Neurological findings in complex regional pain syndromes - analysis of 145 cases
Bibliographic record
Abstract
Early diagnosis is a prerequisite for a successful treatment of complex regional pain syndrome (CRPS). In order to describe neurological symptoms which characterize CRPS, we evaluated 145 patients prospectively. Two-thirds of these were women, the mean age at time of investigation was 50.4 years. CRPS followed limb trauma, surgery and nerve lesion. Employing the current IASP criteria 122 patients were classified as CRPS I and 23 as CRPS II. All patients were assessed clinically pain was quantified using the McGill pain questionnaire, skin temperature was measured by an infrared thermometer and a subgroup of 57 patients was retested in order to determine thermal thresholds (QST). Of our patients 42% reported stressful life events in a close relationship to the onset of CRPS and 41% had a history of chronic pain before CRPS. The latter group of patients gave a higher rating of CRPS pain (P<0.05). The major symptoms were pain at rest in 77% and hyperalgesia in 94%. Typical pain was deep in the limb having a tearing character. Patients getting physical therapy had significantly less pain than those without (P<0.04). Autonomic signs were frequent (98%) and often changed with the duration of CRPS. Skin temperature was warmer in acute and colder in chronic stages (P<0.001). Likewise edema had a higher incidence in acute stages (P<0.001). We found no correlation between pain and autonomic dysfunction. Motor dysfunction (present in 97%) included weakness, tremor, exaggerated tendon reflexes, dystonia or myoclonic jerks. QST revealed increased warm perception thresholds (P<0.02) and decreased cold pain thresholds (P<0.03) of the affected limb. The detailed knowledge of clinical features of CRPS could help physicians early to recognize the disease and thus to improve therapy outcome.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".