ArticleEnvironmental health perspectives2025
A Machine Learning-Based Clustering Analysis to Explore Bisphenol A and Phthalate Exposure from Medical Devices in Infants with Congenital Heart Defects.
Article in Environmental health perspectives, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- An Exploration of Machine Learning Methods in Human Biomonitoring.International journal of environmental research and public health · 2026Review
- Machine Learning Reveals Novel Pediatric Heart Failure Phenotypes with Distinct Mortality and Hospitalization Outcomes.Diagnostics (Basel, Switzerland) · 2025Article
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Authors and funding
8 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundPlastic-containing medical devices are commonly used in critical care units and other patient care settings. Patients are often exposed to xenobiotic agents that are leached out from plastic-containing medical devices, including bisphenol A (BPA) and phthalates. Given the potential health implications, there is an urgent need for a comprehensive understanding of this exposure.
objectivesThis multi-institutional study aimed to determine the time-dependent concentrations and analyze the exposure patterns of bisphenol A (BPA) and phthalate metabolites in urine obtained from infants with congenital heart defects (CHD) undergoing cardiac surgery during the perioperative period.
methodsWe collected daily urine samples from infants with CHD undergoing cardiac surgery during the perioperative period (from birth to 21 d) and measured BPA, di(2-ethylhexyl)phthalate (DEHP) metabolites (MEHP, MEHHP, MEOHP, MECPP), and non-DEHP phthalate metabolites (MBP, MBzP, MMP, MEP, MCPP) using ultra-high-performance liquid chromatography-tandem mass spectrometry. Machine learning-based cluster analysis was utilized to analyze these time-dependent data.
resultsUtilizing a machine learning-based clustering approach, six distinct clustering groups were identified among infants exhibiting similar time-series toxicokinetic exposure patterns. These distinct clustering groups correlated with the utilization of extracorporeal membrane oxygenation (ECMO) and cardiopulmonary bypass (CPB), as well as the intensity of medical care. Notably, clustering groups associated with ECMO use demonstrated elevated levels of urinary BPA and DEHP metabolites compared to those without ECMO use, a trend not observed with non-DEHP metabolites. Moreover, peak concentrations in toxicokinetic profiles were associated with intensity of medical care. DISCUSSION: Our findings suggest that dynamic changes of urinary BPA and DEHP metabolites corresponded to the type and number of medical devices used in infants. Further studies are needed to investigate the potential toxicological risks of infants with CHD undergoing cardiac surgery exposed to these chemicals in medical devices. https://doi.org/10.1289/EHP15034.
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