Plotting Transcutaneous Bilirubin Measurements on Specific Transcutaneous Nomogram Results in Better Prediction of Significant Hyperbilirubinemia in Healthy Term and Near-Term Newborns: A Pilot Study
Bibliographic record
Abstract
BACKGROUND: The American Academy of Pediatrics has recommended a systematic assessment before discharge for the risk of severe hyperbilirubinemia. Plotting total serum bilirubin (TSB) or transcutaneous bilirubin (TcB) on a TSB hour-specific nomogram is proposed as a tool for laboratory evaluation. OBJECTIVES: The aim of this study was to compare the predictive characteristics, particularly the incidence of false negative rate (FNR), of the practice of plotting TcB values on the TSB hour-specific risk nomogram versus on transcutaneous nomogram. METHODS: Paired TSB and TcB measurements were conducted on 141 newborns. Risk of developing significant hyperbilirubinemia was defined as infants with bilirubin level ≥ 75% on TSB or ≥ 95% on TcB nomogram. TSB values, plotted on the TSB nomogram of Bhutani et al. [Pediatrics 1999;103:6-14], were used as reference. TcB values were plotted on the TSB nomogram and on the transcutaneous nomograms of Maisels and Kring [Pediatrics 2006;117:1169-1173] and Fouzas et al. [Pediatrics 2010;125:e52-e57]. RESULTS: Plotting TcB measurements on a TSB nomogram resulted in a trend towards a higher FNR when compared to Maisels' and Fouzas' nomograms (18.0/1,000 compared to 10.2/1,000 and 8.6/1,000 respectively). Although not statistically significant, plotting TcB on transcutaneous nomogram resulted in better predictive values with the Fouzas' nomogram, having the best sensitivity (90.0%) and specificity (87.79%) as well as the highest positive (35.97%) and negative (99.14%) predictive value. CONCLUSION: Plotting TcB on a TSB nomogram may result in increased rate of FNR and decreased predictive characteristics. The practice of plotting TcB on a TSB nomogram needs further evaluation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".