Using inferior vena cava filters to prevent pulmonary embolism.
Bibliographic record
Abstract
OBJECTIVE: To review the evidence for using inferior vena cava (IVC) filters to prevent pulmonary embolism (PE) in high-risk patients. QUALITY OF EVIDENCE: Ovid MEDLINE was searched from 1966 to 2006 for all English-language papers on IVC filters. Evidence was graded according to the 3-level classification system. Most evidence found was level II. MAIN MESSAGE: Inferior vena cava filters are used to prevent PE in patients with contraindications to, complications of, or failure of anticoagulation therapy and patients with extensive free-floating thrombi or residual thrombi following massive PE. Current evidence indicates that IVC filters are largely effective; breakthrough PE occurs in only 0% to 6.2% of cases. Contraindications to implantation of IVC filters include lack of venous access, caval occlusion, uncorrectable coagulopathy, and sepsis. Complications include misplacement or embolization of the filter, vascular injury or thrombosis, pneumothorax, and air emboli. Recurrent PE, IVC thrombosis, filter migration, filter fracture, or penetration of the caval wall sometimes occur with long-term use. CONCLUSION: When used appropriately, IVC filters are a safe and effective method of preventing PE. Using retrievable filters might reduce long-term complications.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".