Successful Percutaneous Retrieval of a Large Pulmonary Cement Embolus Caused by Cement Leakage During Percutaneous Vertebroplasty
Bibliographic record
Abstract
STUDY DESIGN: A case report and literature review. OBJECTIVE: To present a case of dynamic detection of a large pulmonary cement embolus as it formed and migrated during percutaneous vertebroplasty, which was successfully managed by percutaneous endovascular retrieval. SUMMARY OF BACKGROUND DATA: Pulmonary embolism resulting from cement leakage after percutaneous vertebroplasty to treat osteoporotic vertebral compression fracture has been described rarely; however, the frequency of this complication may increase secondary to the expanding use of percutaneous vertebral augmentation techniques. METHODS: The formation of a large embolus of acrylic cement and its migration into the pulmonary artery was observed in real time in a 55-year-old female with osteoporotic vertebral compression fracture of L4 during percutaneous vertebroplasty. RESULTS: Pulmonary arteriography confirmed the presence of the cement embolism in the right pulmonary artery during the operation. Percutaneous endovascular retrieval of the cement fragments was performed successfully via an interventional catheter procedure and subsequent incision of the femoral vein. The patient made an uneventful recovery. CONCLUSION: As illustrated by our case, large cement emboli may be primarily associated with technical aspects of the surgery. When considering the appropriate treatment strategy, percutaneous endovascular retrieval may be considered first. However, risks and benefits should be carefully evaluated on a case-by-case basis. LEVEL OF EVIDENCE: N/A.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".