Employing data science, new research uncovers clues behind unexplainable infant death

 |   Juan Lavista Ferres – General Manager and Lab Director, Microsoft AI for Good

Children's health researchers

Imagine losing your child in their first year of life and having no idea what caused it. This is the heartbreaking reality for thousands of families each year who lose a child to Sudden Unexpected Infant Death (SUID). Despite decades-long efforts to prevent SUID, it remains the leading cause of death for children between one month and one year of age in developed nations. In the U.S. alone, 3,600 children die unexpectedly of SUID each year.

For years, researchers hypothesized that infants who died due to SUID in the earliest stages of the life differed from those dying of SUID later. Now, for the first time, we know, thanks to the single largest study ever undertaken on the subject, this is statistically the case.

Working in collaboration with Tatiana Anderson and Jan-Marino Ramirez at Seattle Children’s Research Institute and Edwin Mitchell at University of Auckland, we analyzed the Center for Disease Control (CDC) data on every child born in the U.S. over a decade, including over 41 million births and 37,000 SUID deaths. We compared all possible groups by the age at the time of death to understand if these populations were different.”

In our study published today in Pediatrics, a leading pediatric journal, we found that SUID deaths during the first week of life, were statistically different from all other SUID deaths that occur between the first week and first year of life. SUID cases in the first week of life have been called SUEND, which stands for Sudden Unexpected Early Neonatal Death. We have called SUID deaths between 7-364 days postperinatal SUID.

The two groups – SUEND and postperinatal SUID – differed by several factors such as birth order, maternal age and marital status. For postperinatal deaths, the risk of SUID progressively while the opposite was true for SUEND deaths where firstborn children were more at risk. Postperinatal SUID rates were higher for unmarried, young mothers (between 15-24 years old) at birth, while unmarried, young mothers of the same age showed a decreased risk of SUEND death. The two groups also had different distributions of birthweight and pregnancy length.

Our study concluded that SUID deaths in the first week differed from postperinatal SUID deaths and that the two groups should be considered separately in future research. Considering these two as different causes may help uncover independent underlying physiological mechanisms and/or genetic factors.

This research is part of Microsoft’s AI for Good initiative, a $125 million five-year program where we utilize AI to help tackle some of the world’s greatest challenges and helping some of the world’s most vulnerable populations. For this research, we leveraged our machine learning, cloud-computing capabilities and advanced modelling techniques powered by AI to analyze the data.

By pairing our capabilities and data scientists with Seattle Children’s medical research expertise, we’re continuing to make progress on identifying the cause of SUID. Earlier this year, we published a study that estimated approximately 22% of SUID deaths in the U.S. were attributable to maternal cigarette-smoking during pregnancy, giving us further evidence that, through our collaboration with experts in varying disciplines, we are getting to the root of this problem and making remarkable advances.

We hope our progress in piecing together the SUID puzzle ultimately saves lives, and gives parents and researchers hope for the future.

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