KRİTİK COVİD 19 HASTALARINDA TORAKS TOMOGRAFİSİNİN PROGNOZDAKİ ÖNEMİ
Yıl 2021,
, 317 - 322, 24.05.2021
Veysel Garani Soylu
,
Öztürk Taşkın
,
Ufuk Demir
,
Yunus Yaşar
Öz
Amaç: Toraks bilgisayarlı tomografi (BT) görüntüleri sıklıkla COVID-19 ve bulaşıcı hastalıkların teşhisini desteklemek için kullanıldı. Bu çalışma, yoğun bakım ünitesinde (YBÜ) izlenen COVID-19 hastalarının prognozunu tahmin etmede spesifik göğüs BT sonuçlarının önemini sorgulamayı amaçlamaktadır.
Gereç ve Yöntem: Bu çalışmaya RT-PCR testleri COVID-19 için pozitif olan 20 kritik hasta dahil edildi. YBÜ'ye kabul edilmeden önce çekilen toraks BT taramalarında kötü prognoz sonuçları; mortalite, invazif ve non-invaziv mekanik ventilatör gereksinimi, APACHE II skorları ve YBÜ yatış günleri ile karşılaştırıldı.
Bulgular : Göğüs BT görüntülerinde kaldırım taşı paterni olan COVID-19 hastalığı nedeniyle YBÜ'de izlenen kritik hastalarda, YBÜ takibinde;invazif mekanik ventilasyon desteği gereksinimi istatistiksel olarak anlamlı bulundu (P = 0.04). Plevral ve perikardiyal efüzyonu olan tüm hastaların invazif mekanik ventilasyon desteğine ihtiyacı oldu. Yoğun bakım ünitesinde kritik COVID-19 hastalarında gözlenen göğüs BT sonuçlarından olan, konsolidasyon / buzlu cam opasite paterninin> 1 olan hastalar daha yüksek (yaklaşık beş kat) ölüm oranına sahipti. Yoğun bakım yatış süresi daha fazla olan hastalarda kaldırım taşı manzarası görünümü mevcuttu.
Sonuç: COVID-19 hastalığında göğüs BT taramalarından elde edilen bazı sonuçların yoğun bakım döneminde hastanın prognozunu öngörebileceğini düşünüyoruz.
Kaynakça
- 1. Huang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395(10223):497-506. doi:10.1016/S0140-6736(20)30183-5
- 2. Zhu N, Zhang D, Wang W, et al. A Novel Coronavirus from Patients with Pneumonia in China, 2019. N Engl J Med. 2020;382(8):727-733. doi:10.1056/NEJMoa2001017
- 3. https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200211-sitrep-22-ncov.pdf?sfvrsn=fb6d49b1
- 4. Shang Y, Xu C, Jiang F, et al. Clinical characteristics and changes of chest CT features in 307 patients with common COVID-19 pneumonia infected SARS-CoV-2: A multicenter study in Jiangsu, China. Int J Infect Dis. 2020;96:157-162. doi:10.1016/j.ijid.2020.05.006
- 5. Lee N, Hui D, Wu A, et al. A major outbreak of severe acute respiratory syndrome in Hong Kong. N Engl J Med. 2003;348(20):1986-1994. doi:10.1056/NEJMoa030685
- 6. 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(6):327-331. doi:10.1097/RLI.0000000000000672
- 7. Tan W. J, Zhao X., Ma X. et al. A novel coronavirus genome identified in a cluster of pneumonia cases—Wuhan, China 2019− 2020. China CDC Weekly 2020; 2 (4): 61-2. doi: 10.46234/ccdcw2020.017
- 8. Chan JF, Yip CC, To KK, et al. Improved Molecular Diagnosis of COVID-19 by the Novel, Highly Sensitive and Specific COVID-19-RdRp/Hel Real-Time Reverse Transcription-PCR Assay Validated In Vitro and with Clinical Specimens. J Clin Microbiol. 2020;58(5):e00310-20. doi:10.1128/JCM.00310-20
- 9. Wang Y, Hou H, Wang W, Wang W. Combination of CT and RT-PCR in the screening or diagnosis of COVID-19. J Glob Health. 2020;10(1):010347. doi:10.7189/jogh.10.010347
- 10. Chung M, Bernheim A, Mei X, et al. CT Imaging Features of 2019 Novel Coronavirus (2019-nCoV). Radiology. 2020;295(1):202-207. doi:10.1148/radiol.2020200230
- 11. Li, X., Zeng, X., Liu, B., et al. COVID-19 infection presenting with CT halo sign. Radiology: Cardiothoracic Imaging, 2(1), doi: 10.1148/ryct.2020200026
- 12. Ai T, Yang Z, Hou H, et al. Correlation of Chest CT and RT-PCR Testing for Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases. Radiology. 2020;296(2):E32-E40. doi:10.1148/radiol.2020200642
- 13. Yang R, Li X, Liu H et all (2020) Chest CT Severity Score: An Imaging Tool for Assessing Severe COVID-19 Radiology: Cardiothoracic Imaging, 2(2) doi:10.1148/ryct.2020200047
