Association of Polycythemia with Outcomes of Acute Coronary Syndrome
Bibliographic record
Abstract
BACKGROUND: Polycythemia has not been extensively studied for its impact on acute coronary syndrome (ACS) outcomes. A previous study reported only 30-day outcomes to be worse in these patients. METHODS: Data from the ACS Israeli survey between 2000 and 2018 were utilized to compare between 3 groups of patients with ACS: anemic group (hemoglobin <12 g/dL for women and <12.5 g/dL for men), normal hemoglobin group, and polycythemic group (>16 g/dL and >16.5 g/dL, respectively). Measured outcomes included 30-day major adverse cardiac events (MACE comprising all-cause mortality, recurrent ACS, need for urgent revascularization, and stroke) and 1- and 5-year all-cause mortality. RESULTS: Of 14,746 ACS patients, 10,752 (72.9%) had normal hemoglobin levels, 3,492 (23.7%) were anemic, and 502 (3.4%) were polycythemic. In comparison with normal and anemic patients, polycythemic patients were younger (55.9 ± 10.5 vs. 61.9 ± 12.4 and 71.1 ± 12.2 for anemic, respectively, p < 0.001 for both), more frequently men (93.8% vs. 81.3% and 63.1%, respectively, p < 0.001), and less likely diabetic or hypertensive. Upon adjustment to baseline characteristics, compared with normal hemoglobin, polycythemia was not independently associated with 30-day MACE or 1-year mortality, but it was independently associated with higher risk for 5-year mortality (HR 1.76, 95% CI: 1.19-2.59, p = 0.005). Similar results were observed after propensity score matching. CONCLUSIONS: Although younger and with fewer comorbidities, polycythemic ACS patients are at increased risk for long-term all-cause mortality. Further study of this association is warranted to understand the causes and possibly to improve the outcomes of these patients.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".