Ureteral stent technology: Drug-eluting stents and stent coatings
Bibliographic record
Abstract
Ureteral stents are commonly used following urological procedures to maintain ureteral patency. However, alongside the benefits of the device, indwelling stents frequently cause significant patient discomfort (pain, urgency, frequency) and can become encrusted and infected. The importance of these sequelae is that they are not only bothersome to the patient but can lead to significant morbidity, urinary retention, ureteral damage, recurrent infections, pyelonephritis and sepsis. When these problems occur, stent removal or replacement alongside antibiotic, analgesic and/or other symptom-modifying therapies are essential to successfully treat the patient. In an attempt to prevent such morbidity, numerous approaches have been investigated over the past several decades to modify the stent itself, thereby affecting changes locally within the urinary tract without significant systemic therapy. These strategies include changes to device design, polymeric composition, drug-elution and surface coatings. Of these, drug-elution and surface coatings are the most studied and display the most promise for advancing ureteral stent use and efficacy. This article reviews these two strategies in detail to determine their clinical potential and guide future research in the area.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".