Bibliographic record
Abstract
Background and objectives: Peripheral arterial disease (PAD) is a known predictor of cardiovascular morbidity and mortality among hemodialysis patients. Although ankle-brachial BP index (ABI) is a simple and reliable test for PAD screening, its sensitivity has been suggested to decrease among dialysis patients. Design, setting, participants, & measurements: We performed a cross-sectional outpatient cohort study to examine prevalence of PAD among hemodialysis patients using duplex ultrasonography of the lower extremity artery. We also evaluate the influence of increased arterial stiffness on impaired accuracy of ABI for PAD screening. Results: Of 315 total patients, 23.8% had PAD. PAD was associated with younger age, diabetes, current smoking, atherosclerotic comorbidities, increased total cholesterol levels, increased triglyceride levels, and lower Kt/V. The receiver operating characteristic analysis (area under the receiver operating characteristic curve = 0.846) showed that sensitivity and specificity of ABI values for PAD were 49.0 and 94.8%, respectively. An ABI cut-off value of 1.05 resulted in the best sensitivity (74.5%) and specificity (84.4%). There was a significant difference in sensitivity of ABI levels <0.9 for detecting PAD among patients in different brachial-ankle pulse wave velocity quartiles. In patients with the highest brachial-ankle pulse wave velocity quartile, PAD was most prevalent (46.5%), and ABI had the highest accuracy in detecting PAD (area under the curve, 0.933). Conclusions: These results suggest that duplex ultrasonography was a useful tool for screening asymptomatic PAD among hemodialysis patients and that the diagnostic value of ABI for PAD was affected by various factors.
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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 | 0.012 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.021 | 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".