Improving the efficacy of enuresis alarm treatment through early prediction of treatment outcome: a machine learning approach - Jönsson, Karl-Axel; Andersson, Edvin; Nevéus, Tryggve; Gärdenfors, Torbjörn; Balkenius, Christian (Frontiers in Urology, 2023)
Bedwetting, also known as enuresis, is the second most common chronic health problem among children and it affects their everyday life negatively. A first-line treatment option is the enuresis alarm. By this method the child is awoken by a detector and alarm unit every time there is urine in the bed, thereby changing the arousal mechanisms and possibly making the child dry after 6-8 weeks of consistent therapy. The enuresis alarm treatment has a reported success rate above 50 percent but entails much work by the families. Another problem is the lack of early predictors of treatment success. The alarm treatment has been further developed by the company Pjama AB that, in addition to the alarm, offers a mobile application where users fill in data about the patient and information about each night throughout the treatment. Wet and dry nights are recorded, as well as the actual timing of the wetting incidents. We used the machine learning model random forest to see if predictions of treatment outcome could be made in early stages of treatment and shorten the evaluation time based on data from 611 patients. This was done by using and analyzing data from patients who had used the Pjama application. The patients were split into training and testing groups to evaluate to what extent the algorithm could make predictions every day about whether a patient’s treatment would become successful, partially successful or unsuccessful. The results show that a large number of patient outcomes can be predicted accurately already in the early stages of treatment. This enables the correct measures to be taken earlier in the treatment, including increasing motivation, adding pharmacotherapy or terminating treatment. This has the potential to shorten the treatment as a whole, and to detect patients who will not respond to the treatment early on, which in turn can improve the lives of children suffering from enuresis. The results show a great potential in making the treatment of enuresis more efficient.