Management of Pediatric Complex Regional Pain Syndrome : A Scoping Review
Bibliographic record
Abstract
Introduction Complex regional pain syndrome (CRPS) is a chronic pain condition characterized by pain that is out of proportion to the inciting trauma or stimulus in the context of autonomic, trophic, and motor changes (1,2). Though pediatric Complex regional pain syndrome (pCRPS) is rare with a minimum Canadian incidence of 1.14/100 000 children (3), outcomes can significantly affect patient function and quality of life e.g. missed school days, withdrawal from activities, mental health challenges, etc (4). There is no gold standard radiologic, laboratory or diagnostic test for pCRPS. In the adult world, numerous diagnostic criteria have been validated and used, with the most recent being the Budapest criteria (2). No diagnostic criteria have been validated for pCRPS. Due to the variability in presentation as well as the lack of gold standard test and validated diagnostic criteria, there often tends to be a delay in diagnosis of pCRPS (1,4,5). Patients often get referred to multiple specialists before a diagnosis is made (3,4,6). This delay in diagnosis is thought to lead to worse outcomes (3,4,6). There are a wide range of pharmacological (NSAIDS, anticonvulsants, antidepressants etc.), non-pharmacological (physiotherapy, TENS, psychotherapy, acupuncture, etc.) and invasive interventional approaches (nerve blocks, sympathetic blocks, spinal cord stimulation, etc.) to pCRPS management (2,3,7,8). Though a multi-disciplinary approach is generally thought to be the most effective, there is still a lot of treatment variability across different centres (3). Considering the high degree of treatment variability, there is a need to evaluate and summarize the current evidence while identifying gaps so at the very least, consensus guidelines can be formed for the management of pCRPS. Hence, we will conduct a scoping review of existing literature to evaluate the management of pCRPS. As our topic is a broad one, a scoping review is more appropriate compared to a traditional systematic review. With a scoping review, we can rigorously assess the range, and nature of research activity in pCRPS, summarize and disseminate practice changing findings while identifying gaps in the literature (9,10). Objectives: The purpose of this review is to evaluate the literature and determine the most effective ways of managing pCRPS, summarise the various outcomes of pCRPS and to identify any gaps in the literature where future research should be conducted.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".