Endovascular treatment of peripheral arterial disease: Endo-STAR framework for the design, conduct, and reporting of trials
Bibliographic record
Abstract
BACKGROUND: Endovascular technologies continue to evolve to meet the large and growing burden of peripheral arterial disease. The overall quality of published RCTs in endovascular treatments for peripheral arterial disease is low, resulting in uncertainty over treatment effectiveness. The aim of this study was to develop a framework to improve the design, conduct, and reporting of future clinical trials for infrainguinal endovascular treatments of peripheral arterial disease. METHODS: The authors undertook the design, development, and pilot testing of a novel framework. The study comprised four distinct phases. Phase 1 represented the development of a preliminary framework using content analysis of endovascular interventions described in previously published RCTs. Phase 2 consisted of focus groups with key stakeholders to further develop, revise, and achieve initial consensus on the framework. Phase 3 corresponded to the creation of a modified Delphi questionnaire to achieve final consensus on the framework. Phase 4 included cognitive interviews with professionals designing or undertaking endovascular lower limb trials to pilot test the framework. RESULTS: Content analysis of 228 endovascular interventions from 112 RCTs identified six key themes, relevant to endovascular peripheral arterial disease interventions, for the framework: expertise; setting; anaesthesia; imaging; intervention components (access; crossing lesion; treating lesion (lesion preparation; intervention; intervention optimization; bailout intervention; and treatment of non-target lesions); and closure of artery); and pharmacological interventions. Further refinements were made to the framework as a result of feedback from three focus groups and a Delphi questionnaire. The framework deconstructs an endovascular intervention into its component parts. The final framework can be accessed at www.endo-star.com. Pilot testing evaluated comprehension, clarity, and completeness of interpretation. CONCLUSION: The Endo-STAR framework deconstructs endovascular interventions into their key component parts and has been designed and pilot tested to enhance the quality of RCTs of endovascular interventions in peripheral arterial disease. It may be used to assist in developing future trial protocols, the standardization of infrainguinal endovascular interventions, the monitoring of adherence to the trial protocol, and as a standardized reporting guideline.
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 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 | 0.793 | 0.671 |
| Meta-epidemiology (narrow) | 0.007 | 0.007 |
| Meta-epidemiology (broad) | 0.011 | 0.017 |
| Bibliometrics | 0.020 | 0.016 |
| Science and technology studies | 0.010 | 0.029 |
| Scholarly communication | 0.028 | 0.013 |
| Open science | 0.016 | 0.020 |
| Research integrity | 0.021 | 0.025 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".