Prognostic importance of temporal changes in resting heart rate in heart failure patients: an analysis of the CHARM program
Bibliographic record
Abstract
BACKGROUND: Resting heart rate (HR) is a predictor of adverse outcome in patients with heart failure (HF). Whether changes in HR over time in patients with chronic HF are also associated with adverse outcome is unknown. We explored the relationship between changes in HR from a preceding visit, time-updated HR (i.e. most recent available HR value from a clinic visit) and subsequent outcomes in patients with chronic HF. METHODS AND RESULTS: We studied 7599 patients enrolled in the candesartan in heart failure: assessment of reduction in mortality and morbidity program. We calculated change in HR from the preceding visit and explored its association with outcomes in Cox proportional hazards models, as well the association between time-updated HR and outcome. An increase in HR from preceding visit was associated with a higher risk of all-cause mortality and the composite endpoint of cardiovascular death or hospitalization for HF (adjusted hazard ratio 1.06, 95% confidence intervals, CI: 1.05-1.08, P < 0.001, per 5 b.p.m. higher HR), with lowering of HR being associated with lower risk, adjusting for covariates, including time-updated β-blocker dose and baseline HR. Time-updated resting HR at each visit was also associated with risk (adjusted hazard ratio 1.07, 95% CI: 1.06-1.09; P < 0.001, per 5 b.p.m. higher HR). CONCLUSIONS: Change in HR over time predicts outcome in patients with chronic HF, as does time-updated HR during follow-up. These data suggest that frequent outpatient monitoring of HR, and identification of changes over time, possibly with remote technologies, may identify patients with HF who may be at increased risk of rehospitalization or death.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".