Assay-Dependent Effects of EDTA Contamination on Magnesium and Iron
Bibliographic record
Abstract
Background Inadvertent submission of ethylenediaminetetraacetic acid (EDTA) based plasma in place of heparinized plasma or contamination of serum or heparinized plasma with EDTA can alter select laboratory measurements. While factitious hypocalcaemia and abnormally low alkaline phosphatase (ALP) are recognized indicators of EDTA contamination, the impact of EDTA on Mg 2+ and Fe 2+ remains uncertain and conflicting. Method Herein, we derived the EDTA concentration required to cause a 50 % decline (EC50 [EDTA] ) for Ca 2+ , ALP, Mg 2+ , and Fe 2+ across two methodologies (Roche Cobas c303 and Abbott Alinity c ) in the presence of EDTA concentration across plasma and serum pools. The concentration of EDTA required to exceed the allowable performance limit (APL [EDTA] ) was also evaluated across methods. Results Mg 2+ measured by an isocitrate dehydrogenase method was resilient against EDTA, while Mg 2+ measured by xylidyl blue had an EC50 [EDTA] and APL [EDTA] of 0.78–1.18 mmol/L and 0.16–0.34 mmol/L, respectively. Fe 2+ measured with a ferene method was resilient to EDTA, whereas ferrrozine method indicated EC50 [EDTA] and APL [EDTA] of 5.6–8.86 mmol/L and 4.68–5.46 mmol/L, respectively. Ca 2+ and ALP exhibited larger EC50 [EDTA] on the Abbott Alinity c . Conclusion Hypomagnesemia and hypoferremia are not definitive markers of potential EDTA contamination, as Mg 2+ and Fe 2+ measurements show method-dependent susceptibilities.
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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 | 0.002 |
| 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".