Predictors of Premature Ventricular Contractions Development in Patients With SARS-CoV-2 Infection
Bibliographic record
Abstract
Background: Epidemiological studies have demonstrated that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-positive patients often develop atrial fibrillation, premature ventricular contractions (PVCs), and conduction disorders. The manifestation of ventricular cardiac arrhythmias accentuates the risk of sudden cardiac death. Methods: A retrospective study was conducted on the cohort of 1,614 patients admitted for coronavirus disease 2019 (COVID-19). Patients were categorized into two groups based on the occurrence of PVCs. Group I comprised 172 patients diagnosed with PVCs of Lown-Wolf class II - IV upon hospital admission; group II (control group) consisted of 1,442 patients without this arrhythmia. Each patient underwent comprehensive clinical, laboratory, and instrumental evaluations. Results: The emergence of PVCs in individuals afflicted with COVID-19 was associated with a 5.879-fold heightened risk of lethal outcome, a 2.904-fold elevated risk of acute myocardial infarction, and a 2.437-fold increased risk of pulmonary embolism. Upon application of diagnostic criteria to evaluate the "cytokine storm", it was discovered that the occurrence of the "cytokine storm" was notably more frequent in the group with PVCs, manifesting in six patients (3.5%), compared to 16 patients (1.1%) in the control group (P < 0.05). The mean extent of lung tissue damage in group I was significantly greater than that of patients in group II (P < 0.05). Notably, the average oxygen saturation level, as measured by pulse oximetry upon hospital admission was 92.63±3.84% in group I and 94.20±3.50% in group II (P < 0.05). Conclusions: The presence of PVCs in COVID-19 patients was found to elevate the risk of cardiovascular complications. Significant independent predictors for the development of PVCs in patients with SARS-CoV-2 infection include: age over 60 years (risk ratio (RR): 4.6; confidence interval (CI): 3.2 - 6.5), a history of myocardial infarction (RR: 3.5; CI: 2.6 - 4.6), congestive heart failure (CHF) with reduced left ventricular ejection fraction (RR: 5.5; CI: 3.9 - 7.6), respiratory failure (RR: 2.3; CI: 1.7 - 3.1), and the presence of a "cytokine storm" (RR: 4.5; CI: 2.9 - 6.0).
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".