Sodium modeling, hypotension, and weight gain in HD
Bibliographic record
Abstract
Sodium modeling is a strategy to decrease the incidence of hypotension during hemodialysis. Side effects include increased interdialytic weight gain. By default, all patients at our dialysis center are started on HD with sodium modeling. Purpose: To compare weight gain and blood pressure after discontinuation of sodium modeling. Methods: Ten patients using sodium modeling were changed to a standard sodium bath after a change in attending physician. After IRB approval, we collected and retrospectively reviewed the change in interdialytic weight gains, episodes of hypotension (defined as an episode of hypotension requiring staff intervention), and starting and ending blood pressure. Data from one week prior to Na change (PRE) was compared to one week after Na change (POST) using a paired samples t‐test. Results: Data from 4 men and 6 women with a mean age of 65.2 ± 13.7 years was reviewed. ESRD diagnoses included diabetes (n = 4) and hypertension (n = 6). Interdialytic weight gain significantly decreased after discontinuation of sodium modeling (PRE 3.86 kg, POST 3.11 kg, p = 0.004). No significant change in blood pressure at the start (PRE 154/82 POST 156/83, p = 0.745) or end of HD (PRE 123/69, POST 130/67, p = 0.201) was observed. However, the frequency of symptomatic hypotension increased after change to standard sodium bath (PRE = 6%, POST = 27%, p = 0.031). All episodes of hypotension occurred in 3 of the 10 study patients. No patient required cessation of HD or transfer to the emergency department. The degree of weight gain was not correlated with the likelihood of intradialytic hypotension. Conclusion: A change from sodium modeling to standard sodium dialysate lowers interdialytic weight gain but increases the incidence of mild symptomatic hypotension. Further study is needed to determine whether mild hypotension is preferable to increased interdialytic weight gain and to determine the relationship of increased weight gain to complications of volume overload such as LVH and CHF.
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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) | 0.000 | 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".