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Covid-19 hastalarının toraks bilgisayarlı tomografi bulgularının sınıflandırılması, klinik ve laboratuar verileriyle korelasyonu

Yıl 2022, Cilt: 13 Sayı: 3, 322 - 332, 27.09.2022
https://doi.org/10.18663/tjcl.1021460

Öz

Amaç: Çalışmanın amacı, popülasyonumuzdaki COVID-19 ile enfekte olan hastaları, Kuzey Amerika Radyoloji Derneği (RSNA) ve Amerikan Radyoloji Koleji (ACR) tarafından tanımlanan radyolojik konsensusa göre sınıflandırmak ve hastaların klinik-laboratuvar bulguları ile ilişkisini göstermektir.
Gereç ve Yöntem: Ankara Şehir Hastanesi'ne ateş, öksürük ve solunum sıkıntısı gibi semptomlarla başvuran ve laboratuvar bulguları Covid-19 ile uyumlu 127 olgu (74 erkek, 53 kadın; yaş aralığı 19-92) dahil edildi. Olguların toraks bilgisayarlı tomografi (BT) bulguları RSNA kriterlerine göre sınıflandırıldı ve klinik-laboratuvar verileriyle ilişkisi istatistiksel olarak değerlendirildi.
Bulgular: Olguların % 47,2'sinde ateş,% 62,2 öksürük, 22 nefes darlığı,% 4,7 ishal ve% 28,3 yorgunluk-halsizlik semptomları vardı. Toraks BT bulguları değerlendirildiğinde hastaların % 55'inde Covid-19 pnömonisi açısından tipik görünüm,% 21'inde indetermine görünüm,% 11'inde atipik görünüm ve% 13'ünde negatif görünüm vardı.
Sonuçlar: Toraks BT incelemesinin Covid-19 pnömonisini değerlendirmede pek çok avantajı olduğu aşikardır. Ancak bulguları daha iyi sınıflandırmak ve klinik-laboratuvar bulguları ile ilişkisini ortaya çıkarmak için daha fazla gözlem yapılması gerekmektedir.

Kaynakça

  • 1. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study [published correction appears in Lancet. 2020 Mar 28;395(10229):1038] [published correction appears in Lancet. 2020 Mar 28;395(10229):1038]. Lancet 2020;395(10229):1054-1062. doi:10.1016/S0140-6736(20)30566-3
  • 2. Bai H.X., Hsieh B, Xiong Z, Halsey K, Choi J.W., Tran T.M.L. et al. Performance of Radiologists in Differentiating COVID-19 from Non-COVID-19 Viral Pneumonia at Chest CT. Radiology 2020;296(2):E46-E54. doi:10.1148/radiol.2020200823
  • 3. Simpson S, Kay FU, Abbara S, Bhalla S, Chung J.H., Chung M et al. Radiological Society of North America Expert Consensus Statement on Reporting Chest CT Findings Related to COVID-19. Endorsed by the Society of Thoracic Radiology, the American College of 2019
  • 4. Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet 2020;395(10223):507-513. doi:10.1016/S0140-6736(20)30211-7
  • 5. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China [published correction appears in Lancet. 2020 Jan 30;:]. Lancet 2020;395(10223):497-506. doi:10.1016/S0140-6736(20)30183-5
  • 6. Hosseiny M, Kooraki S, Gholamrezanezhad A, Reddy S, Myers L. RadiologyPerspective of CoronavirusDisease 2019 (COVID-19): Lessons From Severe Acute Respiratory Syndrome and Middle East Respiratory Syndrome. AJR Am J Roentgenol. 2020;214(5):1078-1082. doi:10.2214/AJR.20.22969
  • 7. Salehi S, Abedi A, Balakrishnan S, Gholamrezanezhad A. CoronavirusDisease 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
  • 8. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China [published correction appears in Lancet. 2020 Jan 30;:]. Lancet 2020;395(10223):497-506. doi:10.1016/S0140-6736(20)30183-5
  • 9. Song F, Shi N, Shan F, Zhang Z, Shen J, Lu H et al. Emerging 2019 Novel Coronavirus (2019-nCoV) Pneumonia. Radiology 2020;295(1):210-217. doi:10.1148/radiol.2020200274
  • 10. Chung M, Bernheim A, Mei X, Zhan N, Huang M, Zeng X et al. CT Imaging Features of 2019 Novel Coronavirus (2019-nCoV). Radiology 2020;295(1):202-207. doi:10.1148/radiol.2020200230
  • 11. 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 [published online ahead of print, 2020 Feb 7]. JAMA 2020;323(11):1061-1069. doi:10.1001/jama.2020.1585
  • 12. Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet 2020;395(10223):507-513. doi:10.1016/S0140-6736(20)30211-7
  • 13. Pan Y, Guan H, Zhou S, Wang Y, Li Q, Zhu T et al. Initial CT findings and temporal changes in patients with the novel coronavirus pneumonia (2019-nCoV): a study of 63 patients in Wuhan, China. EurRadiol. 2020;30(6):3306-3309. doi:10.1007/s00330-020-06731-x
  • 14. Jin YH, Cai L, Cheng ZS, Cheng H, Deng T, Fan Y et al. A rapid advice guideline for the diagnosis and treatment of 2019 novel coronavirus (2019-nCoV) infected pneumonia (standard version). Mil MedRes 2020;7(1):4. Published 2020 Feb 6. doi:10.1186/s40779-020-0233-6

