Many patients suffer from chronic, irritative lower urinary tract symptoms (LUTS). The evaluation and management of these patients have proven difficult with the use of standard diagnostic tools, including urinalysis and urine culture. The growing body of literature on the urinary microbiome has looked at the possible implications of the bladder microbiome and dysbiosis, or perturbations in the microbiome, in conditions associated with chronic LUTS. Disorders such as recurrent urinary tract infections (UTIs) and interstitial cystitis have been studied utilizing 16S rRNA rapid next-generation gene sequencing (NGS) and expanded quantitative urine culture (EQUC). In this article, we first present a brief review of the literature describing the current understanding of the urinary microbiome and the features and applications of NGS and EQUC. Next, we discuss the conditions most commonly associated with chronic, persistent LUTS and present the limitations of current diagnostic practices utilized in this patient population. We then review the limited data available surrounding treatment efficacy and clinical outcomes in patients who have been managed based on results provided by these two recently established diagnostic tools (DNA NGS and/or EQUC). Finally, we propose a variety of clinical scenarios in which the use of these two techniques may affect patients’ clinical outcomes.

BackgroundObstructive Sleep Apnea (OSA) is prevalent throughout the world. However, there are currently limited data concerning the prevalence of OSA in populations that originate from developing countries; the prevalence of OSA is expected to rise in these countries. OSA is poorly characterized amongst Ethiopians, and our study is the first to describe clinical characteristics of OSA among Ethiopians.MethodsWe conducted a retrospective study of primarily Ethiopian patients at an internal medicine clinic in Rockville, Maryland. All patients (n=24) were evaluated for daytime sleepiness using the Epworth Sleepiness Scale (ESS) and received physical examinations and polysomnograms (PSG) by either portable monitoring (Itamar WatchPAT 200 device) or in-lab. Statistical analyses were performed in R.ResultsLinear regression model of Body-Mass Index (BMI) and Apnea-Hypopnea Index (AHI) indicated that for every 1-unit increase in BMI, there was a 0.8657-unit increase in AHI (p<0.05). Pearson's correlation coefficient indicateda positive linear relationship between BMI and AHI (0.47) (p<0.05). Adjusted linear regression model for AHI and oxygen saturation indicated that for every 1-unit increase of AHI, there was a 0.8452-unit decrease in nocturnal oxygen saturation (p<0.05). Pearson's correlation coefficient did not demonstrate significance between AHI and oxygen desaturation (p=0.062). Patients received either continuous positive airway pressure (CPAP) (n=15) or oral appliance therapy (n=3).ConclusionAll patients who complied with therapy reported improved sleep quality, snoring resolution, and improved daytime alertness. Practitioners in developing countries should suspect OSA in the right clinical setting and offer diagnostic and therapeutic services when available.

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