Management of acute venous thromboembolism among a cohort of patients discharged directly from the emergency department
Bibliographic record
Abstract
OBJECTIVE: To report the proportion of patients discharged directly from the emergency department (ED) on traditional therapy (parenteral anticoagulant±warfarin) or a direct oral anticoagulant (DOAC) for the management of acute venous thromboembolism (VTE). DESIGN: Retrospective medical record review across four EDs in Edmonton, Alberta, two in Regina, Saskatchewan and three in rural Alberta. SETTING: EDs from April 2014 through March 2015. PARTICIPANTS: Discharged directly from the ED with acute VTE. Patients were excluded if they had another indication for anticoagulants, were pregnant/breastfeeding or anticipated lifespan <3 months. PRIMARY AND SECONDARY OUTCOME MEASURES: Primarily, the proportion of patients discharged directly from the ED that were prescribed traditional therapy or a DOAC, with comparisons between Edmonton, Regina and rural Alberta. Secondarily, therapy selection was compared based on deep vein thrombosis (DVT) versus pulmonary embolism (PE) and clot burden. Dosing of DOACs was assessed (when applicable) and follow-up in the community was compared. RESULTS: After screening 1723 patients, 417 (24.2%) were included with DVT and PE occurring in 65.5% and 34.5%, respectively. More patients with PE were discharged from EDs in Edmonton (43%) than Regina (7%). Overall, the majority of patients were discharged on traditional therapy (70.7%), with 27.8% receiving a DOAC. Uptake of DOAC use was highest in rural Alberta (53.3%) compared with Edmonton (29.6%) and Regina (12.1%). DOACs were more commonly prescribed for PE (34.0%) than DVT (24.5%) (p=0.04), proximal versus distal DVT (28.4% and 17.3%; p<0.001), and when prescribed were appropriately dosed in 79.3%. Follow-up most commonly occurred via a VTE clinic in Edmonton or family physician in Regina and rural Alberta. CONCLUSIONS: Regional variation in discharging patients directly from the ED with PE is evident. While traditional therapy is most common, uptake of DOACs was modest given the timing of indication approval.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".