P0215EXCESSIVE TISSUE SODIUM STORAGE IN PATIENTS WITH NON-DIALYSIS DEPENDENT CARDIO-RENAL SYNDROME IS COMPARABLE TO HEMODIALYSIS PATIENTS
Bibliographic record
Abstract
Abstract Background and Aims Both CKD and heart failure (HF) are characterized by a propensity to retain sodium. Renal dysfunction worsens the progression of heart failure and is associated with worse outcomes. This may be a result of synergistic aggravation of sodium retention by the two conditions. We aimed to compare tissue Na storage in skin and muscle between cardiorenal (CR) patients and patients with a range of renal dysfunction, including those requiring hemodialysis (HD). Method Proton and 23Na images of the lower limb were acquired on a 3T MRI. We studied 9 CR patients, 7 matched CKD 2-5 patients (without HF) and 31 established HD patients. Regions of interest including skin and soleus were drawn on images to provide a quantitative sodium measurement and these tissue concentrations compared between groups. Blood samples were drawn at each scan in all patients. Spot urine samples were collected for CR patients. Results For CR patients, mean age was 66 ± 8 years, 78% of male, mean estimated glomerular filtration rate (eGFR) was 52 ± 18 mL/min/1.73m2, urea was 11 ± 6 mmol/L. For HD patients, mean age was 66 ± 8.7 years, 68% of male and mean dialysis vintage was 38 ± 37 months for HD patients. Mean age was 63 ± 8, 71 % of male, eGFR 45 ± 29 mL/min/1.73m2 for CKD patients. CR patients displayed an increased amount of salt in skin (32.5 ± 13 mmol/L) and muscle (26 ±4 mmol/L) with levels significantly higher than that seen in GFR matched controls (without HF) and comparable to HD patients (31 ±12 and 28 ± 6 mmol/L p=0.9 and p=0.3 respectively) without meaningful residual renal function. Conclusion The combination of HF and CKD is associated with intense tissue Na storage; resulting in tissue Na accumulation in CR patients (with reasonably well-preserved renal function) similar to CKD patients requiring HD.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".