Salivary IgA as a Useful Biomarker for Dental Caries in Down Syndrome Patients: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
The objective of this systematic review and meta-analysis is to critically analyze and summarize studies reporting association of salivary immunoglobulin A (IgA) levels as a biomarker for dental caries in Down syndrome (DS) patients. Using the keywords salivary [All Fields] AND IgA [All Fields] AND ("down syndrome" [MeSH Terms] OR ("down"[All Fields] AND "syndrome" [All Fields]) OR "down syndrome" [All Fields]), an electronic search was conducted via PubMed and Scopus databases by two authors, H. H. and Z. K. independently. Retrieved studies were screened against the predefined exclusion and inclusion criteria. To estimate the risk of bias, quality assessment of included studies was carried using the Newcastle-Ottawa quality assessment scale for observational studies. Primary search resulted in 10 articles from PubMed and 13 articles from Scopus. Ten studies fulfilled the defined selection criteria and evaluated the salivary IgA (sIgA) level in DS patients with dental caries. Five articles were further analyzed in a quantitative synthesis presented in the meta-analysis. Due to a modified lifestyle and compromised oral hygiene in DS patients, understandably, it is still postulated in the literature that the presence of sIgA can have a protective effect on the occurrence of dental caries as compared with healthy counterparts. As indicated by the present meta-analysis, no conclusions can be drawn as to definitively label sIgA as a biomarker for dental caries. Further, well-designed longitudinal clinical studies and translational research are therefore required before the benchmarking of sIgA as a useful biomarker for dental caries in DS patients with preferable molecular insights.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".