Thromboprophylaxis with dalteparin in medical patients: which patients benefit?
Bibliographic record
Abstract
It is unclear whether thromboprophylaxis produces a consistent risk reduction in different subgroups of medical patients at risk from venous thromboembolism. We performed a retrospective, post hoc analysis of 3706 patients enrolled in the PREVENT study. Patients were at least 40 years old with an acute medical condition requiring hospitalization for at least 4 days and had no more than 3 days of immobilization prior to enrolment. Patients received either subcutaneous dalteparin (5000 IU) or placebo once daily. The primary end point was the composite of symptomatic deep vein thrombosis (DVT), pulmonary embolism, asymptomatic proximal DVT, or sudden death. Primary diagnosis subgroups were acute congestive heart failure, acute respiratory failure, infectious disease, rheumatological disorders, or inflammatory bowel disease. All patients, except those with congestive heart or respiratory failure, had at least one additional risk factor for venous thromboembolism. A risk reduction was shown in patients receiving dalteparin versus placebo. The relative risk (RR) was 0.73 in patients with congestive heart failure, 0.72 for respiratory failure, 0.46 for infectious disease, and 0.97 for rheumatological disorders. The RR was 0.52 in patients aged > or = 75 years, 0.64 in obese patients, 0.34 for patients with varicose veins, and 0.71 in patients with chronic heart failure. No subgroup had a significantly different response from any other. Importantly, multivariate analysis showed that all patient groups benefited from thromboprophylaxis with dalteparin. Our findings, therefore, support the broad application of thromboprophylaxis in acutely ill hospitalized medical patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".