Assessment of live kidney donors by magnetic resonance angiography: reliability and impact on outcomes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Kidney allograft retrieval from live donors requires accurate determination of kidney anatomy prior to surgery, particularly the arterial supply. Traditionally, conventional angiography has been used to obtain this information. Magnetic resonance angiography (MRA) offers a non-invasive, cost-effective alternative, but has been considered to be less accurate. Despite this criticism, many centers have moved to MRA screening of potential kidney donors. The objective of this study is to evaluate our experience of the reliability of MRA in determining the arterial anatomy of living kidney donors as compared to the intra-operative findings. METHODS: We performed a retrospective review of gadolinium-enhanced, ultra-fast, three-dimensional, spoiled gradient-echo MRA in live kidney donors in the Southern Alberta Transplant Program and compared these results with the intra-operative findings during nephrectomy, as the gold standard. RESULTS: Of the 66 patients, an accessory renal artery was found intra-operatively in eight cases; two of which were erroneously diagnosed as normal by MRA. The negative predictive value for MRA was 0.97, false-negative rate was 0.25, and sensitivity was 0.75. No patient experienced side-effects from the MRA procedure. No donor needed conversion to open nephrectomy because of an undetected accessory renal artery. One allograft with an accessory renal artery developed thrombosis of the lower pole of the kidney despite arterial reconstruction. Kidney function in the recipient of this allograft was excellent and there was no urinary leak. CONCLUSION: In our hands, MRA determined the vascular anatomy of potential kidney donors with an acceptable negative predictive value of 97%.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 |
| 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 it