Equipment Entrapment/Loss During Chronic Total Occlusion Percutaneous Coronary Intervention
Bibliographic record
Abstract
BACKGROUND: There is limited data on equipment loss or entrapment during chronic total occlusion (CTO) percutaneous coronary intervention (PCI). METHODS: We analyzed the baseline clinical and angiographic characteristics and outcomes of equipment loss/entrapment at 43 US and non-US centers between 2017 and 2023. RESULTS: Equipment loss/entrapment was reported in 40 (0.4%) of 10 719 cases during the study period. These included guidewire entrapment/fracture (n = 21), microcatheter entrapment/fracture (n = 11), stent loss (n = 8) and balloon entrapment/fracture/rupture (n = 5). The equipment loss/entrapment cases were more likely to have moderate to severe calcification, longer lesion length, higher J-CTO and PROGRESS-CTO complications scores, and use of the retrograde approach compared with the remaining cases. Retrieval was attempted in 71.4% of the guidewire, 90.9% of the microcatheter, 100% of the stent loss, and 100% of the balloon cases, and was successful in 26.7%, 30.0%, 50%, and 40% of the cases, respectively. Procedures complicated by equipment loss/entrapment had higher procedure and fluoroscopy time, contrast volume and patient air kerma radiation dose, lower procedural (60.0% vs 85.6%, P less than .001) and technical (75.0% vs 86.8%, P = .05) success, and higher incidence of major adverse cardiac events (MACE) (17.5% vs 1.8%, P less than .001), acute MI (7.5% vs 0.4%, P less than .001), emergency coronary artery bypass graft (CABG) (2.5% vs 0.1%, P = .03), perforation (20.0% vs 4.9%, P less than .001), and death (7.5% vs 0.4%, P less than .001). CONCLUSIONS: Equipment loss is a rare complication of CTO PCI; it is more common in complex CTOs and is associated with lower technical success and higher MACE.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".