Reliability of Transcutaneous Bilirubin Devices in Preterm Infants: A Systematic Review
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Transcutaneous bilirubin (TcB) devices are widely used for the estimation of serum bilirubin levels in term and near-term infants. Our objective was to review the diagnostic accuracy of TcB devices in preterm infants. METHODS: Medline, Embase, Cochrane library, Cumulative Index to Nursing and Allied Health Literature, and Scopus were searched (from database inception date until December 2012). Additional citations were identified by using the bibliographies of selected articles and from conference proceedings. The studies were included if they compared TcB with total serum bilirubin in preterm infants before phototherapy and presented data as correlation coefficients or as Bland-Altman difference plots. Data were extracted by 1 reviewer and checked for accuracy by the second reviewer. An assessment tool (quality assessment of diagnostic accuracy studies) was used for risk of bias assessments. RESULTS: Twenty-two studies met the inclusion criteria; 21 studies reported results as correlation coefficients, with pooled estimates of r = 0.83 for each site of measurement. Pooled estimates in infants <32 weeks' gestation were similar to the overall preterm population (r = 0.89 [95% confidence interval: 0.82-0.93]). For the 2 commonly used TcB devices (ie, JM103 and BiliCheck), the results were comparable at the forehead site, although the JM103 device exhibited better correlation at the sternum. Analysis of the Bland-Altman plots (13 studies) revealed negligible bias in measurement at the forehead or sternum site by using either the JM-103 or BiliCheck device; however, the JM-103 device exhibited better precision than the BiliCheck (SD for TcB - total serum bilirubin differences: 24.3 and 31.98 µmol/L, respectively). CONCLUSIONS: The TcB devices reliably estimated bilirubin levels in preterm infants and could be used in clinical practice to reduce blood sampling.
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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 | 0.028 | 0.156 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.011 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".