O Impacto da COVID-19 no Diagnóstico de Doenças Cardíacas na América Latina Uma Subanálise do INCAPS COVID
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic has disrupted the delivery of care for cardiovascular diseases in Latin America. However, the effect of the pandemic on the cardiac diagnostic procedure volumes has not been quantified. OBJECTIVE: To assess (1) the impact of COVID-19 on cardiac diagnostic volumes in Latin America and (2) determine its relationship with COVID-19 case incidence and social distancing measures. METHODS: The International Atomic Energy Agency conducted a worldwide survey assessing changes in cardiac diagnostic volumes resulting from COVID-19. Cardiac diagnostic volumes were obtained from participating sites for March and April 2020 and compared to March 2019. Social distancing data were collected from Google COVID-19 community mobility reports and COVID-19 incidence per country from the Our World in Data. RESULTS: Surveys were conducted in 194 centers performing cardiac diagnostic procedures, in 19 countries in Latin America. Procedure volumes decreased 36% from March 2019 to March 2020, and 82% from March 2019 to April 2020. The greatest decreases occurred in echocardiogram stress tests (91%), exercise treadmill tests (88%), and computed tomography calcium scores (87%), with slight variations between sub-regions of Latin America. Changes in social distancing patterns (p < 0.001) were more strongly associated with volume reduction than COVID-19 incidence (p = 0.003). CONCLUSIONS: COVID-19 was associated with a significant reduction in cardiac diagnostic procedures in Latin America, which was more related to social distancing than to the COVID-19 incidence. Better balance and timing of social distancing measures and planning to maintain access to medical care is warranted during a pandemic surge, especially in regions with high cardiovascular mortality.
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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 | 0.065 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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; both teacher heads agree on what is shown here.
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".