Analysis of 60 patients treated with the GoGoBand AI Powered Bedwetting Alarm
Israel Franco, MD1, Jon Coble, MBA,2, Michael Kohonowski, MBA,BSE3, Michael Kohonowski, MBA,BSE3, Steve Zyglowicz, BSE3.
1Yale University, New Haven, CT, USA, 2GoGoBand, Ashland, VA, USA, 3Gogoband, Ashland, VA, USA.
BACKGROUND:Bedwetting alarms (BWA) have been around for more than half a century with little innovation in the field. GOGOBandŽ utilizes real time heart rate variability (HRV) analysis and applied artificial intelligence (AI) to create an alarm that is capable of waking the patient prior to wetting . Our Aim was to evaluate the if the efficacy continues to remain high with the addition of 20 new patients to our servers. METHODS: Data was retrieved and analyzed from our servers, of patients who purchased the GOGOBandŽ which includes a heart rate monitor, moisture sensor, bedside tablet and app for the parents phone in this study. There are 3 modes, training, where the individualized HRV parameters are used to build the alerting model. Once patients are done with training, they enter the Predictive mode where they receive an alarm if an impending urination event is noted. In Weaning mode the alerting is gradually suppressed. Only patients that used the alarm for more than 30 days were included. Data analysis was done with SPSS and xlstat. RESULTS: : A total of 60 subjects that have used the system for more than 30 nights were included in this analysis. Gender mix was 46 males (76.6%) and 14 females (23.3%). The mean age of the subjects is 10.2 yrs. Subjects wet the bed an average of 6.2 nights per week prior to treatment. Severity and number of accidents per night had no impact on the ability to achieve dryness with the GOGO BandŽ device in logistical regression analysis. The data was also segregated based on compliance since it became clear during the analysis that compliant patients achieved better results than non-compliant patients. A crosstab analysis was performed and is reported in table 1. The data clearly indicates that compliant patients >80% are able to remain dry 96% of the time once they enter the weaning phase. CONCLUSIONS: Our findings indicate a 96% success rate in patients that are weaning, this translates to 1.2 wet nights per 30 days. This compares to the same group when starting the use of the alarm had only 14.4 dry nights per 30 days. The addition of the 20 patients indicates that that our results are enduring and seem to be improving as we continue to increase the number of patients that are on the system.
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