Prognostic factors for VTE and bleeding in hospitalized medical patients: a systematic review and meta-analysis
Bibliographic record
Abstract
There may be many predictors of venous thromboembolism (VTE) and bleeding in hospitalized medical patients, but until now, systematic reviews and assessments of the certainty of the evidence have not been published. We conducted a systematic review to identify prognostic factors for VTE and bleeding in hospitalized medical patients and searched Medline and EMBASE from inception through May 2018. We considered studies that identified potential prognostic factors for VTE and bleeding in hospitalized adult medical patients. Reviewers extracted data in duplicate and independently and assessed the certainty of the evidence using the Grading of Recommendations Assessment, Development, and Evaluation approach. Of 69 410 citations, we included 17 studies in our analysis: 14 that reported on VTE, and 3 that reported on bleeding. For VTE, moderate-certainty evidence showed a probable association with older age; elevated C-reactive protein (CRP), D-dimer, and fibrinogen levels; tachycardia; thrombocytosis; leukocytosis; fever; leg edema; lower Barthel Index (BI) score; immobility; paresis; previous history of VTE; thrombophilia; malignancy; critical illness; and infections. For bleeding, moderate-certainty evidence showed a probable association with older age, sex, anemia, obesity, low hemoglobin, gastroduodenal ulcers, rehospitalization, critical illness, thrombocytopenia, blood dyscrasias, hepatic disease, renal failure, antithrombotic medication, and presence of a central venous catheter. Elevated CRP, a lower BI, a history of malignancy, and elevated heart rate are not included in most VTE risk assessment models. This study informs risk prediction in the management of hospitalized medical patients for VTE and bleeding; it also informs guidelines for VTE prevention and future research.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.013 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".