Cardiac-Resynchronization Therapy for Mild-to-Moderate Heart Failure
Bibliographic record
Abstract
BACKGROUND: Cardiac-resynchronization therapy (CRT) benefits patients with left ventricular systolic dysfunction and a wide QRS complex. Most of these patients are candidates for an implantable cardioverter-defibrillator (ICD). We evaluated whether adding CRT to an ICD and optimal medical therapy might reduce mortality and morbidity among such patients. METHODS: We randomly assigned patients with New York Heart Association (NYHA) class II or III heart failure, a left ventricular ejection fraction of 30% or less, and an intrinsic QRS duration of 120 msec or more or a paced QRS duration of 200 msec or more to receive either an ICD alone or an ICD plus CRT. The primary outcome was death from any cause or hospitalization for heart failure. RESULTS: We followed 1798 patients for a mean of 40 months. The primary outcome occurred in 297 of 894 patients (33.2%) in the ICD-CRT group and 364 of 904 patients (40.3%) in the ICD group (hazard ratio in the ICD-CRT group, 0.75; 95% confidence interval [CI], 0.64 to 0.87; P<0.001). In the ICD-CRT group, 186 patients died, as compared with 236 in the ICD group (hazard ratio, 0.75; 95% CI, 0.62 to 0.91; P = 0.003), and 174 patients were hospitalized for heart failure, as compared with 236 in the ICD group (hazard ratio, 0.68; 95% CI, 0.56 to 0.83; P<0.001). However, at 30 days after device implantation, adverse events had occurred in 124 patients in the ICD-CRT group, as compared with 58 in the ICD group (P<0.001). CONCLUSIONS: Among patients with NYHA class II or III heart failure, a wide QRS complex, and left ventricular systolic dysfunction, the addition of CRT to an ICD reduced rates of death and hospitalization for heart failure. This improvement was accompanied by more adverse events. (Funded by the Canadian Institutes of Health Research and Medtronic of Canada; ClinicalTrials.gov number, NCT00251251.).
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".