Evaluation of the Existence of Post-COVID-19 Tachycardia in a Community Healthcare System
Bibliographic record
Abstract
Background: Post-coronavirus disease 2019 (COVID-19) syndrome derives from lingering symptoms after an acute COVID-19 infection. Palpitation was one of the most common symptoms of post-COVID-19 syndrome that correlated with objective data such as persisting sinus tachycardia; but to our best knowledge, there is a scarcity of research regarding the association of COVID-19 and sinus tachycardia in the post-acute setting. Therefore, the purpose was to identify if there is an association between COVID-19 infection and sinus tachycardia in the post-acute phase, namely post-COVID-19 tachycardia (PCT) other than inappropriate sinus tachycardia (IST) and postural orthostatic tachycardia syndrome (POTS). Methods: This retrospective observational study entails 1,425 patients admitted for COVID-19 infection with the interest in finding an association with PCT. The prevalence of PCT was evaluated using descriptive statistics, predictions of patient characteristics and comorbidities were identified using multinomial logistic regression, and associations between patient comorbidities and characteristics were evaluated with corresponding Pearson Chi-square test and post hoc tests Phi and Cramer's V. Results: The percentage of patients with PCT in our sample of interest was an average of 28.18%. There was a strong association of PCT with patients of age group less than 65 years. Other clinical characteristics, such as shorter length of stay, unknown smoking status, and patients with commercial type insurance, had significant association with PCT. COVID-19 severity categorized as "less severe", readmission rates within 30 days, and patients with less comorbidities were more likely to be associated with PCT. Conclusions: PCT is likely a separate entity from IST and POTS, and an important entity under the umbrella of post-COVID-19 syndrome. It warrants further studies to elucidate the underlying pathophysiology and to confirm its presence as a distinct entity.
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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 | 0.023 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".