- 14. Lyu P, Liu X, Zhang R,et al. The Performance of Chest CT in Evaluating the Clinical Severity of COVID-19 Pneumonia: Identifying Critical Cases Based on CT Characteristics. Invest Radiol. 2020;55(7):412-421. doi:10.1097/RLI.0000000000000689
- 15. Xiong Y, Sun D, Liu Y, et al. Clinical and High-Resolution CT Features of the COVID-19 Infection: Comparison of the Initial and Follow-up Changes. Invest Radiol. 2020;55(6):332-339. doi:10.1097/RLI.0000000000000674
- 16. Li K, Fang Y, Li W, et al. CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19). Eur Radiol. 2020;30(8):4407-4416. doi:10.1007/s00330-020-06817-6
- 17. Li LQ, Huang T, Wang YQ, et al. COVID-19 patients' clinical characteristics, discharge rate, and fatality rate of meta-analysis. J Med Virol. 2020;92(6):577-583. doi:10.1002/jmv.25757
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- 19. Bhatraju PK, Ghassemieh BJ, Nichols M, et al. Covid-19 in Critically Ill Patients in the Seattle Region - Case Series. N Engl J Med. 2020;382(21):2012-2022. doi:10.1056/NEJMoa2004500
- 20. Yang X, Yu Y, Xu J, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir Med. 2020;8(5):475-481. doi:10.1016/S2213-2600(20)30079-5
- 21. Li Y, Xia L. Coronavirus Disease 2019 (COVID-19): Role of Chest CT in Diagnosis and Management. AJR Am J Roentgenol. 2020;214(6):1280-1286. doi:10.2214/AJR.20.22954
- 22. Frater JL, Zini G, d'Onofrio G, et al. COVID-19 and the clinical hematology laboratory. Int J Lab Hematol. 2020;42 Suppl 1:11-18. doi:10.1111/ijlh.13229
- 23. Pan F, Yang L, Li Y, et al. Factors associated with death outcome in patients with severe coronavirus disease-19 (COVID-19): a case-control study. Int J Med Sci. 2020;17(9):1281-1292. doi:10.7150/ijms.46614
- 24. Liu F, Zhang Q, Huang C, et al. CT quantification of pneumonia lesions in early days predicts progression to severe illness in a cohort of COVID-19 patients. Theranostics. 2020;10(12):5613-5622. doi:10.7150/thno.45985
- 25. Salehi S, Abedi A, Balakrishnan S, Gholamrezanezhad A. Coronavirus Disease 2019 (COVID-19): A Systematic Review of Imaging Findings in 919 Patients. AJR Am J Roentgenol. 2020;215(1):87-93. doi:10.2214/AJR.20.23034
- 26. Knaus WA, Draper EA, Wagner DP, et al. APACHE II: a severity of disease classification system. Crit Care Med. 1985;13(10):818-829. doi: 10.1097/00003465-198603000-00013
THE IMPORTANCE OF THORACIC TOMOGRAPHY IN PROGNOSIS IN CRITICAL COVID 19 PATIENTS
Yıl 2021,
, 317 - 322, 24.05.2021
Veysel Garani Soylu
,
Öztürk Taşkın
,
Ufuk Demir
,
Yunus Yaşar
Öz
Aim: Computed tomography (CT) images of the chest were often used to support the diagnosis of COVID-19 and infectious diseases. This study aims to question the importance of specific chest CT results in predicting the prognosis of COVID-19 patients being followed up in the intensive care unit (ICU).
Materials and Methods: For this study, 20 critically ill patients whose RT-PCR tests were positive for COVID-19 were included. Mortality, invasive and non-invasive mechanical ventilator requirement, APACHE II scores and ICU staying days were compared chest CT scans with have poor prognosis results before admission to ICU.
Results: Critical patients who were followed up in the ICU due to COVID-19 disease with crazy laying pattern on chest CT images, it was concluded that there is a statistically significant requirement for invasive mechanical ventilation support during the ICU period (P = 0.04). We reported that all patients with pleural and pericardial effusion required invasive mechanical ventilation support. One of the chest CT results observed in critical COVID-19 patients ın ICU is that the consolidation / ground glass opacity pattern> 1 may have a higher (about five-fold) mortality rate. Most of our critical COVID-19 patients who stayed in intensive care for a long time had a crazy laying pattern on chest CT images.
Conclusion: We believe that some results obtained from chest CT scans in COVID-19 disease may predict the prognosis of the patient during the intensive care period.
