About 1 in 11 Americans get kidney stones, which can be incredibly painful for some people. Worse still, they can reoccur. Obviously, any tool to help predict the likelihood of another painful bout would be helpful, especially if it helps encourage those at high risk to do more to prevent them.
Crunching the kidney stone data
A research team from the Mayo Clinic in Rochester, Minnesota used data from 3,364 participants who had a total of 4,951 kidney stone episodes to identify patterns in who was at the greatest risk of recurring incidents. The data was taken from the Rochester (Minnesota) Epidemiology Project from 1984 to 2017. The scientists found these people tended to:
• be male
• be younger
• be overweight (i.e., had a higher BMI)
• have a family history of kidney stones
• (for women) have had previous pregnancies
• had kidney stones in the “lower pole”
• had 3-6 mm stones (vs. smaller or larger)
Updating the old prediction tool
A previous tool used to predict the chances of future incidents used 11 factors, but the tool wasn’t particularly accurate at predicting future episodes for those who had already had at least two occurrences.
The new tool uses 13 factors, including things they learned from analyzing the data from the 3,364 participants, as well as race, kidney stone history and responses to questions about sex.
“Each of the risk factors we identified [is] entered into the model, which then calculates an estimate of the risk of having another kidney stone in the next 5 or 10 years,” explains researcher Dr. John Lieske. He added that someone who has a higher risk of recurrence ay have more “enthusiasm for adopting dietary measures and/or starting drug regimens to prevent future attacks.” The research was published in the journal Mayo Clinic Proceedings in February 2019.
