COVID-19’lu Hastalardaki Prognostik Faktörlerin Değerlendirilmesi: Pandemik Bir Merkez Olan Ankara Şehir Hastanesi Deneyimi

Year 2022, Volume: 8 Issue: 1, 9 - 15, 01.01.2022

Emrah Salman Nevreste Çelikbilek Birsen Özdem Sibel Gökay Sibel Aydoğan Fisun Kırca , Alparslan Toyran Reyhan Bilici Salman Bedia Dinç

https://doi.org/10.53394/akd.1037367

Cited By: 1

Abstract

ÖZ
Amaç: Klinik serviste ve yoğun bakımda takip edilen COVID-19’lu hastalarda temel klinik karakteristikler ve laboratuvar indekslerini sistematik olarak analiz ederek erken dönemde hastalığın olası seyri hakkında ön görüde bulunabilmek amaçlandı.
Gereç ve Yöntemler: Bu retrospektif, tek merkezli çalışma 1 Nisan ile 31 Mayıs 2020 tarihleri arasında Ankara Şehir Hastanesi'nde gerçekleştirilmiştir. Hastalar serviste ve yoğun bakımda takip edilen olmak üzere ikiye ayrıldı ve klinik veriler iki grup arasında karşılaştırıldı. Yoğun bakımdaki COVID-19 hastaları için bağımsız erken prediktörleri tanımlamak için tek değişkenli ve çok değişkenli lojistik regresyon analizi yapıldı. İnterlökin-6’nın yoğun bakımda yatışı öngörmesinde tanısal değerinin olup olmadığının belirlenebilmesi için ROC analizi yapıldı.
Bulgular: Çok değişkenli lojistik regresyon analizine göre artan yaş (Odds oranı [OR] 1,1;%95 güven aralığı [GA] 1,06–1,14; p<0,001 ), lenfosit sayısının düşüklüğü ( OR= 0,1 ;%95 GA 0,03–0,30; p<0,001) ve yüksek interlökin 6 düzeyleri (OR= 1,01;%95 GA 1.00–1,02; p<0,001) bağımsız olarak yoğun bakımda yatan COVID-19’lu hastalarda önemli prediktörlerdendir. ROC eğrisinin altındaki alan 0,89 (%95 GA 0,85-0,94; p<0,001), sınır değer >19,85 pg/ml olarak tespit edildi.
Sonuç: İleri yaş, lenfopeni ve yüksek interlökin 6 düzeyleri olan erken COVID-19’lu hastalarda progresyon daha ileri olup bu hastalar daha çok yoğun bakımda izlenmektedir. Eğer bir hasta bu üç kriterden birine sahipse hastalık sürecinin sürveyansı ve yoğun bakım önceliği artmaktadır. Kritik hastaların erken tespiti, COVID-19 salgınıyla mücadelede işleri kolaylaştıracaktır.
Anahtar Sözcükler: COVID-19, SARS-CoV-2, Lenfopeni, İnterlökin-6, Tek değişkenli analiz, Çok değişkenli analiz

Keywords

COVID-19, SARS-CoV-2, Lenfopeni, İnterlökin-6, Tek değişkenli analiz, Çok değişkenli analiz

Evaluation of Prognostic Factors in Patients with COVID-19: Ankara City Hospital Experience as a Pandemic Center

Abstract

ABSTRACT
Objective: Aim of the study was to analyze systematically the basic clinical characteristics and laboratory indexes in patients with COVID-19 followed in clinical service and intensive care, and to predict the possible course of the disease in the early period.
Methods: This retrospective, single-center study was conducted between April 1 and May 31, 2020 at Ankara City Hospital. The patients were divided into two groups: one received ordinary care, the other intensive therapy, and the clinical data were compared between the two groups.Univariate and multivariate logistic regression analysis were performed to identify independent early predictors for COVID-19 patients in intensive care. ROC analysis was performed to determine whether interleukin-6 has a diagnostic value in predicting hospitalization in intensive care.
Results: Multivariable logistic regression analysis found that increasing age (adjusted odds ratio [OR], 1,1; 95% confidence interval [CI]; 1,06-1,14; p<0,001), lymphopenia (OR, 0,1; 95% CI: 0,03–0,30; p<0,001) and high levels of interleukin-6 (OR, 1,01;95% CI: 1,00-1,02; p<0,001) were the important predictors of COVID-19 independently hospitalized in intensive care. The area under ROC curve of interleukin-6 was 0,89 [95% CI 0,85-0,94; p<0,001] and cut-off value was >19,85 pg/ml.
Conclusion: Progression is more advanced in patients with early COVID-19 with increasing age, lymphopenia and high interleukin 6 levels, and these patients are mostly followed in intensive care.If a patient has one of these three criteria, surveillance of the disease process and intensive care priority increases. Early identification of critical patients will make things easier in tackling the COVID-19 outbreak.

