An evidence-based perspective on lower urinary tract symptoms and telemedicine during the COVID-19 pandemic

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causing the COVID-19 pandemic, has had an enormous effect on conventional clinical practice. Telemedicine has emerged as critical to the provision of healthcare services when reducing the transmission of COVID-19 among patients, families, and clinicians. It has been an essential tool for continuing care for patients with lower urinary tract symptoms (LUTS) during the COVID-19 pandemic and has been the link between socially distant patient contact. The aim of this perspective paper was to identify the strengths and limitations of technology-based care focusing on literature linked to patients with lower urinary tract symptoms (LUTS). We search PubMed and CINHAL Plus for grey literature and secondary research on LUTS and telemedicine during the COVID-19 pandemic. Publications dated between the year March 2020 and March 2021were searched. We gathered key specialist opinions in the field of LUTS from several countries around the world, including the countries that had been hit significantly with COVID-19. This perspective paper proposes that there is evidence to support the use of modern technology to facilitate continued healthcare services for patients with LUTS during the COVID-19 pandemic. Telemedicine has been recognised a crucial digital tool for diagnosis, treatment and follow-up appointments during a time of social distancing. Although there are many advantages of telemedicine, the older adult population and those economically disadvantaged with technology may not benefit from technology-based healthcare. The available literature on telemedicine during the COVID-19 pandemic has proven to be successful in the management of some patients with LUTS. It is certain that the COVID-19 pandemic has given telemedicine a significant drive for implementation now and in the immediate future. Robust data on long-term efficacy and safety of telemedicine is required to ensure there are governance protocols embedded when looking after patients with LUTS

The molecular basis of antibiotic treatment failure in chronic urinary tract infections

Urinary tract infections (UTIs) are amongst the most common infections worldwide, and are becoming increasingly difficult to treat. In addition to the acceleration of classic antimicrobial resistance, recurrence after initial resolution is common. Our clinical experience is that chronically infected patients sometimes fail to respond to antibiotics predicted to be effective from culture-based sensitivity testing, while antibiotics predicted to be unsuitable can succeed. We hypothesized that the bladder environment could lead to differential bacterial gene expression, resulting in differences in minimum inhibitory concentration (MICs) compared with standard culture. Here, using strains of Escherichia coli evolved in the lab to be resistant to amoxicillin–clavulanic acid, we present data that MICs differ depending on which media the assay is performed in (M9, ISO, LB, human urine), as well as in urine-containing supernatant enriched from urothelial organoids. Next, we examined the behaviour of patient-derived Enterococcus faecalis, one of the main causative agents of chronic UTIs in the elderly. We are in the process of evaluating the MIC of first-line UTI antibiotics using growth media supplemented with urine, to more closely mimic the native uropathogen environment. Moreover, we are characterising the resistance genes expressed in those differing environments using next generation sequencing technology and comparing the results with those obtained from bacteria grown on standard diagnostic media. Our work demonstrates the danger of extrapolating biological behaviour from artificial culture substrates and may lead to better diagnostic tests and treatments for chronic UTI

Urinary ATP as an indicator of infection and inflammation of the urinary tract in patients with lower urinary tract symptoms

BACKGROUND: Adenosine-5'-triphosphate (ATP) is a neurotransmitter and inflammatory cytokine implicated in the pathophysiology of lower urinary tract disease. ATP additionally reflects microbial biomass thus has potential as a surrogate marker of urinary tract infection (UTI). The optimum clinical sampling method for ATP urinalysis has not been established. We tested the potential of urinary ATP in the assessment of lower urinary tract symptoms, infection and inflammation, and validated sampling methods for clinical practice. METHODS: A prospective, blinded, cross-sectional observational study of adult patients presenting with lower urinary tract symptoms (LUTS) and asymptomatic controls, was conducted between October 2009 and October 2012. Urinary ATP was assayed by a luciferin-luciferase method, pyuria counted by microscopy of fresh unspun urine and symptoms assessed using validated questionnaires. The sample collection, storage and processing methods were also validated. RESULTS: 75 controls and 340 patients with LUTS were grouped as without pyuria (n = 100), pyuria 1-9 wbc ?l(-1) (n = 120) and pyuria ?10 wbc ?l(-1) (n = 120). Urinary ATP was higher in association with female gender, voiding symptoms, pyuria greater than 10 wbc ?l(-1) and negative MSU culture. ROC curve analysis showed no evidence of diagnostic test potential. The urinary ATP signal decayed with storage at 23°C but was prevented by immediate freezing at ??-20°C, without boric acid preservative and without the need to centrifuge urine prior to freezing. CONCLUSIONS: Urinary ATP may have a role as a research tool but is unconvincing as a surrogate, clinical diagnostic marker

