Peripheral Blood CD8+T Cell as a Prognostic Biomarker for Hospitalised COVID-19 Patients Without Antiviral Treatment
Bibliographic record
Abstract
Background: The status of T lymphocyte subset counts in patients with COVID-19 remains uncertain. This study aimed to assess alterations in peripheral blood CD3+CD8+T (CD8+T) cells among hospitalized COVID-19 patients who have not received antiviral treatment and to evaluate their prognostic value within this patient population. Methods: A single-center, retrospective cohort study and a meta-analysis were conducted. The cohort study was performed at Xiangya Hospital from December 5, 2022, to January 31, 2023. We conducted a meta-analysis to explore the association between peripheral blood CD3+CD8+T cells and mortality in COVID-19 patients who did not receive antiviral therapy. All relevant studies in Embase, PubMed, Web of Science databases were systematically searched for meta-analysis. Results: The retrospective cohort study included 201 patients. A significant decrease in peripheral blood CD8+ T cell count was found to be associated with an increased risk of mortality (adjusted odds ratio [aOR]: 13.88; 95% confidence interval [CI]: 3.15– 61.23), after adjusting for gender, age, comorbidities, severity at admission, steroid therapy, and antibiotic therapy. The threshold value for CD8+T cell counts, determined by the receiver operating characteristic (ROC) curve analysis, was 145.5 (area under the curve [AUC]: 0.828, specificity: 90.3%, sensitivity: 72.9%, P< 0.001). Additionally, A total of 7 studies with 2765 participants were included in the meta-analysis. The meta-analysis reveals a significant association between lower CD8+ T cell counts and mortality (odds ratio [OR] = 3.543, 95% CI: 1.726 to 7.272; I 2 =93%). Conclusion: Peripheral blood CD8+ T cell can serve as a valuable prognostic biomarker for hospitalized patients who do not receive antiviral treatment. Keywords: peripheral blood CD3+CD8+T cell, prognostic biomarker, hospitalised COVID-19 patients
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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 | 0.005 |
| 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) | 0.000 | 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".