Periodontitis and Platelets Status: A Systematic Review With Meta‐Analysis and Trial Sequential Analysis
Bibliographic record
Abstract
AIM: Circulating platelets are essential in hemostasis, thrombosis, and immune responses. Modifications in platelet function may impact immunological reactions to dental biofilm and cardiovascular health. Understanding changes in platelet status and activity in patients with periodontitis is still a subject of investigation. This study aimed to synthesize evidence from observational studies that investigated platelet status and activity in patients with and without periodontitis. METHODS: MEDLINE-PubMed, EMBASE, and Cochrane-CENTRAL Library databases were searched up to November 2024. Primary outcomes included platelet count (PC) and mean platelet volume (MPV). Secondary outcomes encompassed any other biomarker relevant to platelet status and activity. Methodological quality was evaluated using the Newcastle-Ottawa scale, and heterogeneity was analyzed. Descriptive analysis of outcomes and meta-analysis, incorporating trial sequential analysis of PC and MPV, were conducted. The body of evidence was graded by utilizing the Grading of Recommendations Assessment, Development, and Evaluation (GRADE). RESULTS: /L, 95% CI [7.68; 39.43]). There was no statistically significant difference between the groups for MPV (MD = 0.16 fL, 95% CI [-0.49; 0.82]). Trial sequential analysis indicated a conclusive meta-analysis of PC and highlighted the need for additional data on MPV from future trials. CONCLUSIONS: The certainty is moderate for slightly higher PC in patients with periodontitis compared to individuals without it and low for no difference in MPV between the two groups. The evidence is not robust to claim a clear difference in other platelet activation biomarkers between the two groups. TRIAL REGISTRATION: International Prospective Register of Systematic Reviews (PROSPERO) by number: CRD42023439051.
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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 | 0.032 | 0.065 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.026 | 0.055 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".