Substantial decline in hospital admissions for heart failure accompanied by increased community mortality during COVID-19 pandemic
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Bibliographic record
Abstract
AIMS: We hypothesized that a decline in admissions with heart failure during COVID-19 pandemic would lead to a reciprocal rise in mortality for patients with heart failure in the community. METHODS AND RESULTS: We used National Heart Failure Audit data to identify 36 974 adults who had a hospital admission with a primary diagnosis of heart failure between February and May in either 2018, 2019, or 2020. Hospital admissions for heart failure in 2018/19 averaged 160/day but were much lower in 2020, reaching a nadir of 64/day on 27 March 2020 [incidence rate ratio (IRR): 0.40, 95% confidence interval (CI): 0.38-0.42]. The proportion discharged on guideline-recommended pharmacotherapies was similar in 2018/19 compared to the same period in 2020. Between 1 February-2020 and 31 May 2020, there was a 29% decrease in hospital deaths related to heart failure (IRR: 0.71, 95% CI: 0.67-0.75; estimated decline of 448 deaths), a 31% increase in heart failure deaths at home (IRR: 1.31, 95% CI: 1.24-1.39; estimated excess 539), and a 28% increase in heart failure deaths in care homes and hospices (IRR: 1.28, 95% CI: 1.18-1.40; estimated excess 189). All-cause, inpatient death was similar in the COVID-19 and pre-COVID-19 periods [odds ratio (OR): 1.02, 95% CI: 0.94-1.10]. After hospital discharge, 30-day mortality was higher in 2020 compared to 2018/19 (OR: 1.57, 95% CI: 1.38-1.78). CONCLUSION: Compared with the rolling daily average in 2018/19, there was a substantial decline in admissions for heart failure but an increase in deaths from heart failure in the community. Despite similar rates of prescription of guideline-recommended therapy, mortality 30 days from discharge was higher during the COVID-19 pandemic period.
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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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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