Detection and quantification of overactive bladder activity in patients: Can we make it better and automatic?
| Autor: | Dominik Obrist, Francesco Clavica, Fiona C. Burkhard, Michelle Grämiger, Tarcisi Cantieni, Andreas Haeberlin, Elena Stojkova Gafner, Thomas Niederhauser |
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| Rok vydání: | 2017 |
| Předmět: |
Adult
Male medicine.medical_specialty Urology Wavelet Analysis 030232 urology & nephrology Urodynamic studies urologic and male genital diseases 03 medical and health sciences 0302 clinical medicine Pressure medicine Humans In patient 610 Medicine & health Retrospective Studies Urinary Bladder Overactive business.industry Middle Aged medicine.disease Bladder pressure female genital diseases and pregnancy complications Surgery Urodynamics Overactive bladder 570 Life sciences biology Female Neurology (clinical) business Algorithms 030217 neurology & neurosurgery |
| Zdroj: | Neurourology and Urodynamics. 37:823-831 |
| ISSN: | 0733-2467 |
| Popis: | Aims To explore the use of time-frequency analysis as an analytical tool to automatically detect pattern changes in bladder pressure recordings of patients with overactive bladder (OAB). To provide quantitative data on the bladder's non-voiding activity which could improve the current diagnosis and potentially the treatment of OAB. Methods We developed an algorithm, based on time-frequency analysis, to analyze bladder pressure during the filling phase of urodynamic studies. The algorithm was used to generate a bladder overactivity index (BOI) for a quantitative estimation of the average bladder non-voiding-activity. We tested the algorithm with one control group and two groups of patients with OAB symptoms: one group with detrusor overactivity (DO), assessed by an experienced urologist (OAB-with-DO group), and another group for which detrusor overactivity was not diagnosed (OAB-without-DO group). Results The algorithm identified diagnostically significant data on the bladder non-voiding activity in a specified frequency range. BOI was significantly higher for both OAB groups compared to the control group: the median value of BOI was twice as big in OAB-without-DO and more than four times higher in OAB-with-DO compared to control group. Moreover the algorithm was successfully tested to detect episodes of detrusor overactivity. Conclusions We have shown that a simple algorithm, based on time-frequency analysis of bladder pressure, may be a promising tool in the clinical setting. The algorithm can provide quantitative data on non-voiding bladder activity in patients and quantify the changes according to phenotype. Moreover the algorithm can detect DO, showing potential for triggering conditional bladder stimulation. |
| Databáze: | OpenAIRE |
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