Blood pressure dependent elasticity measurements of porcine kidney ex-vivo
Bibliographic record
Abstract
Kidney transplantation is standard of care for end-stage renal failure. Monitoring graft health after transplantation to ensure graft longevity is important and usually carried out through the use of biopsy. Ultrasound elastography has the potential to allow regular non-invasive monitoring of graft health via the level of fibrosis. Results of kidney elastography research to date have been variable. It is hypothesized that the changes in blood pressure are a confounding factor in elasticity measurements and may explain the varied results. Using a controlled set-up on porcine kidneys ex-vivo, the effects of changes in pressure with flow from a peristaltic pump were examined (n=5). Each kidney was measured from 0 mmHg to 130 mmHg. It was found that the measured elasticity of the kidney was dependent on the input pressure of the pump. Increasing the input pressure resulted in an increase in the measured elasticity, from an average 21 ± 3 kPa at 0 mmHg to approximately 34 ± 9 kPa at 130 mmHg. These results suggest that the phase of the cardiac cycle be considered in kidney elastography using electrocardiogram (ECG) monitoring.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".