Citation: | HUO M, LI L G, SUN Y, et al. Analysis of Coronavirus Disease 2019 Chest High-resolution Computed Tomography Manifestations between Groups with Different Neutrophil- to-Lymphocyte Ratios[J]. CT Theory and Applications, 2023, 32(3): 387-394. DOI: 10.15953/j.ctta.2023.027. (in Chinese). |
[1] |
LIU Y, DU X, CHEN J, et al. Neutrophil-to-lymphocyte ratio as an independent risk factor for mortality in hospitalized patients with COVID-19[J]. Journal of Infection, 2020, 81(1): e6−e12. doi: 10.1016/j.jinf.2020.04.002
|
[2] |
YANG A P, LIU J P, TAO W Q, et al. The diagnostic and predictive role of NLR, d-NLR and PLR in COVID-19 patients[J]. International Immunopharmacology, 2020, 84: 106504. doi: 10.1016/j.intimp.2020.106504
|
[3] |
LI X, LIU C, MAO Z, et al. Predictive values of neutrophil-to-lymphocyte ratio on disease severity and mortality in COVID-19 patients: Systematic review and meta-analysis[J]. Critical Care, 2020, 24(1): 647. doi: 10.1186/s13054-020-03374-8
|
[4] |
费明明, 童飞, 陶小根, 等. 中性粒细胞/淋巴细胞比值对新型冠状病毒肺炎患者疾病分型的诊断价值[J]. 中华危重病急救医学, 2020,32(5): 554−558. doi: 10.3760/cma.j.cn121430-20200413-00506
FEI M M, TONG F, TAO X G, et al. Value of neutrophil-to-lymphocyte ratio in the classification diagnosis of coronavirus disease 2019[J]. Chinese Critical Care Medicine, 2020, 32(5): 554−558. (in Chinese). doi: 10.3760/cma.j.cn121430-20200413-00506
|
[5] |
李文平, 张鹏举, 许金环, 等. 免疫检查点抑制剂相关肺炎的临床及CT表现分析[J]. 中华放射学杂志, 2022,56(12): 1352−1358. doi: 10.3760/cma.j.cn112149-20220217-00126
LI W P, ZHANG P J, XU J H, et al. Clinical and CT imaging features of immune checkpoint inhibitor-associated pneumonia[J]. Chinese Journal of Radiology, 2022, 56(12): 1352−1358. (in Chinese). doi: 10.3760/cma.j.cn112149-20220217-00126
|
[6] |
BUONACERA A, STANCANERLLI B, COLACI M, et al. Neutrophil to lymphocyte ratio: An emerging marker of the relationships between the immune system and diseases[J]. International Journal of Molecular Sciences, 2022, 23(7): 3636.
|
[7] |
FEST J, RUITER T R, GROOT KOERKAMP B, et al. The neutrophil-to-lymphocyte ratio is associated with mortality in the general population: The rotterdam study[J]. European Journal of Epidemiology, 2019, 34(5): 463-470.
|
[8] |
SIMADIBRATA D M, CALVIN J, WIJAYA A D, et al. Neutrophil-to-lymphocyte ratio on admission to predict the severity and mortality of COV9 patients: A meta-analysis[J]. American Journal of Emergency Medicine, 2021, 42: 60−69. doi: 10.1016/j.ajem.2021.01.006
|
[9] |
CAI J, LI H, ZHANG C, et al. The neutrophil-to-lymphocyte ratio determines clinical efficacy of corticosteroid therapy in patients with COVID-19[J]. Cell Metabolism, 2021, 33(2): 258−269. e3. doi: 10.1016/j.cmet.2021.01.002
|
[10] |
BATAH S S, ABRO A T. Pulmonary pathology of ARDS in COVID-19: A pathological review for clinicians[J]. Respiratory Medicine, 2021, 176: 106239. doi: 10.1016/j.rmed.2020.106239
|
[11] |
RUBIN G D, YERSON C J, HARAMATI L B, et al. The role of chest imaging in patient management during the COVID-19 pandemic: A multinational consensus statement from the Fleischner Society[J]. Radiology, 2020, 296(1): 172-180.
