Sudden Cardiac Death After Acute Heart Failure Hospital Admission: Insights from ASCEND-HF
Bibliographic record
Abstract
AIMS: The incidence of and factors associated with sudden cardiac death (SCD) early after an acute heart failure (HF) hospital admission have not been well defined. METHODS AND RESULTS: We assessed SCD and ventricular arrhythmias in the Acute Study of Clinical Effectiveness of Nesiritide in Decompensated Heart Failure (ASCEND-HF) trial, which included patients with acute HF with reduced or preserved ejection fraction. SCD, resuscitated SCD (RSCD), and sustained ventricular tachycardia/ventricular fibrillation (VT/VF) were adjudicated from randomization through 30 days and were combined into a composite endpoint. Baseline characteristics associated with this composite were determined by logistic regression. RSCD and VT/VF were included as time-dependent variables in a Cox model evaluating the association of these variables with 180-day all-cause mortality. Among 7011 patients, the 30-day all-cause mortality rate was 3.8%; SCD accounted for 17% of these deaths. The 30-day composite event rate was 1.8% (n = 121). Ten patients had more than one event with 30-day Kaplan-Meier event rates of 0.6% for SCD [95% confidence interval (CI) 0.5%-0.9%, n = 43], 0.4% for RSCD (95% CI 0.2%-0.5%, n = 24), and 0.9% for VT/VF (95% CI 0.7%-1.2%, n = 64). In the multivariable model, chronic obstructive pulmonary disease, history of VT, male sex, and longer QRS duration were associated with SCD, RSCD, or VT/VF. A RSCD or VT/VF event was associated with higher 180-day mortality (adjusted hazard ratio 6.6, 95% CI 4.8-9.1, P < 0.0001). CONCLUSIONS: Approximately 2% of patients admitted for acute HF experienced SCD, RSCD, or VT/VF within 30 days of admission, and SCD accounted for 17% of all deaths within 30 days.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".