Cardiac Remodelling Predicts Outcome in Patients with Chronic Heart Failure
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Bibliographic record
Abstract
AIMS: Surveillance imaging is often used to detect remodelling, a change in cardiac geometry, and/or function; however, there are limited data in patients with chronic heart failure (HF). We sought to characterize cardiac remodelling in patients with chronic HF and evaluate its association with outcome. METHODS AND RESULTS: A prospective cohort of patients at risk for HF or with chronic HF underwent cardiac magnetic resonance (CMR) at baseline and 1 year. Ventricular function, volumes, mass, left atrial volume, global longitudinal strain, and myocardial scar were measured. The primary outcome was a composite of death or cardiovascular hospitalization up to 5 years from the 1 year scan. Cox regression was used to identify 1 year CMR predictors of outcome after adjusting for baseline risk. A total of 262 patients (median age 68 years, 57% males) including 96 at risk for HF, 97 with HF and preserved ejection fraction, and 69 with HF and reduced ejection fraction were included. In the patients with HF, 55 events were identified during follow-up. After adjustment for baseline clinical risk, Cox proportion hazard regressions only identified 1 year change in left ventricular (LV) mass index as a CMR predictor of outcome, adjusted hazard ratio 1.21 (1.02, 1.44) per 10% increase, P = 0.031. Cardiac remodelling defined as a 1 year change in LV mass index ≥15% was observed in 35% of patients with HF. Patients with adverse remodelling of LV mass index had more events on Kaplan-Meier analyses compared to those with no remodelling, log-rank P = 0.004 for overall cohort, P = 0.035 for heart failure with preserved ejection fraction and P = 0.035 for heart failure and reduced ejection fraction. CONCLUSIONS: Cardiac remodelling is common during serial CMR assessment of patients with chronic HF. Change in LV mass predicted long-term outcomes whereas change in left ventricular ejection fraction did not.
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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 | 0.000 | 0.000 |
| 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 it