Incidence, clinical features, and outcomes of COVID-19 in Canada: impact of sex and age
Bibliographic record
Abstract
Male sex and older age have been reported to be associated with worse outcomes from COVID-19. It was postulated that estrogens may play a role in reducing the severity of the disease and may therefore offer a treatment option for COVID-19 patients. However, more female cases and deaths from COVID-19 have been recorded in Canada. To determine the potential role of estrogens, we analyzed COVID-19 data from Canada, focusing on the impact of sex and age. Although the overall incidence rate is higher in females than in males, when several high risk groups, including health care workers and long-term care residences, which are predominantly females, were excluded, we found that females had a lower incidence rate than males between the ages of 20s to 70s. Interestingly, this sex-based difference is more evident in females of the reproductive ages (20-49) than in postmenopausal patients (60s or older). Males have significantly higher hospitalization, ICU admission, and case fatality rates; however, a greater difference was observed in the older age groups. Finally, symptom manifestation varied between sexes. Some of the symptoms, which were more frequently observed in patients who recovered than patients who died, were more commonly observed in females of the reproductive age compared to their male counterparts. Since only females of the reproductive age have much higher circulating estrogens than males, these findings suggest that estrogens may play a role in reducing COVID-19 incidence and in the development of symptoms, especially those related to better survival.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".