COVID-19 Chest CT Quantification: Triage and Prognostic Value in Different Ages.

IF 1.2 Q2 MEDICINE, GENERAL & INTERNAL
Alireza Almasi Nokiani, Razieh Shahnazari, Mohammad Amin Abbasi, Farshad Divsalar, Marzieh Bayazidi, Azadeh Sadatnaseri
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引用次数: 0

Abstract

Objective: We evaluated the triage and prognostic performance of seven proposed computed tomography (CT)-severity score (CTSS) systems in two different age groups.Design: Retrospective study.Setting: COVID-19 pandemic.Participants: Admitted COVID-19, PCR-positive patients were included, excluding patients with heart failure and significant pre-existing pulmonary disease.Methods: Patients were divided into two age groups: ≥65 years and ≤64 years. Clinical data indicating disease severity at presentation and at peak disease severity were recorded. Initial CT images were scored by two radiologists according to seven CTSSs (CTSS1-CTSS7). Receiver operating characteristic (ROC) analysis for the performance of each CTSS in diagnosing severe/critical disease on admission (triage performance) and at peak disease severity (prognostic performance) was done for the whole cohort and each age group separately.Results: Included were 96 patients. Intraclass correlation coefficient (ICC) between the two radiologists scoring the CT scan images were good for all the CTSSs (ICC=0.764-0.837). In the whole cohort, all CTSSs showed an unsatisfactory area under the curve (AUC) in the ROC curve for triage, excluding CTSS2 (AUC=0.700), and all CTSSs showed acceptable AUCs for prognostic usage (0.759-0.781). In the older group (≥65 years; n=55), all CTSSs excluding CTSS6 showed excellent AUCs for triage (0.804-0.830), and CTSS6 was acceptable (AUC=0.796); all CTSSs showed excellent or outstanding AUCs for prognostication (0.859-0.919). In the younger group (≤64 years; n=41), all CTSSs showed unsatisfactory AUCs for triage (AUC=0.487-0.565) and prognostic usage (AUC=0.668-0.694), excluding CTSS6, showing marginally acceptable AUC for prognostic performance (0.700).Conclusion: Those CTSSs requiring more numerous segmentations, namely CTSS2, CTSS7, and CTSS5 showed the best ICCs; therefore, they are the best when comparison between two separate scores is needed. Irrespective of patients' age, CTSSs show minimal value in triage and acceptable prognostic value in COVID-19 patients. CTSS performance is highly variable in different age groups. It is excellent in those aged ≥65 years, but has little if any value in younger patients. Multicenter studies with larger sample size to evaluate results of this study should be conducted.

COVID-19胸部CT量化:不同年龄的分诊及预后价值。
目的:我们评估七种建议的计算机断层扫描(CT)-严重程度评分(CTSS)系统在两个不同年龄组的分类和预后表现。设计:回顾性研究。背景:COVID-19大流行。参与者:纳入入院的COVID-19, pcr阳性患者,排除心力衰竭和明显的既往肺部疾病患者。方法:将患者分为≥65岁和≤64岁两组。临床数据表明疾病严重程度在首发和疾病严重程度的高峰记录。初始CT图像由两名放射科医生根据7个ctss评分(CTSS1-CTSS7)。在整个队列和每个年龄组中分别对每个CTSS在入院时诊断严重/危重疾病(分诊表现)和疾病严重程度高峰时(预后表现)的表现进行受试者工作特征(ROC)分析。结果:纳入96例患者。两名放射科医师对CT扫描图像评分的类内相关系数(ICC)均较好(ICC=0.764-0.837)。在整个队列中,除CTSS2 (AUC=0.700)外,所有CTSSs在ROC曲线上的曲线下面积(AUC)均不理想,所有CTSSs的预后使用AUC均可接受(0.759-0.781)。老年组(≥65岁;n=55),除CTSS6外,所有CTSS6的AUC都很好(0.804-0.830),CTSS6是可以接受的(AUC=0.796);所有CTSSs的auc均为优或突出(0.859 ~ 0.919)。青壮年组(≤64岁;n=41),除CTSS6外,所有CTSSs的分类AUC (AUC=0.487-0.565)和预后使用AUC (AUC=0.668-0.694)均不理想,预后表现AUC略可接受(0.700)。结论:CTSS2、CTSS7、CTSS5分割次数较多的CTSS2、CTSS7、CTSS5的ICCs最好;因此,当需要对两个单独的分数进行比较时,它们是最好的。无论患者年龄如何,ctss在COVID-19患者的分诊价值最小,预后价值可接受。不同年龄组的CTSS表现差异很大。它在年龄≥65岁的患者中效果很好,但在年轻患者中几乎没有任何价值。需要更大样本量的多中心研究来评价本研究的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Clinical Medicine & Research
Clinical Medicine & Research MEDICINE, GENERAL & INTERNAL-
CiteScore
1.80
自引率
7.10%
发文量
25
期刊介绍: Clinical Medicine & Research is a peer reviewed publication of original scientific medical research that is relevant to a broad audience of medical researchers and healthcare professionals. Articles are published quarterly in the following topics: -Medicine -Clinical Research -Evidence-based Medicine -Preventive Medicine -Translational Medicine -Rural Health -Case Reports -Epidemiology -Basic science -History of Medicine -The Art of Medicine -Non-Clinical Aspects of Medicine & Science
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