History of hypertension is associated to 5-year non sudden cardiovascular mortality in patients with acute myocardial infarction without heart failure
Bibliographic record
Abstract
Influence of history of hypertension (HT) over long-term mortality after myocardial infarction (MI) is uncertain. Since presence of heart failure (HF) is crucial for treatment and prognosis of MI, we investigated whether HT influences mortality in the patients with and without HF. This is a prospective study on 505 consecutive, unselected, caucasian race patients admitted to 3 coronary care units for definite MI in north Italy. HF was evaluated according to Killip classification (class 1-4) on the first week from admission. All patients completed 5 years follow up (global mortality, non sudden cardiovascular mortality (non-SCVM), sudden death (SD) and non-CV mortality (non-CVM) were considered as outcomes). Baseline variables were were age, gender, diabetes, HT, history of hypercholestolemia, history of angina or MI, CK-MB peak, revascularization, ACE-I and β-blocker therapy. Threehundred and ten patients (mean age 63.1±11.9 years, 20% female, 43% HT) had no HF and 195 (mean age 71.9±10.2 years, 43% female, 52% HT) had. Among no-HF patients, global mortality rate was 18% in NT and 29% in HT (p=0.02) and non-SCVM was 6% in NT and 16% in HT (p=0.002). Among HF-patients, global mortality rate was 53% in NT and 65% in HT (ns) and non-SCVM was 29% in NT and 49% in HT (p=0.003). At bivariate analysis, HT was associated to global mortality only in the patients without HF (RR=1.7,CL=1.1-2.7, p=0.02) while it was associated to non-SCVM both in no-HF (RR=3.0,CL=1.5-6.6, p=0.002) and HF group (RR=2.0,CL=1.3-3.2, p=0.003). No associations were found between HT and SD and non-CVM. After adjustment, HT remained independently associated to non-SCVM (RR=2.3,CL=1.1-5.4,p=0.03) along with age (p=0.0002) and diabetes (0.0003), while HT was no longer associated in the HF patients. HT is independently associated to 5-year non-SCVM in the patients with MI without HF. This observation strengthens the link between HT and the worsening of the atherosclerotic vascular 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".