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DOI 10.1289/ehp15034

Медицинская библиотека · Environmental health perspectives · 2025

A Machine Learning-Based Clustering Analysis to Explore Bisphenol A and Phthalate Exposure from Medical Devices in Infants with Congenital Heart Defects.

Chou Wei-Chun, Gaynor J William, Graham Eric M, Klepczynski Brenna, Walker Tia, Coker Eric S, Ittenbach Richard F, Lin Zhoumeng

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Аннотация

BACKGROUND

Plastic-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.

OBJECTIVES

This 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.

METHODS

We 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.

RESULTS

Utilizing 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.

Для цитирования: Chou Wei-Chun, Gaynor J William, Graham Eric M, Klepczynski Brenna, Walker Tia, Coker Eric S, Ittenbach Richard F, Lin Zhoumeng. A Machine Learning-Based Clustering Analysis to Explore Bisphenol A and Phthalate Exposure from Medical Devices in Infants with Congenital Heart Defects.. Environmental health perspectives. 2025. DOI: 10.1289/ehp15034.

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