Incidence of Venous Thromboembolism and Effect of Anticoagulant Dosing in Hospitalized COVID-19 Patients
Bibliographic record
Abstract
Background: Coronavirus disease 2019 (COVID-19) is characterized by coagulopathy and thrombotic events. We examined factors associated with development of venous thromboembolism (VTE) in COVID-19 and to discern if higher dose of anticoagulation was beneficial in these patients. Methods: This study involves an observational study of prospectively collected data in the setting of a large community hospital in a rural setting in Northeast Georgia with COVID-19 between March 1, 2020 and February 5, 2021. Anticoagulation dose (none, standard, intermediate, and therapeutic dosages) was studied in adult patients (≥ 18 years). We constructed multivariable logistic regression model to examine the association of clinical characteristics with VTE. To examine the effect of dose of anticoagulation in preventing VTE, we used inverse probability weighted regression adjustment. Results: Of the 4,645 patients with COVID-19, 251 (5.4%) patients were found to have VTE. Of these, 91 had pulmonary embolism, 148 had deep venous thrombosis (DVT) and 12 had both. A total of 129 of VTE cases were diagnosed at admission. Of all admissions, 12.9% did not receive any DVT prophylaxis, 70.4% received prophylactic dose, 1.3% received intermediate dose and 15.5% received therapeutic dose. Male gender (odds ratio (OR): 1.55, 95% confidence interval (CI): 1.0 - 2.4, P = 0.04) and Black race (OR: 2.0, 95% CI: 1.2 - 3.4, P = 0.01), along with higher levels of lactate dehydrogenase (LDH) and D-dimer were associated with higher odds of developing VTE. Patients receiving steroids had lower rates of VTE (3.9% vs. 8.3%, P < 0.001). Use of intermediate or therapeutic anticoagulation was not associated with lower odds of developing VTE. However, patients on therapeutic anticoagulation had lower odds of in hospital mortality when compared to standard dose (OR: 0.47, 95% CI: 0.27 - 0.80, P = 0.006). Conclusions: In COVID-19, D-dimer and LDH can be useful in predicting VTE. Steroids appear to have some protective role in development of VTE. Therapeutic anticoagulation did not result in lower rates of VTE but was associated with in-hospital mortality.
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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 | 0.001 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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".