Cross-over data supporting long-term antibiotic treatment in patients with painful lower urinary tract symptoms, pyuria and negative urinalysis

PURPOSE: To measure the effects of an unplanned, sudden cessation of treatment in an unselected group of patients with chronic painful LUTS managed with protracted antimicrobial treatment and to report these observational data collected from a cross-over process. MATERIALS AND METHODS: The imposition of a guideline resulted in the immediate cessation of antibiotic treatment in a cohort of patients with chronic painful LUTS and microscopic pyuria. Patients were assessed before treatment withdrawal, whilst off treatment, and following reinstatement. Outcome measures included a validated symptom score, microscopic enumeration of urinary white cells and uroepithelial cells, and routine urine culture. RESULTS: These patients had reported treatment-resistant, painful LUTS for a mean of 6.5 years before treatment at this centre. Treatment was stopped in 221 patients (female = 210; male = 11; mean age = 56 years; SD = 17.81). Sixty-six per cent of women were post-menopausal. After unplanned treatment cessation, 199 patients (90%; female = 188; male = 9) reported deterioration. Eleven patients required hospital care in association with disease recurrence, including acute urinary tract infection (UTI) and urosepsis. Symptom scores increased after cessation and recovered on reinitiating treatment (F = 33; df = 2; p < 0.001). Urinary leucocyte (F = 3.7; df = 2; p = 0.026) and urothelial cells counts mirrored symptomatic changes (F = 6.0; df = 2; p = 0.003). Routine urine culture results did not reflect changes in disease status. CONCLUSION: These data support the hypothesis that treating painful LUTS associated with pyuria with long-term antimicrobial courses, despite negative urine culture, is effective. The microscopy of fresh unspun, unstained urine to count white cells and epithelial cells offers a valid method of monitoring disease. An unplanned cessation of antibiotic therapy produced a resurgence of symptoms and lower urinary tract inflammation in patients with chronic LUTS, supporting an infective aetiology below the level of routine detection

Altered urothelial ATP signaling in a major subset of human overactive bladder patients with pyuria

Overactive Bladder (OAB) is an idiopathic condition, characterized by urgency, urinary frequency, and urgency incontinence, in the absence of routinely traceable urinary infection. We have described microscopic pyuria (?10 wbc/?l) in patients suffering from the worst symptoms. It is established that inflammation is associated with increased ATP release from epithelial cells, and extracellular ATP originating from the urothelium following increased hydrostatic pressure is a mediator of bladder sensation. Here, using bladder biopsy samples, we have investigated urothelial ATP signaling in OAB patients with microscopic pyuria. Basal, but not stretch-evoked, release of ATP was significantly greater from the urothelium of OAB patients with pyuria than from non-OAB patients or OAB patients without pyuria (<10 wbc/?l). Basal ATP release from the urothelium of OAB patients with pyuria was inhibited by the P2 receptor antagonist suramin and abolished by the hemichannel blocker carbenoxolone, which differed from stretch-activated ATP release. Altered P2 receptor expression was evident in the urothelium from pyuric OAB patients. Furthermore, intracellular bacteria were visualized in shed urothelial cells from ?80% of OAB patients with pyuria. These data suggest that increased ATP release from the urothelium, involving bacterial colonization, may play a role in the heightened symptoms associated with pyuric OAB patients

