Clinical spectrum of COVID-19 complications in young adults: combined analysis of the American Heart Association COVID-19 Cardiovascular Disease Registry and the Outcomes Registry for Cardiac Conditions in Athletes
Bibliographic record
Abstract
BACKGROUND: While young adults 18-24 years old bear a significant proportion of COVID-19 diagnoses, the risk factors for hospitalisation and severe COVID-19 complications in this population are poorly understood. OBJECTIVE: The objective of this study was to identify risk factors for hospitalisation and other COVID-19 complications across the health spectrum of young adults diagnosed with COVID-19 infection. STUDY DESIGN: Retrospective cohort study. PARTICIPANTS: Young adults (aged 18-24) with confirmed COVID-19 infection from the American Heart Association (AHA) COVID-19 Cardiovascular Disease Registry of hospitalised patients and the Outcomes Registry for Cardiac Conditions in Athletes (ORCCA) study of collegiate athletes. The AHA registry included 636 young adults from 152 hospitals. The ORCCA registry consisted of 3653 competitive college athletes from 42 colleges and universities. INTERVENTION: None (exposure to COVID-19). PRIMARY AND SECONDARY OUTCOME MEASURES: Main outcomes included hospitalisation, death, major adverse cardiovascular events (MACE) and other severe clinical events. RESULTS: In comparison to the ORCCA registry, patients in the AHA registry were more likely to be female (59% vs 33%); had higher average body mass index (BMI) (32.4 vs 25.6); and had increased prevalence of diabetes (10% vs 0.4%), hypertension (7% vs 0.6%), chronic kidney disease (2% vs 0%) and asthma (14% vs 8%), all with p<0.01. There were eight (2%) deaths in the AHA hospitalised registry compared with zero in the ORCCA cohort. BMI was a statistically significant predictor of death in the hospitalised cohort (OR 1.05, 95% CI 1.00, 1.10). No significant predictors of MACE or other severe clinical events were identified. CONCLUSIONS: The risk of cardiac events in young adults aged 18-24 diagnosed with COVID-19 infection is low. Patients who were hospitalised (AHA registry) were more likely to have pre-existing medical comorbidities and higher BMI than healthy collegiate athletes (ORCCA registry). Once hospitalised, elevated BMI is associated with increased mortality although other drivers of MACE and other severe clinical events remain unclear.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".