Outpatient Treatment of Pulmonary Embolism with Dalteparin
Bibliographic record
Abstract
BACKGROUND: Pulmonary embolism is a common complication of deep vein thrombosis. It has been established that low molecular weight heparin may be used to treat deep vein thrombosis or pulmonary embolism and randomized studies have established that outpatient management of deep vein thrombosis with low molecular weight heparin is at least as effective as in-hospital management with unfractionated heparin. METHODS: This was a prospective cohort study of eligible patients with pulmonary embolism managed as outpatients using dalteparin (200 U/kg s/c daily) for a minimum of five days and warfarin for 3 months. Outpatients included those managed exclusively out of hospital and those managed initially for 1-3 days as inpatients who then completed therapy out of hospital. Reasons for admission included hemodynamic instability; hypoxia requiring oxygen therapy; admission for another medical reason; severe pain requiring parenteral analgesia or high risk of major bleeding. Patients were followed for three months for clinically apparent recurrent venous thromboembolism and bleeding. RESULTS: Between three teaching hospitals, a total of 158 patients with pulmonary embolism were identified. Fifty patients were managed as inpatients and 108 as outpatients. Of the outpatients, 27 were managed for an average of 2.5 days as inpatients and then completed dalteparin therapy as outpatients. The remaining 81 patients were managed exclusively as outpatients with dalteparin. For all outpatients the overall symptomatic recurrence rate of venous thromboembolism was 5.6% (6/108) with only 1.9% (2/108) major bleeds. There were a total of four deaths with none due to pulmonary embolism or major bleed. CONCLUSIONS: This prospective study suggests that outpatient management of pulmonary embolism is feasible and safe for the majority of patients.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".