Clinical urine microscopy for urinary tract infections

Urinary tract infections (UTI) are a common disorder. Its diagnosis can be made by microscopic examination of voided urine for cellular markers of infection. We present a dataset containing 300 images and 3,562 manually annotated urinary cells labelled into seven classes of clinically significant urinary content. It is an enriched dataset with samples acquired from the unstained and untreated urine of patients with symptomatic UTI. The aim of the dataset is to facilitate UTI diagnosis in nearly all clinical settings by using a simple imaging system which leverages advanced machine learning techniques. Data acquisition 300 urine samples were obtained from patients with symptomatic UTI between April and August 2022 from a specialist LUTS outpatient clinic in central London. Urine samples were collected as natural voids and processed on-site within one hour to mitigate cellular degradation. Brightfield microscopic examination (Olympus BX41F microscope frame, U-5RE quintuple nosepiece, U-LS30 LED illuminator, U-AC Abbe condenser) was performed at x20 objective (Olympus PLCN20x Plan C N Achromat 20x/0.4). A disposable haemocytometer (C Chip™) was used for enumeration of red cells (RBC), white cells (WBC), epithelial cells (EPC), and the presence of other cellular content per 1 µl of urine by two experienced microscopists. Images were acquired using the aforementioned brightfield microscope using a 0.5X C-mount adapter connected to a digital colour camera (Infinity 3S-1UR, Teledyne Lumenera). Images were taken in 16-bit colour in 1392 x 1040 .tif format using Capture and Analyse software. An enriched dataset approach was taken to maximise urinary cellular content in the acquired images. Such data curation was also necessary to overcome class imbalance. Daily Kohler illumination and global white balance was performed to ensure consistency in image acquisition. Dataset annotation 300 images were acquired and manually annotated by first identifying cells of interest as a binary semantic segmentation task. Individual pixels were dichotomously labelled as either informative cells, foreground, or non-informative background. Non-informative background was further constrained by including unidentifiable cells, such as debris or grossly out-of-focus particles. Binary annotation was initially performed using ilastik, an open-source software using a Random Forest classifier for pixel classification, then manually refined at the pixel level to ensure accurate semantic segmentation. This produced a binary mask in 1392 x 1040 .tif format for each corresponding raw colour image. Objects of interest were then manually labelled by two expert microscopists into one of seven clinically significant multi-class categories: rods, RBC/WBC, yeast, miscellaneous, single EPC, small EPC sheet, and large EPC sheet. This produced a multi-class mask in 1392 x 1040 .tif format with a label as pixel value from 0-7, where 0 is background (Table 1). Data structure The dataset is organised into three root folders: img (image), bin_mask (binary mask), and mult_mask (multi-class mask). Each folder has 300 files in .tif format and labelled with an incremental number. Table1 Folder Files Objects Count Pixel Values img 300 Raw data 0-255 bin_mask 300 Background/Foreground 0/1 mult_mask 300 Background/Class 0 Rod 1697 1 RBC/WBC 1056 2 Yeast 41 3 Miscellaneous 550 4 Single EPC 182 5 Small EPC sheet 26 6 Large EPC sheet 10 7 Total 356

Clinical urine microscopy for urinary tract infections

Urinary tract infections (UTI) are a common disorder. Its diagnosis can be made by microscopic examination of voided urine for cellular markers of infection. We present a dataset containing 300 images and 3,562 manually annotated urinary cells labelled into seven classes of clinically significant urinary content. It is an enriched dataset with samples acquired from the unstained and untreated urine of patients with symptomatic UTI. The aim of the dataset is to facilitate UTI diagnosis in nearly all clinical settings by using a simple imaging system which leverages advanced machine learning techniques. Data acquisition 300 urine samples were obtained from patients with symptomatic UTI between April and August 2022 from a specialist LUTS outpatient clinic in central London. Urine samples were collected as natural voids and processed on-site within one hour to mitigate cellular degradation. Brightfield microscopic examination (Olympus BX41F microscope frame, U-5RE quintuple nosepiece, U-LS30 LED illuminator, U-AC Abbe condenser) was performed at x20 objective (Olympus PLCN20x Plan C N Achromat 20x/0.4). A disposable haemocytometer (C Chip™) was used for enumeration of red cells (RBC), white cells (WBC), epithelial cells (EPC), and the presence of other cellular content per 1 µl of urine by two experienced microscopists. Images were acquired using the aforementioned brightfield microscope using a 0.5X C-mount adapter connected to a digital colour camera (Infinity 3S-1UR, Teledyne Lumenera). Images were taken in 16-bit colour in 1392 x 1040 .tif format using Capture and Analyse software. An enriched dataset approach was taken to maximise urinary cellular content in the acquired images. Such data curation was also necessary to overcome class imbalance. Daily Kohler illumination and global white balance was performed to ensure consistency in image acquisition. Dataset annotation 300 images were acquired and manually annotated by first identifying cells of interest as a binary semantic segmentation task. Individual pixels were dichotomously labelled as either informative cells, foreground, or non-informative background. Non-informative background was further constrained by including unidentifiable cells, such as debris or grossly out-of-focus particles. Binary annotation was initially performed using ilastik, an open-source software using a Random Forest classifier for pixel classification, then manually refined at the pixel level to ensure accurate semantic segmentation. This produced a binary mask in 1392 x 1040 .tif format for each corresponding raw colour image. Objects of interest were then manually labelled by two expert microscopists into one of seven clinically significant multi-class categories: rods, RBC/WBC, yeast, miscellaneous, single EPC, small EPC sheet, and large EPC sheet. This produced a multi-class mask in 1392 x 1040 .tif format with a label as pixel value from 0-7, where 0 is background (Table 1). Data structure The dataset is organised into three root folders: img (image), bin_mask (binary mask), and mult_mask (multi-class mask). Each folder has 300 files in .tif format and labelled with an incremental number. Table1 Folder Files Objects Count Pixel Values img 300 Raw data 0-255 bin_mask 300 Background/Foreground 0/1 mult_mask 300 Background/Class 0 Rod 1697 1 RBC/WBC 1056 2 Yeast 41 3 Miscellaneous 550 4 Single EPC 182 5 Small EPC sheet 26 6 Large EPC sheet 10 7 Total 356