Hospital admissions during Covid-19 lock-down in Germany: Differences in discretionary and unavoidable cardiovascular events
Bibliographic record
Abstract
BACKGROUND: A decline in hospitalization for cardiovascular events and catheter laboratory activation was reported for the United States and Italy during the initial stage of the Covid-19 pandemic of 2020. We report on the deployment of emergency services for cardiovascular events in a defined region in western Germany during the government-imposed lock-down period. METHODS: We examined 5799 consecutive patients who were treated by emergency services for cardiovascular events during the Covid-19 pandemic (January 1 to April 30, 2020), and compared those to the corresponding time frame in 2019. Examining the emergency physicians' records provided by nine locations in the area, we found a 20% overall decline in cardiovascular admissions. RESULTS: The greatest reduction could be seen immediately following the government-imposed social restrictions. This reduction was mainly driven by a reduction in discretionary admissions for dizziness/syncope (-53%), heart failure (-38%), exacerbated COPD (-28%) and unstable angina (-23%), while unavoidable admissions for ST-elevation myocardial infarction (STEMI), cardiopulmonary resuscitation (CPR) and stroke were unchanged. There was a greater decline in emergency admissions for patients ≥60 years. There was also a greater reduction in emergency admissions for those living in urban areas compared to suburban areas. CONCLUSIONS: During the Covid-19 pandemic, a significant decline in hospitalization for cardiovascular events was observed during the government-enforced shutdown in a predefined area in western Germany. This reduction in admissions was mainly driven by "discretionary" cardiovascular events (unstable angina, heart failure, exacerbated COPD and dizziness/syncope), but events in which admission was unavoidable (CPR, STEMI and stroke) did not change.
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".