Thromboprophylaxis in the intensive care unit: Focus on medical–surgical patients
Bibliographic record
Abstract
Critically ill patients in the medical-surgical intensive care unit are at high risk for deep venous thrombosis and pulmonary embolism, which comprise venous thromboembolism. Herein, we describe the prevalence, incidence, risk factors, clinical consequences, prophylaxis against venous thromboembolism in critically ill patients, and compliance with thromboprophylaxis. We focus primarily on medical-surgical intensive care unit patients, who represent the largest subgroup of critically ill patients. Despite the large and growing number of critically ill patients in our aging society, their high risk for venous thromboembolism, and the morbidity and mortality associated with this complication of critical illness, relatively few rigorous studies are available. Large, well-designed, randomized trials of thromboprophylaxis, powered to detect differences in patient-important outcomes, are required to advance our understanding and care of these vulnerable patients. Furthermore, because thromboprophylaxis is a common error of omission in hospitalized patients, redoubled efforts are needed to ensure that it is used in practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| 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 teacher head, 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".