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COVID-19 yoğun bakım hastalarında klinik şiddet ve mortalite predüktörleri: CTSS ve CO-RADS

Year 2022, , 116 - 123, 26.03.2022
https://doi.org/10.18663/tjcl.1052791

Abstract

Giriş: Coronavirus disease 2019 (COVID-19)’un tanısınında polimeraz zincir reaksiyon (PCR) testi negatif fakat klinik bulguları olan hastalarda toraks bilgisayarlı tomografi (BT) önemli rol oynar. Bu çalışmanın amacı; yoğun bakım COVID-19 hastalarında CO-RADS ve/veya BT şiddet skoru (CTSS) ile hastalığın klinik şiddetinin ve/veya mortalitesinin predikte edilip edilemeyeceğini belirlemektir.
Gereç ve Yöntemler: Çalışmaya retrospektif olarak, 23 Mart - 31 Aralık 2020 tarihleri arasındaki PCR pozitif, toraks BT’si olan COVID-19 yoğun bakım hastaları dahil edildi. BT’ler bağımsız iki radyolog tarafından hastaların klinik bilgileri verilmeden değerlendirildi. Her bir BT için CO-RADS ve CTSS hesaplandı, patolojik özellikler kaydedildi. Hastaların demografik, klinik özellikleri ve mortalite oranları kaydedildi. COVID-19’un klinik şiddetine göre hastalar üçe ayrılarak (orta (nazal/maske oksijen), ağır (noninvasive mekanik ventilatör (NIMV) veya yüksek akımlı nazal oksijen (YNO)), çok ağır (invaziv mekanik ventilatör (IMV))) karşılaştırıldı. Mortalite ve klinik şiddet belirteçleri logistic regresyon analizi ile belirlendi.
Bulgular: Çalışmaya 473 hasta dahil edildi. Hastalar klinik şiddetine göre orta (%34,7), ağır (%11,8) ve çok ağır (%53,5) üç gruba ayrıldı. Tüm hastaların CTSS ortalaması 19,58 ve CO-RADS 5 grubundaki hasta oranı %50,7 idi. Mortalite oranı %41,2 idi. APACHE II score ve CTSS klinik şiddet belirleteçleri; yaş, kadın cinsiyet ve CO-RADS ise mortalite belirteçleri olarak bulundu. Mortaliteyi öngören CO-RADS cut-off değeri 5 idi. Buzlu cam görünümü %84,4 oranı ile en sık saptanan patolojik bulgu idi. Mortalite belirteci olan CO-RADS ve APACHE II için ROC eğrisi çizdirildi ve eğri altındaki alan (EAA) değerleri sırasıyla 0.580 ve 0.881 idi. Klinik şiddet belirteci olan CTSS için EAA 0.697 olarak saptandı. APACHE II skoru için %77 sensitivite ve %79 spesifite ile mortalite cut-off değeri 16.5 olarak bulundu (LR:3.7). CTSS için %61 sensitivite ve %66 spesifite ile klinik şiddet cut-off değeri 18.5 olarak bulundu.
Sonuç: CO-RADS mortaliteyi, CTSS ise klinik şiddeti predikte etmede kullanılabilen radyolojik temelli skor sistemleridir.