Kaynakça
- 1. Huang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395(10223):497-506. doi:10.1016/S0140-6736(20)30183-5
- 2. Zhu N, Zhang D, Wang W, et al. A Novel Coronavirus from Patients with Pneumonia in China, 2019. N Engl J Med. 2020;382(8):727-733. doi:10.1056/NEJMoa2001017
- 3. https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200211-sitrep-22-ncov.pdf?sfvrsn=fb6d49b1
- 4. Shang Y, Xu C, Jiang F, et al. Clinical characteristics and changes of chest CT features in 307 patients with common COVID-19 pneumonia infected SARS-CoV-2: A multicenter study in Jiangsu, China. Int J Infect Dis. 2020;96:157-162. doi:10.1016/j.ijid.2020.05.006
- 5. Lee N, Hui D, Wu A, et al. A major outbreak of severe acute respiratory syndrome in Hong Kong. N Engl J Med. 2003;348(20):1986-1994. doi:10.1056/NEJMoa030685
- 6. 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(6):327-331. doi:10.1097/RLI.0000000000000672
- 7. Tan W. J, Zhao X., Ma X. et al. A novel coronavirus genome identified in a cluster of pneumonia cases—Wuhan, China 2019− 2020. China CDC Weekly 2020; 2 (4): 61-2. doi: 10.46234/ccdcw2020.017
- 8. Chan JF, Yip CC, To KK, et al. Improved Molecular Diagnosis of COVID-19 by the Novel, Highly Sensitive and Specific COVID-19-RdRp/Hel Real-Time Reverse Transcription-PCR Assay Validated In Vitro and with Clinical Specimens. J Clin Microbiol. 2020;58(5):e00310-20. doi:10.1128/JCM.00310-20
- 9. Wang Y, Hou H, Wang W, Wang W. Combination of CT and RT-PCR in the screening or diagnosis of COVID-19. J Glob Health. 2020;10(1):010347. doi:10.7189/jogh.10.010347
- 10. Chung M, Bernheim A, Mei X, et al. CT Imaging Features of 2019 Novel Coronavirus (2019-nCoV). Radiology. 2020;295(1):202-207. doi:10.1148/radiol.2020200230
- 11. Li, X., Zeng, X., Liu, B., et al. COVID-19 infection presenting with CT halo sign. Radiology: Cardiothoracic Imaging, 2(1), doi: 10.1148/ryct.2020200026
- 12. Ai T, Yang Z, Hou H, et al. Correlation of Chest CT and RT-PCR Testing for Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases. Radiology. 2020;296(2):E32-E40. doi:10.1148/radiol.2020200642
- 13. Yang R, Li X, Liu H et all (2020) Chest CT Severity Score: An Imaging Tool for Assessing Severe COVID-19 Radiology: Cardiothoracic Imaging, 2(2) doi:10.1148/ryct.2020200047
- 14. Lyu P, Liu X, Zhang R,et al. The Performance of Chest CT in Evaluating the Clinical Severity of COVID-19 Pneumonia: Identifying Critical Cases Based on CT Characteristics. Invest Radiol. 2020;55(7):412-421. doi:10.1097/RLI.0000000000000689
- 15. Xiong Y, Sun D, Liu Y, et al. Clinical and High-Resolution CT Features of the COVID-19 Infection: Comparison of the Initial and Follow-up Changes. Invest Radiol. 2020;55(6):332-339. doi:10.1097/RLI.0000000000000674
- 16. Li K, Fang Y, Li W, et al. CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19). Eur Radiol. 2020;30(8):4407-4416. doi:10.1007/s00330-020-06817-6
- 17. Li LQ, Huang T, Wang YQ, et al. COVID-19 patients' clinical characteristics, discharge rate, and fatality rate of meta-analysis. J Med Virol. 2020;92(6):577-583. doi:10.1002/jmv.25757
- 18. https://covid19.saglik.gov.tr/TR-66935/genel-koronavirus-tablosu.html
- 19. Bhatraju PK, Ghassemieh BJ, Nichols M, et al. Covid-19 in Critically Ill Patients in the Seattle Region - Case Series. N Engl J Med. 2020;382(21):2012-2022. doi:10.1056/NEJMoa2004500
- 20. Yang X, Yu Y, Xu J, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir Med. 2020;8(5):475-481. doi:10.1016/S2213-2600(20)30079-5
- 21. Li Y, Xia L. Coronavirus Disease 2019 (COVID-19): Role of Chest CT in Diagnosis and Management. AJR Am J Roentgenol. 2020;214(6):1280-1286. doi:10.2214/AJR.20.22954
- 22. Frater JL, Zini G, d'Onofrio G, et al. COVID-19 and the clinical hematology laboratory. Int J Lab Hematol. 2020;42 Suppl 1:11-18. doi:10.1111/ijlh.13229
- 23. Pan F, Yang L, Li Y, et al. Factors associated with death outcome in patients with severe coronavirus disease-19 (COVID-19): a case-control study. Int J Med Sci. 2020;17(9):1281-1292. doi:10.7150/ijms.46614
- 24. Liu F, Zhang Q, Huang C, et al. CT quantification of pneumonia lesions in early days predicts progression to severe illness in a cohort of COVID-19 patients. Theranostics. 2020;10(12):5613-5622. doi:10.7150/thno.45985
- 25. Salehi S, Abedi A, Balakrishnan S, Gholamrezanezhad A. Coronavirus Disease 2019 (COVID-19): A Systematic Review of Imaging Findings in 919 Patients. AJR Am J Roentgenol. 2020;215(1):87-93. doi:10.2214/AJR.20.23034
- 26. Knaus WA, Draper EA, Wagner DP, et al. APACHE II: a severity of disease classification system. Crit Care Med. 1985;13(10):818-829. doi: 10.1097/00003465-198603000-00013