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Assessing accuracy of BiliPredics algorithm in predicting individual bilirubin progression in neonates-results from a
Britta Steffens1,2, Gilbert Koch1,2, Corinna Engel3
1Pediatric Pharmacology and Pharmacometrics, University of Basel Children's Hospital (UKBB), Basel, Switzerland.
Insights
Neonatal jaundice prediction is improved with the BiliPredics algorithm, accurately forecasting bilirubin levels up to 60 hours post-discharge. This tool helps reduce rehospitalizations by enabling safer jaundice risk assessment.
Area of Science:
- Neonatal Medicine
- Medical Technology
- Predictive Analytics
Background:
- Neonatal jaundice is a common condition, often peaking after hospital discharge, leading to readmissions.
- The BiliPredics algorithm offers a novel approach to predict individual bilirubin progression.
- Early prediction is crucial for managing jaundice and preventing complications.
Purpose of the Study:
- To evaluate the accuracy of the BiliPredics algorithm in predicting neonatal bilirubin levels before hospital discharge.
- To assess the algorithm's performance using different measurement types (TSB, TcB) and prediction horizons.
- To determine the clinical utility of the BiliPredics tool in real-world neonatal care.
Main Methods:
- A prospective, multi-center study involving 276 neonates meeting bilirubin criteria.
- Testing various scenarios with total serum bilirubin (TSB) and transcutaneous bilirubin (TcB) measurements.
- Utilizing absolute and relative prediction errors, and clinical acceptance conditions for accuracy assessment.
Main Results:
- The BiliPredics algorithm demonstrated small median prediction errors (8.5%-9.5% for TSB up to 60h, 13.8% for TcB up to 48h).
- Clinical acceptance conditions were met across tested scenarios.
- Combined TSB-TcB measurements showed comparable accuracy to individual methods.
Conclusions:
- The BiliPredics algorithm accurately predicts bilirubin progression in neonates.
- The tool reliably forecasts bilirubin levels up to 60h (TSB) and 48h (TcB/combined).
- This predictive capability can optimize jaundice risk assessment at discharge, potentially reducing rehospitalizations.
Background:
Neonatal jaundice affects more than half of neonates. As bilirubin values usually peak few days after hospital discharge, jaundice remains a leading cause of rehospitalization. The recently developed BiliPredics algorithm, integrated in the first CE-approved bilirubin prediction tool, predicts individual bilirubin progression for up to 60 h into the future. Goal of the prospective study was to assess accuracy of this algorithm in predicting individual bilirubin prior to hospital discharge in neonates.
Methods:
A prospective multi-center study was conducted in 2021 at the University Children's Hospitals in Tübingen and Regensburg, Germany. Various scenarios differing in type and number of bilirubin measurements and in prediction horizon were tested. Primary objective was prediction accuracy of the BiliPredics algorithm based on total serum bilirubin (TSB) measurements or based on transcutaneous bilirubin (TcB) measurements alone. Secondary objective was prediction accuracy based on combinations of TSB and TcB measurements. For assessment of accuracy, two validation metrics, absolute prediction error and relative prediction error , and two clinical acceptance conditions, margin of error of the 95%-confidence interval (95%-CI) and percentage of clinically relevant mis-predictions defined as , were investigated.
Results:
Out of 455 enrolled neonates, 276 neonates met bilirubin inclusion criteria and were included in the analyses. Irrespective from tested prediction horizons, median was small (8.5% to 9.5%) utilizing TSB measurements for up to 30 and 60 h and slightly higher (13.8%) utilizing TcB measurements for up to 48 h. The same applied for median . Both clinical acceptance conditions were fulfilled across tested scenarios. Results for combined TSB-TcB scenarios up to a prediction horizon of 48 h without adjustment for type of measurement were comparable to TSB and TcB scenarios fulfilling both clinical acceptance conditions.
Conclusion:
Results from this prospective study in neonates confirm that the BiliPredics algorithm accurately predicts bilirubin progression up to 60 h with TSB measurements and up to 48 h with TcB or combined TSB-TcB measurements. As such, prediction tools utilizing this algorithm are expected to facilitate and safely optimize jaundice risk assessment at hospital discharge with the potential to reduce jaundice-related rehospitalizations.
