Abstract 12413: Haemoglobin and Change in Haemoglobin Status Predict Mortality, Cardiovascular Events and Bleeding in Stable Coronary Artery Disease: A Clarify Registry Analysis of 21,829 Patients From 45 Countries
Bibliographic record
Abstract
Anaemia is a predictor of adverse outcome in patients with acute myocardial infarction and those undergoing revascularisation. Little is known regarding the relationship of hemoglobin (Hb) or its change over time on outcomes in patients with CAD. The CLARIFYregistry provides a unique contemporary opportunity to explore this relationship . Methods: 33 283 patients from 45 countries were enrolled in the CLARIFY registry of stable CAD (Nov 2009 -July 2010). Hb values were available for 21,829 patients, who were divided into groups according to Hb quintiles and anaemia status (WHO criteria) at each of baseline and follow-up (anaemic[A]/normal[N]) (status at baseline/follow-up): (i) N/N (ii) A/N (iii) N/A, (iv) A/A. Results: (Table) Whilst patients with lower Hb were less commonly treated with aspirin and ACEIs, they more commonly received thienopyridines, anticoagulants and ARBs. Low Hb was a consistent predictor of mortality, adverse CV event and major bleeds after controlling for various factors at baseline. Anaemia at follow up was independently associated with higher all-cause mortality (p<0.001, HR 1.9 [1.5, 2.3] for A/A and 1.9 [1.5, 2.3] for N/A), non-CV mortality (p<0.001) and CV mortality (p = 0.001). Patients whose baseline anaemia normalised during follow-up (A/N) did not appear to be at increased risk of death (HR 1.0 [0.8, 1.3], although risk of major bleeding was greater (HR 2.1 [1.2, 3.4], p=0.01). Sensitivity analyses were performed after excluding patients with heart failure and chronic kidney disease at baseline and yielded qualitatively similar results. Conclusions: In this large contemporary stable CAD population, low Hb was an independent predictor of mortality, adverse CV event and major bleeds. Persisting or new onset anaemia is a powerful predictor of CV and non-CV mortality. Whilst low Hb may play a pathophysiological role in CV disease progression, the data suggest that it is also likely to be a marker of other co-morbid 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".