Download PDF
Rofo 2025; 197(02): 163-171
DOI: 10.1055/a-2293-8132
Chest

Prävalenz und prognostische Rolle der thorakalen Lymphadenopathie bei Covid-19

Article in several languages: English | deutsch
Autorinnen/Autoren
,
RACOON Study Group
Supported by: Bundesministerium für Bildung und Forschung Funded by „NUM 2.0“ (FKZ: 01KX2121)
› Further Information
Also available at
   Permissions and Reprints

Zusammenfassung

Ziel Die Coronavirus-Pandemie 2019 (COVID-19) hat sich weltweit ausgebreitet und stellt nach wie vor eine ernste Bedrohung für die globale Gesundheit dar. Die prognostische Rolle der thorakalen Lymphadenopathie bei Covid-19 ist unklar. Ziel der vorliegenden systematischen Übersichtsarbeit und Meta-Analyse war es, die prognostische Rolle der thorakalen Lymphadenopathie für die Vorhersage der hospitalen Mortalität bei Patienten mit COVID-19 zu analysieren.

Materialien und Methoden Die Datenbanken MEDLINE, Cochrane und SCOPUS wurden nach thorakaler Lymphadenopathie und der intrahospitalen Mortalität bei COVID-19-Patienten bis Juni 2023 durchsucht. Insgesamt waren 21 Studien für die Analyse geeignet und wurden in die vorliegende Studie aufgenommen. Die Qualität der eingeschlossenen Studien wurde anhand der Newcastle-Ottawa-Skala eingeschätzt. Die Meta-Analyse wurde mit RevMan 5.3 durchgeführt. Die Heterogenität wurde mit dem Inkonsistenzindex (I²) berechnet. DerSimonian und Laird Random-Effects-Modelle mit inversen Varianzgewichtungen wurden ohne weitere Korrekturen durchgeführt.

Ergebnisse Die eingeschlossenen Studien umfassten 4621 Patienten. Die Prävalenz der mediastinalen Lymphadenopathie variierte in den Studien zwischen 1 % und 73,4 %. Die gepoolte Prävalenz betrug 16,7 % mit 95 % CI = (15,6 %; 17,8 %). Die hospitale Mortalität war bei Patienten mit mediastinaler Lymphadenopathie höher (34,7 %) als bei Patienten ohne mediastinale Lymphadenopathie (20,0 %). Die gepoolte Odds Ratio für den Einfluss der mediastinalen Lymphadenopathie auf die Mortalität betrug 2,13 (95 % CI = [1,80–2,52]; p < 0,001).

Schlussfolgerung Thorakale Lymphadenopathie tritt in 16,7 % bei Patienten mit COVID-19 auf. Bei COVID-19 ist das Vorhandensein einer thorakalen Lymphadenopathie mit einem etwa zweifach erhöhten Risiko der Krankenhausmortalität verbunden.

Kernaussagen 

  • Die Prävalenz der COVID-19-Lymphadenopathie beträgt 16,7 %.

  • Patienten mit COVID-19-Lymphadenopathie haben ein erhöhtes Krankenhausmortalitätsrisiko.

  • Bei Lymphadenopathie besteht eine nahezu verdoppelte Mortalitätsrate.

Zitierweise

  • Bucher AM, Sieren M, Meinel F et al. Prevalence and prognostic role of thoracic lymphadenopathy in Covid-19. Rofo 2025; 197: 163 – 171

Keywords

mediastinum - thorax - CT - infection - COVID-19 - meta-analysis


Publication History

Received: 04 January 2024

Accepted: 15 March 2024

Article published online:
22 July 2024

© 2024. Thieme. All rights reserved.

