Ischemic Electrocardiographic Abnormalities and Prognosis in Decompensated Heart Failure
Bibliographic record
Abstract
BACKGROUND: Identification of coronary ischemia may enable targeted diagnostic and therapeutic strategies for acute heart failure. We determined the risk of 30-day mortality associated with ischemic ECG abnormalities in patients with acute heart failure. METHODS AND RESULTS: Among 8772 patients (53.4% women, median 78 years [Q1, Q3: 68,84]) presenting with acute heart failure to 86 hospital emergency departments in Ontario, Canada, Q-waves, T-wave inversion, or ST-depression were present in 51.8% of subjects. However, presence of ST-depression was the only finding associated with 30-day mortality with adjusted odds ratio 1.24 (95% confidence interval [CI], 1.02-1.50). Using continuous net reclassification improvement, addition of ST-depression to the Emergency Heart failure Mortality Risk Grade model reclassified 16.9% of patients overall, and 29.3% of those with a history of ischemic heart disease (both P<0.001). By adding ST-depression to the model, the Emergency Heart failure Mortality Risk Grade was extended to predict 30-day death with high discrimination (c-statistic 0.801), with 0.57% mortality rate in the lowest risk decile. Adjusted odds ratios for 30-day mortality were 2.81 (95% CI, 1.48-5.31; P=0.002) in quintile 2, 7.41 (95% CI, 4.13-13.30; P<0.001) in quintile 3, and 14.47 (95% CI, 8.20-25.54; P<0.001) in quintile 4 compared with the lowest risk quintile. When the highest risk quintile was subdivided into 2 equally sized risk strata (deciles 9 and 10), the adjusted odds ratios for 30-day mortality were 27.20 (95% CI, 15.33-48.27; P<0.001) in decile 9 and 58.96 (95% CI, 33.54-103.65; P<0.001) in highest risk decile 10. CONCLUSIONS: Presence of ST-depression on the ECG reclassified risk of 30-day mortality in patients with acute heart failure, identifying both high- and low-risk subsets.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".