Host‐derived salivary biomarkers in diagnosing periodontal disease: systematic review and meta‐analysis
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: To systematically evaluate the accuracy of host-derived salivary biomarkers in the diagnosis of periodontal disease based on the given sensitivity and specificity information. MATERIALS AND METHODS: Studies were eligible for inclusion if they had compared the diagnostic application of salivary biomarkers with clinical examination of periodontal disease. A detailed search was performed in five databases without restrictions on subject age, chronology, or language. Additionally, a partial grey-literature search was conducted. The revised Quality Assessment of Diagnostic Accuracy Studies tool and Meta-analysis were used to evaluate the selected studies. RESULTS: From the 905 screened studies, four were included in the qualitative and quantitative analysis. One biomarker, macrophage inflammatory protein-1α (MIP-1α), had excellent diagnostic accuracy and two, interleukin-1β (IL-1β) and interleukin-6 (IL-6), showed acceptable diagnostic values. However, the only biomarker considered excellent was evaluated in a single study, which may reduce the robustness of the results. CONCLUSION: There is currently limited evidence to confirm the diagnostic capability of salivary biomarkers in the clinical assessment of periodontal disease. Notwithstanding, the summary findings showed the growing importance of salivary biomarker, and can guide larger, well-controlled, diagnostic accuracy studies. Likewise, although not conclusive, MIP-1α, IL-1β, and IL-6 may be promising biomarkers for future studies.
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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.024 | 0.009 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 it