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脑计算机断层扫描图像灰-白比值对心脏骤停后神经系统转归的预测价值:一项荟萃分析。

Prognostic Values of the Gray-to-White Matter Ratio on Brain Computed Tomography Images for Neurological Outcomes after Cardiac Arrest: A Meta-Analysis.

机构信息

Emergency Department, Cangzhou Central Hospital, No. 16 Xinhua Road, Yunhe Qu, Cangzhou 061000, China.

出版信息

Biomed Res Int. 2020 Nov 3;2020:7949516. doi: 10.1155/2020/7949516. eCollection 2020.

DOI:10.1155/2020/7949516
PMID:33490256
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7803139/
Abstract

MATERIALS AND METHODS

The PubMed, ScienceDirect, Web of Science, and China National Knowledge Infrastructure databases were searched for all relevant articles published before March 31, 2020, without any language restrictions. The pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated with a random-effects model using Stata 14.0 software.

RESULT

A total of 24 eligible studies with 2812 CA patients were recruited in the meta-analysis. The pooled result showed that decreased GWR was correlated with poor neurological outcomes after CA (OR = 11.28, 95% CI: 6.29-20.21, and < 0.001) with moderate heterogeneity ( = 71.5%, < 0.001). The pooled sensitivity and specificity were 0.58 (95% CI: 0.47-0.68) and 0.95 (95% CI: 0.87-0.98), respectively. The area under the curve (AUC) of GWR was 0.84 (95% CI: 0.80-0.87). Compared with GWR (cerebrum) and GWR (average), GWR using the basal ganglion level of brain CT had the highest AUC of 0.87 (0.84-0.90). Subgroup analysis indicated that heterogeneity may be derived from the time of CT measurement, preset specificity, targeted temperature management, or proportion of cardiac etiology. Sensitivity analysis indicated that the result was stable, and Deeks' plot showed no possible publication bias ( = 0 .64).

CONCLUSION

Current research suggests that GWR, especially using the basal ganglion level of brain CT, is a useful parameter for determining neurological outcomes after CA.

摘要

材料和方法

检索了 PubMed、ScienceDirect、Web of Science 和中国国家知识基础设施数据库,以获取截至 2020 年 3 月 31 日之前发表的所有相关文章,没有任何语言限制。使用 Stata 14.0 软件,采用随机效应模型计算汇总优势比(OR)和 95%置信区间(CI)。

结果

荟萃分析共纳入 24 项符合条件的研究,涉及 2812 例 CA 患者。汇总结果显示,CA 后 GWR 降低与不良神经结局相关(OR=11.28,95%CI:6.29-20.21,<0.001),存在中度异质性(I²=71.5%,<0.001)。汇总的敏感性和特异性分别为 0.58(95%CI:0.47-0.68)和 0.95(95%CI:0.87-0.98)。GWR 的曲线下面积(AUC)为 0.84(95%CI:0.80-0.87)。与 GWR(大脑)和 GWR(平均)相比,使用脑 CT 基底节水平的 GWR 具有最高的 AUC(0.87,0.84-0.90)。亚组分析表明,异质性可能来源于 CT 测量时间、预设特异性、目标温度管理或心脏病因比例。敏感性分析表明结果稳定,Deeks 图表明无可能的发表偏倚(=0.64)。

结论

目前的研究表明,GWR,特别是使用脑 CT 基底节水平,是判断 CA 后神经结局的有用参数。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e36/7803139/437d29159e40/BMRI2020-7949516.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e36/7803139/cc5f58acd8df/BMRI2020-7949516.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e36/7803139/105a80c78a23/BMRI2020-7949516.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e36/7803139/eb5aafcab806/BMRI2020-7949516.003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e36/7803139/437d29159e40/BMRI2020-7949516.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e36/7803139/cc5f58acd8df/BMRI2020-7949516.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e36/7803139/105a80c78a23/BMRI2020-7949516.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e36/7803139/eb5aafcab806/BMRI2020-7949516.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e36/7803139/540d59cc4148/BMRI2020-7949516.004.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e36/7803139/437d29159e40/BMRI2020-7949516.006.jpg

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