Complicated Urinary Tract Infections

Augustin, Goran

doi:10.1007/978-3-031-26021-6_27

Cited by 3 publications

(3 citation statements)

References 100 publications

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“…Algumas ITUs são mais simples, e por isso podem receber uma terapia com antibióticos em nível ambulatorial. Em contrapartida, as infecções mais complicadas apresentam maior deficiência no tratamento e maior risco à saúde da gestante, normalmente necessitam da utilização de medicamentos com uso mais prolongado e de alguns exames laboratoriais complementares 17 .…”

Section: Conduta Terapêutica Para Infecção De Trato Urináriounclassified

Manejo de infecção urinária durante a gestação

Cunha,

Alencar,

Takamori

et al. 2023

GANJ

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ARTIGO DE REVISÃO Manejo de infecção urinária durante a gestação Management of urinary tract infection during pregnancy Manejo de la infección del tracto urinario durante el embarazo ResumoObjetivou-se verificar as estratégias utilizadas no pré-natal em relação à prevenção de infecção urinária na gestação. Trata-se de uma revisão integrativa da literatura, realizada em julho de 2023, na Plataforma de Base de Dados da Biblioteca Virtual em Saúde, com o intuito de identificar pesquisas relacionadas à prevenção de infecção urinária na gestação de 2018 a 2023. Mediante os Descritores em Ciências da Saúde: "gravidez", "infecção urinária", "assistência pré-natal", "prevenção primária" e "educação em saúde" que foram integrados por meio do operador booleano "AND". Cinco artigos foram selecionados. Estratégias eficazes no controle da infecção urinária na gestação, como monitoramento regular, tratamentos específicos e promoção de hábitos higiênicos, são essenciais para garantir a saúde materna e fetal, prevenindo complicações durante a gravidez. Conclui-se que pesquisas em relação às infecções urinárias são incipientes e cabe à equipe de saúde realizar orientações em relação a técnica correta da coleta de urina, solicitar exames precocemente para diagnosticar e tratar os casos, e instituir tratamento antimicrobiano mais adequado e eficaz, quanto mais cedo a infecção for controlada, melhores serão os resultados.

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Section: Conduta Terapêutica Para Infecção De Trato Urináriounclassified

Manejo de infecção urinária durante a gestação

Cunha,

Alencar,

Takamori

et al. 2023

GANJ

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“…Urinary tract infections (UTIs) represent a significant global public health concern, affecting approximately 150 million individuals annually [1,2]. These infections, broadly categorized into uncomplicated and complicated UTIs [3,4] can lead to serious complications if left untreated, such as pyelonephritis, hypertension, renal scarring, and sepsis [5,6].…”

Section: Introductionmentioning

confidence: 99%

Decline in ESBL Production and Carbapenem Resistance in Urinary Tract Infections among Key Bacterial Species during the COVID-19 Pandemic

Altamimi,

Binkhamis,

Alhumimidi

et al. 2024

Antibiotics

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The COVID-19 pandemic has led to significant changes in healthcare practices, including increased antibiotic usage. This study aimed to investigate the impact of the pandemic on the prevalence of extended-spectrum β-lactamase (ESBL) production and carbapenem resistance among key bacterial species causing urinary tract infections (UTIs). Conducted at King Fahad Medical City in Riyadh from January 2018 to December 2022, the study analyzed urine samples from 9697 UTI patients. Patients were categorized into ‘pre-COVID-19’ and ‘during COVID-19’ groups. Bacterial isolates were identified, and antimicrobial susceptibility testing was performed following guidelines. ESBL production was detected using the Double-Disc Synergy Test. Escherichia coli and Klebsiella pneumoniae were the main pathogens. During the pandemic, ESBL production decreased in E. coli by 1.9% and in K. pneumoniae by 6.0%. Carbapenem resistance also declined, with E. coli displaying a 1.2% reduction and K. pneumoniae and Pseudomonas aeruginosa displaying 10.7% and 7.9% reductions, respectively. Notably, logistic regression analysis revealed that the odds of ESBL presence were 10% lower during the COVID-19 pandemic (OR 0.91; 95% CI 0.83–0.99; p = 0.040), and there was a significant reduction in the odds of carbapenem resistance (OR 0.43; 95% CI 0.37–0.51; p < 0.001). This study reveals a significant decrease in ESBL production and carbapenem resistance among UTI pathogens during the COVID-19 pandemic, hinting at the impact of modified antibiotic and healthcare approaches. It emphasizes the need for persistent antimicrobial resistance surveillance and policy adaptation to address resistance challenges, offering key directions for future public health actions.

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“…Bladder (cystitis) infections can sometimes ascend to the kidney(s) (pyelonephritis) and potentially into the bloodstream resulting in bacteraemia. Up to 50% of human sepsis cases are associated with Escherichia coli (E. coli) originating from a urinary tract infection (6,7). Conversely and much less commonly, kidney infections and UTIs can result from a bloodstream infection.…”

Section: Introductionmentioning

confidence: 99%

Predictive phage therapy forEscherichia coliurinary tract infections: cocktail selection for therapy based on machine learning models

Keith,

Park de la Torriente,

Chalka

et al. 2023

Preprint

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This study supports the development of predictive bacteriophage (phage) therapy: the concept of phage cocktail selection to treat a bacterial infection based on machine learning models (MLM). For this purpose, MLM were trained on thousands of measured interactions between a panel of phage and sequenced bacterial isolates. The concept was applied toEscherichia coli(E. coli) associated with urinary tract infections. This is an important common infection in humans and companion animals from which multi-drug resistant (MDR) bloodstream infections can originate. The global threat of MDR infection has reinvigorated international efforts into alternatives to antibiotics including phage therapy.E. coliexhibit extensive genome-level variation due to horizontal gene transfer via phage and plasmids. Associated with this, phage selection forE. coliis difficult as individual isolates can exhibit considerable variation in phage susceptibility due to differences in factors important to phage infection including phage receptor profiles and resistance mechanisms. The activity of 31 phage were measured on 314 isolates with growth curves in artificial urine. Random Forest models were built for each phage from bacterial genome features and the more generalist phage, acting on over 20% of the bacterial population, exhibited F1 scores of >0.6 and could be used to predict phage cocktails effective against previously untested strains. The study demonstrates the potential of predictive models which integrate bacterial genomics with phage activity datasets allowing their use on data derived from direct sequencing of clinical samples to inform rapid and effective phage therapy.Significance StatementWith the growing challenge of antimicrobial resistance there is an urgency for alternative treatments for common bacterial diseases including urinary tract infections (UTIs).Escherichia coliis the main causative agent of UTIs in both humans and companion animals with multidrug resistant strains such as the globally disseminated ST131 becoming more common. Bacteriophage (phage) are natural predators of bacteria and potentially an alternative therapy. However, a major barrier for phage therapy is the specificity of phage on target bacteria and therefore difficulty efficiently selecting the appropriate phage. Here, we demonstrate a genomics driven approach using machine learning prediction models combined with phage activity clustering to select phage cocktails based only on the genome sequence of the infecting bacterial strain.

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Complicated Urinary Tract Infections

Cited by 3 publications

References 100 publications

Manejo de infecção urinária durante a gestação

Manejo de infecção urinária durante a gestação

Decline in ESBL Production and Carbapenem Resistance in Urinary Tract Infections among Key Bacterial Species during the COVID-19 Pandemic

Predictive phage therapy forEscherichia coliurinary tract infections: cocktail selection for therapy based on machine learning models

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