Chronic pain in pachyonychia congenita: evidence for neuropathic origin
Bibliographic record
Abstract
BACKGROUND: Pachyonychia congenita (PC) is a rare autosomal dominant skin disease, with chronic pain being the most prominent complaint. Histological studies showing alterations in sensory innervation, along with reports on alterations in mechanical sensitivity, suggest that PC may be a form of neuropathy. OBJECTIVES: Here, for the first time, we aim to evaluate systematically the sensory function of patients with PC vs. controls, in order to investigate the pathophysiology of PC. METHODS: Patients (n = 62) and controls (n = 45) completed the McGill and Douleur Neuropathique-4 (DN4) questionnaires. Sensory testing included detection and pain thresholds, pathological sensations, conditioned pain modulation (CPM) and temporal summation of pain. RESULTS: A moderate-to-severe chronic pain in the feet, throbbing and stabbing in quality, was highly prevalent among patients with PC (86%) and was especially debilitating during weight bearing. In addition, the majority of patients had a DN4 score ≥ 4 (62%), static allodynia (55%) and tingling (53%) in the feet. Compared with controls, patients with PC exhibited thermal and mechanical hypoaesthesia and mechanical hyperalgesia in the feet. CPM was reduced among the patients, and was associated with more enhanced mechanical hyperalgesia in the feet. The specific gene and nature of the causative mutation did not affect any of these features. CONCLUSIONS: Although thermal and mechanical hypoaesthesia may result from thicker skin, its presentation in painful regions, along with mechanical hyperalgesia and allodynia, point towards the possibility of neuropathic changes occurring in PC. The clinical features and DN4 scores support this possibility and therefore neuropathic pain medications may be beneficial for patients with PC.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".