S1479 Repeatability Coefficient of Velacur Scans in the Same Patient Taken at Least 2 Weeks Apart
Bibliographic record
Abstract
Introduction: As non-invasive biomarkers become the standard of care for diagnosis and monitoring of patients with chronic liver disease, it is important to understand the repeatability of any test. Here we report the results of the ‘different-day’ measurements for Velacur elasticity and attenuation in patients with non-alcoholic fatty liver disease. Methods: As part of protocol for a clinical study, adult participants were asked to complete an additional optional visit with a repeated Velacur scan. All scans were completed by a qualified Velacur scanner, but the repeated scans were not always completed by the same scanner. Exams were collected at 2 sites, in Vancouver, BC and in Coronado, CA. Between 5 and 10 volume measurements were completed during each visit as per protocol and the median of these measurements was used as the exam result for this analysis. The primary objective was to estimate the repeatability coefficient (RPC) for both elasticity and attenuation measurements, on the same subject, on a different day. Scans were completed at least 2 weeks apart. Results: A total of 20 subjects with clinically confirmed non-alcoholic fatty liver disease were included in this analysis Velacur scan repeatability. The average number of days between scans was 24.8, ranging from 15 to 37 days. Average age for these patients was 57 years, and 52% were female. The mean BMI was 29.9 +/- 5.8 kg/m2, and mean FIB-4 was 1.72 +/- 1.05. The mean elasticity for visit 1 was 8.3 kPa and 8.1 kPa for visit 2. Patients represented the full spectrum of disease with stiffness with measurements for visit 1 ranging from 4.8 kPa to 15.2 kPa. The mean attenuation measurement for visit 1 was 324 dB/m and 313 dB/m for visit 2, ranging from 206 to 402 dB/m. The RCP for elasticity was 31% and for attenuation was 19%. Conclusion: The repeatability coefficients are important to be able to understand what a true change might constitute, rather than differences attributable to measurement error. The results measured here were taken further apart than during other similar studies (measured 7 days apart), so might also incorporate some real changes in the patient disease state. The results are the first step in understanding the repeatability of Velacur measurements in a NAFLD/NASH patient population (Figure 1).Figure 1.: Correlation and Bland-Altman plots of Velacur elasticity and attenuation for measurements taken from the same patient, at least 2 weeks apart.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".