The Effectiveness of Rehabilitation Interventions on Pain and Disability for Complex Regional Pain Syndrome
Bibliographic record
Abstract
OBJECTIVES: To summarize and critically appraise the body of evidence on conservative management of complex regional pain syndrome (CRPS), we conducted a systematic review and meta-analysis of randomized controlled trials (RCTs). METHODS: We conducted a literature search from inception to November 2021 in the following databases: Embase, Medline, CINAHL, Google Scholar, PEDRO, and Psychinfo. Two independent reviewers conducted risk of bias and quality assessment. Qualitative synthesis and meta-analysis were the methods for summarizing the findings of the RCTs. The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach was used to rate the overall quality and certainty of the evidence on each treatment outcome. RESULT: Through a database search, 751 records were found, and 33 RCTs were eligible for inclusion. Studies were published between 1995 and 2021. The overall risk of bias for 2 studies was low, 8 studies were unclear, and 23 studies were high.Low-quality evidence suggests that mirror therapy (as an addition to conventional stroke rehabilitation interventions) and graded motor imagery program (compared with routine rehabilitation interventions) may result in a large improvement in pain and disability up to 6-month follow-up in poststroke CRPS-1 patients. Low-quality evidence suggests that pain exposure therapy and aerobic exercises as an additive treatment to physical therapy interventions may result in a large improvement in pain up to a 6-month follow-up. The evidence is very uncertain about the effect of all other targeted interventions over conventional physical therapy or sham treatments on pain and disability. DISCUSSION: There is an ongoing need for high-quality studies to inform conservative management choices in CRPS.
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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 | 0.042 | 0.134 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.018 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| 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".