Idiopathic orofacial and nociplastic pain in elderly patients: a narrative review
Bibliographic record
Abstract
Background and Objective: Idiopathic orofacial pain (IOFP) includes burning mouth syndrome (BMS), persistent idiopathic facial pain (PIFP), and persistent idiopathic dentoalveolar pain (PIDAP). We aimed to perform a narrative review on the role of nociplastic pain mechanisms in IOFP in elderly patients. Methods: We conducted a PubMed search using only English for studies published between April 1990 and September 2021 on IOFP and nociplastic pain using the following search terms: “(Burning Mouth Syndrome OR Persistent Idiopathic Dentoalveolar Pain OR Atypical Odontalgia) AND (Temporal Summation OR Conditioned Pain Modulation OR Quantitative Sensory Testing) AND (1990/04/01:2021/9/01[Date - Entry])”. Key Content and Findings: We identified 43 potentially relevant articles, and upon review selected 13 studies for this review; 9 were for BMS, and 4 were for PIDAP or atypical odontalgia. The IOFPs are caused by a decrease in the function of descending pain inhibition. Conditioned pain modulation (CPM) represents a natural inhibitory process on pain, which decreases with age in the orofacial region. Reduced CPM may be one of the reasons for the increased prevalence of chronic pain in older individuals. Lack of brain structures or dysregulation in the endogenous opioid system could also be a factor in the lack of the CPM effect in older individuals. Conclusions: This review implies the idiopathic oral pain syndromes may have more nociplastic pain components than psychogenic pain. Future research is needed to further assess the relationship between nociplastic pain and psychogenic pain on the orofacial regions.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".