Beta-blocker and calcium-channel blocker therapy in patients with cardiovascular pathologies during post-COVID period
Bibliographic record
Abstract
Early in 2020, the infection caused by SARS-CoV-2 emerged and caused the COVID-19 pandemic. For a long time, management of patients with the acute novel coronavirus infection was of primary importance. With accumulation of clinical information and data on the causative agents of novel coronavirus infection it became obvious that the COVID-19 consequences and post-hospital follow-up of patients are important as well. Due to the direct and mediated cardiac toxicity of SARS-CoV-2 virus, cardiovascular patients are at high risk at any stage of the disease. Therefore, one of the priorities for healthcare professionals is development of the ways to improve the quality and prognosis of life for cardiovascular patients in the post-COVID period. The article discusses large-scale studies including the data from the International Register «Analysis of Chronic Non-infectious Diseases Dynamics After COVID-19 Infection in Adult Patients» (AСTIV-SARS-CoV-2), as regards drug therapy of cardiovascular patients with a focus on beta-blockers and calcium-channel blockers. In mentioned publications, beta-blocker therapy demonstrated favourable impact on the novel coronavirus infection severity in cardiovascular patients, reduction in mortality rates during the hospital and post-hospital periods. Data on the use of calcium-channel blockers have been studied to a lesser extent; however, calcium-channel blockers are thought to be one of the most commonly prescribed groups in the therapy of patients with persistent complaints of high blood pressure at the post-hospital period. A study of the impact of some categories of antihypertensives on the outcome for cardiovascular patients with COVID-19 is warranted.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| 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".