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SARS-CoV-2 感染病例的流行病学、临床特征与异常影像表现。

Epidemiological, clinical characteristics of cases of SARS-CoV-2 infection with abnormal imaging findings.

机构信息

State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, No. 79 QingChun Road, Hangzhou, Zhejiang 310003, China.

State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, No. 79 QingChun Road, Hangzhou, Zhejiang 310003, China.

出版信息

Int J Infect Dis. 2020 May;94:81-87. doi: 10.1016/j.ijid.2020.03.040. Epub 2020 Mar 20.

DOI:10.1016/j.ijid.2020.03.040
PMID:32205284
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7270493/
Abstract

PURPOSE

To investigate the epidemiological and clinical characteristics of COVID-19 patients with abnormal imaging findings.

METHODS

Patients confirmed with SARS-CoV-2 infection in Zhejiang province from January 17 to February 8 who had undergone CT or X-ray were enrolled. Epidemiological and clinical data were analyzed among those with abnormal or normal imaging findings.

RESULTS

Excluding 72 patients with normal images, 230 of 573 patients showed abnormalities affecting more than two lung lobes. The median radiographic score was 2.0, and there was a negative correlation between that score and the oxygenation index (ρ = -0.657, P < 0.001). Patients with abnormal images were older (46.65 ± 13.82), with a higher rate of coexisting condition (28.8%), a lower rate of exposure history, and longer time between onset and confirmation (5 days) than non-pneumonia patients (all P < 0.05). A higher rate of fever, cough, expectoration and headache, a lower level of lymphocytes, albumin, and serum sodium levels and a higher total bilirubin, creatine kinase, lactate dehydrogenase, and C-reactive protein levels and a lower oxygenation index were observed in pneumonia patients (all P < 0.05). Muscle ache, shortness of breath, nausea and vomiting, lower lymphocytes levels, and higher serum creatinine and radiographic score at admission were predictive factors for the severe/critical subtype.

CONCLUSION

Patients with abnormal images have more obvious clinical manifestations and laboratory changes. Combing clinical features and radiographic scores can effectively predict severe/critical types.

摘要

目的

探讨 COVID-19 患者影像学异常的流行病学和临床特征。

方法

纳入 2020 年 1 月 17 日至 2 月 8 日在浙江省经 SARS-CoV-2 感染确诊且行 CT 或 X 线检查的患者。分析影像学异常和正常患者的流行病学和临床资料。

结果

排除 72 例影像学正常患者后,573 例患者中 230 例存在影响两个以上肺叶的异常。影像学评分中位数为 2.0,与氧合指数呈负相关(ρ=-0.657,P<0.001)。异常图像患者年龄较大(46.65±13.82 岁),共存疾病发生率较高(28.8%),暴露史发生率较低,发病至确诊时间较长(5 天),而非肺炎患者(均 P<0.05)。肺炎患者发热、咳嗽、咳痰、头痛发生率较高,淋巴细胞、白蛋白、血清钠水平较低,总胆红素、肌酸激酶、乳酸脱氢酶、C 反应蛋白水平较高,氧合指数较低(均 P<0.05)。入院时肌肉疼痛、呼吸急促、恶心呕吐、淋巴细胞水平较低、血清肌酐和影像学评分较高是重症/危重症的预测因素。

结论

影像学异常患者的临床表现和实验室变化更为明显。结合临床特征和影像学评分可有效预测重症/危重症。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce05/7270493/5b71495f4329/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce05/7270493/5b71495f4329/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce05/7270493/5b71495f4329/gr1_lrg.jpg

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4
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