Patients' Preferences and Expectations in Overactive Bladder: A Systematic Review.
Antonio CicioneRiccardo LombardoVincenzo UmbacaGiorgia TemaGiacomo GalloJordi StiraCarmen GravinaBeatrice TurchiAntonio FrancoElisa ManciniAntonio NacchiaRocco DamianoAndrea TubaroCosimo De NunzioPublished in: Journal of clinical medicine (2023)
The aim of our study is to review the current available knowledge regarding preferences and expectations of patients with overactive bladder (OAB). The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement guidelines were followed for this manuscript's preparation. Three online databases were searched: PubMed/Medline, Embase, and Scopus, while a combination of the following keywords was used: detrusor overactivity, overactive bladder, urinary incontinence, perspectives, expectations, and preferences. Overall, 1349 studies were retrieved and screened while only 10 studies appeared to be relevant for the scope of this review. Most of the studies were related to preferences about OAB medications (i.e., antimuscarinics); four of them reported patients' inclinations to alternative treatments in the case of medication therapy failure (i.e., neuromodulation, Botox). No data were found about diagnosis or other aspects of disease management (i.e., surgery, follow-up). Based on these findings, from the patient's point of view, the ideal medication should be cheap, without risk of cognitive function impairment, and able to reduce daytime urinary frequency and incontinence episodes.
Keyphrases
- end stage renal disease
- meta analyses
- systematic review
- ejection fraction
- urinary incontinence
- newly diagnosed
- healthcare
- chronic kidney disease
- prognostic factors
- peritoneal dialysis
- minimally invasive
- obstructive sleep apnea
- decision making
- case control
- emergency department
- physical activity
- machine learning
- atrial fibrillation
- mesenchymal stem cells
- electronic health record
- deep learning
- cell therapy
- mass spectrometry
- percutaneous coronary intervention
- acute coronary syndrome
- artificial intelligence
- health information