COVID-19 Pneumonia-Related ARDS – Can We Predict Mortality with Laboratory Parameters?

Year 2024, , 61 - 68, 29.08.2024

Emine Özsarı , Muhammed Emin Demirkol , Süleyman Özsarı , Musa Kaya , Derya Kocadağ , Zeynep Baysal

https://doi.org/10.47493/abantmedj.1416495

Abstract

Objective: To examine the laboratory characteristics of COVID-19 pneumonia-related ARDS patients who lived or died. Materials and methods: Retrospectively, two-center of patients who were hospitalized in the intensive care unit were researched in Abant Izzet Baysal University Education and Research Hospital in Bolu, Turkey. Between March 31 and December 31, 2020, data on the demographic characteristics, routine laboratory results, including arterial blood gas tests, and clinical outcomes were collected for both the survivor and non-survivor groups. Results: The median age of the 509 patients was 70 years (interquartile range, 59-79 years); 326 patients (64%) were men, and 161 patients (31.6%) tested positive for RT-PCR. While 232 (45.6%) patients in the non-survivor group died, 277 patients were discharged (54.4%) as survivors. The mortality markers of WBC, RBC, HGB, Ph, pO2, pCO2, HCO3, PLT, PCT, NEU, ALT, and D-dimer did not differ significantly (p>0.05). CRP, RDW, LDH, ferritin, urea, and creatinine levels were substantially higher and associated with death in the non-survivor group (p 0.05). Conclusion: A greater risk of death was linked to older age and the number of days spent in the hospital, most likely as a result of persistent underlying issues and weakened immune responses. Risk variables for the progression were CRP, LDH, RDW, ferritin, urea, and creatinine. With the help of laboratory parameters to predict mortality, we can define earlier the changes in immune insufficiency, coagulation problems, hepatic injury, and kidney injury.

Keywords

ARDS, COVID 19, laboratory parameters, mortality

COVID 19 Pnömonisi Sonrası Gelişen ARDS'de Laboratuvar Parametreleri Mortaliteyi Öngörmede Kullanılabilir Mi?

Abstract

Amaç: Yaşayan veya ölen COVİD-19 pnömonisine bağlı ARDS hastalarının laboratuvar özelliklerini incelemek. Gereç ve yöntem: Bolu Abant İzzet Baysal Üniversitesi Eğitim ve Araştırma Hastanesi'nde yoğun bakım ünitesinde yatan hastaların iki merkezi retrospektif olarak araştırıldı. 31 Mart ile 31 Aralık 2020 tarihleri ​​arasında hem hayatta kalan hem de hayatta kalmayan gruplar için demografik özellikler, arteriyel kan gazı testleri dahil rutin laboratuvar sonuçları ve klinik sonuçlara ilişkin veriler toplandı. Bulgular: 509 hastanın ortanca yaşı 70 (çeyrekler arası aralık, 59-79 yıl) idi; 326 hasta (%64) erkekti ve 161 hastanın (%31,6) RT-PCR testi pozitif çıktı. Hayatta kalan grupta 232 (%45,6) hasta hayatını kaybederken, 277 hasta (%54,4) sağ olarak taburcu edildi. WBC, RBC, HGB, Ph, pO2, pCO2, HCO3, PLT, PCT, NEU, ALT ve D-dimer mortalite belirteçleri anlamlı farklılık göstermedi (p>0,05). Hayatta kalmayan grupta CRP, RDW, LDH, ferritin, üre ve kreatinin düzeyleri önemli ölçüde daha yüksekti ve ölümle ilişkiliydi (p < 0.05). Sonuç: Daha büyük ölüm riski, ileri yaş ve hastanede geçirilen gün sayısıyla bağlantılıydı; büyük ihtimalle kalıcı altta yatan sorunlar ve zayıflamış bağışıklık tepkilerinin bir sonucuydu. İlerlemeye ilişkin risk değişkenleri CRP, LDH, RDW, ferritin, üre ve kreatinindi. Mortaliteyi tahmin etmeye yönelik laboratuvar parametrelerinin yardımıyla bağışıklık yetersizliği, pıhtılaşma sorunları, karaciğer hasarı ve böbrek hasarındaki değişiklikleri daha erken tanımlayabiliriz.

