A new computer algorithm enables prediction, in the early stages of pregnancy or even before pregnancy has occurred, of which women are at a high risk of gestational diabetes, indicate researchers at the Weizmann Institute of Science, Rehovot, Israel.
Scientists analyzed data on nearly 600,000 pregnancies available from Israel's largest health organization, Clalit Health Services. It may be possible, based on these predictions, to prevent gestational diabetes using nutritional and lifestyle changes.
"Our ultimate goal has been to help the health system take measures so as to prevent diabetes from occurring in pregnancy," says senior author Eran Segal, professor in the Department of Computer Science and Applied Mathematics and the Department of Molecular Cell Biology.
Gestational diabetes is characterized by high blood sugar levels that develop during pregnancy in women who did not previously have diabetes. It occurs in three percent to nine percent of all pregnancies and is fraught with risks for both mother and baby.
Typically, gestational diabetes is diagnosed between the 24th and 28th weeks of pregnancy, with the help of a tolerance test in which the woman drinks a glucose solution and then undergoes a blood test to see how quickly the glucose is cleared from her blood.
In the new study, Segal and colleagues started out by applying a machine learning method to Clalit's health records on some 450,000 pregnancies in women who gave birth between 2010-17. Gestational diabetes had been diagnosed by glucose tolerance testing in about four percent of these pregnancies. After processing the "big data"--an...