Diagnostic usefulness of procalcitonin as a marker of bacteremia in patients with acute pyelonephritis

作者
Young Eun Ha,Cheol‐In Kang,Yu Mi Wi,Doo Ryeon Chung,Eun‐Suk Kang,Nam Yong Lee,Jae‐Hoon Song,Kyong Ran Peck
出处
期刊:Scandinavian Journal of Clinical & Laboratory Investigation [Taylor & Francis]
卷期号:73 (5): 444-448 被引量:17
标识
DOI:10.3109/00365513.2013.803231
摘要

BACKGROUND: Acute pyelonephritis (APN) is one of the most common community-acquired infections and frequently accompanies bacteremia. The purpose of this study was to investigate the diagnostic role of procalcitonin in predicting bacteremia in patients with APN. METHODS: We conducted a retrospective study of patients with APN who visited the emergency department (ED) at Samsung Medical Center, Seoul. Predictors of bacteremia were analyzed and receiver operating characteristics (ROC) curves were plotted for procalcitonin, C-reactive protein (CRP), and leukocytes. RESULTS: During the study period, a total of 147 patients who had microbiologically proven APN and available initial procalcitonin concentrations were identified. Of these, bacteremia was present in 84 patients. Multivariate analysis showed that age, hypotension, and higher procalcitonin concentrations independently predicted the presence of bacteremia. Procalcitonin had better discriminative power than CRP, as reflected by area under the ROC curve analysis (0.746 [95% CI, 0.667-0.826] vs. 0.602 [95% CI, 0.509-0.694], p = 0.02). At a cut-off value of 1.63 μg/L, procalcitonin predicted bacteremia with a sensitivity, specificity, positive predictive value, negative predictive value and accuracy of 61.9, 81.0, 81.3, 61.4 and 70.1%, respectively. CONCLUSION: Procalcitonin concentration could be used as a reliable marker to predict bacteremia in patients with APN in the ED.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Driscoll完成签到 ,获得积分10
1秒前
今后应助hhhh采纳,获得10
1秒前
等意送汝发布了新的文献求助10
1秒前
萨芬撒完成签到,获得积分10
1秒前
秃然发布了新的文献求助10
2秒前
2秒前
4秒前
丘比特应助sylvia采纳,获得10
4秒前
5秒前
5秒前
5秒前
天天完成签到,获得积分20
6秒前
丰富语蕊应助hdbys采纳,获得10
8秒前
9秒前
zxf发布了新的文献求助10
9秒前
村上春树的摩的完成签到 ,获得积分10
9秒前
丹丹发布了新的文献求助10
10秒前
yylg完成签到 ,获得积分10
11秒前
11秒前
fengruiyi完成签到,获得积分10
11秒前
务实寄松发布了新的文献求助10
12秒前
12秒前
13秒前
深情安青应助等意送汝采纳,获得10
15秒前
16秒前
柠檬不吃酸完成签到 ,获得积分10
16秒前
单纯黑米完成签到,获得积分10
17秒前
科研通AI6.3应助勿念采纳,获得10
18秒前
王志鹏完成签到 ,获得积分10
18秒前
Z_yiming完成签到,获得积分10
19秒前
husuhew完成签到,获得积分10
19秒前
zzzz146发布了新的文献求助10
20秒前
lemon完成签到 ,获得积分10
20秒前
BOB完成签到 ,获得积分10
20秒前
zxf完成签到,获得积分10
20秒前
21秒前
Derek完成签到,获得积分0
22秒前
科研甜菜发布了新的文献求助10
22秒前
unkoohh完成签到,获得积分10
22秒前
Lucas应助焱鑫采纳,获得10
22秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Handbuch Trainingswissenschaft – Trainingslehre 500
Additive Manufacturing Design and Applications (ASM Handbook, Volume 24A) 500
Variations: A More Diverse Picture of Contemporary Art 400
A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) Fourth Edition 400
Induction Heating and Heat Treatment (ASM Handbook, Volume 4C) 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7586749
求助须知:如何正确求助?哪些是违规求助? 9165076
关于积分的说明 19614483
捐赠科研通 7167188
什么是DOI,文献DOI怎么找? 3266728
关于科研通互助平台的介绍 2431714
邀请新用户注册赠送积分活动 2258547