Assessment of periodontal health status in patients with Parkinson's disease—A systematic review and meta‐analysis of cross‐sectional studies
Bibliographic record
Abstract
INTRODUCTION: Parkinson's disease (PKD) is neurodegenerative disorder marked by tremors, bradykinesia, muscle rigidity and reduction in precise hand movements which could lead to improper oral hygiene and Periodontal disease. Current systematic review aims to review existing literature and provide assessment of periodontal health in PKD patients through a meta-analysis METHODS: Review was performed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines and registered in PROSPERO-CRD42023451700. Databases were searched for studies having sufficient data on periodontal health in patients with PKD compared to healthy controls and reporting outcomes in terms of various periodontal parameters of probing depth (PD), plaque index (PI), clinical attachment level (CAL), presence of bleeding on probing and gingivitis. Quality assessment of included was evaluated using Newcastle Ottawa Scale (NOS). RESULTS: Eleven studies fulfilled the eligibility criteria, of which ten studies were suitable for meta-analysis. Pooled estimate through the SMD showed that all periodontal parameters were altered and significantly deteriorated in PKD compared to controls but this group differences were statistically insignificant (p > 0.05). Publication bias through the funnel plot showed symmetric distribution with absence of systematic heterogeneity. CONCLUSION: Parkinson's disease could be a possible factor in deterioration of periodontal health.
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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 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.025 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".