Lazar Dragos Stefan, Nica Maria, Codreanu Daniel Romeo, Kosa Alma Gabriela, Visinescu Lucian L, Popescu Corneliu Petru, Efrem Ion Cristian, Florescu Simin Aysel, Gherlan George Sebastian
"Dr Victor Babes" Clinical Hospital of Infectious and Tropical Diseases, "Carol Davila" University of Medicine and Pharmacy, 030303 Bucharest, Romania.
Department of Information Systems & Analytics Austin, Texas State University, San Marcos, TX 78666, USA.
Antibiotics (Basel). 2024 Dec 3;13(12):1170. doi: 10.3390/antibiotics13121170.
The emergence of carbapenem-resistant pathogenic bacteria is a growing global public health concern. Carbapenem-resistant uropathogenic strains of can cause uncomplicated or complicated urinary tract infections, leading to a high risk of treatment failure and the spread of resistance determinants. The objectives of this 24-month study were to identify the prognostic characteristics of patients who were infected with carbapenem-resistant () and to create a tool to estimate the probability of a infection before having the complete results of a patient's antibiogram. We found that 41.6% of all urinary infections with were caused by . Factors such as male gender, the presence of upper urinary tract infections, invasive urinary maneuvers, recent infection with or carriage of the germ, and the nosocomial occurrence of UTIs with were predictive for infection. Based on these factors, we proposed a model to estimate the presence of . A retrospective case-control study including all hospitalized patients with urinary tract infections (UTIs) caused by was carried out. We reported data as percentages, identified independent predictors of the presence of , and proposed a tool to evaluate the probability through multivariate analysis. Through this study, we aim to provide clinicians with a tool to support decision making regarding first-line antibiotic treatment.
耐碳青霉烯类病原菌的出现是一个日益严重的全球公共卫生问题。耐碳青霉烯类尿路致病性菌株可引起单纯性或复杂性尿路感染，导致治疗失败风险高以及耐药决定因素的传播。这项为期24个月的研究的目的是确定感染耐碳青霉烯类大肠埃希菌（CR-E）患者的预后特征，并创建一种工具，在获得患者抗菌谱的完整结果之前估计CR-E感染的概率。我们发现，所有大肠埃希菌尿路感染中有41.6%是由CR-E引起的。男性性别、上尿路感染的存在、侵入性尿路操作、近期感染或携带该病菌以及医院内发生的CR-E尿路感染等因素可预测CR-E感染。基于这些因素，我们提出了一个模型来估计CR-E的存在情况。开展了一项回顾性病例对照研究，纳入了所有因CR-E引起尿路感染（UTI）的住院患者。我们以百分比形式报告数据，确定CR-E存在的独立预测因素，并通过多变量分析提出一种评估概率的工具。通过这项研究，我们旨在为临床医生提供一种工具，以支持有关一线抗生素治疗的决策。