Classification of thorax computed tomography findings of Covid-19 patients, their correlation with clinical and laboratory data

Yıl 2022, Cilt: 13 Sayı: 3, 322 - 332, 27.09.2022
https://doi.org/10.18663/tjcl.1021460

Öz

Aim: The aim of the study is to classify patients infected with Covid-19 in our population according to the radiological consensus defined by Radiology Society of North America (RSNA) and American College of Radiology (ACR) and to show the relationship of the patients with clinical-laboratory findings.
Material and Methods: 127 cases (74 males, 53 females; age range 19-92 years) who applied to Ankara City Hospital with symptoms such as fever, cough and respiratory distress and whose laboratory findings were compatible with Covid-19 were included in our study. The thorax computed tomography (CT) findings of the cases were classified according to the RSNA criteria and their relationship with clinical-laboratory data was statistically evaluated.
Results: 47.2% of them had fever, 62.2% cough, 22 dyspnea, 4.7% diarrhea and 28.3% fatigue-malaise symptoms. When the thorax CT findings were evaluated, 55% of the patients had a typical appearance, 21% intermediate appearance, 11% atypical appearance and 13% negative appearance.
Conclusion: It is obvious that thoracic CT examination has many advantages in evaluating Covid-19 pneumonia. However, it was concluded that more observations should be made in order to classify the findings better and to reveal their relationship with clinical-laboratory findings.

Kaynakça

  • 1. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study [published correction appears in Lancet. 2020 Mar 28;395(10229):1038] [published correction appears in Lancet. 2020 Mar 28;395(10229):1038]. Lancet 2020;395(10229):1054-1062. doi:10.1016/S0140-6736(20)30566-3
  • 2. Bai H.X., Hsieh B, Xiong Z, Halsey K, Choi J.W., Tran T.M.L. et al. Performance of Radiologists in Differentiating COVID-19 from Non-COVID-19 Viral Pneumonia at Chest CT. Radiology 2020;296(2):E46-E54. doi:10.1148/radiol.2020200823
  • 3. Simpson S, Kay FU, Abbara S, Bhalla S, Chung J.H., Chung M et al. Radiological Society of North America Expert Consensus Statement on Reporting Chest CT Findings Related to COVID-19. Endorsed by the Society of Thoracic Radiology, the American College of 2019
  • 4. Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet 2020;395(10223):507-513. doi:10.1016/S0140-6736(20)30211-7
  • 5. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China [published correction appears in Lancet. 2020 Jan 30;:]. Lancet 2020;395(10223):497-506. doi:10.1016/S0140-6736(20)30183-5
  • 6. Hosseiny M, Kooraki S, Gholamrezanezhad A, Reddy S, Myers L. RadiologyPerspective of CoronavirusDisease 2019 (COVID-19): Lessons From Severe Acute Respiratory Syndrome and Middle East Respiratory Syndrome. AJR Am J Roentgenol. 2020;214(5):1078-1082. doi:10.2214/AJR.20.22969
  • 7. Salehi S, Abedi A, Balakrishnan S, Gholamrezanezhad A. CoronavirusDisease 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
  • 8. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China [published correction appears in Lancet. 2020 Jan 30;:]. Lancet 2020;395(10223):497-506. doi:10.1016/S0140-6736(20)30183-5
  • 9. Song F, Shi N, Shan F, Zhang Z, Shen J, Lu H et al. Emerging 2019 Novel Coronavirus (2019-nCoV) Pneumonia. Radiology 2020;295(1):210-217. doi:10.1148/radiol.2020200274
  • 10. Chung M, Bernheim A, Mei X, Zhan N, Huang M, Zeng X et al. CT Imaging Features of 2019 Novel Coronavirus (2019-nCoV). Radiology 2020;295(1):202-207. doi:10.1148/radiol.2020200230
  • 11. 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 [published online ahead of print, 2020 Feb 7]. JAMA 2020;323(11):1061-1069. doi:10.1001/jama.2020.1585
  • 12. Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet 2020;395(10223):507-513. doi:10.1016/S0140-6736(20)30211-7
  • 13. Pan Y, Guan H, Zhou S, Wang Y, Li Q, Zhu T et al. Initial CT findings and temporal changes in patients with the novel coronavirus pneumonia (2019-nCoV): a study of 63 patients in Wuhan, China. EurRadiol. 2020;30(6):3306-3309. doi:10.1007/s00330-020-06731-x
  • 14. Jin YH, Cai L, Cheng ZS, Cheng H, Deng T, Fan Y et al. A rapid advice guideline for the diagnosis and treatment of 2019 novel coronavirus (2019-nCoV) infected pneumonia (standard version). Mil MedRes 2020;7(1):4. Published 2020 Feb 6. doi:10.1186/s40779-020-0233-6
Toplam 14 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Sağlık Kurumları Yönetimi
Bölüm Özgün Makale
Yazarlar

