Retrievable Inferior Vena Cava Filters: A Tertiary Centre Perspective and Quality Assurance Study
Bibliographic record
Abstract
PURPOSE: To conduct a retrospective review and quality assurance study of inferior vena cava (IVC) filter retrieval over a two-year period at a tertiary care centre. METHODS: Patients who underwent IVC filter placement or retrieval over a two-year period were identified. Medical records were reviewed for patient characteristics, filter indication, time to filter retrieval, and complications. RESULTS: IVC filters were placed in 229 patients between January 1, 2015 and December 31, 2016. 113 retrievals were attempted and 101 filters were successfully retrieved (89.4%). Median time to first retrieval attempt was 48 days (range of 5-728). Seventy-one patients died in the interval after filter insertion before a retrieval attempt at a median time of 27 days (range of 3-430). In 17 patients, retrieval was complicated by or delayed because of penetration of IVC wall (n = 6), large thrombus burden trapped by filter (n = 5), filter tilt or migration (n = 3), and unclear reasons (n = 3). Time-to-first unsuccessful retrieval attempt was 141 days (median). Of all filters placed, 55.9% were never retrieved. Excluding deceased patients with in-situ filters (n = 71) and unsuccessful retrievals left in-situ as permanent filters (n = 5), there remains 52 patients (33%), with a median filter in-situ time of 488 days. CONCLUSION: Our study indicates that as many as 33% of patients may have been lost to follow-up of their in-situ IVC filter. Considering widespread reports of long-term complications and the recent safety alert issued by Health Canada, it is evident that a unified strategy is needed to track patients post filter insertion.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".