Redefining the concept of residual renal function with kidney sodium MRI: a pilot study
Bibliographic record
Abstract
BACKGROUND: The concept of residual kidney function (RKF) is exclusively based upon urine volume and small solute clearance, making RKF challenging to assess in clinical practice. The aim of this study was to test the technical feasibility of obtaining usable sodium magnetic resonance imaging (23Na-MRI) kidney images in hemodialysis (HD) participants. METHODS: We conducted an exploratory prospective study to quantify the cortico-medullary sodium gradient in 17 healthy volunteers and 21 HD participants. Participants fasted for 8 h prior to their study visit. Urine samples were collected to measure urinary osmolarity, before MRI. Proton and sodium pictures were merged; regions of interest were delineated for the medulla and cortex when feasible. In cases where cortex could not be identified, we considered the corticomedullary gradient (CMG) to be no longer present, resulting in a medulla-to-cortex ratio of 1. RESULTS: Median (interquartile range) fasting medulla-to-cortex ratio was significantly higher 1.56 (1.5-1.61) in healthy volunteers compared with HD patients 1.22 (1.13-1.3), P < .0001. Medulla to cortex ratio and median urinary osmolarity were correlated (r = 0.87, P < .0001) in the whole population. We found a significant association between HD vintage and medulla-to-cortex ratio, whereas we did not find any association with urine volume. Sodium signal intensity distribution within healthy kidney describes two different peaks relating to well defined cortex and medulla, whereas HD participants displays only a single peak indicative of the markedly lower sodium concentration. LIMITATIONS: This study is only exploratory, with a modest number of patients. CONCLUSIONS: The application of kidney 23Na-MRI to the study of RKF in patients receiving maintenance HD is practical and provides a previously unavailable ability to interrogate the function of remnant tubular function.Clinical Trial Registration: NCT05014178.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".