Symptoms and signs in patients with suspected neuropathic pain
Bibliographic record
Abstract
The study sought to determine if symptoms and signs cluster differentially in groups of patients with increasing evidence of neuropathic pain (NP). We prospectively looked at symptoms and signs in 214 patients with suspected chronic NP of moderate to severe intensity. According to a set of clinical criteria the patients were a priori classified as having the so-called 'Definite NP' (n = 91), 'Possible NP' (n = 71), or 'Unlikely NP' (n = 52). A recording of symptoms including pain descriptors, intensity of five categories of pain, Short Form McGill Pain Questionnaire, and Major Depression Inventory were done. Sensory tests including repetitive pinprick stimulation, examination for cold-evoked pain by an acetone drop and brush-evoked pain were carried out in the maximal pain area and in a control area. High intensity of superficial ongoing pain, and touch or cold provoked pain was associated with chronic pain classified as definite or possible neuropathic. Intensity of deep ongoing pain, and 'paroxysms' was similar in the three groups. Brush-evoked pain was more frequent in definite NP. The McGill Pain Questionnaire and the used pain descriptors could not distinguish between the three clinical categories. Although certain symptoms (touch or cold provoked pain) and signs (brush-evoked allodynia) are more prominent in patients with definite or possible NP, we found considerable overlap with the clinical presentation of patients with unlikely NP.
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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 | 0.000 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".