Validation of Distinct Bladder Pain Phenotypes Utilizing the MAPP Research Network Cohort.

INTRODUCTION AND HYPOTHESIS: As interstitial cystitis/bladder pain syndrome (IC/BPS) likely represents multiple pathophysiologies, we sought to validate three clinical phenotypes of IC/BPS patients in a large, multi-center cohort using unsupervised machine learning (ML) analysis. METHODS: Using the female Genitourinary Pain Index and O'Leary-Sant Indices, k-means unsupervised clustering was utilized to define symptomatic phenotypes in 130 premenopausal IC/BPS participants recruited through the Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) research network. Patient-reported symptoms were directly compared between MAPP ML-derived phenotypic clusters to previously defined phenotypes from a single center (SC) cohort. RESULTS: Unsupervised ML categorized IC/BPS participants into three phenotypes with distinct pain and urinary symptom patterns: myofascial pain, non-urologic pelvic pain, and bladder-specific pain. Defining characteristics included presence of myofascial pain or trigger points on examination for myofascial pain patients (p = 0.003) and bladder pain/burning for bladder-specific pain patients (p < 0.001). The three phenotypes were derived using only 11 features (fGUPI subscales and ICSI/ICPI items), in contrast to 49 items required previously. Despite substantial reduction in classification features, unsupervised ML independently generated similar symptomatic clusters in the MAPP cohort with equivalent symptomatic patterns and physical examination findings as the SC cohort. CONCLUSIONS: The reproducible identification of IC/BPS phenotypes, distinguishing bladder-specific pain from myofascial and genital pain, using independent ML analysis of a multicenter database suggests these phenotypes reflect true pathophysiologic differences in IC/BPS patients.

Molecular Diagnostic Methods Versus Conventional Urine Culture for Diagnosis and Treatment of Urinary Tract Infection: A Systematic Review and Meta-analysis.

Context: Urine culture has low sensitivity in the diagnosis of urinary tract infection (UTI). Next-generation sequencing (NGS) and polymerase chain reaction (PCR) are culture-independent molecular methods available for commercial use to diagnose UTI. Objective: To systematically evaluate the evidence comparing the diagnostic and therapeutic values of molecular diagnostic methods to urine culture in the management of UTI in adults. Evidence acquisition: We performed a critical review of Embase, Ovid, and PubMed in February 2022 according to the Preferred Reporting Items for Systematic Review and Meta-analyses statement. Studies involving pregnant women, ureteral stones, ureteral stents, and percutaneous nephrostomy tubes were excluded. Risk of bias and methodological quality were assessed using the Cochrane risk of bias tool and Newcastle Ottawa Scale. Fifteen publications were selected for inclusion. Evidence synthesis: Included reports compared NGS (nine studies) and PCR (six studies) to urine culture. A meta-analysis of seven similar studies utilizing NGS demonstrates that NGS is more sensitive in the identification of urinary bacteria and detects greater species diversity per urine sample than culture. PCR protocols designed to detect a diverse range of microbes had increased sensitivity and species diversity compared with culture. Phenotypic and genotypic resistomes are concordant in approximately 85% of cases. There is insufficient evidence to compare patient symptomatic responses to antibiotic therapy guided by molecular testing versus standard susceptibility testing. Conclusions: Moderately strong evidence exists that molecular diagnostics demonstrate increased sensitivity in detecting urinary bacteria at the expense of poor specificity in controls. Additional data comparing patient symptoms and cure rates following antibiotic selection directed by molecular methods compared with culture are needed to elucidate their place in UTI care. Patient summary: We compare culture-independent molecular methods with urine culture in the management of urinary tract infection. We found good evidence that molecular methods detect more bacteria than culture; however, the clinical implications to support their routine use are unclear.