Evaluation of a 1,25-Dihydroxyvitamin D Enzyme Immunoassay
Bibliographic record
Abstract
BACKGROUND: Radioactive reagents are used in most assays for measurement of 1,25-dihydroxyvitamin D [1,25(OH)(2)D]. We evaluated a 1,25(OH)(2)D enzyme immunoassay (EIA) from IDS Ltd. that uses solid-phase immunoextraction and colorimetric detection and compared results to those of the thymus radioreceptor assay (RRA) for 1,25(OH)(2)D. METHODS: We collected serum samples (n = 145) representing an even distribution (0-200 pmol/L) of 1,25(OH)(2)D concentrations and Vitamin D External Quality Assessment Scheme (DEQAS) proficiency survey samples from 2004 surveys (n = 15) and stored them at -20 degrees C. We analyzed all samples with both EIA and RRA methods. We calculated imprecision using 5 QC samples in quadruplicate in each run (n = 6), including both pooled patient material used for QC with the RRA and QC material included in the EIA reagent set. We evaluated calibration stability by analyzing calibrators from different lots on the same plate and determining if calculated sample values drifted significantly. RESULTS: Deming linear regression between IDS EIA and RRA methods yielded slope 1.25 (95% CI 1.13-1.37), y-intercept -3 (95% CI -18 to 12), R(2) = 0.74. DEQAS proficiency survey samples for 2004 were all within 30% of the all-methods-trimmed mean. Imprecision CVs were 12%-16% within-run and 15%-20% between-run. CONCLUSIONS: We find no evidence of inferiority to the classic calf-thymus receptor assay for 1,25(OH)(2)D and no disadvantage in the results generated by the IDS EIA using samples from the major proficiency survey for 1,25(OH)(2)D. According to the product insert, however, the IDS EIA underestimates 1,25(OH)(2)D(2) compared with the D(3) form.
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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 | 0.013 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".