|
[12] |
KWEE T C, KWEE R M. Chest CT in COVID-19: What the radiologist needs to know[J]. Radiographics, 2020, 40(7): 1848−1865. doi: 10.1148/rg.2020200159
|
[13] |
SIMPSON S, KAY F U, ABBARA S, et al. Radiological Society of North America expert consensus document on reporting chest CT findings related to COVID-19: Endorsed by the Society of Thoracic Radiology, the American College of Radiology, and RSNA[J]. Radiology Cardiothoracic Imaging, 2020, 2(2): e200152. doi: 10.1148/ryct.2020200152
|
[14] |
CHO J L, VILLACRESES R, NAGPAL P, et al. Quantitative chest CT assessment of small airways disease in post-acute SARS-CoV-2 infection[J]. Radiology, 2022, 304(1): 185−192. doi: 10.1148/radiol.212170
|
[15] |
TOUSSIE D, VOUTSINAS N, FINKELSTEIN M, et al. Clinical and chest radiography features determine patient outcomes in young and middle-aged adults with COVID-19[J]. Radiology, 2020, 297(1): E197−E206. doi: 10.1148/radiol.2020201754
|
[16] |
孙莹, 李玲, 刘晓燕, 等. 早期新型冠状病毒肺炎的胸部薄层平扫CT表现特征[J]. CT理论与应用研究, 2023,32(1): 131−138. DOI: 10.15953/j.ctta.2023.006.
SUN Y, LI L, LIU X Y, et al. Characteristics of chest thin-slice non-contrast CT in early novel coronavirus pneumonia[J]. CT Theory and Applications, 2023, 32(1): 131−138. DOI: 10.15953/j.ctta.2023.006. (in Chinese).
|
[17] |
LEE J H, KOH J, JEON Y K, et al. An integrated radiologic-pathologic understanding of COVID-19 pneumonia[J]. Radiology, 2023, 306(2): e222600. doi: 10.1148/radiol.222600
|
[18] |
KLIGERMAN S J, TNKSJ F R, GALVIN J R. From the radiologic pathology archives: Organization and fibrosis as a response to lung injury in diffuse alveolar damage, organizing pneumonia, and acute fibrinous and organizing pneumonia[J]. Radiographics, 2013, 33(7): 1951−75. doi: 10.1148/rg.337130057
|
[19] |
LARICI A R, CICCHETTI G, MARANO R, et al. Multimodality imaging of COVID-19 pneumonia from diagnosis to follow-up: A comprehensive review[J]. European Journal of Radiology, 2020, 131: 109217. doi: 10.1016/j.ejrad.2020.109217
|
[20] |
GRASSELLI G, TONETTI T, PROTTI A, et al. Pathophysiology of COVID-19-associated acute respiratory distress syndrome: A multicentre prospective observational study[J]. The Lancet Respiratory Medicine, 2020, 8(12): 1201−1208. doi: 10.1016/S2213-2600(20)30370-2
|
[21] |
DURHAN G, DÜZGÜN S A, DEMIRKAZIK F B, et al. Visual and software-based quantitative chest CT assessment of COVID-19: Correlation with clinical findings[J]. Diagnostic Interventional Radiology, 2020, 26(6): 557−564. doi: 10.5152/dir.2020.20407
|
[22] |
BERNHEIM A, MEI X, HUANG M, et al. Chest CT findings in coronavirus disease-19 (COVID-19): Relationship to duration of infection[J]. Radiology, 2020, 295(3): 200463. doi: 10.1148/radiol.2020200463
|
[23] |
INOUE A, TAKAHASHI H, IBE T, et al. Comparison of semiquantitative chest CT scoring systems to estimate severity in coronavirus disease 2019 (COVID-19) pneumonia[J]. European Radiology, 2022, 32(5): 3513−3524. doi: 10.1007/s00330-021-08435-2
|
[24] |
LI K, FANG Y, LI W, et al. CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19)[J]. European Radiology, 2020, 30(8): 4407−4416. doi: 10.1007/s00330-020-06817-6
|
[25] |
杜丹, 谢元亮, 李惠, 等. 人工智能定量测量对新型冠状病毒肺炎患者胸部CT炎性病灶动态变化的评估价值[J]. 中华放射学杂志, 2021,55(3): 250−256.
DU D, XIE Y L, LI H, et al. The value of quantitative artificial intelligence measurement in evaluation of CT dynamic changes for COVID-19[J]. Chinese Journal of Radiology, 2021, 55(3): 250−256. (in Chinese).
|
[26] |
NAIK B R, SAKALECHA A K, SUNIL B N, et al. Computed tomography severity scoring on high-resolution computed tomography thorax and inflammatory markers with COVID-19 related mortality in a designated COVID hospital[J]. Cureus, 2022, 14(4): e24190.
|
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