The mortality predicting ability of chest X-ray severity scoring systems in Covid-19 pneumonia.

I. Kodikara, B. Galabada, N. S. Hettiarachchi
{"title":"The mortality predicting ability of chest X-ray severity scoring systems in Covid-19 pneumonia.","authors":"I. Kodikara, B. Galabada, N. S. Hettiarachchi","doi":"10.4038/cmj.v66i4.9507","DOIUrl":null,"url":null,"abstract":"Introduction\nAlthough several chest X-ray (CXR) severity scoring systems are in use to assess Covid-19 pneumonia (CP), inhomogeneity has been observed among the assessment methodologies.\n\n\nObjectives\nTo describe and validate severity scoring system based on different features to identify the most suitable scoring system to predict CP severity and outcome.\n\n\nMethod\nThis retrospective study examined CXRs (n=147) of CP patients (n=85) to calculate severity scores using three scoring systems based on area infiltrated and the density patterns: A, A&D, and New. The best scoring system to predict the mortality was identified using the area under the curve (AUC) and linear regression analysis.\n\n\nResults\nRegardless of the scoring system used, CXR severity has shown a good correlation to clinical CP severity (A: χ2=6.745; p =0.034; A&D: χ2=12.404; p =0.002; New: χ2=10.219; p =0.006). The mortality predictability of all scoring systems were satisfactory with high AUC (\"A\": AUC=0.685, sensitivity:67.4%, specificity:54.5% at a cut-off point of 5/8; positive predictive value (PPV): 40.3%, negative predictive value (NPV):78.6%\"; A&D\": AUC=0.748, sensitivity:69.6%, specificity:61.4% at a cut-off point of 7/16, PPV:45.1%, NPV:81.6%; \"New\": AUC=0.727; p ≤ 0.001, sensitivity:67.4%, specificity:68.3% at a cut-off point of 18/48, PPV:49.2%, NPV:82.1%). Additionally, the mortality predicting ability of the \"New\" scoring system was significantly higher than the other two systems (OR:2.897; CI [1.071-7.8.36]; p=0.036).\n\n\nConclusion\nCovid-19 pneumonia severity assessed with the CXR severity scoring systems correlated significantly with clinical severity and outcome. Overall, the \"New\" CXR severity scoring system is comparatively better at predicting the mortality of Covid-19 pneumonia.","PeriodicalId":122256,"journal":{"name":"The Ceylon medical journal","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Ceylon medical journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4038/cmj.v66i4.9507","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Introduction Although several chest X-ray (CXR) severity scoring systems are in use to assess Covid-19 pneumonia (CP), inhomogeneity has been observed among the assessment methodologies. Objectives To describe and validate severity scoring system based on different features to identify the most suitable scoring system to predict CP severity and outcome. Method This retrospective study examined CXRs (n=147) of CP patients (n=85) to calculate severity scores using three scoring systems based on area infiltrated and the density patterns: A, A&D, and New. The best scoring system to predict the mortality was identified using the area under the curve (AUC) and linear regression analysis. Results Regardless of the scoring system used, CXR severity has shown a good correlation to clinical CP severity (A: χ2=6.745; p =0.034; A&D: χ2=12.404; p =0.002; New: χ2=10.219; p =0.006). The mortality predictability of all scoring systems were satisfactory with high AUC ("A": AUC=0.685, sensitivity:67.4%, specificity:54.5% at a cut-off point of 5/8; positive predictive value (PPV): 40.3%, negative predictive value (NPV):78.6%"; A&D": AUC=0.748, sensitivity:69.6%, specificity:61.4% at a cut-off point of 7/16, PPV:45.1%, NPV:81.6%; "New": AUC=0.727; p ≤ 0.001, sensitivity:67.4%, specificity:68.3% at a cut-off point of 18/48, PPV:49.2%, NPV:82.1%). Additionally, the mortality predicting ability of the "New" scoring system was significantly higher than the other two systems (OR:2.897; CI [1.071-7.8.36]; p=0.036). Conclusion Covid-19 pneumonia severity assessed with the CXR severity scoring systems correlated significantly with clinical severity and outcome. Overall, the "New" CXR severity scoring system is comparatively better at predicting the mortality of Covid-19 pneumonia.
胸片严重程度评分系统对Covid-19肺炎病死率的预测能力
虽然有几种胸部x线(CXR)严重程度评分系统用于评估Covid-19肺炎(CP),但观察到评估方法之间存在不均匀性。目的描述和验证基于不同特征的严重程度评分系统,以确定最适合预测CP严重程度和预后的评分系统。方法回顾性分析CP患者(85例)的x射线影像(n=147),采用A、A&D和New三种基于浸润面积和密度模式的评分系统计算严重程度评分。采用曲线下面积(AUC)和线性回归分析确定了预测死亡率的最佳评分体系。结果无论采用何种评分系统,CXR严重程度与临床CP严重程度均有良好的相关性(χ2=6.745;p = 0.034;A&D:χ2 = 12.404;p = 0.002;新:χ2 = 10.219;p = 0.006)。所有评分系统的死亡率可预测性都令人满意,具有较高的AUC(“A”:AUC=0.685,敏感性:67.4%,特异性:54.5%,截止点为5/8;阳性预测值(PPV): 40.3%,阴性预测值(NPV):78.6%;A&D”:AUC=0.748,敏感性:69.6%,特异性:61.4% (7/16),PPV:45.1%, NPV:81.6%;“新”:AUC = 0.727;p≤0.001,敏感性:67.4%,特异性:68.3%(截断点为18/48),PPV:49.2%, NPV:82.1%)。此外,“新”评分系统的死亡率预测能力显著高于其他两种评分系统(OR:2.897;CI (1.071 7.8.36);p = 0.036)。结论采用CXR严重程度评分系统评估的新冠肺炎严重程度与临床严重程度及转归显著相关。总体而言,“新”CXR严重程度评分系统在预测Covid-19肺炎死亡率方面相对更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书