Patients Consenting to or Declining Extended Follow-up (Up to Ten Years) in the Carotid Revascularization Endarterectomy (CEA) versus Stenting (CAS) Trial (CREST) (P2.268)
Bibliographic record
Abstract
OBJECTIVE: To describe differences between patients choosing or declining extended CREST follow-up (≤10 years). BACKGROUND: Long-term data are needed to assess the durability of CEA versus CAS. Identifying characteristics of those asked to extend participation may suggest mechanisms to improve long-term retention. DESIGN/METHODS: Following completion of the primary outcome, active CREST participants were asked to extend their original four-year commitment up to ten years. Characteristics of those who consented were compared with those who declined. Univariate and multivariable logistic regression were used for analysis; backwards stepwise logistic regression was used to determine the factors associated with continuation. RESULTS: Of 1921 active participants for whom extended follow-up consent was requested, 1695 (89[percnt]; mean age 68.4) consented; 226 (12[percnt]; mean age 69.6) declined. Of those who consented versus those who declined, 48[percnt] vs. 65[percnt] were symptomatic at baseline (p<0.0001), 24[percnt] vs. 35[percnt] were smokers (p=0.001), 87[percnt] vs. 81[percnt] were dyslipidemic (p=0.01) and 29[percnt] vs. 36[percnt] were diabetic (p=0.5). Additional differences between those who consented versus declined included mean years followed at time of consent (3.7 years vs. 4.8 years (p=30 patients versus sites randomizing <30 (48[percnt] vs. 30[percnt] (p<0.0001)). Multivariable logistic regression indicated that those with lower odds of consenting were older (OR 0.75; 95[percnt] CI 0.63, 0.91), more likely symptomatic (OR 0.56; 95[percnt] CI 0.41, 0.78), smokers (OR 0.45; 95[percnt] CI 0.32, 0.63), diabetic (OR 0.70; 95[percnt] CI 0.51, 0.95), followed 5+ years vs. <3 (OR 0.21;95[percnt] CI 0.13, 0.73) and randomized at sites with <30 patients (OR 0.48;95[percnt]CI 0.35, 0.66). CONCLUSIONS: Symptomatic status, increasing age, higher levels of atherosclerotic risk factors, randomized at lower volume centers, and longer time in follow-up, were associated with declining long-term participation. Identifying factors associated with reduced willingness to extend participation can suggest targeted mechanisms to improve long-term retention. Funding: NINDS (US) [R01 NS038384]
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".