Regular Use of VKA Prior to COVID-19 Associated with Lower 7-Day Survival in Hospitalized Frail Elderly COVID-19 Patients: The GERIA-COVID Cohort Study
Bibliographic record
Abstract
Background. Vitamin K concentrations are inversely associated with the clinical severity of COVID-19. The objective of this cohort study was to determine whether the regular use of vitamin K antagonist (VKA) prior to COVID-19 was associated with short-term mortality in frail older adults hospitalized for COVID-19. Methods. Eighty-two patients consecutively hospitalized for COVID-19 in a geriatric acute care unit were included. The association of the regular use of VKA prior to COVID-19 with survival after 7 days of COVID-19 was examined using a propensity-score-weighted Cox proportional-hazards model accounting for age, sex, severe undernutrition, diabetes mellitus, hypertension, prior myocardial infarction, congestive heart failure, prior stroke and/or transient ischemic attack, CHA2DS2-VASc score, HAS-BLED score, and eGFR. Results. Among 82 patients (mean ± SD age 88.8 ± 4.5 years; 48% women), 73 survived COVID-19 at day 7 while 9 died. There was no between-group difference at baseline, despite a trend for more frequent use of VKA in those who did not survive on day 7 (33.3% versus 8.2%, p = 0.056). While considering “using no VKA” as the reference (hazard ratio (HR) = 1), the HR for 7-day mortality in those regularly using VKA was 5.68 [95% CI: 1.17; 27.53]. Consistently, COVID-19 patients using VKA on a regular basis had shorter survival times than the others (p = 0.031). Conclusions. Regular use of VKA was associated with increased mortality at day 7 in hospitalized frail elderly patients with COVID-19.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".