Assessing the utility of testing aluminum levels in dialysis patients
Bibliographic record
Abstract
Plasma aluminum (Al) is routinely tested in many dialysis patients. Aluminum exposure may lead to acute toxicity and levels in excess of ∼2.2 μmol/L (60 μg/L) should be avoided. Historically, toxicity has been caused by excessive dialyzate Al but modern reverse osmosis (RO) water should be Al free. Nevertheless, many units continue to perform routine Al levels on dialysis patients. This single-center study retrospectively analyzed Al levels in plasma, raw water feed, and RO product between 2010 and 2013 using our database (Nephworks 6) with the aim of determining the utility of these measurements. Two thousand fifty-eight plasma Al tests in 755 patients (61.9% male, mean age 64.7 years) were reviewed showing mean ± SD of 0.41 ± 0.30 μmol/L. One hundred eleven (5.4%) tests from 61 patients had Al levels >0.74 μmol/L and 45 (73.8%) of these patients were or had been prescribed Al hydroxide (Al(OH)(3)) as a phosphate binder. Seven patients had Al concentrations >2.2 μmol/L with no source of Al identified in 1 patient. One hundred sixty-six patients taking Al(OH)(3) (78.7% of all patients on Al(OH)(3)) had levels ≤0.74 μmol/L, the odds ratio of plasma Al > 0.74 μmol/L on Al(OH)3 was 9. The cost of plasma Al assay is $A30.60; thus, costs were $A62,974.80 over the study period. Despite RO feed water Al levels as high as 48 μmol/L, Al output from the RO was almost always undetectable (<0.1 μmol/L) with dialyzate Al levels > 2.2 μmol/L only 3 times since 2010, and never in the last 3 years. Routine unselected testing of plasma Al appears unnecessary and expensive and more selective testing in dialysis patients should be considered.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".