Keywords

ARDS, COVID 19, laboratuvar parametreleri, mortalite

References

• WHO Coronavirus Disease (COVID-19) Dashboard [Internet], 2021 [accessed 2021 Oct 29]. Available from: https://covid19.who.int/.
• Ministry of Health, Republic of Turkey. COVID-19 web page of the Republic of Turkey, Ministry of Health [Internet]. 2021 [accessed 2021 Oct 29], https://covid19.saglik.gov.tr.
• Worldometer, Countries where covid-19 has spread [Internet] [accessed 2021 Oct 29, https://www.worldometers.info/coronavirus/countries-where-coronavirus-has-spread
• S.Matta, et al., Morbidity and mortality trends of COVID-19 in top 10 countries, Indian J. Tubercul. 67 (2020) 167–172.
• Zhang J, et al., Hospitals' responsibility in response to the threat of infectious disease outbreak in the context of the coronavirus disease 2019 pandemic: implications for low and middle-income countries, Glob. Health J. 4 (2020) 113–117.
• Watson J, et al., Interpreting a COVID-19 test result, BMJ 369 (2020), m1808.
• Huang C, Wang Y, Li X,et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China.Lancet. doi:10.1016/S0140-6736(20)30183-5
• Chen N, Zhou M, Dong X, 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
• Zhu N, Zhang D, Wang W, et al. A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med. 2020;382:727–33. 4. World Health Organization. COVID-19 outbreak. https://www.who.int.
• Wu Z, McGoogan JM. Characteristics of and important lessons from the coronavirus disease 2019 outbreak in China: summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention. JAMA. 2020.
• Grasselli G, Zangrillo A, Zanella A,et al. Baseline characteristics and outcomes of 1591 patients infected with SARSCoV-2 admitted to ICUs of the Lombardy region. Italy JAMA. 2020;24:122.
• Cao J, Hu X, Cheng W,et al.Clinical features and short-term outcomes of 18 patients with coronavirus disease 2019 in intensive care unit. Intensive Care Med. 2020;46:851–3.
• 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;2600: 1–7.
• Y.Varol, et al., The impact of Charlson comorbidity index on mortality from SARSCoV-2 virus infection and a novel COVID-19 mortality index: CoLACD, Int. J. Clin. Pract. (2020), https://doi.org/10.1111/ijcp.13858.e13858.
• G. Aksel, et al., Early predictors of mortality for moderate to severely ill patients with COVID-19, Am. J. Emerg. Med. (2020), https://doi.org/10.1016/j. ajem.2020.08.076.
• G. Onder, et al., Case-fatality rate and characteristics of patients dying about COVID-19 in Italy, J. Am. Med. Assoc. 323 (2020) 1775–1776.
• A. Bahl, et al., Early predictors of in-hospital mortality in patients with COVID-19 in a large American cohort, Intern. Emerg. Med. 15 (2020) 1485–1499.
• L.Q. Li, et al., COVID-19 patients' clinical characteristics, discharge rate, and fatality rate of meta-analysis, J. Med. Virol. 92 (2020) 577–583.
• S. Richardson, et al., Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area, J. Am. Med. Assoc. 323 (2020) 2052–2059.
• Jin M, et al., Gender differences in patients with COVID-19: focus on severity and mortality, Front. Public. Health 8 (2020) 152.
• Chidambaram V, et al., Factors associated with disease severity and mortality among patients with COVID-19: a systematic review and meta-analysis, PloS One 15 (2020), e0241541.
• Huang I, et al., C-reactive protein, procalcitonin, D-dimer, and ferritin in severe coronavirus disease-2019: a meta-analysis, Ther. Adv. Respir. Dis. 14 (2020), 1753466620937175.
• Özsari, S., Özsari, E., Demirkol, M.E. Comparison of neutrophil-lymphocyte ratio, platelet lymphocyte ratio, and mean platelet volume and PCR test in COVID-19 patients. Revista da Associação Médica Brasileira, 67(2021), 40-45.
• P.R. Martins-Filho, et al., Factors associated with mortality in patients with COVID-19. A quantitative evidence synthesis of clinical and laboratory data, Eur. J. Intern. Med. 76 (2020) 97–99.
• Kokturk, N., Babayigit, C., Kul, S., Cetinkaya, P. D., Nayci, S. A., Baris, S. A.,Bayram, H. (2021). The predictors of COVID-19 mortality in a nationwide cohort of Turkish patients. Respiratory Medicine, 183, 106433.