Different Patterns of Bundle-Branch Blocks and the Risk of Incident Heart Failure in the Women’s Health Initiative (WHI) Study
Bibliographic record
Abstract
BACKGROUND: We evaluated the risk of incident heart failure (HF) associated with bundle-branch blocks (BBBs) in postmenopausal women. METHODS AND RESULTS: Cox's regression was used to evaluate hazard ratios with 95% confidence intervals for HF among 65975 participants of the Women's Health Initiative (WHI) study during an average follow-up of 14 years. BBBs observed in 1676 women at baseline were categorized into left, right, and indetermined-type BBBs (LBBB, RBBB, and intraventricular conduction defect, respectively). Compared with women with no BBB, LBBB, and intraventricular conduction defect were strong predictors of incident HF in multivariable-adjusted risk models (hazard ratio, 3.79; confidence interval, 2.95-4.87 for LBBB and hazard ratio, 3.53; confidence interval, 2.14-5.81 for intraventricular conduction defect). RBBB was not a significant predictor of incident HF in multivariable-adjusted risk model, but the combination of RBBB and left anterior fascicular block was a strong predictor (hazard ratio, 2.96; confidence interval, 1.77-4.93). QRS duration was an independent predictor of incident HF only in LBBB, with more pronounced risk at QRS ≥ 140 ms than at <140 ms. QRS nondipolar voltage (RNDPV) was an independent predictor in both RBBB and LBBB and, in addition, in LBBB, QRS/STT angle and ST J-point depression in aVL were independent predictors. CONCLUSIONS: LBBB, intraventricular conduction defect, and RBBB combined with left anterior fascicular block are strong predictors of incident HF in multivariable-adjusted risk models, but RBBB is not a significant predictor. QRS duration ≥ 140 ms may warrant consideration in LBBB as an indication for further diagnostic evaluation for possible therapeutic and preventive action. Clinical Trial Registration- URL: http://www.clinicaltrials.gov. Unique identifier: NCT00000611.
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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 | 0.001 | 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 | 0.000 |
| 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".