Bibliographic record
Abstract
PURPOSE OF REVIEW: Cardiac resynchronization therapy (CRT) can reduce morbidity and mortality in patients with heart failure. However, a proportion of patients do not respond to CRT. This review addresses important clinical questions regarding patient selection for CRT. RECENT FINDINGS: Three recent large randomized trials show that CRT reduces morbidity and mortality in patients with New York Heart Association (NYHA) functional class II heart failure. Observational studies and a recent meta-analysis suggest that patients with NYHA III heart failure and atrial fibrillation may benefit from CRT. However, atrioventricular node ablation should be considered in this population to ensure greater than 92% biventricular pacing. Data from clinical trials do not support the use of CRT in patients with baseline right bundle branch block (RBBB). SUMMARY: Careful selection of CRT candidates is vital to improve patient outcomes and reduce exposure to unnecessary complications. This review summarizes recent data on the selection of CRT candidates, with emphasis on patients with NYHA I and II heart failure, atrial fibrillation and RBBB.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.006 |
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".