Circulating Troponin and Further Left Ventricular Ejection Fraction Improvement in Patients with Previously Recovered Left Ventricular Ejection Fraction
Bibliographic record
Abstract
AIMS: The aim of this study is to determine factors associated with long-term recovery of left ventricular ejection fraction (LVEF) in patients with heart failure with reduced EF (HFrEF) and if further recovery also occurs in this group. METHODS AND RESULTS: Among 621 participants enrolled in the Alberta Heart Failure Etiology and Analysis Team (HEART) Study, 316 with Stage C HF underwent comprehensive imaging and biomarker testing at enrolment and at 1-year follow up. Using pre-enrolment data, HF with recovered EF (HFrecEF) was defined as an absolute improvement ≥5% in LVEF from the prior lowest LVEF value, with a final LVEF value > 35% at or prior to study baseline. Participants with all LVEF > 40% were included for comparison. Hospitalization-free survival to 5 years was performed. The median cohort age was 66 years, and time from diagnosis was 4 years; 82% were male patients. Of the 316 patients, 95 (30%) patients had HFrecEF and 56 (18%) patients pHFrEF. On multivariate analysis, only shorter duration of HF was predictive of HFrecEF status. Over 1 year, LVEF increased in the HFrecEF group 4.0% (0.15-7.90, P = 0.042) as compared with persistent HFrEF, who in turn demonstrated higher baseline serum high sensitivity Troponin-T with further increase at follow up 0.55(0.33-0.86, P = 0.011). No change in any parameter in the HFpEF/HFmrEF group at follow up was observed. CONCLUSIONS: Patients with HFrecEF demonstrate evidence of additional late improvement in LVEF and unchanged troponin levels, in contrast to those with persistent HFrEF, where LVEF does not improve and serum troponin rises over time. These data help to inform mechanisms relating to late LV remodelling.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".