ORAL MANIFESTATIONS OF SICKLE CELL DISEASE AND ITS EFFECTS ON DENTAL AND PERIODONTAL HEALTH: A SYSTEMATIC REVIEW
Bibliographic record
Abstract
Background: Sickle cell disease is a genetic disorder that manifests itself in several organs. There is little consensus in the literature on oral manifestations, particularly dental and periodontal. This study aimed to identify the oral manifestations of sickle cell disease, focusing on dental and periodontal manifestations. Methods: An electronic search was performed in PubMed, Embase, and African Index Medicus. Quality and risk of bias were assessed using the Newcastle-Ottawa Scale, the modified Newcastle-Ottawa Scale, and the 2013 Guideline CARE. This systematic review covered research published between 2000 and 2022. Results: A total of 962 articles were identified, 26 of which were selected, including 13 case-control studies, 4 cohort studies, 7 cross-sectional studies, and 2 case reports. The risk of bias was high for 3.84% of the studies, medium for 38.46%, and low for 57.60%. Oral manifestations were reported in 24 studies, with a predominance of periodontal ones in 10 studies. An association between sickle cell disease and dental caries, pulpal necrosis, and delayed tooth eruption has been reported. Conclusion: Several oral manifestations, particularly periodontal, of sickle cell disease have been reported. However, current data do not provide evidence of a possible association between sickle cell disease and oral symptoms, particularly periodontal manifestations.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".