Comparison of Serum Bilirubin to Transcutaneous Bilirubin During and After Phototherapy
Bibliographic record
Abstract
Objective: To compare transcutaneous bilirubin with total serum bilirubin in neonates during and after phototherapyStudy design: A prospective observational study for one yearParticipants: 799 neonates >35 weeks of gestation, developing jaundice within 10 days of life.Intervention: A photo-occlusive patch was applied over the sternum. TcB assessment with Drager JM 103 multi wavelength handheld transcutaneous bilirubinometer was done in this area paired with a concurrent serum sample during and 24 hours after stopping phototherapy.Outcome: In our study the mean TCB during phototherapy was 13.26 ± 2.42 mg/dl with minimum value of 4.50 mg/dL and maximum value of 18.40 mg/dL in the study population (95% CI 13.09 to 13.43 mg/dL). The mean TSB during phototherapy was 13.06 ± 2.52 mg/dl with minimum value of 4.30 mg/dL and maximum value of 18.70 mg/dl in the study population (95% CI 12.88 to 13.23 mg/dL). The mean TCB 24 hours after stopping phototherapy was 10.37 ± 2 mg/dL with minimum value of 4.20 mg/dL and maximum value of 16.10 mg/dL in the study population (95% CI 10.33 to 10.61 mg/dL). The mean TSB 24 hours after stopping phototherapy was 10.47 ± 2.02 mg/dL, minimum value of 4.80 mg/dl and maximum value of 15.30 mg/dL in the study population (95% CI 10.33 to 10.61).Results: Transcutaneous bilirubin has a good correlation with total serum bilirubin during phototherapy. (r=0.881, P<0.001). Transcutaneous bilirubin has a significant correlation with total serum bilirubin after phototherapy. (r=0.912, P<0.001).Conclusion: In our study transcutaneous bilirubin correlated significantly with total serum bilirubin at the patched sternal site during and 24 hours after stopping phototherapy, supporting previous studies.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".