Short-Term Association of Pre-Dialysis Calculated Serum Osmolality and Its Per-Quarter Change with Mortality in Maintenance Hemodialysis Patients
Bibliographic record
Abstract
Background: Homeostatic regulation of serum osmolality (SOsm) is critical for normal cellular function. Since kidney plays an important role in maintaining homeostasis, patients with kidney dysfunction might be unable to maintain homeostasis. However, it is unknown if SOsm can predict risk of mortality in maintenance hemodialysis (HD) patients. Methods: We identified 16,402 patients who transitioned to maintenance HD in a large U.S. dialysis organization over 5 years (2007-2011) and had available calculated pre-dialysis SOsm (Sodium and Potassium and blood urea nitrogen (BUN) and Glucose) at baseline. We used the equation with the best fit between measured and calculated SOsm as follows: 2x([Na, in mmol/L]+[K, in mmol/L])+[Glucose, in mg/dL]/18+[BUN in mg/dL]/2.8. We divided the patients into ten groups based on their calculated SOsm (SOsm updated at quarterly intervals as a proxy of short-term exposure): <300, 300-<304, 304-<307, 307-<309, 309-<311, 311-<313, 313-<315, 315-<317, 317-<321 (reference group) and ≥321 mOsm/Kg, and calculated SOsm’s per quarter change from the date of first dialysis: <-8.0, -8.0-<-6.0, -6.0-<-4.0, -4.0-<-2.0, -2.0-<0, 0-<+2.0 (reference group), +2.0-<+4.0, +4.0-<+6.0, +6.0-<+8.0and ≥+8.0 mOsm/Kg. All-cause mortality risk was estimated using multivariable Cox models. Results: The patients were 56% male, 48% non-white, and the mean age was 63 ± 13 (mean ± SD) years. Those with low calculated SOsm tended to be older. In timevarying analysis, the association between all-cause mortality showed that patients with the lowest calculated SOsm had the highest hazard ratio after fully adjusted (Figure A). We observed a U-shaped association between all-cause mortality and per quarter change in calculated SOsm such that SOsm change levels ±8.0 mOsm/Kg were associated with higher mortality risk (Figure B). Conclusions: This result suggests that short-term and a wide range of changes in serum osmolality may increase the risk of all-cause mortality in hemodialysis patients.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".