References

  • 1. WHO. WHO Timeline – COVID-19 [online]. 2021. https://www.who.int/news-room/detail/08-04-2020-who-timeline–-covid-19;accessed 11 March 2020
  • 2. Prokop M, van Everdingen W, van Rees Vellinga T et al. CO-RADS: a categorical ct assessment scheme for patients suspected of having COVID19-definition and evaluation. Radiology 2020; 296: 97-104.
  • 3. Herpe G, Lederlin M, Naudin M et al. Efficacy of Chest CT for COVID-19 Pneumonia Diagnosis in France. Radiology 2021; 298: 81-7.
  • 4. Machnicki S, Patel D, Singh A et al. The Usefulness of Chest CT Imaging in Patients With Suspected or Diagnosed COVID-19. Chest 2021; 160: 652-70.
  • 5. Use of chest imaging in COVID-19. https://www.who.int/publications/i/item/use-of-chest-imaging-in-covid-19. WHO/2019-nCoV/Clinical/Radiology_imaging/2020.1
  • 6. Lieveld A.W.E, Azijli K, Teunissen B.P et al. Chest CT in COVID-19 at the ED: Validation of the COVID-19 Reporting and Data System (CO-RADS) and CT Severity Score: A Prospective, Multicenter, Observational Study. Chest 2021; 159: 1126-35.
  • 7. Ai T, Yang Z, Hou H et al. Correlation of Chest CT and RT-PCR Testing in Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases. Radiology 2020; 26: 200642.
  • 8. Zayed N.E, Bessar M.A, Lutfy S. CO-RADS versus CT-SS scores in predicting severe COVID-19 patients: retrospective comparative study. The Egyptian Journal of Bronchology 2021; 15: 13.
  • 9. Mruk B, Plucińska D, Walecki J, Półtorak-Szymczak G, Sklinda K. Chest Computed Tomography (CT) Severity Scales in COVID-19 Disease: A Validation Study. Med Sci Monit 2021; 27: 931283.
  • 10. Yang R, Li X, Liu H et al. Chest CT Severity Score: An Imaging Tool for Assessing Severe COVID-19. Radiol Cardiothorac Imaging 2020; 2: 200047.
  • 11. Bellos I, Tavernaraki K, Stefanidis K et al. Chest CT severity score and radiological patterns as predictors of disease severity, ICU admission, and viral positivity in COVID-19 patients. Respir Investig 2021; 59: 436-45.
  • 12. Abbasi B, Akhavan R, Khameneh A et al. Evaluation of the relationship between inpatient COVID-19 mortality and chest CT severity score. Am J Emerg Med 2021; 45: 458-63.
  • 13. Kurri N, Tyagi B, Singhal E et al. Assessing the Impact of Inflammatory Markers and CT Severity Score on Disease Severity of COVID-19 Patients Admitted to ICU at a Tertiary Hospital. Journal of The Association of Physicians of India 2021; 69: 41-9.
  • 14. Xie L, Hou K, Xu H et al. Chest CT features and progression of patients with coronavirus disease 2019. Br J Radiol 2020; 93: 20200219.
  • 15. Atta H, Hasan H.A, Elmorshedy R, Gabr A, Abbas W.A, El-Barody M.M. Validation of imaging reporting and data system of coronavirus disease 2019 lexicons CO-RADS and COVID-RADS with radiologists’ preference: a multicentric study. Egyptian Journal of Radiology and Nuclear Medicine 2021; 52: 109.
  • 16. Nguyen N.T, Chinn J, Ferrante M.D, Kirby K.A, Hohmann S.F, Amin A. Male gender is a predictor of higher mortality in hospitalized adults with COVID-19. PLoS One 2021; 16: 254066.
  • 17. Risk for COVID-19 Infection, Hospitalization, and Death By Age Group. CDC COVID-19.https://www.cdc.gov/coronavirus/2019-ncov/covid-data/investigations-discovery/hospitalization-death- by-age.html

Clinical severity and mortality predictors in COVID-19 intensive care patients: CTSS and CO-RADS

Year 2022, , 116 - 123, 26.03.2022
https://doi.org/10.18663/tjcl.1052791

Abstract

Aim: Chest computed tomography (CT) plays an important role in the diagnosis of coronavirus infection disease 2019 (COVID-19) in patients with negative polymerase chain reaction (PCR) test but with clinical findings. The aim of this study; to determine whether the disease can predict clinical severity and/or mortality with CO-RADS and/or CTSS in intensive care COVID-19 patients.
Materials and Methods: In the study retrospectively, COVID-19 intensive care patients with PCR positive and chest CT between 23 March - 31 December 2020 were included. CTs were evaluated by two independent radiologists without providing the clinical information of the patients. CO-RADS and CTSS were calculated for each CT, and pathological features were recorded. Demographic, clinical characteristics and mortality rates of the patients were recorded. Patients were divided into three groups [mild (nasal/mask oxygen), severe (noninvasive mechanichal ventilator (NIMV) or high flow nasal oxygen (HFO)), critically severe (invasive mechanichal ventilation (IMV))] according to the clinical severity of COVID-19. Mortality and clinical severity markers were determined by logistic regression analysis.
Results: Four hundered seventy three patients were included in the study. Patients were divided into three groups according to clinical severity, mild (34.7%), severe (11.8%), and critically severe (53.5%). The mean CTSS of all patients was 19.58 and the rate of patients in the CO-RADS 5 group was 50.7%. The mortality rate was 41.2%. APACHE II score and CTSS were preductors of clinical severity; age, female gender and CO-RADS were found as mortality preductors. The CO-RADS cut-off value predicting mortality was 5. Ground glass appearance was the most common pathological finding with a rate of 84.4%. Receiver operating characteristic (ROC) curves were drawn for mortality markers CO-RADS and APACHE II, and the area under the curve (AUC) values were 0.580 and 0.881, respectively. AUC was found to be 0.697 in the ROC curve drawn for CTSS, which is a clinical indicator of severity. The mortality cut-off value was found to be 16.5 with 77% sensitivity and 79% specificity for the APACHE II score (LR:3.7). The clinical severity cut-off value was found to be 18.5, with 61% sensitivity and 66% specificity for the CTSS.
Conclusion: CO-RADS can be used to predict mortality and CTSS can be used to predict clinical severity which are radiological-based scoring systems.

