Prognosis of nonspecific ST-segment changes, T wave abnormalities and Q waves in patients visiting emergency departments for acute decompensated heart failure: a cohort study
Bibliographic record
Abstract
Purpose: To determine the risk of 30-day mortality associated with specific ECG abnormalities in patients visiting emergency departments (ED) with acute decompensated heart failure (ADHF). Methods: Population-based prospective cohort of 9,017 HF patients, visiting EDs between 2004-2007 in Ontario, Canada. We evaluated ST depression, Q waves, T wave inversions or its combinations in the presenting ECG. We used multivariable logistic regression models to adjust for variables in the EHMRG score and other variables of clinical importance, including troponin I levels. Patients with major ECG alterations were excluded from the final analysis. Results: ECG alterations were present in 54.9% of the subjects. The mean age was 75.84±11.79 years, 53.4% were female, and 52.7% had HF of ischemic etiology. The prevalence of diabetes and arterial hypertension was 38.2 and 66.4%, respectively and 27% of the patients were discharged home from the ED. In the overall cohort, the presence of T wave inversion (adjusted odds ratio [OR]: 1.34; 95% Confidence interval [CI]: 1.02-1.74) and the concomitancy of ST depression + Q wave (OR: 1.92; CI: 1.14-3.24) were independently associated with mortality. Meanwhile, in patients with ischemic etiology, the presence of ST depression (OR: 1.87; CI: 1.18-2.95) and the combinations of ST depression + Q wave (OR: 2.36; CI: 1.23-4.55) and ST depression + T wave inversion (OR: 1.63; CI: 1.06-2.50) were significant. Moreover, in patients that were discharged home, the presence of combined ST depression + T wave inversion was associated with a poor prognosis (OR: 2.26, CI: 1.13-4.49). Conclusions: Isolated or combined minor ECG alterations were associated with an increased risk of mortality at 30 days in patients presenting to ED with ADHF. These findings are particularly relevant in patients with ischemic etiology, where ST depression was independently associated with mortality. The ECG may assist in clinical decision making of decompensated patients with heart failure in the setting of the ED.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".