Measures of Success and Health-Related Quality of Life in Lower-Extremity Vascular Surgery
Bibliographic record
Abstract
Lower-extremity vascular surgery is most often indicated for patients with critical leg ischemia but has increasingly been used for patients with disabling intermittent claudication. This article reviews indications, follow-up protocols, and procedure-related outcomes including perioperative and late mortality, complications, and long-term patency rates, which vary with patient risk factors, vascular disease severity, and hospital volume. Population-based studies have yet to establish whether rates of limb-preserving bypass surgery are related to overall amputation rates, partly because of the continued high rate of primary amputation. The functional benefits of vascular surgery have been traditionally assessed by treadmill protocols and batteries of physical tests. Claudication treatment is increasingly being measured by both generic and disease-specific functional and health-related quality-of-life questionnaires. Patient self-reported measures of physical functioning and walking ability are reviewed. Finally, conclusions are presented about trends in lower-extremity bypass surgery rates.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".