MEDIASTINAL LYMPHADENOPATHY AS A PREDICTOR OF WORSE OUTCOME IN SEVERE COVID-19 CASES
DOI:
https://doi.org/10.55519/JAMC-02-9469Abstract
Background: This cross-sectional study is aimed at evaluating the association of mediastinal lymphadenopathy with COVID-19 prognosis in severe cases. Place and Duration of Study: Department of Medicine, Pak Emirates Military Hospital, Pakistan, from June to July 2020. Methods: One hundred and fifty (150) laboratory-confirmed SARS CoV-2 infected, severe cases in Intensive Care Unit/ High Dependency Unit were included. These cases were divided into two categories, i.e., with and without mediastinal lymphadenopathy on High Resolution Computed Tomography chest. The two categories were compared on the basis of data obtained including age, gender, comorbid, White Blood Cell count, lymphocyte count, median days of hospitalization, need for invasive ventilation, Intensive Care Unit admission, clinical outcome and High-Resolution Computed Tomography chest findings. The data was compiled on a questionnaire and analysed on SPSS 24. Result: Total 155 severe COVID-19 patients were reviewed, out of which 36 (23.2%) had mediastinal lymphadenopathy (category 1) and 119 (76.8%) had no mediastinal lymphadenopathy (category 2). Laboratory findings including median of white blood cells and lymphocyte percentage had no significant change in both categories. Intensive care unit admissions were 12 (33.3%) and 56 (47.1%) in category 1 and 2 respectively. Median days of hospitalization (8 days) and mortality rate (16%) were almost the same in both categories. Conclusion: Our study concludes that presence of mediastinal lymphadenopathy in severe COVID-19 cases is not associated with worse outcome. However, overall prevalence of mediastinal lymphadenopathy in severe cases is high (23.2%).References
Adegunsoye A, Oldham JM, Bonham C, Hrusch C, Nolan P, Klejch W, et al. Prognosticating Outcomes in Interstitial Lung Disease by Mediastinal Lymph Node Assessment. An Observational Cohort Study with Independent Validation. Am J Respir Crit Care Med 2019;199(6):747–59.
Kirchner J, Kirchner EM, Goltz JP, Obermann A, Kickuth R. Enlarged hilar and mediastinal lymph nodes in chronic obstructive pulmonary disease. J Med Imaging Radiat Oncol 2010;54(4):333–8.
Franquet T. Imaging of pulmonary viral pneumonia. Radiology 2011;260(1):18–39.
Kiyono K, Sone S, Sakai F, Imai Y, Watanabe T, Izuno I, et al. The number and size of normal mediastinal lymph nodes: a postmortem study. AJR Am J Roentgenol 1988;150(4):771–6.
Libshitz HI, Mckenna RJ. Mediastinal lymph node size in lung cancer. AJR Am J Roentgenol 1984;143(4):715–8.
Kramer H, Groen HJ. Current Concepts in the Mediastinal Lymph Node Staging of nonsmall Cell Lung Cancer. Ann Surg 2003;238(2):180–8.
Walker CM, Chung JH, Abbott GF, Little BP, El-Sherief AH, Shepard JA, et al. Review Mediastinal lymph node staging: from noninvasive to surgical. J Roentgenol 2012;199(1):W54–64.
Koo HJ, Kim MY, Shin SY, Shin S, Kim SS, Lee SW, et al. Evaluation of Mediastinal Lymph Nodes in Sarcoidosis, Sarcoid Reaction, and Malignant Lymph Nodes Using CT and FDG-PET/CT. Medicine (Baltimore) 2015;94(27):e1095.
Rusch VW, Crowley J, Giroux DJ, Goldstraw P, Im JG, Tsuboi M, et al. The IASLC Lung Cancer Staging Project: proposals for the revision of the N descriptors in the forthcoming seventh edition of the TNM classification for lung cancer. J Thorac Oncol 2007;2(7):603–12.
Hung JJ, Jeng WJ, Hsu WH, Lin SF, Hsieh CC, Huang BS, et al. Prognostic factors in pathological stage IB non small cell lung cancer greater than 3 cm. Eur Respir J 2010;36(6):1355–61.
Udoji TN, Phillips GS, Berkowitz EA, Berkowitz D, Ross C, Bechara RI. Mediastinal and hilar lymph node measurements. comparison of multidetector-row computed tomography and endobronchial ultrasound. Ann Am Thorac Soc 2015;12(6):914–20.
