Cardiovascular Outcomes in Nova Scotia During the Early Phase of the COVID-19 Pandemic
Bibliographic record
Abstract
Background This study sought to determine the impact of the COVID-19 pandemic response to healthcare delivery on outcomes in patients with cardiovascular disease. Methods This is a population-based cohort study performed in the province of Nova Scotia, Canada (population 979,499), between the pre-COVID (March 1, 2017-March 16, 2020) and in-COVID (March 17, 2020-December 31, 2020) periods. Adult patients (age ≥ 18 years) with new-onset or existing cardiovascular disease were included for comparison between periods. The main outcome measures included the following: cardiovascular emergency department visits or hospitalizations, mortality, and out-of-hospital cardiac arrest. Results In the first month of the in-COVID period, emergency department visits (n = 51,750) for cardiac symptoms decreased by 20.8% (95% confidence interval [CI] 14.0%-27.0%, P < 0.001). Cardiovascular hospitalizations (n = 20,609) declined by 48.1% (95% CI 40.4% to 54.9%, P < 0.001). The in-hospital mortality rate increased in patients with cardiovascular admissions in secondary care institutions by 55.1% (95% CI 10.1%-118%, P = 0.013). A decline of 20.4%-44.0% occurred in cardiovascular surgical/interventional procedures. The number of out-of-hospital cardiac arrests (n = 5528) increased from a monthly mean of 115 ± 15 to 136 ± 14, beginning in May 2020. Mortality for ambulatory patients awaiting cardiac intervention (n = 14,083) increased from 0.16% (n = 12,501) to 2.49% (n = 361) in the in-COVID period ( P < 0.0001). Conclusions This study demonstrates increased cardiovascular morbidity and mortality during restrictions maintained during the COVID-19 period, in an area with a low burden of COVID-19. As the healthcare system recovers or enters subsequent waves of COVID-19, these findings should inform communication to the public regarding cardiovascular symptoms, and policy for delivery of cardiovascular care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".