Meta‐Analysis of Salivary Flow Rates in Young and Older Adults
Bibliographic record
Abstract
OBJECTIVES: To determine whether salivary flow decreases as a function of aging. DESIGN: Meta-analysis. SETTING: Literature review. PARTICIPANTS: Individuals aged 18 and older reported to be free of major systemic disease. MEASUREMENTS: Relevant studies were identified through a literature search of several databases, from their inception to June 2013. Studies were included if saliva had been collected on at least one occasion in subjects aged 18 and older and if the data were presented in a manner that enabled comparisons of younger and older participants. Differences in salivary flow rates between age groups were calculated for each salivary source and condition and reported as standardized mean differences (SMDs), standard errors (SEs) and 95% confidence intervals (CIs). The results were pooled using a random effects model. A separate analysis examining medication use was also conducted. RESULTS: Forty-seven studies were included. Whole (SMD = 0.551, SE = 0.056, 95% CI = 0.423-0.678, P < .001) and submandibular and sublingual (SMSL) (SMD = 0.582, SE = 0.123, 95% CI = 0.341-0.823, P < .001) salivary flow rates were reduced significantly in older participants and in unstimulated and stimulated conditions. In contrast, parotid and minor gland salivary flow rates were not significantly reduced with increasing age. Additionally, unstimulated and stimulated SMSL, and unstimulated whole salivary flow rates were significantly lower in older adults, regardless of medication usage. CONCLUSION: The aging process is associated with reduced salivary flow in a salivary-gland-specific manner; this reduction in salivary flow cannot be explained on the basis of medications. These findings have important clinical implications for maintaining optimal oral health in older adults.
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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 | 0.017 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.055 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".