Pneumococcal vaccination and risk of myocardial infarction
Bibliographic record
Abstract
BACKGROUND: Based on promising results from laboratory studies, we hypothesized that pneumococcal vaccination would protect patients from myocardial infarction. METHODS: We conducted a hospital-based case-control study that included patients considered to be at risk of myocardial infarction. We used health databases to obtain hospital diagnoses and vaccination status. We compared patients who had been admitted for treatment of myocardial infarction with patients admitted to a surgical department in the same hospital for a reason other than myocardial infarction between 1997 and 2003. RESULTS: We found a total of 43 209 patients who were at risk; of these, we matched 999 cases and 3996 controls according to age, sex and year of hospital admission. Cases were less likely than controls to have been vaccinated (adjusted odds ratio [OR] 0.53, 95% confidence interval [CI] 0.40-0.70). This putative protective role of the vaccine was not observed for patients who had received the vaccine up to 1 year before myocardial infarction (adjusted OR 0.85, 95% CI 0.54-1.33). In contrast, if vaccination had occurred 2 years or more before the hospital admission, the association was stronger (adjusted OR 0.33, 95% CI 0.20-0.46). INTERPRETATION: Pneumococcal vaccination was associated with a decrease of more than 50% in the rate myocardial infarction 2 years after exposure. If confirmed, this association should generate interest in exploring the putative mechanisms and may offer another reason to promote pneumococcal vaccination.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".