Dalteparin Thromboprophylaxis in Critically Ill Patients with Severe Renal Insufficiency: The Direct Study.
Bibliographic record
Abstract
Abstract Background: Critically ill patients with renal insufficiency are at high risk for deep vein thrombosis (DVT). Low-molecular-weight heparins (LMWHs) effectively prevent DVT but are avoided in patients with renal insufficiency because of potential bioaccumulation and potential bleeding risk. However, evidence is lacking that LMWHs bioaccumulate in such patients. Objectives: The objectives of DIRECT were, in critically ill patients with severe renal insufficiency, to determine if dalteparin prophylaxis leads to bioaccumulation and bleeding from excessive anticoagulation and to determine the pharmacodynamic profile of dalteparin. Methods: Multi-center, open-label, prospective cohort study of critically ill patients with a creatinine clearance <30 mL/min who receive dalteparin, 5000 IU once-daily, subcutaneously for up to 30 days. Dalteparin bioaccumulation in a patient was defined by a trough anti-Xa level >0.40 IU/mL, measured twice-weekly 20 hours after the prior dalteparin dose. The pharmacodynamic profile of dalteparin was assessed by anti-Xa levels measured at 0, 1, 2, 4, 8, 12, 20, and 24 hours after the prior dose on days 3, 10, and 17 of treatment. Results: We enrolled 156 patients with a mean (SD) creatinine clearance of 18.9 (6.5) mL/min; of these, 18 were excluded because they died or were discharged before testing (n = 3) or had prevalent DVT (n = 14) or pulmonary embolism (n = 1) within 48 hours of enrollment. Of 138 patients included, the median (inter-quartile range [IQR]) duration of dalteparin treatment was 7 days (4, 12). In 120 pa tients who had ≥1 trough anti-Xa measured (427 total), none had dalteparin bioaccumulation; the median (IQR) trough anti-Xa level was <0.1 IU/mL (<0.1, <0.1). In 138 patients who received ≥1 dose of dalteparin,10 patients (7.2%; 95% CI: 4.0, 12.8) had a major bleed, all with trough anti-Xa levels ≤0.18 IU/mL. The pharmacodynamic profile of dalteparin, shown in the Figure, was typical for drugs that do not bioaccumulate, with a typical peak and decline after 3, 10, and 17 days of treatment. Conclusions: In critically ill patients with severe renal insufficiency, thromboprophylaxis with dalteparin did not bioaccumulate. Dalteparin, 5000 IU once-daily, appears to be a reasonable option for thromboprophylaxis of critically ill patients with severe renal insufficiency. Figure Figure
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".