Corrected QT Interval Prolongation, Elevated Troponin, and Mortality in Hospitalized COVID-19 Patients
Bibliographic record
Abstract
BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has risen to the level of a global pandemic. Growing evidence has proven the cardiac involvement in SARS-CoV-2 infection. This study aims to evaluate the ability of cardiovascular complications determined by elevated troponin and electrocardiogram findings (e.g., corrected QT interval (QTc)) in predicting the severity of SARS-CoV-2 infection among hospitalized patients. METHODS: This is a retrospective review of medical records of 800 patients, admitted to Richmond University Medical Center in Staten Island, NY, and tested positive for SARS-CoV-2 between March 1, 2020 and July 31, 2020. A total of 339 patients met the study inclusion and exclusion criteria and were included in statistical analysis. RESULTS: Elevated serum troponin levels on admission statistically correlated with mortality in SARS-CoV-2 patients. Prolonged QTc was shown to have an independent statistically significant association with mortality among patients hospitalized with SARS-CoV-2. CONCLUSIONS: Growing concern for cardiovascular sequelae of coronavirus disease 2019 (COVID-19) has prompted many researchers to investigate the role of cardiovascular complications in mortality due to SARS-CoV-2. Obtaining a simple electrocardiogram for hospitalized patients with COVID-19 could provide an independent prognostic tool and prompt more coordinated treatment strategies to prevent mortality among patients hospitalized with COVID-19.
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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 | 0.219 |
| 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 | 0.001 |
| 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".