References

  • 1. WHO. WHO Timeline – COVID-19 [online]. 2021. https://www.who.int/news-room/detail/08-04-2020-who-timeline–-covid-19;accessed 11 March 2020
  • 2. Prokop M, van Everdingen W, van Rees Vellinga T et al. CO-RADS: a categorical ct assessment scheme for patients suspected of having COVID19-definition and evaluation. Radiology 2020; 296: 97-104.
  • 3. Herpe G, Lederlin M, Naudin M et al. Efficacy of Chest CT for COVID-19 Pneumonia Diagnosis in France. Radiology 2021; 298: 81-7.
  • 4. Machnicki S, Patel D, Singh A et al. The Usefulness of Chest CT Imaging in Patients With Suspected or Diagnosed COVID-19. Chest 2021; 160: 652-70.
  • 5. Use of chest imaging in COVID-19. https://www.who.int/publications/i/item/use-of-chest-imaging-in-covid-19. WHO/2019-nCoV/Clinical/Radiology_imaging/2020.1
  • 6. Lieveld A.W.E, Azijli K, Teunissen B.P et al. Chest CT in COVID-19 at the ED: Validation of the COVID-19 Reporting and Data System (CO-RADS) and CT Severity Score: A Prospective, Multicenter, Observational Study. Chest 2021; 159: 1126-35.
  • 7. Ai T, Yang Z, Hou H et al. Correlation of Chest CT and RT-PCR Testing in Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases. Radiology 2020; 26: 200642.
  • 8. Zayed N.E, Bessar M.A, Lutfy S. CO-RADS versus CT-SS scores in predicting severe COVID-19 patients: retrospective comparative study. The Egyptian Journal of Bronchology 2021; 15: 13.
  • 9. Mruk B, Plucińska D, Walecki J, Półtorak-Szymczak G, Sklinda K. Chest Computed Tomography (CT) Severity Scales in COVID-19 Disease: A Validation Study. Med Sci Monit 2021; 27: 931283.
  • 10. Yang R, Li X, Liu H et al. Chest CT Severity Score: An Imaging Tool for Assessing Severe COVID-19. Radiol Cardiothorac Imaging 2020; 2: 200047.
  • 11. Bellos I, Tavernaraki K, Stefanidis K et al. Chest CT severity score and radiological patterns as predictors of disease severity, ICU admission, and viral positivity in COVID-19 patients. Respir Investig 2021; 59: 436-45.
  • 12. Abbasi B, Akhavan R, Khameneh A et al. Evaluation of the relationship between inpatient COVID-19 mortality and chest CT severity score. Am J Emerg Med 2021; 45: 458-63.
  • 13. Kurri N, Tyagi B, Singhal E et al. Assessing the Impact of Inflammatory Markers and CT Severity Score on Disease Severity of COVID-19 Patients Admitted to ICU at a Tertiary Hospital. Journal of The Association of Physicians of India 2021; 69: 41-9.
  • 14. Xie L, Hou K, Xu H et al. Chest CT features and progression of patients with coronavirus disease 2019. Br J Radiol 2020; 93: 20200219.
  • 15. Atta H, Hasan H.A, Elmorshedy R, Gabr A, Abbas W.A, El-Barody M.M. Validation of imaging reporting and data system of coronavirus disease 2019 lexicons CO-RADS and COVID-RADS with radiologists’ preference: a multicentric study. Egyptian Journal of Radiology and Nuclear Medicine 2021; 52: 109.
  • 16. Nguyen N.T, Chinn J, Ferrante M.D, Kirby K.A, Hohmann S.F, Amin A. Male gender is a predictor of higher mortality in hospitalized adults with COVID-19. PLoS One 2021; 16: 254066.
  • 17. Risk for COVID-19 Infection, Hospitalization, and Death By Age Group. CDC COVID-19.https://www.cdc.gov/coronavirus/2019-ncov/covid-data/investigations-discovery/hospitalization-death- by-age.html
There are 17 citations in total.

