Accuracy of Doppler Ultrasonography in Measuring Radial Artery Wall Thickness in Hemodialysis Patients: Comparison with Histologic Examination
Bibliographic record
Abstract
Increased radial artery wall thickness (RAWT) is considered to be associated with early failure of radiocephalic arteriovenous fistula (AVF) as well as coronary artery atherosclerosis in hemodialysis patients. Therefore, exact measurement of RAWT by noninvasive method before the operation is very important. Objective: This study was designed to evaluate accuracy of Doppler ultrasonography in measuring RAWT in hemodialysis patients. Methods: This study enrolled 21 hemodialysis patients undergoing radiocephalic AVF operation for the first time. We measured RAWT (intima‐media thickness) using high‐resolution Doppler ultrasonography at the wrist before the AVF operation. We obtained specimens of the radial artery during the AVF operation and then measured RAWT by histologic examination. Results: Mean age of the patients was 60 ± 13 years and the number of females was 7 (33.3%). Mean values of RAWT measured by Doppler ultrasonography and histologic examination were 485 ± 93 μm (300–700 μm) and 426 ± 106 μm (300–700 μm), respectively. The value of RAWT of Doppler sonographic measurement well correlated with that of histologic measurement (r = 0.800, p < 0.001). Conclusion: Our data suggest that Doppler ultrasonography is an effective tool in measuring RAWT in hemodialysis patients before AVF operation.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".