Periodontitis and chronic kidney disease: a systematic review of the association of diseases and the effect of periodontal treatment on estimated glomerular filtration rate
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIM: The aim of this systematic review (SR) was to evaluate the association between periodontitis and chronic kidney disease (CKD) and the effect of periodontal treatment (PT) on the estimated glomerular filtration rate (eGFR). METHODS: MEDLINE, EMBASE and Cochrane Central Register of Controlled Trials (CENTRAL) databases were searched up to and including September 30, 2012 to observational (S1) and interventional (S2) studies on the association of periodontitis with CKD. Studies were considered eligible for inclusion if they reported the eGFR. Search was conducted by two independent reviewers. The methodological quality of the observational studies was assessed using the Newcastle-Ottawa Scale (NOS) adapted for this review, and the Cochrane's Collaboration risk of bias assessment tool. A random-effects odds-ratio meta-analysis was conducted to estimate the degree of association between periodontitis and CKD. RESULTS: Search strategy identified 2456 potentially eligible articles, of which four cross-sectional, one retrospective, and three interventional studies were included. Four S1, 80.0% reported some degree of association between periodontitis and CKD. Similarly, such an outcome was supported by pooled estimates (OR: 1.65, 95% Confidence Interval: 1.35, 2.01, p < 0.00001, χ(2) = 1.70, I(2 ) = 0%). All interventional studies found positive outcomes related to treatment. CONCLUSION: There is quite consistent evidence to support the positive association between periodontitis and CKD, as well as the positive effect of PT on eGFR.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it