Increased Mortality in Patients With Acutely Decompensated Heart Failure During the COVID-19 Pandemic in Toronto, Canada
Bibliographic record
Abstract
Background: Coronavirus disease 2019 (COVID-19) has resulted in a reduction in patients seeking timely consultation for illnesses that are not related to COVID-19. Previously, we reported a decline in the number of emergency department (ED) visits and hospitalizations for acute decompensated heart failure (ADHF) during the 2020 COVID-19 pandemic vs that in 2019. We aimed to determine the consequences of these early trends on ADHF-patient morbidity and mortality. Methods: We compared consecutive patients presenting with ADHF to 3 academic medical centres in Toronto, Canada from March 1-September 28, 2020, vs those from the same time period in 2019. We used multivariate logistic regression models to evaluate whether the odds of hospitalization after presenting to the ED, recurrent ED visits or readmission within 30 days, and in-hospital all-cause mortality differed by timeframe. Results: We observed that, during the COVID-19 pandemic, a lower total number of patients presented to the hospital with ADHF, vs that in 2019. Despite this difference, the probability of being admitted to the hospital did not differ for patients seen in 2020 vs 2019. Among ADHF patients admitted to the hospital, however, we observed a significantly higher proportion being admitted to the intensive care unit, and a relative 66% increase in in-hospital mortality during the 2020 COVID-19 era, compared to that in 2019. Conclusions: Our findings suggest that improved messaging may be needed for patients living with chronic health conditions, including HF, during the pandemic, to educate and encourage them to present to hospital services when in need.
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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 | 0.000 |
| 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 | 0.000 |
| 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 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".