Interleukin-17, a salivary biomarker for COVID-19 severity
Bibliographic record
Abstract
OBJECTIVES: T-helper 17 cell-mediated response and their effector IL-17 cytokine induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a major cause of COVID-19 disease severity and death. Therefore, the study aimed to determine if IL-17 level in saliva mirrors its circulatory level and hence can be used as a non-invasive biomarker for disease severity. METHODS: Interleukin-17 (IL-17) level was evaluated by ELISA in saliva and blood of 201 adult COVID-19 patients with different levels of severity. The IL-17 saliva level was also associated with COVID-19 disease severity, and need for mechanical ventilation and/or death within 29 days after admission of severe COVID-19 patients. RESULTS: We found that IL-17 level in saliva of COVID-19 patients reflected its circulatory level. High IL-17 level in saliva was associated with COVID-19 severity (P<0.001), need for mechanical ventilation (P = 0.002), and/or death by 29 days (P = 0.002), after adjusting for patients' demographics, comorbidity, and COVID-19 serum severity markers such as D-Dimer, C-reactive protein, and ferritin. CONCLUSION: We propose that saliva IL-17 level could be used as a biomarker to identify patients at risk of developing severe COVID-19.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.004 | 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".