Migration from RIA to LC-MS/MS for aldosterone determination: Implications for clinical practice and determination of plasma and urine reference range intervals in a cohort of healthy Belgian subjects
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Bibliographic record
Abstract
Background: Aldosterone measurement is critical for diagnosis of primary aldosteronism and disorders of the renin-angiotensin system. We developed an LC-MS/MS method for plasma and urinary aldosterone and compared it to our RIA method. We present a reference interval study for a Belgian population. Methods: 68 plasma and 23 urine samples were assayed for as part of a method comparison. For the reference interval study, we enrolled 282 healthy Caucasian volunteers (114 Male: mean age 35 ± 11 y and 168 Female: mean age 42 ± 13 y). A subset of 139 healthy volunteers agreed to a 24-h urine collection. For the method validation, 5 plasma and 8 urine pools were run in triplicate and quadruplicate, respectively, on 3 different days. Results: Between-run imprecision (CV) was 2.8-5.1% for plasma and 4.5-8.6% for urine, except at the low urine concentration of 2.99 nmol/L where a CV of 15.4% was observed. The limit of quantitation was 0.04 nmol/L for plasma and 6.65 nmol/L for urine. Recoveries, based on spiking experiments into natural matrix, did not differ significantly from 100%. Regression comparisons showed that, on average, RIA generated results were 59% and 11% higher than LC-MS/MS for plasma and urine, respectively. The MS reference interval we propose for plasma aldosterone is 0.07 nmol/L-0.73 nmol/L for women and 0.04 nmol/L-0.41 nmol/L for men. No gender difference was observed for urine aldosterone. The reference interval was determined to be <60.94 nmol/day. Conclusions: The LC-MS/MS method was validated and reference intervals for plasma and urine were established. A significant bias between RIA and LC-MS/MS was noted.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it