Prevalence and severity of oral disease in adults with chronic kidney disease: a systematic review of observational studies
Bibliographic record
Abstract
BACKGROUND: Oral disease may be increased in people with chronic kidney disease (CKD) and, due to associations with inflammation and malnutrition, represents a potential modifiable risk factor for cardiovascular disease and mortality. We summarized the prevalence of oral disease in adults with CKD and explored any association between oral disease and mortality. METHODS: We used systematic review of observational studies evaluating oral health in adults with CKD identified in MEDLINE (through September 2012) without language restriction. We summarized prevalence and associations with all-cause and cardiovascular mortality using random-effects meta-analysis. We explored for sources of heterogeneity between studies using meta-regression. RESULTS: Eighty-eight studies in 125 populations comprising 11 340 adults were eligible. Edentulism affected one in five adults with CKD Stage 5D (dialysis) {20.6% [95% confidence interval (CI), 16.4-25.6]}. Periodontitis was more common in CKD Stage 5D [56.8% (CI, 39.3-72.8)] than less severe CKD [31.6% (CI, 19.0-47.6)], although data linking periodontitis with premature death were scant. One-quarter of patients with CKD Stage 5D reported never brushing their teeth [25.6% (CI, 10.2-51.1)] and a minority used dental floss [11.4% (CI, 6.2-19.8)]; oral pain was reported by one-sixth [18.7% (CI, 8.8-35.4)], while half of patients experienced a dry mouth [48.4% (CI, 37.5-59.5)]. Data for kidney transplant recipients and CKD Stages 1-5 were limited. CONCLUSIONS: Oral disease is common in adults with CKD, potentially reflects low use of preventative dental services, and may be an important determinant of health in this clinical setting.
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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 | 0.015 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.015 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 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".