Key Words: COVID-19, SARS-CoV-2, Lymphopenia, Interleukin-6, Univariate analysis, Multivariate analysis

Keywords

COVID-19, SARS-CoV-2, Lymphopenia, Interleukin-6, Univariate analysis, Multivariate analysis

References

• 1. Weiss SR, Leibowitz JL. Coronavirus pathogenesis. Adv Virus Res 2011; 81: 85-164. 2. Hui DS, I Azhar E, Madani TA, Ntoumi F, Kock R, Dar O, Ippolito G, Mchugh TD, Memish ZA, Drosten C, Zumla A, Petersen E. The continuing 2019-nCoV epidemic threat of novel coronaviruses to global health - The latest 2019 novel coronavirus outbreak in Wuhan, China. Int J Infect Dis 2020; 91: 264-6.
• 3. Lu R, Zhao X, Li J, Niu P, Yang B, Wu H, Wang W, Song H, Huang B, Zhu N, Bi Y, Ma X, Zhan F, Wang L, Hu T, Zhou H, Hu Z, Zhou W, Zhao L, Chen J, Meng Y, Wang J, Lin Y, Yuan J, Xie Z, Ma J, Liu WJ, Wang D, Xu W, Holmes EC, Gao GF, Wu G, Chen W, Shi W, Tan W. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. The Lancet 2020; 395: 565-74.
• 4. Wan S, Yi Q, Fan S, Lv J, Zhang X, Guo L, Lang C, Xiao Q, Xiao K, Yi Z, Qiang M, Xiang J, Zhang B, Chen Y. Characteristics of lymphocyte subsets and cytokines in peripheral blood of 123 hospitalized patients with 2019 novel coronavirus pneumonia (NCP). MedRxiv, 2020.
• 5. Ivashkiv LB, Donlin LT. Regulation of type I interferon responses. Nature reviews Immunology 2014; 14: 36-49.
• 6. Li G, Fan Y, Lai Y, Han T, Li Z, Zhou P, Pan P, Wang W, Hu D, Liu X, Zhang Q, Wu J. Coronavirus infections and immune responses. J Med Virol 2020; 92: 424-32.
• 7. George, M R. Hemophagocytic lymphohistiocytosis: review of etiologies and management. Journal of blood medicine 2014; 5: 69.
• 8. Meduri, G., Kohler G, Headley S, Tolley E, Stentz F, Postlethwaite A. Inflammatory cytokines in the BAL of patients with ARDS. Persistent elevation over time predicts poor outcome.Chest 1995; 8: 1303-14.
• 9. Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, Qiu Y, Wang J, Liu Y, Wei Y, Xia J, Yu T, Zhang X, Zhang L. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. . The Lancet 2020; 395: 507-13.
• 10. Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, Liu L, Shan H, Lei CL, Hui DSC, Du B, Li LJ, Zeng G, Yuen KY, Chen RC, Tang CL, Wang T, Chen PY, Xiang J, Li SY, Wang JL, Liang ZJ, Peng YX, Wei L, Liu Y, Hu YH, Peng P, Wang JM, Liu JY, Chen Z, Li G, Zheng ZJ, Qiu SQ, Luo J, Ye CJ, Zhu SY, Zhong NS; China Medical Treatment Expert Group for Covid-19. Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med 2020; 382 : 1708-20.
• 11. Wang X, Fang J, Zhu Y, Chen L, Ding F, Zhou R, Ge L, Wang F, Chen Q, Zhang Y, Zhao Q. Clinical characteristics of non-critically ill patients with novel coronavirus infection (COVID-19) in a Fangcang Hospital. Clin Microbiol Infect 2020; 26: 1063-106.
• 12. Ji D, Zhang D, Xu J, Chen Z, Yang T, Zhao P, Chen G, Cheng G, Wang Y, Bi J, Tan L, Lau G, Qin E. Prediction for Progression Risk in Patients With COVID-19 Pneumonia: The CALL Score. Clin Infect Dis 2020; 71: 1393-9.
• 13. He Z, Zhao C, Dong Q, Zhuang H, Song S, Peng G, Dwyer DE. Effects of severe acute respiratory syndrome (SARS) coronavirus infection on peripheral blood lymphocytes and their subsets. Int J Infect Dis 2005; 9: 323-30.
