Use of Serial Patient Hemoglobin A1c Differences to Determine Long-Term Imprecision of Immunoassay and High-Performance Liquid Chromatography Analyzers
Bibliographic record
Abstract
BACKGROUND: The quality of the HbA1c assay is inversely proportional to the variation of the assay. Most published measures of HbA1c variation are limited by the data collection period, the statistical treatment of outliers, and even the noncommutability of the products used to generate the variation measurements. We have used an alternate approach to derive HbA1c variation, using serial patient data. METHODS: HbA1c measurements of outpatient blood sample pairs drawn within 30 days of each other were made on three different immunoassay systems: the Roche INTEGRA 700, the Roche INTEGRA 400, and the Dade Dimension RxL; and two high-performance liquid chromatography assays: the Tosoh G7 and the Tosoh 2.2+. The standard deviation of duplicates was calculated for the following time intervals: 1 to 3 days, 4 to 6 days, 7 to 9 days,.., 28 to 30 days. These intra-individual variations were then plotted; extrapolation to time zero yields the long term total random error which consists of both analytic and pre-analytic error. Data collection periods were usually 2 years. RESULTS: At the mean HbA1cs of 7.08%, 7.14%, 7.20%, 6.96%, and 7.51% for populations tested on the Roche INTEGRA 700, Roche INTEGRA 400, Dade Dimension RxL, Tosoh 2.2+, and Tosoh G7, respectively, the total analytic imprecisions (coefficient of variation) were 2.56%, 2.29%, 2.25%, 1.66%, and 1.14%, respectively. CONCLUSION: Assessment of the HbA1c long term total imprecisions shows that while the three immunoassay systems are acceptable, the Tosoh HbA1c analyzers demonstrate superior analytic performance.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".