Treatment-Dose LMWH versus Prophylactic/Intermediate Dose Heparins in High-Risk COVID-19 Inpatients: Rationale and Design of the HEP-COVID Trial
Bibliographic record
Abstract
Coronavirus disease-2019 (COVID-19) has been associated with significant risk of venous thromboembolism (VTE), arterial thromboembolism (ATE), and mortality particularly among hospitalized patients with critical illness and elevated D-dimer (Dd) levels. Conflicting data have yet to elucidate optimal thromboprophylaxis dosing. HEP-COVID (NCT04401293) is a phase 3, multicenter, pragmatic, prospective, randomized, pseudo-blinded, active control trial to evaluate efficacy and safety of therapeutic-dose low-molecular-weight heparin (LMWH) versus prophylactic-/intermediate-dose LMWH or unfractionated heparin (UFH) for prevention of a primary efficacy composite outcome of VTE, ATE, and all-cause mortality 30 ± 2 days post-enrollment. Eligible patients have COVID-19 diagnosis by nasal swab or serologic testing, requirement for supplemental oxygen per investigator judgment, and Dd >4 × upper limit of normal (ULN) or sepsis-induced coagulopathy score ≥4. Subjects are randomized to enoxaparin 1 mg/kg subcutaneous (SQ)/two times a day (BID) (creatinine clearance [CrCl] ≥ 30 mL/min) or 0.5 mg/kg (CrCl 15-30 mL/min) versus local institutional prophylactic regimens including (1) UFH up to 22,500 IU (international unit) daily (divided BID or three times a day), (2) enoxaparin 30 and 40 mg SQ QD (once daily) or BID, or (3) dalteparin 2,500 IU or 5,000 IU QD. The principal safety outcome is major bleeding. Events are adjudicated locally. Based on expected 40% relative risk reduction with treatment-dose compared with prophylactic-dose prophylaxis, 308 subjects will be enrolled (assuming 20% drop-out) to achieve 80% power. Distinguishing design features include an enriched population for the composite endpoint anchored on Dd >4 × ULN, stratification by intensive care unit (ICU) versus non-ICU, and the ability to capture asymptomatic proximal deep venous thrombosis via screening ultrasonography prior to discharge.
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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 | 0.011 | 0.008 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".