The Impact of Albumin Use on Resolution of Hyponatremia in Hospitalized Patients With Cirrhosis
Bibliographic record
Abstract
OBJECTIVES: Hyponatremia is associated with poor outcomes in cirrhosis independent of MELD. While intravenous albumin has been used in small series, its role in hyponatremia is unclear. The aim of this study is to determine the effect of albumin therapy on hyponatremia. METHODS: Hospitalized cirrhotic patients included in the NACSELD (North American Consortium for End-Stage Liver Disease) cohort with hyponatremia (Na <130mmol/L) were divided into those receiving intravenous albumin or not. Determinants of hyponatremia resolution (Na ≥135 meq/L) and 30-day survival were analyzed using regression and ANCOVA models. RESULTS: Overall, 2435 patients, of whom 1126 had admission hyponatremia, were included. Of these, 777 received 225 (IQR 100,400) g of albumin, while 349 did not. Patients given albumin had a higher admission MELD score, and serum creatinine and lower admission Na and mean arterial pressure (MAP). However they experienced a higher maximum Na and hyponatremia resolution (69% vs 61%, p = 0.008) compared to those who did not. On regression, delta Na was independently associated with admission creatinine, MAP and albumin use. On ANCOVA with logistic regression, there was a significant difference in hyponatremia resolution between those who did or did not receive albumin, even after adjustment for admission Na and GFR (85.41% vs 44.78%, p = 0.0057, OR: 1.50 95% CI: 1.13-2.00). Independent predictors of 30-day survival were hyponatremia resolution, age, ACLF, and admission GFR. CONCLUSION: Hospitalized patients with cirrhosis and hyponatremia who received intravenous albumin had a higher rate of hyponatremia resolution independent of renal function and baseline sodium levels, which was in turn associated with a better 30-day survival.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".