Georg Thieme Verlag KG
Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany

 

  • References

  • 1 Chopra V, Flanders SA, Vaughn V. et al. Variation in COVID-19 characteristics, treatment and outcomes in Michigan: an observational study in 32 hospitals. BMJ Open 2021; 11: e044921
    CrossrefPubMedSearch in Google Scholar
  • 2 Besutti G, Ottone M, Fasano T. et al. The value of computed tomography in assessing the risk of death in COVID-19 patients presenting to the emergency room. Eur Radiol 2021; 31: 9164-9175
    CrossrefPubMedSearch in Google Scholar
  • 3 Wang D, Hu B, Hu C. et al. Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. JAMA 2020; 323: 1061-1069
    CrossrefPubMedSearch in Google Scholar
  • 4 Huang C, Wang Y, Li X. et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. The Lancet 2020; 395: 497-506
    CrossrefPubMedSearch in Google Scholar
  • 5 Fernandes Q, Inchakalody VP, Merhi M. et al. Emerging COVID-19 variants and their impact on SARS-CoV-2 diagnosis, therapeutics and vaccines. Ann Med 2022; 54: 524-540
    CrossrefPubMedSearch in Google Scholar
  • 6 Liu B, Spokes P, He W. et al. High risk groups for severe COVID-19 in a whole of population cohort in Australia. BMC Infect Dis 2021; 21: 685
    CrossrefPubMedSearch in Google Scholar
  • 7 Zheng Z, Peng F, Xu B. et al. Risk factors of critical & mortal COVID-19 cases: A systematic literature review and meta-analysis. J Infect 2020; 81: e16-e25
    CrossrefPubMedSearch in Google Scholar
  • 8 Dessie ZG, Zewotir T. Mortality-related risk factors of COVID-19: a systematic review and meta-analysis of 42 studies and 423,117 patients. BMC Infect Dis 2021; 21: 855
    CrossrefPubMedSearch in Google Scholar
  • 9 Kwee TC, Kwee RM. Chest CT in COVID-19: What the Radiologist Needs to Know. RadioGraphics 2020; 40: 1848-1865
    CrossrefPubMedSearch in Google Scholar
  • 10 Salehi S, Abedi A, Balakrishnan S. et al. Coronavirus Disease 2019 (COVID-19): A Systematic Review of Imaging Findings in 919 Patients. Am J Roentgenol 2020; 215: 87-93
    CrossrefPubMedSearch in Google Scholar
  • 11 Machnicki S, Patel D, Singh A. et al. The Utility of Chest CT imaging in suspected or diagnosed COVID-19 Patients – a review of literature. Chest 2021;
    CrossrefPubMedSearch in Google Scholar
  • 12 Li K, Wu J, Wu F. et al. The Clinical and Chest CT Features Associated With Severe and Critical COVID-19 Pneumonia. Invest Radiol 2020; 55: 327-331
    CrossrefPubMedSearch in Google Scholar
  • 13 Meyer H-J, Wienke A, Surov A. Extrapulmonary CT Findings Predict In-Hospital Mortality in COVID-19. A Systematic Review and Meta-Analysis. Acad Radiol 2022; 29: 17-30
    CrossrefPubMedSearch in Google Scholar
  • 14 Page M, McKenzie J, Bossuyt P. et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021; 372: n71
    CrossrefPubMedSearch in Google Scholar
  • 15 Strang A. Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol 2010; 25: 603-605
    CrossrefPubMedSearch in Google Scholar
  • 16 Leeflang MMG, Deeks JJ, Gatsonis C. et al. Systematic reviews of diagnostic test accuracy. Ann Intern Med 2008; 149: 889-897
    CrossrefPubMedSearch in Google Scholar
  • 17 Zamora J, Abraira V, Muriel A. et al. Meta-DiSc: a software for meta-analysis of test accuracy data. BMC Med Res Methodol 2006; 6: 31
    CrossrefPubMedSearch in Google Scholar
  • 18 DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials 1986; 7: 177-188
    CrossrefPubMedSearch in Google Scholar
