Abstract 19059: Risk Factors for the First Cardiopulmonary Hospitalization Differ From Those of Recurrent Cardiopulmonary Hospitalizations in Patients With Cardiovascular Disease Vaccinated Against Influenza — <i>A Secondary Analysis of the INVESTED Trial</i>
Bibliographic record
Abstract
Background: Influenza vaccines are recommended for patients with CVD due to their protective effects and favorable safety profile. Patients with recent MI/HF hospitalization are at high risk of multiple events, but it is not known which flu vaccine type can mitigate recurrent events. Research Questions: What are predictors of recurrent cardiopulmonary hospitalization and death in patients with CVD and does the high-dose trivalent flu vaccine reduce the rate of recurrent events compared with standard-dose quadrivalent vaccine? Methods: In this pragmatic, active comparator trial, patients with recent MI/HF hospitalization across 157 sites were randomized to either vaccine type and revaccinated each enrolled season (2016-2019). Recurrent event analysis with a Markov multistate model, negative binomial, and Lin-Wei-Yang-Ying regression models was applied, adjusting for clinical and sociodemographic factors, flu infection and vaccine history, with vaccine type as the main exposure. Cardiopulmonary hospitalization and all-cause death comprised the multistate model’s main states and the composite primary outcome for remaining analyses. Results: Among 5260 patients (mean age 65.5 years; 28% women; 63% with recent HF), 12% were readmitted ≥1 for cardiopulmonary causes, accounting for half of total cardiopulmonary hospitalization. In the multistate model, a history of comorbidities (e.g., low LVEF and COPD) was associated with recurrent hospitalization (Figure), whereas age and frailty primarily determined a higher rate of death, particularly after a first hospitalization. There were no significant differences between the vaccines on the rate of recurrent events and death in the multistate and negative binomial regression models. Conclusions: As hospitalizations accrue, the association of certain predictors changes in this population. Alternative strategies beyond vaccine type are needed to mitigate the total burden of cardiopulmonary disease.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.006 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".