Bibliographic record
Abstract
OBJECTIVE: Complex regional pain syndromes (CRPS) represent curious and difficult syndromes for both patient and clinician. CRPS presents as a triad of signs and symptoms, usually after a seemingly trivial injury to a peripheral joint or appendage. The clinical triad includes severe pain, vasomotor changes in and around the affected area, and trophic changes in the affected limb. Many of the acute symptoms are similar to those seen after many acute injuries, which makes an early diagnosis often times difficult. Current treatment protocols revolve around aggressive physical therapy plus pharmacologic interventions aimed at limiting sympathetic nervous system activity. OBJECTIVE: To review the literature on CRPS regarding symptoms, diagnosis, treatment, and causal mechanisms and to discuss alternative treatment approaches and the possible role of chiropractic care in patient rehabilitation. DATA SOURCES: Texts, review articles, and randomized clinical trials investigating treatments, causes, and epidemiology. CONCLUSIONS: Recent research calls into question the predominant theories that view excessive sympathetic nervous system activity as the cause of CRPS. No evidence of an increase in sympathetic nervous system activity has been found, and new theories suggest that an increase in the sensitivity of neurotransmitter receptors may be the cause of CRPS. Alternatively, other research has suggested that a local inflammatory process may in fact cause CRPS. Although no research has been completed examining the role of chiropractic care in the treatment of CRPS, there is reason to believe that spinal manipulation may be beneficial to patients with CRPS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".