Influenza Vaccination for the Prevention of Cardiovascular Disease in the Americas: Consensus document of the Inter-American Society of Cardiology and the Word Heart Federation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Cardiovascular mortality is decreasing but remains the leading cause of death world-wide. Respiratory infections such as influenza significantly contribute to morbidity and mortality in patients with cardiovascular disease. Despite of proven benefits, influenza vaccination is not fully implemented, especially in Latin America. Objective: The aim was to develop a regional consensus with recommendations regarding influenza vaccination and cardiovascular disease. Methods: A multidisciplinary team composed by experts in the management and prevention of cardiovascular disease from the Americas, convened by the Inter-American Society of Cardiology (IASC) and the World Heart Federation (WHF), participated in the process and the formulation of statements. The modified RAND/UCLA methodology was used. This document was supported by a grant from the WHF. Results: An extensive literature search was divided into seven questions, and a total of 23 conclusions and 29 recommendations were achieved. There was no disagreement among experts in the conclusions or recommendations. Conclusions: There is a strong correlation between influenza and cardiovascular events. Influenza vaccination is not only safe and a proven strategy to reduce cardiovascular events, but it is also cost saving. We found several barriers for its global implementation and potential strategies to overcome them.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it