Nondermatomal somatosensory deficits: overview of unexplainable negative sensory phenomena in chronic pain patients
Bibliographic record
Abstract
PURPOSE OF REVIEW: To review the literature and our current understanding of nondermatomal somatosensory deficits (NDSDs) associated with chronic pain in regards to their prevalence, assessment and clinical presentation, cause and pathophysiology, relationship with conversion disorder and psychological factors, as well as their treatment and prognosis. RECENT FINDINGS: NDSDs are negative sensory deficits consisting of partial or total loss of sensation to pinprick, light touch or other cutaneous modalities. Although they had been noted more than a century ago and appear prevalent in chronic pain populations, they are poorly studied. They may be very mild or very dense, may occupy large body areas, are often highly dynamic and changeable or, to the contrary, very stable and long lasting. NDSDs may occur in the absence of biomedical pathology or coexist with structural musculoskeletal or nervous system abnormalities. They appear to be associated with psychological factors and a poor prognosis for response to treatment and return to work. Recent brain imaging studies provide a basis for understanding NDSD pathophysiology. SUMMARY: NDSDs represent prevalent phenomena associated with chronic pain. Further, research is needed to elucidate their origin, response to treatment, and prevalence in the general population, primary care settings, and nonpain patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".