Low-molecular-weight heparin venous thromboprophylaxis in critically ill patients with renal dysfunction: A subgroup analysis of the PROTECT trial
Bibliographic record
Abstract
INTRODUCTION: There is concern about excessive bleeding when low-molecular-weight heparins (LMWHs) are used for venous thromboembolism (VTE) prophylaxis in renal dysfunction. Our objective was to evaluate whether LMWH VTE prophylaxis was safe and effective in critically ill patients with renal dysfunction by conducting a subgroup analysis of PROTECT, a randomized blinded trial. METHODS: We studied intensive care unit (ICU) patients with pre-ICU dialysis-dependent end-stage renal disease (ESRD; pre-specified subgroup; n = 118), or severe renal dysfunction at ICU admission (defined as ESRD or non-dialysis dependent with creatinine clearance [CrCl] <30 ml/min; post hoc subgroup; n = 590). We compared dalteparin, 5000 IU daily, with unfractionated heparin (UFH), 5000 IU twice daily, and considered outcomes of proximal leg deep vein thrombosis (DVT); pulmonary embolism (PE); any VTE; and major bleeding. Adjusted hazard ratios [HR] were calculated using Cox regression. RESULTS: In patients with ESRD, there was no significant difference in DVT (8.3% vs. 5.2%, p = 0.76), any VTE (10.0% vs. 6.9%; p = 0.39) or major bleeding (5.0% vs. 8.6%; p = 0.32) between UFH and dalteparin. In patients with severe renal dysfunction, there was no significant difference in any VTE (10.0% vs. 6.4%; p = 0.07) or major bleeding (8.9% vs. 11.0%; p = 0.66) but an increase in DVT with dalteparin (7.6% vs. 3.7%; p = 0.04). Interaction p-values for comparisons of HRs (ESRD versus not) were non-significant. CONCLUSIONS: In critically ill patients with ESRD, or severe renal dysfunction, there was no significant difference in any VTE or major bleeding between UFH and dalteparin. Patients with severe renal dysfunction who received dalteparin had more proximal DVTs than those on UFH; this finding did not hold in patients with ESRD alone.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".