Department of Radiology, School of Medicine, Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Imam Khomeini Hospital, Tehran University of Medical Sciences, Qarib St, Keshavarz Blvd, Tehran, 14194, Iran.
Advance Thoracic Research Center, Tehran University of Medical Sciences, Tehran, Iran.
Eur Radiol. 2021 Jul;31(7):5178-5188. doi: 10.1007/s00330-020-07623-w. Epub 2021 Jan 15.
Proposing a scoring tool to predict COVID-19 patients' outcomes based on initially assessed clinical and CT features.
All patients, who were referred to a tertiary-university hospital respiratory triage (March 27-April 26, 2020), were highly clinically suggestive for COVID-19 and had undergone a chest CT scan were included. Those with positive rRT-PCR or highly clinically suspicious patients with typical chest CT scan pulmonary manifestations were considered confirmed COVID-19 for additional analyses. Patients, based on outcome, were categorized into outpatient, ordinary-ward admitted, intensive care unit (ICU) admitted, and deceased; their demographic, clinical, and chest CT scan parameters were compared. The pulmonary chest CT scan features were scaled with a novel semi-quantitative scoring system to assess pulmonary involvement (PI).
Chest CT scans of 739 patients (mean age = 49.2 ± 17.2 years old, 56.7% male) were reviewed; 491 (66.4%), 176 (23.8%), and 72 (9.7%) cases were managed outpatient, in an ordinary ward, and ICU, respectively. A total of 439 (59.6%) patients were confirmed COVID-19 cases; their most prevalent chest CT scan features were ground-glass opacity (GGO) (93.3%), pleural-based peripheral distribution (60.3%), and multi-lobar (79.7%), bilateral (76.6%), and lower lobes (RLL and/or LLL) (89.1%) involvement. Patients with lower SpO, advanced age, RR, total PI score or PI density score, and diffuse distribution or involvement of multi-lobar, bilateral, or lower lobes were more likely to be ICU admitted/expired. After adjusting for confounders, predictive models found cutoffs of age ≥ 53, SpO ≤ 91, and PI score ≥ 8 (15) for ICU admission (death). A combination of all three factors showed 89.1% and 95% specificity and 81.9% and 91.4% accuracy for ICU admission and death outcomes, respectively. Solely evaluated high PI score had high sensitivity, specificity, and NPV in predicting the outcome as well.
We strongly recommend patients with age ≥ 53, SpO ≤ 91, and PI score ≥ 8 or even only high PI score to be considered as high-risk patients for further managements and care plans.
• Chest CT scan is a valuable tool in prioritizing the patients in hospital triage. • A more accurate and novel 35-scale semi-quantitative scoring system was designed to predict the COVID-19 patients' outcome. • Patients with age ≥ 53, SpO ≤ 91, and PI score ≥ 8 or even only high PI score should be considered high-risk patients.
提出一种基于初始临床和 CT 特征预测 COVID-19 患者结局的评分工具。
纳入 2020 年 3 月 27 日至 4 月 26 日期间因高度疑似 COVID-19 而被转诊至三级大学医院呼吸分诊的所有患者，且所有患者均接受了胸部 CT 扫描。对于 rRT-PCR 检测阳性或具有典型胸部 CT 扫描肺部表现且高度疑似 COVID-19 的患者，将进行进一步分析。根据结局，将患者分为门诊、普通病房住院、重症监护病房（ICU）住院和死亡；比较其人口统计学、临床和胸部 CT 扫描参数。采用新的半定量评分系统对肺部 CT 扫描特征进行评分，以评估肺部受累（PI）。
共回顾了 739 例患者的胸部 CT 扫描结果（平均年龄 49.2±17.2 岁，56.7%为男性）；491 例（66.4%）、176 例（23.8%）和 72 例（9.7%）患者分别在门诊、普通病房和 ICU 接受治疗。共有 439 例（59.6%）患者被确诊为 COVID-19 病例；他们最常见的胸部 CT 扫描特征是磨玻璃影（GGO）（93.3%）、胸膜基周边分布（60.3%）和多叶分布（79.7%）、双侧（76.6%）和下叶（RLL 和/或 LLL）（89.1%）受累。SpO2 较低、年龄较大、RR、总 PI 评分或 PI 密度评分较高，以及弥漫性分布或多叶、双侧或下叶受累程度较高的患者更有可能被 ICU 收治/死亡。在调整混杂因素后，预测模型发现年龄≥53、SpO2≤91 和 PI 评分≥8（15）可用于预测 ICU 收治（死亡）。所有三个因素的组合对 ICU 收治和死亡结局的特异性和准确性分别为 89.1%和 95%、81.9%和 91.4%。单独评估高 PI 评分也能很好地预测结局，具有较高的敏感性、特异性和阴性预测值。
我们强烈建议将年龄≥53、SpO2≤91 和 PI 评分≥8 或仅高 PI 评分的患者视为高危患者，以制定进一步的管理和护理计划。
胸部 CT 扫描是医院分诊中优先考虑患者的有价值工具。
设计了一种更准确和新颖的 35 分半定量评分系统来预测 COVID-19 患者的结局。
年龄≥53、SpO2≤91 和 PI 评分≥8 或甚至仅高 PI 评分的患者应被视为高危患者。