Dhooria S, Agarwal R, Aggarwal AN, Gupta N, Gupta D, Behera D. Agreement of Mediastinal Lymph Node Size Between Computed Tomography and Endobronchial Ultrasonography: A Study of 617 Patients. Ann Thorac Surg 2015;99(6):1894–8.
Rubin GD, Ryerson CJ, Haramati LB, Sverzellati N, Kanne JP, Raoof S, et al. The Role of Chest Imaging in Patient Management during the COVID-19 Pandemic: A Multinational Consensus Statement from the Fleischner Society. Radiology 2020;296(1):172–80.
Fang Y, Zhang H, Xie J, Lin M, Ying L, Pang P, et al. Sensitivity of Chest CT for COVID-19: Comparison to RT-PCR. Radiology 2020;296(2):E115–7.
Rodrigues JCL, Hare SS, Edey A, Devaraj A, Jacob J, Johnstone A, et al. An update on COVID-19 for the radiologist - A British society of Thoracic Imaging statement. Clin Radiol 2020;75(5):323–5.
Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, et al. China Medical Treatment Expert Group for Covid-19. Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med 2020;382(18):1708–20.
Simpson S, Kay FU, Abbara S, Bhalla S, Chung JH, Chung M, 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. Radiol Cardiothorac Imaging 2020;2(2):e200152.
de Jaegere TMH, Krdzalic J, Fasen BACM, Kwee RM. Radiological Society of North America Chest CT Classification System for Reporting COVID-19 Pneumonia: Interobserver Variability and Correlation with RT-PCR. Radiol Cardiothorac Imaging 2020;2(3):e200213.
Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, et al. Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. JAMA 2020;323(11):1061–9.
Pan F, Ye T, Sun P, Gui S, Liang B, Li L, et al. Time Course of Lung Changes at Chest CT during Recovery from Coronavirus Disease 2019 (COVID-19). Radiology 2020;295(3):715–21. Ref no 20&22 are same
Shi H, Han X, Jiang N, Cao Y, Alwalid O, Gu J et al. Radiological findings from 81 patients with COVID-19 pneumonia in Wuhan, China: a descriptive study. Lancet Infect Dis 2020;20(4):425–34.
Pan F, Ye T, Sun P, Gui S, Liang B, Li L, et al. Time Course of Lung Changes at Chest CT during Recovery from Coronavirus Disease 2019 (COVID-19). Radiology 2020;295(3):715–21. Ref no 20&22 are same
Grifoni E, Valoriani A, Cei F, Vannucchi V, Moroni F, Pelagatti L. The CALL Score for Predicting Outcomes in Patients With COVID-19. Clin Infect Dis 2021;72(1):182–3.
Ji D, Zhang D, Xu J, Chen Z, Yang T, Zhao P et al. Prediction for Progression Risk in Patients With COVID-19 Pneumonia: The CALL Score. Clin Infect Dis 2020;71(6):1393–9.
WHO. Clinical management of COVID-19: interim guidance, 27 May 2020. World Health Organization; 2020.
Aly MH, Rahman SS, Ahmed WA, Alghamedi MH, Al Shehri AA, Alkalkami, et al. Indicators of Critical Illness and Predictors of Mortality in COVID-19 Patients. Infect Drug Resist 2020;13:1995–2000.
Shang Y, Liu T, Wei Y, Li J, Shao L, Liu M, et al. Scoring systems for predicting mortality for severe patients with COVID-19. EClinicalMedicine 2020;24:100426.
Valette X, du Cheyron D, Goursaud S. Mediastinal lymphadenopathy in patients with severe COVID-19. Lancet Infect Dis 2020;20(11):1230.
Sardanelli F, Cozzi A, Monfardini L, Bnà C, Foà RA, Spinazzola A, et al. Association of mediastinal lymphadenopathy with COVID-19 prognosis. Lancet Infect Dis 2020;20(11):1230–1.
Li K, Wu J, Wu F, Guo D, Chen L, Fang Z, et al. The Clinical and Chest CT Features Associated with Severe and Critical COVID-19 Pneumonia. Invest Radiol 2020;55(6):327–31.
Satici C, Cengel F, Gurkan O, Demirkol MA, Altunok ES, Esatoglu SN. Mediastinal lymphadenopathy may predict 30-day mortality in patients with COVID-19. Clin Imaging 2021;75:119–24
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