• 14. Booth CM, Matukas LM, Tomlinson GA, Rachlis AR, Rose DB, Dwosh HA, Walmsley SL, Mazzulli T, Avendano M, Derkach P, Ephtimios IE, Kitai I, Mederski BD, Shadowitz SB, Gold WL, Hawryluck LA, Rea E, Chenkin JS, Cescon DW, Poutanen SM, Detsky AS. Clinical features and short-term outcomes of 144 patients with SARS in the greater Toronto area. JAMA 2003;289: 2801-9.
• 15. Yang YM, Hsu CY, Lai CC, Yen MF, Wikramaratna PS, Chen HH, Wang TH. Impact of Comorbidity on Fatality Rate of Patients with Middle East Respiratory Syndrome. Sci Rep 2017; 7: 11307.
• 16. O'Donnell DR, Carrington D. Peripheral blood lymphopenia and neutrophilia in children with severe respiratory syncytial virus disease. Pediatr Pulmonol 2002; 34: 128-30.
• 17. Chen RF, Chang JC, Yeh WT, Lee CH, Liu JW, Eng HL, Yang KD. Role of vascular cell adhesion molecules and leukocyte apoptosis in the lymphopenia and thrombocytopenia of patients with severe acute respiratory syndrome (SARS). Microbes Infect 2006; 8: 122-7.
• 18. Qu R, Ling Y, Zhang YH, Wei LY, Chen X, Li XM, Liu XY, Liu HM, Guo Z, Ren H, Wang Q. Platelet-to-lymphocyte ratio is associated with prognosis in patients with coronavirus disease-19. J Med Virol 2020; 92: 1533-41.
• 19. Tay MZ, Poh CM, Rénia L, MacAry PA, Ng LFP. The trinity of COVID-19: immunity, inflammation and intervention. Nat Rev Immunol 2020; 20: 363-74.
• 20. Azkur AK, Akdis M, Azkur D, Sokolowska M, van de Veen W, Brüggen MC, O'Mahony L, Gao Y, Nadeau K, Akdis CA. Immune response to SARS-CoV-2 and mechanisms of immunopathological changes in COVID-19. Allergy 2020; 75: 1564-8.
• 21. Liu Y, Yang Y, Zhang C, Huang F, Wang F, Yuan J, Wang Z, Li J, Li J, Feng C, Zhang Z, Wang L, Peng L, Chen L, Qin Y, Zhao D, Tan S, Yin L, Xu J, Zhou C, Jiang C, Liu L. Clinical and biochemical indexes from 2019-nCoV infected patients linked to viral loads and lung injury. Sci China Life Sci 2020; 63: 364-74.
• 22. Tanaka T, Narazaki M, Kishimoto T. IL-6 in inflammation, immunity, and disease. Cold Spring Harb Perspect Biol 2014; 6 :16295.
• 23. Stüber F, Wrigge H, Schroeder S, Wetegrove S, Zinserling J, Hoeft A, Putensen C. Kinetic and reversibility of mechanical ventilation-associated pulmonary and systemic inflammatory response in patients with acute lung injury. Intensive Care Med 2002; 28: 834-41.
• 24. Parsons PE, Eisner MD, Thompson BT, Matthay MA, Ancukiewicz M, Bernard GR, Wheeler AP; NHLBI Acute Respiratory Distress Syndrome Clinical Trials Network. Lower tidal volume ventilation and plasma cytokine markers of inflammation in patients with acute lung injury. Crit Care Med 2005; 33:1-6.
• 25. Herold T, Jurinovic V, Arnreich C, Lipworth BJ, Hellmuth JC, von Bergwelt-Baildon M, Klein M, Weinberger T. Elevated levels of IL-6 and CRP predict the need for mechanical ventilation in COVID-19. J Allergy Clin Immunol 2020; 146 :128-36.
• 26. Gong J, Dong H, Xia Q, Huang Z, Wang D, Zhao Y, Liu W, Tu S, Zhang M, Wang Q, Lu F. Correlation Analysis Between Disease Severity and Inflammation-related Parameters in Patients with COVID-19 Pneumonia. MedRxiv, 2020.