Advances in the Diagnosis of Urinary Tract Infection: A Narrative Review

Urinary tract infections are among the most frequent bacterial infections, significantly impacting patient morbidity and healthcare resources. Prompt and accurate diagnosis is crucial to ensure effective treatment, prevent complications such as pyelonephritis or sepsis, and reduce inappropriate anti...

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Main Authors: Juan Victor Ariel Franco, Nicolás Meza
Format: Article
Language:English
Published: Korean Association of Urogenital Tract Infection and Inflammation 2025-04-01
Series:Urogenital Tract Infection
Subjects:
Online Access:http://euti.org/upload/pdf/uti-2550020010.pdf
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author Juan Victor Ariel Franco
Nicolás Meza
author_facet Juan Victor Ariel Franco
Nicolás Meza
author_sort Juan Victor Ariel Franco
collection DOAJ
description Urinary tract infections are among the most frequent bacterial infections, significantly impacting patient morbidity and healthcare resources. Prompt and accurate diagnosis is crucial to ensure effective treatment, prevent complications such as pyelonephritis or sepsis, and reduce inappropriate antibiotic use, contributing to antimicrobial resistance (AMR). Despite consensus across international guidelines from organizations, challenges persist, particularly in distinguishing true infections from asymptomatic bacteriuria or nonspecific symptoms, especially in older adults. Recent advancements in diagnostic technology have emerged to address these limitations, including molecular diagnostics, point-of-care testing (POCT), and artificial intelligence (AI)-driven predictive models. Molecular techniques, notably polymerase chain reaction, loop-mediated isothermal amplification, and metagenomic next-generation sequencing, offer enhanced sensitivity and specificity, rapid detection times, and comprehensive identification of pathogens and resistance profiles. POCT innovations, such as lateral flow immunoassays, enzymatic-based rapid tests, and novel biosensors, facilitate prompt bedside diagnosis, although specificity challenges remain. Meanwhile, AI and machine learning models demonstrate significant potential for risk stratification, prediction of infection, and improving antibiotics prescription practices yet face barriers related to validation, practical integration, and clinical acceptability. Despite promising developments, significant gaps remain, including limited real-world implementation evidence, high costs, and insufficient data from diverse populations. Further rigorous clinical studies, economic evaluations, and practical implementation assessments are urgently required. Addressing these research gaps could substantially improve patient outcomes, optimize antibiotic stewardship, and reduce the global burden of AMR.
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spelling doaj-art-05d09cc84c7246faafac642e850cdf1f2025-08-20T03:58:11ZengKorean Association of Urogenital Tract Infection and InflammationUrogenital Tract Infection2465-82432465-85102025-04-01201172710.14777/uti.2550020010431Advances in the Diagnosis of Urinary Tract Infection: A Narrative ReviewJuan Victor Ariel Franco0Nicolás Meza1 Institute of General Practice, Centre for Health and Society, Medical Faculty, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany Interdisciplinary Centre for Health Studies CIESAL, Universidad de Valparaíso, Viña del Mar, ChileUrinary tract infections are among the most frequent bacterial infections, significantly impacting patient morbidity and healthcare resources. Prompt and accurate diagnosis is crucial to ensure effective treatment, prevent complications such as pyelonephritis or sepsis, and reduce inappropriate antibiotic use, contributing to antimicrobial resistance (AMR). Despite consensus across international guidelines from organizations, challenges persist, particularly in distinguishing true infections from asymptomatic bacteriuria or nonspecific symptoms, especially in older adults. Recent advancements in diagnostic technology have emerged to address these limitations, including molecular diagnostics, point-of-care testing (POCT), and artificial intelligence (AI)-driven predictive models. Molecular techniques, notably polymerase chain reaction, loop-mediated isothermal amplification, and metagenomic next-generation sequencing, offer enhanced sensitivity and specificity, rapid detection times, and comprehensive identification of pathogens and resistance profiles. POCT innovations, such as lateral flow immunoassays, enzymatic-based rapid tests, and novel biosensors, facilitate prompt bedside diagnosis, although specificity challenges remain. Meanwhile, AI and machine learning models demonstrate significant potential for risk stratification, prediction of infection, and improving antibiotics prescription practices yet face barriers related to validation, practical integration, and clinical acceptability. Despite promising developments, significant gaps remain, including limited real-world implementation evidence, high costs, and insufficient data from diverse populations. Further rigorous clinical studies, economic evaluations, and practical implementation assessments are urgently required. Addressing these research gaps could substantially improve patient outcomes, optimize antibiotic stewardship, and reduce the global burden of AMR.http://euti.org/upload/pdf/uti-2550020010.pdfurinary tract infectionspoint-of-care testingpolymerase chain reactionmicrobial drug resistance
spellingShingle Juan Victor Ariel Franco
Nicolás Meza
Advances in the Diagnosis of Urinary Tract Infection: A Narrative Review
Urogenital Tract Infection
urinary tract infections
point-of-care testing
polymerase chain reaction
microbial drug resistance
title Advances in the Diagnosis of Urinary Tract Infection: A Narrative Review
title_full Advances in the Diagnosis of Urinary Tract Infection: A Narrative Review
title_fullStr Advances in the Diagnosis of Urinary Tract Infection: A Narrative Review
title_full_unstemmed Advances in the Diagnosis of Urinary Tract Infection: A Narrative Review
title_short Advances in the Diagnosis of Urinary Tract Infection: A Narrative Review
title_sort advances in the diagnosis of urinary tract infection a narrative review
topic urinary tract infections
point-of-care testing
polymerase chain reaction
microbial drug resistance
url http://euti.org/upload/pdf/uti-2550020010.pdf
work_keys_str_mv AT juanvictorarielfranco advancesinthediagnosisofurinarytractinfectionanarrativereview
AT nicolasmeza advancesinthediagnosisofurinarytractinfectionanarrativereview