Differential trajectories in LVEF predicts divergent clinical outcomes in HFrEF patients
Bibliographic record
Abstract
Abstract Background Recovery or improvement in LVEF is observed in many HFrEF patients following optimal medical management and device therapies, but whether this reflects true myocardial recovery remains controversial and the significance of LVEF decompensation in relation to clinical outcomes is unclear. Purpose To elucidate clinical characteristics and assess prognosis of HFrEF patients with differential trajectories in LVEF. Methods Heart failure (HF) patients were enrolled in a prospective Heart Function registry from outpatient cardiology clinics at an academic institution between Feb 2018 and Nov 2019. Retrospective analysis was conducted on 2D-echocardiography (echo) performed between Jan 2009 and Nov 2019. In total, 590 patients met the inclusion criteria with ≥2 repeated echo evaluations separated by ≥1 year. Patient demographics and clinical characteristics at enrollment were collected through review of medical records. Cardiovascular and HF specific admissions were captured using the corresponding ICD-10-CA codes. During a median follow-up of 5.9 years (IQR: 3.1 to 8.5 years) from the first echo date, clinical outcomes were assessed through composite mortality and hospitalizations endpoints. Results We identified 3 independent cohorts with 279 patients having permanently reduced LVEF (<40%, HFrEF), 236 patients with recovered LVEF (>40% on serial evaluations, HFrecEF) and 75 patients with subsequent decompensation in LVEF (>40%, then <40%, HFdecEF) following initial recovery. Use of ACE inhibitors or ARBs (94% vs. 99% vs. 91%) and beta blockers (88% vs. 87% vs. 87%) at baseline echo was similar amongst HFrEF, HFrecEF and HFdecEF cohorts respectively. HFrecEF cohort had higher usage of MRA (55% vs. 65% vs. 44%, p=0.002) and diuretics (74% vs. 80% vs. 65%, p=0.026). HFdecEF cohort was characterized by a predominance of males (80% vs. 69% vs. 80%, p=0.01), and more patients with ischemic etiology (41% vs. 28% vs. 60%, p<0.001) compared with the HFrecEF cohort and resembled more closely to demographics of the HFrEF cohort. Median LVEF at baseline echo was similar across the cohorts. However, HFdecEF cohort had lower LV end-diastolic diameter (p<0.001), LV end-systolic diameter (p<0.001) and LV mass (p=0.01) compared with the HFrEF cohort sharing similarities with the HFrecEF cohort on baseline echo, suggesting lesser extent of adverse cardiac remodeling in both HFrecEF and HFdecEF cohorts initially. Over a median 5.9 years follow-up, HFdecEF and HFrEF patients had a significantly higher risk (compared to those with HFrecEF) of composite all-cause mortality with all-cause (80% vs. 75% vs. 57%, p=0.004), cardiovascular (48% vs. 50% vs. 29%, p=0.001) and HF hospitalizations (31% vs. 32% vs. 16%, p=0.004). Conclusion HFrEF patients who never recover their LVEF and patients with decompensation in LVEF following initial recovery represent a clinically higher risk group than patients who remained recovered during follow-up. Funding Acknowledgement Type of funding source: Foundation. Main funding source(s): University of Alberta Hospital Foundation, Canadian Institutes of Health Research
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".