COVID-19 mRNA vaccine effectiveness against hospitalisation and death in veterans according to frailty status during the SARS-CoV-2 delta (B.1.617.2) variant surge in the USA: a retrospective cohort study
Bibliographic record
Abstract
Background: Studies have shown that COVID-19 vaccination is effective at preventing infection and death in older populations. However, whether vaccination effectiveness is reduced in patients with frailty is unclear. We aimed to compare vaccine effectiveness against hospitalisation and death after COVID-19 during the surge of the delta (B.1.617.2) variant of SARS-CoV-2 according to patients' frailty status. Methods: In this retrospective cohort study, we used data derived from the US Veterans Health Administration (VHA) facilities and the US Department of Veterans Affairs (VA) COVID-19 Shared Data Resource, which contains information from the VA National Surveillance Tool, death certificates, and National Cemetery Administration. We included veterans aged 19 years or older who tested positive for SARS-CoV-2 using RT-PCR or antigen tests between July 25 and Sept 30, 2021, with no record of a previous positive test. Deaths were identified through VHA facilities, death certificates, and National Cemetery Administration data available from VA databases. We also retrieved data including sociodemographic characteristics, medical conditions diagnosed at baseline, frailty score, and vaccination information. The primary outcomes were COVID-19-associated hospitalisations and all-cause deaths at 30 days from testing positive for SARS-CoV-2. The odds ratio (OR) for COVID-19-associated hospitalisation and hazard ratio (HR) for death of vaccinated patients compared with the unvaccinated patients were estimated according to frailty categories of robust, pre-frail, or frail. Vaccine effectiveness was estimated as 1 minus the OR for COVID-19-associated hospitalisation, and 1 minus the HR for death. Findings: We identified 57 784 veterans (mean age 57·5 years [SD 16·7], 50 642 [87·6%] males, and 40 743 [70·5%] White people), of whom 28 497 (49·3%) were categorised as robust, 16 737 (29·0%) as pre-frail, and 12 550 (21·7%) as frail. There were 2577 all-cause deaths (676 [26·2%] in the vaccinated group and 1901 [73·8%] in the unvaccinated group), and 7857 COVID-19-associated hospitalisations (2749 [35·0%] in the vaccinated group and 5108 [65·0%] in the unvaccinated group) within 30 days of a positive SARS-CoV-2 test. Vaccine effectiveness against COVID-19-associated hospitalisation within 30 days of a positive SARS-CoV-2 test was 65% (95% CI 61-69) in the robust group, 54% (48-58) in the pre-frail group, and 36% (30-42) in the frail group. By 30 days of a positive SARS-CoV-2 test, the vaccine effectiveness for all-cause death was 79% (95% CI 74-84) in the robust group, 79% (75-83) in the pre-frail group, and 68% (63-71) in the frail group. Interpretation: Compared with non-frail patients (pre-frail and robust), those with frailty had lower levels of vaccination protection against COVID-19-associated hospitalisation and all-cause death. Future studies investigating COVID-19 vaccine effectiveness should incorporate frailty assessments and actively recruit older adults with frailty. Funding: Miami VA Healthcare System Geriatric Research Education and Clinical Center.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".