus on the optimal content, frequency, and intensity of case management.
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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 | 0.015 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.040 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".