Feng Ding-Yun, Zhou Jian-Xia, Li Xia, Wu Wen-Bin, Zhou Yu-Qi, Zhang Tian-Tuo
Department of Pulmonary and Critical Care Medicine, Third Affiliated Hospital of Sun Yat-Sen University, Institute of Respiratory Diseases of Sun Yat-Sen University, Guangzhou, People's Republic of China.
Infect Drug Resist. 2022 Sep 12;15:5401-5409. doi: 10.2147/IDR.S377480. eCollection 2022.
is the most common microorganism in sputum cultures from long-term hospitalized patients and is often the cause of hospital-acquired pneumonia (HAP), which is usually associated with poor prognosis and high mortality. It is sometimes difficult to distinguish between infection and colonization. This study aimed to evaluate factors that differentiate infection from colonization and predict mortality in patients with nosocomial pneumonia caused by .
The data used in this study were collected in our hospital between January 2018 and December 2020 from patients whose sputum cultures were positive for .
A total of 714 patients were included, with 571 in the infection group and 143 in the colonization group. The in-hospital mortality rate in the infection group was 20.5%. Univariate and multivariate logistic regression analyses showed that age, total number of inpatient departments, absolute neutrophil count, and C-reactive protein (CRP) level helped distinguish between infection and colonization. The area under the receiver operating characteristic curve (ROC) of the identification model was 0.694. In the infection group, age, Charlson comorbidity score, neutrophil-to-lymphocyte ratio, blood urea nitrogen/albumin ratio, CRP level, presence of multidrug resistance, and clinical pulmonary infection score (≥6) ratio were associated with in-hospital mortality. The area under the ROC curve for the prediction model was 0.828. The top three drug resistance rates in the infection group were 100% (cefazolin), 98.77% (ceftriaxone), and 71.8% (cefuroxime).
The combination of common parameters helps identify respiratory tract infection or colonization. Several novel predictors can be used to predict the risk of death from pneumonia to reduce mortality. The drug resistance of remains high.
是长期住院患者痰培养中最常见的微生物,常为医院获得性肺炎(HAP)的病因,HAP通常预后不良且死亡率高。有时难以区分感染与定植。本研究旨在评估区分感染与定植的因素,并预测由 引起的医院内肺炎患者的死亡率。
本研究使用的数据于2018年1月至2020年12月在我院收集,来自痰培养 呈阳性的患者。
共纳入714例患者,其中感染组571例,定植组143例。感染组的院内死亡率为20.5%。单因素和多因素逻辑回归分析显示,年龄、住院科室总数、绝对中性粒细胞计数和C反应蛋白(CRP)水平有助于区分感染与定植。识别模型的受试者工作特征曲线(ROC)下面积为0.694。在感染组中,年龄、Charlson合并症评分、中性粒细胞与淋巴细胞比值、血尿素氮/白蛋白比值、CRP水平、多重耐药的存在以及临床肺部感染评分(≥6)比值与院内死亡率相关。预测模型的ROC曲线下面积为0.828。感染组前三位的耐药率分别为100%(头孢唑林)、98.77%(头孢曲松)和71.8%(头孢呋辛)。
常见参数的组合有助于识别 呼吸道感染或定植。几种新的预测指标可用于预测 肺炎的死亡风险以降低死亡率。 的耐药性仍然很高。