Quantitative Burden of COVID-19 Pneumonia on Chest CT Predicts Adverse Outcomes: A Post-Hoc Analysis of a Prospective International Registry.
Quantitative Burden of COVID-19 Pneumonia on Chest CT Predicts Adverse Outcomes: A Post-Hoc Analysis of a Prospective International Registry.
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DOI：
10.1148/ryct.2020200389
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发表时间：
2020-10
期刊：
影响因子：
--
通讯作者：
Dey D
中科院分区：
文献类型：
--
作者：
Grodecki K;Lin A;Cadet S;McElhinney PA;Razipour A;Chan C;Pressman B;Julien P;Maurovich-Horvat P;Gaibazzi N;Thakur U;Mancini E;Agalbato C;Menè R;Parati G;Cernigliaro F;Nerlekar N;Torlasco C;Pontone G;Slomka PJ;Dey D
检查CT衍生的COVID-19肺炎定量负担和衰减的独立和增量价值，以预测临床恶化或死亡。这是对2020年1月10日至5月6日期间在四家中心住院的实验室确诊COVID-19和胸部CT成像的连续患者的前瞻性国际登记研究的回顾性分析。使用半自动研究软件从CT中量化磨玻璃样阴影（GGO）和实变的总负荷（以百分比表示）和平均衰减。主要结局为临床恶化（入住重症监护室、有创机械通气或血管加压药治疗）或院内死亡。进行逻辑回归以评估临床和CT参数对主要结局的预测价值。最终人群包括120例患者（平均年龄64 ± 16岁，78例男性），其中39例（32.5%）发生临床恶化或死亡。在临床和CT参数的多变量回归中，（比值比[OR]，3.4; 95%置信区间[CI]：1.7，6.9/加倍; P = 0.001）和GGO衰减增加（OR，3.2; 95% CI：1.3，8.3/标准差，P = 0.02）是恶化或死亡的独立预测因子; C反应蛋白也是（OR，2.1; 95% CI：1.3，3.4/加倍; P = 0.004）、心力衰竭史（OR 1.3; 95% CI：1.1，1.6，P = 0.01）和慢性肺部疾病（OR，1.3; 95% CI：1.0，1.6; P = 0.02）。定量CT测量增加了增量预测值，超出了仅具有临床参数的模型（曲线下面积，0.93 vs 0.82，P = .006）。根据Youden指数确定的COVID-19肺炎负担的最佳预后临界值为实变大于或等于1.8%，GGO大于或等于13.5%。胸部CT上实变或GGO的定量负荷可独立预测COVID-19肺炎患者的临床恶化或死亡。CT衍生的指标具有超过临床参数的增量预后价值，可能有助于对COVID-19患者进行风险分层。
To examine the independent and incremental value of CT-derived quantitative burden and attenuation of COVID-19 pneumonia for the prediction of clinical deterioration or death. This was a retrospective analysis of a prospective international registry of consecutive patients with laboratory-confirmed COVID-19 and chest CT imaging, admitted to four centers between January 10 and May 6, 2020. Total burden (expressed as a percentage) and mean attenuation of ground glass opacities (GGO) and consolidation were quantified from CT using semi-automated research software. The primary outcome was clinical deterioration (intensive care unit admission, invasive mechanical ventilation, or vasopressor therapy) or in-hospital death. Logistic regression was performed to assess the predictive value of clinical and CT parameters for the primary outcome. The final population comprised 120 patients (mean age 64 ± 16 years, 78 men), of whom 39 (32.5%) experienced clinical deterioration or death. In multivariable regression of clinical and CT parameters, consolidation burden (odds ratio [OR], 3.4; 95% confidence interval [CI]: 1.7, 6.9 per doubling; P = .001) and increasing GGO attenuation (OR, 3.2; 95% CI: 1.3, 8.3 per standard deviation, P = .02) were independent predictors of deterioration or death; as was C-reactive protein (OR, 2.1; 95% CI: 1.3, 3.4 per doubling; P = .004), history of heart failure (OR 1.3; 95% CI: 1.1, 1.6, P = .01), and chronic lung disease (OR, 1.3; 95% CI: 1.0, 1.6; P = .02). Quantitative CT measures added incremental predictive value beyond a model with only clinical parameters (area under the curve, 0.93 vs 0.82, P = .006). The optimal prognostic cutoffs for burden of COVID-19 pneumonia as determined by Youden’s index were consolidation of greater than or equal to 1.8% and GGO of greater than or equal to 13.5%. Quantitative burden of consolidation or GGO on chest CT independently predict clinical deterioration or death in patients with COVID-19 pneumonia. CT-derived measures have incremental prognostic value over and above clinical parameters, and may be useful for risk stratifying patients with COVID-19.
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预测病毒性肺炎患者死亡风险的临床特征：MuLBSTA 评分
影响因子：
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作者：
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