Venous thromboembolism risk and prophylaxis in the acute hospital care setting: report from the ENDORSE study in Egypt
Bibliographic record
Abstract
BACKGROUND: Venous thromboembolism (VTE) is a leading cause of hospital-related deaths worldwide. However, the proportion of patients at risk of VTE who receive appropriate prophylaxis in Egypt is unknown. The ENDORSE study in Egypt is part of a global initiative to uncover the incidence of high-risk surgical and medical patients and determine what proportion of these patients receive appropriate VTE prophylaxis. METHODS: Ten Egyptian hospitals participated in this observational study, enrolling all surgical and medical patients that met the study criteria. This resulted in a cohort of 1,008 patients in acute care facilities who underwent a retrospective chart review. Each patient's VTE risk status and the presence or absence of appropriate prophylactic care was assessed according to the American College of Chest Physicians (ACCP) guidelines 2004. RESULTS: Of the 1,008 patients enrolled, 395 (39.2%) were found to be at high-risk for VTE. Overall, 227 surgical patients were at high-risk, although only 80 (35.2%) received ACCP-recommended prophylaxis. Similarly, 55/268 (32.75%) of high-risk medical patients received appropriate VTE prophylaxis. Low molecular weight heparin was the most commonly used anticoagulant, while mechanical prophylactic use was quite low (1.5%) in high-risk patients. CONCLUSIONS: In Egypt, more than one-third of all patients hospitalized for surgery or acute medical conditions are at high risk for developing VTE. However, only a small fraction of these patients receive appropriate VTE prophylaxis. Corrective measures are necessary for preventing VTE morbidity and mortality in these high risk 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".