Limitations and opportunities of whole blood bilirubin measurements by GEM premier 4000®
Bibliographic record
Abstract
BACKGROUND: Neonatal hyperbilirubinemia has traditionally been screened by either total serum bilirubin or transcutaneous bilirubin. Whole blood bilirubin (TwB) by the GEM Premier 4000® blood gas analyzer (GEM) is a relatively new technology and it provides fast bilirubin results with a small sample volume and can measure co-oximetry and other analytes. Our clinical study was to evaluate the reliability of TwB measured by the GEM and identify analytical and clinical factors that may contribute to possible bias. METHODS: 440 consecutive healthy newborn samples that had plasma bilirubin ordered for neonatal hyperbilirubinemia screening were included. TwB was first measured using the GEM, after which the remainder of the blood was spun and plasma neonatal bilirubin was measured using the VITROS 5600® (VITROS). RESULTS: 62 samples (14%) were excluded from analysis due to failure in obtaining GEM results. Passing-Bablok regression suggested that the GEM results were negatively biased at low concentrations of bilirubin and positively biased at higher concentrations relative to the VITROS results (y = 1.43x-61.13). Bland-Altman plots showed an overall negative bias of the GEM bilirubin with a wide range of differences compared to VITROS. Both hemoglobin concentration and hemolysis affected the accuracy of the GEM results. Clinically, male infants had higher mean bilirubin levels, and infants delivered by caesarean section had lower hemoglobin levels. When comparing the number of results below the 40th percentile and above the 95th percentile cut-offs in the Bhutani nomogram which would trigger discharge or treatment, GEM bilirubin exhibited poor sensitivity and poor specificity in contrast to VITROS bilirubin. CONCLUSIONS: An imperfect correlation was observed between whole blood bilirubin measured on the GEM4000® and plasma bilirubin on the VITROS 5600®. The contributors to the observed differences between the two instruments were specimen hemolysis and the accuracy of hemoglobin measurements, the latter of which affects the calculation of plasma-equivalent bilirubin. Additionally, the lack of standardization of total bilirubin calibration particularly in newborn specimens, may also account for some of the disagreement in results.
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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 | 0.086 | 0.112 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".