Diagnostic accuracy of novel serological biomarkers to detect acute mesenteric ischemia: a systematic review and meta-analysis

医学 缺血修饰白蛋白 内科学 金标准(测试) 血清学 荟萃分析 诊断准确性 胃肠病学 病理 缺血 免疫学 心肌缺血 抗体
作者
Nikki Treskes,Alexandra M. Persoon,Arthur R. H. van Zanten
出处
期刊:Internal and Emergency Medicine [Springer Science+Business Media]
卷期号:12 (6): 821-836 被引量:107
标识
DOI:10.1007/s11739-017-1668-y
摘要

Laparotomy remains the gold standard for diagnosis of acute mesenteric ischemia (AMI), but is often unhelpful or too late due to non-specific clinical and radiological signs. This systematic review and meta-analysis aims to evaluate the diagnostic accuracy of the novel serological biomarkers intestinal fatty acid-binding protein (I-FABP), α-glutathione S-transferase (α-GST), d-lactate, ischemia modified albumin (IMA), and citrulline to detect AMI. A systematic search of electronic databases was performed to identify all published diagnostic accuracy studies on I-FABP, α-GST, d-lactate, IMA, and citrulline. Articles were selected based on pre-defined inclusion and exclusion criteria. Risk of bias and applicability were assessed. Two-by-two contingency tables were constructed to calculate accuracy standards. Summary estimates were computed using random-effects models. The search yielded 1925 papers, 21 were included in the final analysis. Pooled sensitivity and specificity for investigated biomarkers were: I-FABP (Uden); 79.0 (95% CI 66.5–88.5) and 91.3 (87.0–94.6), I-FABP (Osaka); 75.0 (67.9–81.2) and 79.2 (76.2–82.0), d-lactate; 71.7 (58.6–82.5) and 74.2 (69.0–79.0), α-GST; 67.8 (54.2–79.5) and 84.2 (75.3–90.9), IMA; 94.7 (74.0–99.9) and 86.4 (65.1–97.1), respectively. One study investigated accuracy standards for citrulline: sensitivity 39% and specificity 100%. The novel serological biomarkers I-FABP, α-GST, IMA, and citrulline may offer improved diagnostic accuracy of acute mesenteric ischemia; however, further research is required to specify threshold values and accuracy standards for different aetiological forms.

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
Tian发布了新的文献求助20
2秒前
Dor.Ma发布了新的文献求助30
3秒前
3秒前
蓝天发布了新的文献求助10
4秒前
打打应助racill采纳,获得10
4秒前
nys发布了新的文献求助25
5秒前
6秒前
7秒前
Akim应助EpiphanyQ采纳,获得10
7秒前
上官若男应助鱼鱼采纳,获得10
7秒前
追寻凡白完成签到,获得积分20
7秒前
隐形曼青应助蓝天采纳,获得10
7秒前
8秒前
8秒前
神经蛙蛙蛙完成签到 ,获得积分10
9秒前
无极微光应助yzc采纳,获得20
9秒前
脑洞疼应助药猜猜爱采纳,获得10
10秒前
wsj发布了新的文献求助30
10秒前
烟雨发布了新的文献求助10
10秒前
11秒前
11秒前
打打应助玩命的赛君采纳,获得50
11秒前
11秒前
11秒前
桐桐应助ky采纳,获得10
12秒前
maolin发布了新的文献求助100
12秒前
激动的涔发布了新的文献求助10
12秒前
ZXK666发布了新的文献求助10
13秒前
煲珠公发布了新的文献求助10
14秒前
EpiphanyQ完成签到,获得积分10
14秒前
15秒前
16秒前
IT小师弟完成签到,获得积分10
16秒前
16秒前
情怀应助哈哈物怪采纳,获得10
17秒前
18秒前
moo发布了新的文献求助10
18秒前
追寻凡白发布了新的文献求助30
19秒前
19秒前
李一琳发布了新的文献求助10
20秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(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
Environmental Leverage in Times of Climate Crisis: Product Standards, Carbon Border Measures and Preferential Trade Agreements 1000
Matrix Methods in Data Mining and Pattern Recognition 510
Social Skills Improvement System-Rating Scales--Chinese Version 500
Dynamische Polarisation von H-1 und B-11 in (CH-3)-3NBH-3 500
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 7218668
求助须知:如何正确求助?哪些是违规求助? 8849454
关于积分的说明 18674882
捐赠科研通 6875712
什么是DOI,文献DOI怎么找? 3186049
关于科研通互助平台的介绍 2348711
邀请新用户注册赠送积分活动 2160172