Britta Steffens, Gilbert Koch, Corinna Engel, Axel R Franz, Marc Pfister, Sven Wellmann
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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 <math><mo>(</mo> <mrow><mi>a</mi> <mi>P</mi> <mi>E</mi></mrow> <mo>)</mo></math> and relative prediction error <math><mo>(</mo> <mrow><mi>r</mi> <mi>P</mi> <mi>E</mi></mrow> <mo>)</mo></math> , and two clinical acceptance conditions, margin of error of the 95%-confidence interval (95%-CI) and percentage of clinically relevant mis-predictions defined as <math><mi>a</mi> <mi>P</mi> <mi>E</mi> <mo>></mo> <mn>85</mn> <mspace></mspace> <mspace></mspace> <mi>μ</mi> <mrow><mi>mol</mi> <mo>/</mo> <mi>L</mi></mrow> </math> , were investigated.</p><p><strong>Results: </strong>Out of 455 enrolled neonates, 276 neonates met bilirubin inclusion criteria and were included in the analyses. Irrespective from tested prediction horizons, median <math><mi>r</mi> <mi>P</mi> <mi>E</mi></math> 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 <math><mi>a</mi> <mi>P</mi> <mi>E</mi></math> . 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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"7 ","pages":"1497165"},"PeriodicalIF":3.2000,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11878101/pdf/","citationCount":"0","resultStr":"{\"title\":\"Assessing accuracy of BiliPredics algorithm in predicting individual bilirubin progression in neonates-results from a prospective multi-center study.\",\"authors\":\"Britta Steffens, Gilbert Koch, Corinna Engel, Axel R Franz, Marc Pfister, Sven Wellmann\",\"doi\":\"10.3389/fdgth.2025.1497165\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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 <math><mo>(</mo> <mrow><mi>a</mi> <mi>P</mi> <mi>E</mi></mrow> <mo>)</mo></math> and relative prediction error <math><mo>(</mo> <mrow><mi>r</mi> <mi>P</mi> <mi>E</mi></mrow> <mo>)</mo></math> , and two clinical acceptance conditions, margin of error of the 95%-confidence interval (95%-CI) and percentage of clinically relevant mis-predictions defined as <math><mi>a</mi> <mi>P</mi> <mi>E</mi> <mo>></mo> <mn>85</mn> <mspace></mspace> <mspace></mspace> <mi>μ</mi> <mrow><mi>mol</mi> <mo>/</mo> <mi>L</mi></mrow> </math> , were investigated.</p><p><strong>Results: </strong>Out of 455 enrolled neonates, 276 neonates met bilirubin inclusion criteria and were included in the analyses. Irrespective from tested prediction horizons, median <math><mi>r</mi> <mi>P</mi> <mi>E</mi></math> 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 <math><mi>a</mi> <mi>P</mi> <mi>E</mi></math> . 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.</p><p><strong>Conclusion: </strong>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.</p>\",\"PeriodicalId\":73078,\"journal\":{\"name\":\"Frontiers in digital health\",\"volume\":\"7 \",\"pages\":\"1497165\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2025-02-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11878101/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers in digital health\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3389/fdgth.2025.1497165\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in digital health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fdgth.2025.1497165","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
摘要
背景:新生儿黄疸影响超过一半的新生儿。由于胆红素值通常在出院后几天达到峰值,黄疸仍然是再次住院的主要原因。最近开发的BiliPredics算法集成在第一个ce批准的胆红素预测工具中,预测未来60小时内个体胆红素的进展。这项前瞻性研究的目的是评估该算法在预测新生儿出院前个体胆红素的准确性。方法:于2021年在德国宾根和雷根斯堡的大学儿童医院进行了一项前瞻性多中心研究。在不同的情况下,不同的胆红素测量的类型和数量和预测水平进行了测试。主要目的是BiliPredics算法基于总血清胆红素(TSB)测量或仅基于经皮胆红素(TcB)测量的预测准确性。次要目标是基于TSB和TcB测量组合的预测准确性。为了评估准确性,研究了两个验证指标,绝对预测误差(a P E)和相对预测误差(r P E),以及两个临床接受条件,95%置信区间的误差范围(95% ci)和临床相关错误预测百分比(定义为P E > 85 μ mol / L)。结果:在455名纳入的新生儿中,276名新生儿符合胆红素纳入标准,并被纳入分析。与测试的预测水平无关,使用TSB测量长达30和60小时的中位数r P E很小(8.5%至9.5%),使用TcB测量长达48小时的中位数r P E略高(13.8%)。这同样适用于平均市盈率。两种临床接受条件在测试场景中都得到了满足。在不调整测量类型的情况下,联合TSB-TcB方案在48 h的预测范围内的结果与满足临床接受条件的TSB和TcB方案相当。结论:这项对新生儿的前瞻性研究结果证实,BiliPredics算法准确地预测了TSB测量60 h内的胆红素进展,TcB或TSB-TcB联合测量48 h内的胆红素进展。因此,利用该算法的预测工具有望促进和安全地优化医院出院时的黄疸风险评估,并有可能减少黄疸相关的再住院。
Assessing accuracy of BiliPredics algorithm in predicting individual bilirubin progression in neonates-results from a prospective multi-center study.
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.