Details

Primary Language English
Subjects Health Care Administration
Journal Section Orıgınal Artıcle
Authors

Behiye Deniz Kosovalı 0000-0001-9385-6542

Esra Yurduseven Çıvgın 0000-0003-4790-3146

Erdem Özkan

Tülay Tunçer Peker 0000-0001-6467-407X

Mehmet Mutlu

Publication Date March 26, 2022
Published in Issue Year 2022

Cite

APA Kosovalı, B. D., Yurduseven Çıvgın, E., Özkan, E., Tunçer Peker, T., et al. (2022). Clinical severity and mortality predictors in COVID-19 intensive care patients: CTSS and CO-RADS. Turkish Journal of Clinics and Laboratory, 13(1), 116-123. https://doi.org/10.18663/tjcl.1052791
AMA Kosovalı BD, Yurduseven Çıvgın E, Özkan E, Tunçer Peker T, Mutlu M. Clinical severity and mortality predictors in COVID-19 intensive care patients: CTSS and CO-RADS. TJCL. March 2022;13(1):116-123. doi:10.18663/tjcl.1052791
Chicago Kosovalı, Behiye Deniz, Esra Yurduseven Çıvgın, Erdem Özkan, Tülay Tunçer Peker, and Mehmet Mutlu. “Clinical Severity and Mortality Predictors in COVID-19 Intensive Care Patients: CTSS and CO-RADS”. Turkish Journal of Clinics and Laboratory 13, no. 1 (March 2022): 116-23. https://doi.org/10.18663/tjcl.1052791.
EndNote Kosovalı BD, Yurduseven Çıvgın E, Özkan E, Tunçer Peker T, Mutlu M (March 1, 2022) Clinical severity and mortality predictors in COVID-19 intensive care patients: CTSS and CO-RADS. Turkish Journal of Clinics and Laboratory 13 1 116–123.
IEEE B. D. Kosovalı, E. Yurduseven Çıvgın, E. Özkan, T. Tunçer Peker, and M. Mutlu, “Clinical severity and mortality predictors in COVID-19 intensive care patients: CTSS and CO-RADS”, TJCL, vol. 13, no. 1, pp. 116–123, 2022, doi: 10.18663/tjcl.1052791.
ISNAD Kosovalı, Behiye Deniz et al. “Clinical Severity and Mortality Predictors in COVID-19 Intensive Care Patients: CTSS and CO-RADS”. Turkish Journal of Clinics and Laboratory 13/1 (March 2022), 116-123. https://doi.org/10.18663/tjcl.1052791.
JAMA Kosovalı BD, Yurduseven Çıvgın E, Özkan E, Tunçer Peker T, Mutlu M. Clinical severity and mortality predictors in COVID-19 intensive care patients: CTSS and CO-RADS. TJCL. 2022;13:116–123.
MLA Kosovalı, Behiye Deniz et al. “Clinical Severity and Mortality Predictors in COVID-19 Intensive Care Patients: CTSS and CO-RADS”. Turkish Journal of Clinics and Laboratory, vol. 13, no. 1, 2022, pp. 116-23, doi:10.18663/tjcl.1052791.
Vancouver Kosovalı BD, Yurduseven Çıvgın E, Özkan E, Tunçer Peker T, Mutlu M. Clinical severity and mortality predictors in COVID-19 intensive care patients: CTSS and CO-RADS. TJCL. 2022;13(1):116-23.


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