Supplementary Material for: Transcutaneous versus Total Serum Bilirubin Measurements in Preterm Infants
Bibliographic record
Abstract
Introduction: Transcutaneous bilirubin (TcB) measurement offers a noninvasive approach for bilirubin screening; however, its accuracy in preterm infants is unclear. This study determined the agreement between TcB and total serum bilirubin (TSB) among preterm infants. Methods: A multisite prospective cohort study was conducted at 3 NICUs in Ontario, Canada, September 2016 to June 2018. Among 296 preterm infants born at 240/7 to 356/7 weeks, 856 TcB levels were taken at the forehead, sternum, and before and after the initiation of phototherapy with TSB measurements. Bland-Altman plots and 95% limits of agreement (LOA) expressed agreement between TcB and TSB. Results: The overall mean TcB-TSB difference was −24.5 μmol/L (95% LOA −103.3 to 54.3), 1.6 μmol/L (95% LOA −73.4 to 76.5) before phototherapy, and −31.1 μmol/L (95% LOA −105.5 to 43.4) after the initiation of phototherapy. The overall mean TcB-TSB difference was −15.2 μmol/L (95% LOA −86.8 to 56.3) at the forehead and −24.4 μmol/L (95% LOA −112.9 to 64.0) at the sternum. The mean TcB-TSB difference was −31.4 μmol/L (95% LOA −95.3 to 32.4) among infants born 24–28 weeks, −25.5 μmol/L (95% LOA −102.7 to 51.8) at 29–32 weeks, and −15.9 μmol/L (95% LOA −107.4 to 75.6) at 33–35 weeks. Measures did not differ by maternal ethnicity. Conclusion: Among preterm infants, TcB may offer a noninvasive, immediate approach to screening for hyperbilirubinemia with more careful use in preterm infants born at <33 weeks’ gestation, as TcB approaches treatment thresholds. Its underestimation of TSB after the initiation of phototherapy warrants the use of TSB for clinical decision-making after the initiation of phototherapy.
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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 | 0.002 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.815 | 0.229 |
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".