Implantation of a Coronary Stent Into the Canaliculus of a Human Cadaver: A Pilot Study
Bibliographic record
Abstract
PURPOSE: To evaluate the possibility of implanting a drug-eluting coronary stent into the canaliculus of a human cadaver. METHODS: The punctum and canaliculus of an embalmed human cadaver were identified and dilated using a punctum dilator and Bowman probes. At this stage, the integrity of the lacrimal drainage system was assessed by dacryoendoscopy. A drug-eluting coronary stent, which was collapsed around a balloon at the tip of a catheter, was inserted into the canaliculus. The balloon was inflated to expand and lock the spring-like stent into position. The balloon catheter was then deflated and removed from the canaliculus. Dacryoendoscopy was used once again to assess the position of each stent after implantation. RESULTS: The four canaliculi of one human cadaver were successfully identified, dilated, and intubated using drug-eluting coronary stents. Dacryoendoscopy confirmed that each stent achieved a satisfactory position within the canaliculi. The seamless integration of the stent with the surrounding tissues resulted in a significant dilation of the canaliculi. The procedure was deemed short and simple, with the time required to implant a stent into the canaliculus and asses its position being less than a minute. CONCLUSIONS: Canalicular obstructions can often be a source of therapeutic challenges. Our pilot study shows that a drug-eluting coronary stent can be implanted with precision into the canaliculus of a human cadaver. We propose that at least some canalicular obstructions could be treated using a novel rigid mesh tube similar to drug-eluting coronary stents.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".