Tissue sodium concentrations in chronic kidney disease and dialysis patients by lower leg sodium-23 magnetic resonance imaging
Bibliographic record
Abstract
BACKGROUND: Sodium-23 magnetic resonance imaging (23Na MRI) allows direct measurement of tissue sodium concentrations. Current knowledge of skin, muscle and bone sodium concentrations in chronic kidney disease (CKD) and renal replacement therapy patients is limited. In this study we measured the tissue sodium concentrations in CKD, hemodialysis (HD) and peritoneal dialysis (PD) patients with 23Na MRI of the lower leg and explored their correlations with established clinical biomarkers. METHODS: Ten healthy controls, 12 CKD Stages 3-5, 13 HD and 10 PD patients underwent proton and 23Na MRI of the leg. The skin, soleus and tibia were segmented manually and tissue sodium concentrations were measured. Plasma and serum samples were collected from each subject and analyzed for routine clinical biomarkers. Tissue sodium concentrations were compared between groups and correlations with blood-based biomarkers were explored. RESULTS: Tissue sodium concentrations in the skin, soleus and tibia were higher in HD and PD patients compared with controls. Serum albumin showed a strong, negative correlation with soleus sodium concentrations in HD patients (r = -0.81, P < 0.01). Estimated glomerular filtration rate showed a negative correlation with tissue sodium concentrations (soleus: r = -0.58, P < 0.01; tibia: r = -0.53, P = 0.01) in merged control-CKD patients. Hemoglobin was negatively correlated with tissue sodium concentrations in CKD (soleus: r = -0.65, P = 0.02; tibia: r = -0.73, P < 0.01) and HD (skin: r = -0.60, P = 0.04; tibia: r = -0.76, P < 0.01). CONCLUSION: Tissue sodium concentrations, measured by 23Na MRI, increase in HD and PD patients and may be associated with adverse metabolic effects in CKD and dialysis.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".