Post-COVID Syndrome and Tachycardia: Theoretical Base and Treatment Experience
Bibliographic record
Abstract
The coronavirus pandemic showed not only an increase in levels of excess morbidity and mortality in the acute phase, but also persisting symptoms 4 weeks after the onset of the disease. A review of international studies on the prevalence and diversity of the manifestations of postcoid syndrome is presented. The data on such a manifestation of post-COVID syndrome as postural orthostatic tachycardia syndrome (POTS) are accumulating. Pathogenetic mechanisms, modern diagnostic criteria and research data on the prevalence of this syndrome are presented in the article. The Canadian Cardiovascular Society has proposed medications as a treatment for POTS, including the sinus node If channel inhibitor ivabradine. Data from several studies showing the effectiveness of this drug for POTS, including after suffering COVID-19, are presented in the article. Clinical data on the prevalence of tachycardia among patients admitted to the Sechenov University hospital are presented. About 18% of patients with hypertension and 21% of patients with normal blood pressure had a high heart rate. A clinical example of the use of ivabradine in a patient after a coronavirus infection is presented. Drug interactions and individual tolerance of ivabradine in patients after coronavirus infection are being discussed. The authors put forward the hypothesis about the further prospect of using ivabradine in the treatment of clinical manifestations of postcoid syndrome on the basis of literature data and their own experience.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".