Emergency Visits or Hospitalizations for Cardiovascular Diagnoses in the Post-Acute Phase of COVID-19
Bibliographic record
Abstract
Background: Prior studies of COVID-19 cardiovascular sequelae include diagnoses made within 4 weeks, but the World Health Organization definition for "postacute phase" is >3 months. Objectives: The purpose of this study was to determine which cardiovascular diagnoses in the postacute phase of COVID-19 are associated with SARS-CoV-2 infection. Methods: Retrospective cohort study of all adults in Alberta who had a positive SARS-CoV-2 reverse transcription polymerase chain reaction test between March 1, 2020 and June 30, 2021, matched (by age, sex, Charlson Comorbidity score, and test date) with controls who had a negative reverse transcription polymerase chain reaction test. Results: The 177,892 patients with laboratory confirmed SARS-CoV-2 infection (mean age 42.7 years, 49.7% female) were more likely to visit an emergency department (5.7% vs 3.3%), be hospitalized (3.4% vs 2.1%), or die (1.3% vs 0.4%) within 1 month than matched test-negative controls. After 3 months, cases were significantly more likely than controls to have an emergency department visit or hospitalization for diabetes mellitus (1.5% vs 0.7%), hypertension (0.6% vs 0.4%), heart failure (0.2% vs 0.1%), or kidney injury (0.3% vs 0.2%). In the 6,030 patients who had survived a hospitalization for COVID-19, postacute phase risks were substantially greater for diabetes mellitus (9.5% vs 3.0%, adjusted odds ratio [aOR]: 3.16 [95% CI: 2.43-4.12]), hypertension (3.5% vs 1.4%, aOR: 2.89 [95% CI: 1.97-4.23]), heart failure (2.1% vs 0.7%, aOR: 3.16 [95% CI: 1.88-5.29]), kidney injury (3.1% vs 0.8%, aOR: 2.70 [95% CI: 1.71-4.28]), bleeding (1.5% vs 0.5%, aOR: 3.40 [95% CI: 1.83-6.32]), and venous thromboembolism (0.8% vs 0.3%, aOR: 3.60 [95% CI: 1.59-8.13]). Conclusions: Clinicians should screen COVID-19 survivors for diabetes mellitus, hypertension, heart failure, and kidney dysfunction in the postacute phase.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".