World Workshop on Oral Medicine<scp>VI</scp>: a systematic review of medication‐induced salivary gland dysfunction
Bibliographic record
Abstract
The aim of this paper was to perform a systematic review of the pathogenesis of medication-induced salivary gland dysfunction (MISGD). Review of the identified papers was based on the standards regarding the methodology for systematic reviews set forth by the World Workshop on Oral Medicine IV and the PRISMA statement. Eligible papers were assessed for both the degree and strength of relevance to the pathogenesis of MISGD as well as on the appropriateness of the study design and sample size. A total of 99 papers were retained for the final analysis. MISGD in human studies was generally reported as xerostomia (the sensation of oral dryness) without measurements of salivary secretion rate. Medications may act on the central nervous system (CNS) and/or at the neuroglandular junction on muscarinic, α-and β-adrenergic receptors and certain peptidergic receptors. The types of medications that were most commonly implicated for inducing salivary gland dysfunction were those acting on the nervous, cardiovascular, genitourinary, musculoskeletal, respiratory, and alimentary systems. Although many medications may affect the salivary flow rate and composition, most of the studies considered only xerostomia. Thus, further human studies are necessary to improve our understanding of the association between MISGD and the underlying pathophysiology.
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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 | 0.012 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".