  • 19 Egger M, Smith G, Schneider M. et al. Bias in meta-analysis detected by a simple, graphical test. BMJ 1997; 315: 629-634
    CrossrefPubMedSearch in Google Scholar
  • 20 Abbasi B, Akhavan R, Ghamari Khameneh A. et al. Evaluation of the relationship between inpatient COVID-19 mortality and chest CT severity score. Am J Emerg Med 2021; 45: 458-463
    CrossrefPubMedSearch in Google Scholar
  • 21 Abrishami A, Eslami V, Arab-Ahmadi M. et al. Prognostic value of inflammatory biomarkers for predicting the extent of lung involvement and final clinical outcome in patients with COVID-19. J Res Med Sci Off J Isfahan Univ Med Sci 2021; 26: 115
    CrossrefPubMedSearch in Google Scholar
  • 22 Ashtari S, Vahedian-Azimi A, Shojaee S. et al. Computed tomographic features of coronavirus disease-2019 (COVID-19) pneumonia in three groups of Iranian patients: A single center study. Radiologia 2021; 63: 314-323
    CrossrefPubMedSearch in Google Scholar
  • 23 Collado-Chagoya R, Hernández-Chavero H, Ordinola Navarro A. et al. CT findings in survivors and non-survivors of COVID-19 and clinical usefulness of a CT scoring system. Radiologia 2022; 64: 11-16
    CrossrefPubMedSearch in Google Scholar
  • 24 Colombi D, Villani GD, Maffi G. et al. Qualitative and quantitative chest CT parameters as predictors of specific mortality in COVID-19 patients. Emerg Radiol 2020; 27: 701-710
    CrossrefPubMedSearch in Google Scholar
  • 25 Eslami V, Abrishami A, Zarei E. et al. The Association of CT-measured Cardiac Indices with Lung Involvement and Clinical Outcome in Patients with COVID-19. Acad Radiol 2021; 28: 8-17
    CrossrefPubMedSearch in Google Scholar
  • 26 Gunduz Y, Karacan A, Karabay O. et al. Can Chest Computed Tomography Findings of Symptomatic COVID-19 Patients Upon Admission Indicate Disease Prognosis and Clinical Outcome?. Curr Med Imaging 2022; 18: 658-665
    CrossrefPubMedSearch in Google Scholar
  • 27 Kavosi H, Nayebi Rad S, Atef Yekta R. et al. Cardiopulmonary predictors of mortality in patients with COVID-19: What are the findings?. Arch Cardiovasc Dis 2022; 115: 388-396
    CrossrefPubMedSearch in Google Scholar
  • 28 Kaya F, Konya PŞ, Demirel E. et al. Visual and Quantitative Assessment of COVID-19 Pneumonia on Chest CT: The Relationship with Disease Severity and Clinical Findings. Curr Med Imaging 2021; 17: 1142-1150
    CrossrefPubMedSearch in Google Scholar
  • 29 Khosravi B, Aghaghazvini L, Sorouri M. et al. Predictive value of initial CT scan for various adverse outcomes in patients with COVID-19 pneumonia. Heart Lung J Crit Care 2021; 50: 13-20
    CrossrefPubMedSearch in Google Scholar
  • 30 Lee JE, Jeong WG, Nam BD. et al. Impact of Mediastinal Lymphadenopathy on the Severity of COVID-19 Pneumonia: A Nationwide Multicenter Cohort Study. J Korean Med Sci 2022; 37: e78
    CrossrefPubMedSearch in Google Scholar
  • 31 Li H, Luo S, Zhang Y. et al. Longitudinal Chest CT Features in Severe/Critical COVID-19 Cases and the Predictive Value of the Initial CT for Mortality. J Inflamm Res 2021; 14: 1111-1124
    CrossrefPubMedSearch in Google Scholar
  • 32 Meyer H-J, Melekh B, Wienke A. et al. Clinical importance of thoracal lymphadenopathy in COVID-19. J Infect Public Health 2023; 16: 1244-1248
    CrossrefPubMedSearch in Google Scholar
  • 33 Mruk B, Walecki J, Górecki A. et al. Chest computed tomography (CT) as a predictor of clinical course in coronavirus disease. Med Sci Monit 2021; 27: e931285
    CrossrefPubMedSearch in Google Scholar
