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The Apple Watch is effective in predicting the pain scores of folks with sickle cell disease

A new report from researchers of a coalition including Duke University and Northwestern University offers details of a study to determine the feasibility of using the Apple Watch to predict the pain scores in people with sickle cell disease. It found that the smartwatch had a “strong performance” in predicting pain scores. 

The study enrolled 20 patients with sickle cell disease, all of whom identified as Black or African American and consisted of 12 (60%) females and 8 (40%) males. There were 14 individuals diagnosed with hemoglobin type SS (70%). The median age of the population was 35.5 (IQR 30-41) years. 

The median time each individual spent wearing the Apple Watch was 2 hours and 17 minutes and a total of 15,683 data points were collected across the population. All models outperformed the null models, and the best-performing model was the random forest model, which was able to predict the pain scores with an accuracy of 84.5%, and a RMSE of 0.84.

Conclusions: The strong performance of the model in all metrics validates feasibility and the ability to use data collected from a noninvasive device, the Apple Watch, to predict the pain scores during VOCs. The researchers found that Apple Watch is a “novel and feasible approach and presents a low-cost method that could benefit clinicians and individuals with sickle cell disease in the treatment of VOCs [vaso-occulsive crises.”




Article provided with permission from AppleWorld.Today
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