Successful management of severe hyponatremia in CKD‐VD: In a cost limited setting
Bibliographic record
Abstract
Patients with end stage renal disease (ESRD) and severe hyponatremia always pose a challenge to manage. It is necessary to correct biochemical parameters, advanced azotemia, and fluid overload with conventional haemodialysis (HD) but it may correct serum sodium (Na) rapidly resulting in neurological complications like seizures and osmotic demyelination syndrome. Continuous renal replacement therapy (CRRT) is an ideal modality to manage such patients. However, most of the centers in the developing or underdeveloped nations do not have CRRT facility. We present two cases of ESRD, who had advanced azotemia requiring dialysis, also had persistent vomiting and severe hyponatremia (one with Na 107, another with Na 109 mEq/L), both cases were managed with conventional HD using dialysate Na concentration of 128 mEq/L (lowest permissible level of Na in a traditional HD machine) and keeping the blood flow of 50 mL/min. The serum Na increased by 1 mEq/L/h during first HD session, during the next session blood flow increased to 100 mL/min, and serum Na increased by two mEq/L/h. At the end of 48 hours, we were able to successfully correct serum Na by 18 mEq/L, with complete resolution of uremic manifestations and no neurological deficits. The current reports highlight management of hyponatremia in newly diagnosed ESRD in a cost limited setting.
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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 | 0.000 |
| 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) | 0.001 | 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 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".