Outcome Validation of the Beckman Coulter Access Analyzer in a Second-Trimester Down Syndrome Serum Screening Application
Bibliographic record
Abstract
BACKGROUND: Mid-trimester maternal serum alpha-fetoprotein (AFP) and unconjugated estriol (uE3) are 30% lower and human chorionic gonadotropin (hCG) is twofold higher in Down syndrome pregnancies compared with unaffected pregnancies. In maternal serum screening, patient-specific risks are calculated using published gaussian frequency distribution parameters for these three markers obtained with previously available immunoassays. New immunoassays must generate similar distribution parameters if the accuracy of assigned risks and overall performance of prenatal screening are to be maintained. METHODS: Agreement between the Beckman Coulter Access and the Bayer Immuno 1 assays for AFP and hCG and the Amersham Amerlex-M RIA for uE3 was assessed in 558 fresh sera. Precision was measured over 6 weeks. Median concentrations were calculated by regression of 568 Caucasian singleton pregnancy samples against gestational age in days. Frozen mid-trimester sera from 44 confirmed Down syndrome singleton pregnancies (cases) were selected without conscious bias for reanalysis, and each case was matched with five control specimens from unaffected pregnancies. Serum markers were expressed as the multiple of the median (MoM) concentration derived from the control samples, corrected for maternal weight and converted to their log-equivalent values. Normality was assessed using probability plots and the Shapiro-Wilk W-test. Gaussian distribution parameters were compared with established values, and Down syndrome risk calculations were assessed with a commonly used risk algorithm. RESULTS: The Access AFP and hCG assays had consistent proportional agreement with the established assays, whereas agreement between the uE3 methods was less consistent. Analytical imprecision was 3-6% at mid-trimester concentrations. Normal distributions were obtained for the log MoM values of all three markers in both the Down syndrome and unaffected populations, and their gaussian distribution parameters compared well with established values. The performance of the Access assays in an established trivariate risk algorithm for Down syndrome was equal to the performance exhibited by traditional methods. CONCLUSION: The Beckman Coulter Access analyzer provides valid mid-trimester serum AFP, uE3, and hCG results and risk assessments when applied in a prenatal Down syndrome screening service.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".