  • 34 Pilechian S, Pirsalehi A, Arabkoohi A. Mediastinal lymphadenopathy and prognosis of COVID-19 disease. Iran J Microbiol 2021; 13: 495-501
    CrossrefPubMedSearch in Google Scholar
  • 35 Qayyum W, Khan SA, Saeed L. et al. Corona Virus Disease-19 Clinical And Laboratory Characteristics Associated With Disease Severity In Patients Presenting At A Tertiary Care Hospital Of Peshawar. J Ayub Med Coll Abbottabad 2021; 33: 507-512
    PubMedSearch in Google Scholar
  • 36 Sampsonas F, Lagadinou M, Kalogeropoulou C. et al. CTPA imaging findings, beyond pulmonary embolism, in patients with Severe Acute Respiratory Syndrome Corona Virus-2 infection and their relation to clinical outcome – a single center experience. Eur Rev Med Pharmacol Sci 2022; 26: 4520-4527
    CrossrefPubMedSearch in Google Scholar
  • 37 Sardanelli F, Cozzi A, Monfardini L. et al. Association of mediastinal lymphadenopathy with COVID-19 prognosis. Lancet Infect Dis 2020; 20: 1230-1231
    CrossrefPubMedSearch in Google Scholar
  • 38 Satici C, Cengel F, Gurkan O. et al. Mediastinal lymphadenopathy may predict 30-day mortality in patients with COVID-19. Clin Imaging 2021; 75: 119-124
    CrossrefPubMedSearch in Google Scholar
  • 39 Tharwat S, Saleh GA, Saleh M. et al. Chest CT Total Severity Score on Admission to Predict In-Hospital Mortality in COVID-19 Patients with Acute and Chronic Renal Impairment. Diagn Basel 2022; 12
    CrossrefPubMedSearch in Google Scholar
  • 40 Yang W, Cao Q, Qin L. et al. Clinical characteristics and imaging manifestations of the 2019 novel coronavirus disease (COVID-19):A multi-center study in Wenzhou city, Zhejiang, China. J Infect 2020; 80: 388-393
    CrossrefPubMedSearch in Google Scholar
  • 41 Charpentier E, Soulat G, Fayol A. et al. Visual lung damage CT score at hospital admission of COVID-19 patients and 30-day mortality. Eur Radiol 2021; 31: 8354-8363
    CrossrefPubMedSearch in Google Scholar
  • 42 Zakariaee SS, Salmanipour H, Naderi N. et al. Association of chest CT severity score with mortality of COVID-19 patients: a systematic review and meta-analysis. Clin Transl Imaging 2022; 10: 663-676
    CrossrefPubMedSearch in Google Scholar
  • 43 Bao C, Liu X, Zhang H. et al. Coronavirus Disease 2019 (COVID-19) CT Findings: A Systematic Review and Meta-analysis. J Am Coll Radiol 2020; 17: 701-709
    CrossrefPubMedSearch in Google Scholar
  • 44 Zeng Z, Wu C, Lin Z. et al. Development and validation of a simple-to-use nomogram to predict the deterioration and survival of patients with COVID-19. BMC Infect Dis 2021; 21: 356
    CrossrefPubMedSearch in Google Scholar
  • 45 Hassanipour S, Azadbakht O, Dehnavi Z. et al. Meta-analysis: COVID-19 diagnosis in chest CT – master key for radiologists. Egypt J Radiol Nucl Med 2021; 52: 86
    CrossrefPubMedSearch in Google Scholar
  • 46 Cömert RG, Cingöz E, Meşe S. et al. Radiological Imaging of Viral Pneumonia Cases Identified Before the COVİD-19 Pandemic Period and COVİD-19 Pneumonia Cases Comparison of Characteristics. 2022;
    CrossrefPubMedSearch in Google Scholar
  • 47 Erturk SM, Durak G, Ayyildiz H. et al. Covid-19: Correlation of Early Chest Computed Tomography Findings With the Course of Disease. J Comput Assist Tomogr 2020; 44: 633-639
    CrossrefPubMedSearch in Google Scholar
  • 48 Haslbauer JD, Matter MS, Stalder AK. et al. Histomorphological patterns of regional lymph nodes in COVID-19 lungs. Pathol 2021; 42: 89-97
    CrossrefPubMedSearch in Google Scholar