Single Center Trends in Acute Coronary Syndrome Volume and Outcomes During the COVID-19 Pandemic
Bibliographic record
Abstract
BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has greatly affected healthcare delivery across the world. In this report, we aim to further characterize the changes in cardiac catheterization at our institution, specifically in the setting of acute coronary syndrome (ACS). METHODS: We performed a retrospective analysis of patients undergoing cardiac catheterization between December 23, 2019 and April 12, 2020 at our institution. All patients with cardiac catheterizations for ACS, ST-elevation myocardial infarction (STEMI) activation, and out-of-hospital cardiac arrest (OHCA) were analyzed. Cardiac catheterization volume, as well as clinical and procedural characteristics of patients undergoing cardiac catheterization, was compared before and during the COVID-19 pandemic. RESULTS: Patients presenting with ACS and OHCA were similar in terms of demographics and comorbidities during both time periods. The mean monthly volume for ACS cases dropped by 26% during the pandemic, which was consistent among both unstable angina/non-ST-elevation myocardial infarction (UA/NSTEMI) and STEMI cases. OHCA volume decreased significantly as well (five cases per month before to zero cases during the pandemic, P = 0.01). Among patients with STEMI, initial markers of cardiac injury, door-to-balloon time, and all-cause mortality were similar in both time periods. CONCLUSIONS: With the start of the COVID-19 pandemic, there was a reduction in cardiac catheterization volume across the spectrum of ACS at our institution, which was consistent with reports from other centers across the globe. Patients with STEMI during the initial phase of the COVID-19 pandemic did not seem to have delays in presentation or significant differences in all-cause mortality at our institution.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".