Fervers Philipp, Kottlors Jonathan, Große Hokamp Nils, Bremm Johannes, Maintz David, Tritt Stephanie, Safarov Orkhan, Persigehl Thorsten, Vollmar Nils, Bansmann Paul Martin, Abdullayev Nuran
Department of Radiology, University Hospital of Cologne, Cologne, Germany.
Department of Radiology, Helios Dr. Horst Schmidt Kliniken Wiesbaden, Wiesbaden, Germany.
PLoS One. 2021 Jul 21;16(7):e0255045. doi: 10.1371/journal.pone.0255045. eCollection 2021.
Cardiovascular comorbidity anticipates severe progression of COVID-19 and becomes evident by coronary artery calcification (CAC) on low-dose chest computed tomography (LDCT). The purpose of this study was to predict a patient's obligation of intensive care treatment by evaluating the coronary calcium burden on the initial diagnostic LDCT.
Eighty-nine consecutive patients with parallel LDCT and positive RT-PCR for SARS-CoV-2 were included from three centers. The primary endpoint was admission to ICU, tracheal intubation, or death in the 22-day follow-up period. CAC burden was represented by the Agatston score. Multivariate logistic regression was modeled for prediction of the primary endpoint by the independent variables "Agatston score > 0", as well as the CT lung involvement score, patient sex, age, clinical predictors of severe COVID-19 progression (history of hypertension, diabetes, prior cardiovascular event, active smoking, or hyperlipidemia), and laboratory parameters (creatinine, C-reactive protein, leucocyte, as well as thrombocyte counts, relative lymphocyte count, d-dimer, and lactate dehydrogenase levels).
After excluding multicollinearity, "Agatston score >0" was an independent regressor within multivariate analysis for prediction of the primary endpoint (p<0.01). Further independent regressors were creatinine (p = 0.02) and leucocyte count (p = 0.04). The Agatston score was significantly higher for COVID-19 cases which completed the primary endpoint (64.2 [interquartile range 1.7-409.4] vs. 0 [interquartile range 0-0]).
CAC scoring on LDCT might help to predict future obligation of intensive care treatment at the day of patient admission to the hospital.
心血管合并症预示着COVID-19的严重进展,并通过低剂量胸部计算机断层扫描(LDCT)上的冠状动脉钙化(CAC)得以显现。本研究的目的是通过评估初始诊断性LDCT上的冠状动脉钙化负荷来预测患者接受重症监护治疗的必要性。
从三个中心纳入了89例连续的并行LDCT检查且SARS-CoV-2逆转录聚合酶链反应(RT-PCR)呈阳性的患者。主要终点是在22天随访期内入住重症监护病房(ICU)、气管插管或死亡。CAC负荷用阿加斯顿评分表示。通过“阿加斯顿评分>0”这一自变量以及CT肺部受累评分、患者性别、年龄、COVID-19严重进展的临床预测因素(高血压病史、糖尿病、既往心血管事件、当前吸烟或高脂血症)和实验室参数(肌酐、C反应蛋白、白细胞以及血小板计数、相对淋巴细胞计数、D-二聚体和乳酸脱氢酶水平)建立多因素逻辑回归模型,以预测主要终点。
排除多重共线性后,“阿加斯顿评分>0”是多因素分析中预测主要终点的独立回归变量(p<0.01)。其他独立回归变量为肌酐(p = 0.02)和白细胞计数(p = 0.04)。完成主要终点的COVID-19病例的阿加斯顿评分显著更高(64.2[四分位间距1.7 - 409.4] vs. 0[四分位间距0 - 0])。
LDCT上的CAC评分可能有助于在患者入院当天预测未来接受重症监护治疗的必要性。