Evidence of descending inhibition deficits in atypical but not classical trigeminal neuralgia
Bibliographic record
Abstract
Trigeminal neuralgia (TN) is a rare neuropathic facial pain disorder. Two forms of TN, classical TN (CTN) and atypical TN (ATN), are reported and probably have different aetiologies. The aim of the present study was to evaluate the functional integrity of the diffuse noxious inhibitory controls (DNIC) in (1) a group of patients with classical trigeminal neuralgia (CTN), (2) a group of patients with atypical trigeminal neuralgia (ATN), and (3) a group of healthy controls in order to determine if a descending pain modulation deficit could participate in the pathophysiology of TN pain. DNIC responses of 14 CTN patients, 14 ATN patients and 14 healthy controls were obtained by comparing thermode-induced facial heat pain scores before and after activating DNIC. DNIC was triggered using a standard counter-irritation paradigm (i.e., immersion of the arm in painfully cold water). General sensitivity to pain was also evaluated by measuring mechanical pain thresholds over 18 points located outside the trigeminal territory. Healthy participants and CTN patients showed a 21% and 16% reduction in thermode-induced pain following the immersion, respectively (all p-values <.01), whereas ATN patients experienced no change (p=.57). ATN patients also had more tender points (mechanical pain thresholds<4.0kg) than CTN and healthy controls (all p-values <.05). Taken together, these results suggest that the underlying physiopathology differs between CTN and ATN and that a deficit in descending inhibition may further contribute to the pain experienced by patients with ATN.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".