Suppr超能文献

预测工具在全因急性呼吸道感染老年个体风险分层中的应用。

Utility of predictive tools for risk stratification of elderly individuals with all-cause acute respiratory infection.

机构信息

Duke University School of Medicine, Durham, NC, USA.

Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, USA.

出版信息

Infection. 2019 Aug;47(4):617-627. doi: 10.1007/s15010-019-01299-1. Epub 2019 Mar 30.

Abstract

PURPOSE

A number of scoring tools have been developed to predict illness severity and patient outcome for proven pneumonia, however, less is known about the utility of clinical prediction scores for all-cause acute respiratory infection (ARI), especially in elderly subjects who are at increased risk of poor outcomes.

METHODS

We retrospectively analyzed risk factors and outcomes of individuals ≥ 60 years of age presenting to the emergency department with a clinical diagnosis of ARI.

RESULTS

Of 276 individuals in the study, 40 had proven viral infection and 52 proven bacterial infection, but 184 patients with clinically adjudicated ARI (67%) remained without a proven microbial etiology despite extensive clinical (and expanded research) workup. Patients who were older, had multiple comorbidities, or who had proven bacterial infection were more likely to require hospital and ICU admission. We identified a novel model based on 11 demographic and clinical variables that were significant risk factors for ICU admission or mortality in elderly subjects with all-cause ARI. As comparators, a modified PORT score was found to correlate more closely with all-cause ARI severity than a modified CURB-65 score (r, 0.54, 0.39). Interestingly, modified Jackson symptom scores were found to inversely correlate with severity (r, - 0.34) but show potential for differentiating viral and bacterial etiologies.

CONCLUSIONS

Modified PORT, CURB-65, Jackson symptom scores, and a novel ARI scoring tool presented herein all offer predictive ability for all-cause ARI in elderly subjects. Such broadly applicable scoring metrics have the potential to assist in treatment and triage decisions at the point of care.

摘要

目的

已经开发出许多评分工具来预测已确诊肺炎的疾病严重程度和患者预后,但对于临床预测评分在所有病因急性呼吸道感染(ARI)中的作用知之甚少,尤其是在那些发生不良结局风险增加的老年患者中。

方法

我们回顾性分析了急诊科就诊的年龄≥60 岁的具有 ARI 临床诊断的个体的危险因素和结局。

结果

在研究的 276 名患者中,40 名患有明确的病毒感染,52 名患有明确的细菌感染,但 184 名具有临床判定的 ARI(67%)尽管进行了广泛的临床(和扩展的研究)评估,但仍未确定明确的微生物病因。年龄较大、有多种合并症或有明确细菌感染的患者更有可能需要住院和 ICU 入院。我们确定了一个基于 11 个人口统计学和临床变量的新模型,这些变量是老年患者所有病因 ARI 发生 ICU 入院或死亡的显著危险因素。作为比较,改良 PORT 评分与所有病因 ARI 严重程度的相关性较改良 CURB-65 评分更为密切(r 值分别为 0.54 和 0.39)。有趣的是,改良的 Jackson 症状评分与严重程度呈负相关(r 值为-0.34),但具有区分病毒和细菌病因的潜力。

结论

改良 PORT、CURB-65、Jackson 症状评分和本文提出的新的 ARI 评分工具都为老年患者的所有病因 ARI 提供了预测能力。这些广泛适用的评分指标有可能在护理点协助治疗和分诊决策。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验