Short Report: Hospitalization for New-Onset Heart Failure in Survivors of Hospitalized COVID-19
Bibliographic record
Abstract
AIMS: Previous studies have reported an incidence of new-onset heart failure (HF) among COVID-19 survivors ranging from 0.7 to 8.5 per 100 person-years, but they relied on administrative data for outcome ascertainment. Given the public health implications, a more accurate characterization of the HF burden post-COVID-19 is important. METHODS AND RESULTS: We conducted a prospective cohort study of survivors of hospitalized COVID-19 and tracked the incidence of new-onset HF hospitalizations over the 12-month period following the index COVID-19 episode. Outcome ascertainment was based on a combination of chart reviews, patient interviews, and pre-specified clinical, radiographic and laboratory criteria. We identified 2140 survivors of COVID-19 hospitalization that were free of HF at the time of discharge. Their mean age was 67 years and 48% were Black/African-Americans. The incidence rate of hospitalized new-onset HF was 0.5 per 100 person-years. Higher BMI and dialysis dependency at baseline were significantly associated with HF development. The 1-year mortality rate was 3%. CONCLUSIONS: The incidence of new-onset HF post-COVID-19 in our study was lower than in previous reports, despite involving an older population with more comorbidities and/or more severe COVID-19 overall. Reliance on administrative data for outcome adjudication in prior studies may have led to an overestimation of the HF burden post-COVID-19.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".