Th1/Th2 immune regulation and functional resilience in older adults following severe COVID-19: a prospective cohort study
Bibliographic record
Abstract
BACKGROUND: Older adults recovering from severe COVID-19 exhibit heterogeneous trajectories, ranging from persistent frailty to full functional recovery. The biological mechanisms underpinning resilience in this population remain poorly defined. This study aimed to investigate the association between Th1/Th2 immune regulation and functional resilience, defined as improvement in frailty status, among older survivors of severe COVID-19. METHODS: We conducted a prospective study at a tertiary respiratory center in Mexico. Twenty-four patients aged 65 or older with a history of severe COVID-19 were assessed at 4 and 12 months post-discharge. Frailty was evaluated using a validated phenotype adapted for the Mexican population. Peripheral blood mononuclear cells (PBMCs) were analyzed by flow cytometry to quantify CD4+ T cell subsets, cytokine production (IFN-γ, TNF, and IL-10), and the expression of T-bet, GATA-3, and TIM-3. RESULTS: Thirteen participants showed improved frailty status over 12 months. Resilient patients exhibited a higher Th1/Th2 (T-bet/GATA-3) ratio at 4 months post-discharge and increased IFN-γ and TNF production at 12 months. TIM-3 expression on CD4+ cells and circulating levels were also elevated in the resilient group. CONCLUSIONS: A Th1-skewed immune profile early after recovery and sustained proinflammatory cytokine activity are associated with resilience in older adults following severe COVID-19. These findings offer insight into immune mechanisms that may support functional recovery in aging populations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".