Murathan Köksal 0000-0002-5936-2925

Erdem Özkan 0000-0001-8120-7051

Adalet Aypak 0000-0001-8850-2475

Esragül Akınci 0000-0003-3412-8929

Bircan Kayaaslan 0000-0002-2502-3810

İmran Hasanoğlu 0000-0001-6692-3893

Ayşe Kalem 0000-0002-4759-0066

Fatma Eser Bu kişi benim 0000-0002-0282-6346

Fatma Gül Büyükbayraktar İmamoğlu Bu kişi benim 0000-0002-1295-144X

Rahmet Güner 0000-0002-1029-1185

Yayımlanma Tarihi 27 Eylül 2022
Yayımlandığı Sayı Yıl 2022 Cilt: 13 Sayı: 3

Kaynak Göster

APA Köksal, M., Özkan, E., Aypak, A., Akınci, E., vd. (2022). Classification of thorax computed tomography findings of Covid-19 patients, their correlation with clinical and laboratory data. Turkish Journal of Clinics and Laboratory, 13(3), 322-332. https://doi.org/10.18663/tjcl.1021460
AMA Köksal M, Özkan E, Aypak A, Akınci E, Kayaaslan B, Hasanoğlu İ, Kalem A, Eser F, Büyükbayraktar İmamoğlu FG, Güner R. Classification of thorax computed tomography findings of Covid-19 patients, their correlation with clinical and laboratory data. TJCL. Eylül 2022;13(3):322-332. doi:10.18663/tjcl.1021460
Chicago Köksal, Murathan, Erdem Özkan, Adalet Aypak, Esragül Akınci, Bircan Kayaaslan, İmran Hasanoğlu, Ayşe Kalem, Fatma Eser, Fatma Gül Büyükbayraktar İmamoğlu, ve Rahmet Güner. “Classification of Thorax Computed Tomography Findings of Covid-19 Patients, Their Correlation With Clinical and Laboratory Data”. Turkish Journal of Clinics and Laboratory 13, sy. 3 (Eylül 2022): 322-32. https://doi.org/10.18663/tjcl.1021460.
EndNote Köksal M, Özkan E, Aypak A, Akınci E, Kayaaslan B, Hasanoğlu İ, Kalem A, Eser F, Büyükbayraktar İmamoğlu FG, Güner R (01 Eylül 2022) Classification of thorax computed tomography findings of Covid-19 patients, their correlation with clinical and laboratory data. Turkish Journal of Clinics and Laboratory 13 3 322–332.
IEEE M. Köksal, “Classification of thorax computed tomography findings of Covid-19 patients, their correlation with clinical and laboratory data”, TJCL, c. 13, sy. 3, ss. 322–332, 2022, doi: 10.18663/tjcl.1021460.
ISNAD Köksal, Murathan vd. “Classification of Thorax Computed Tomography Findings of Covid-19 Patients, Their Correlation With Clinical and Laboratory Data”. Turkish Journal of Clinics and Laboratory 13/3 (Eylül 2022), 322-332. https://doi.org/10.18663/tjcl.1021460.
JAMA Köksal M, Özkan E, Aypak A, Akınci E, Kayaaslan B, Hasanoğlu İ, Kalem A, Eser F, Büyükbayraktar İmamoğlu FG, Güner R. Classification of thorax computed tomography findings of Covid-19 patients, their correlation with clinical and laboratory data. TJCL. 2022;13:322–332.
MLA Köksal, Murathan vd. “Classification of Thorax Computed Tomography Findings of Covid-19 Patients, Their Correlation With Clinical and Laboratory Data”. Turkish Journal of Clinics and Laboratory, c. 13, sy. 3, 2022, ss. 322-3, doi:10.18663/tjcl.1021460.
Vancouver Köksal M, Özkan E, Aypak A, Akınci E, Kayaaslan B, Hasanoğlu İ, Kalem A, Eser F, Büyükbayraktar İmamoğlu FG, Güner R. Classification of thorax computed tomography findings of Covid-19 patients, their correlation with clinical and laboratory data. TJCL. 2022;13(3):322-3.


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