Pandemi servisinde yatan COVID-19 hastalarının yatış kan değerleri ile prognozlarının öngörülebilirliğinin değerlendirilmesi: Retrospektif bir çalışma

Abstract

Amaç: Prognostik öngörücüler, devam eden COVID-19 pandemisi sırasında sağlık sisteminin hızlı tepki vermesi ve optimal kullanımı için önemlidir. COVID-19 hastalarında erken evrelerden başlayarak birçok hematolojik parametrenin bozulabileceği bildirilmiştir. Mevcut çalışma ile serviste takip edilen hastaların hematolojik ve biyokimyasal değerlerinin, yoğun bakım yatışı ve mortalite ile ilişkisinin belirlenmesi amaçlanmıştır. Yöntem: Bu çalışma geriye dönük dosya tarama çalışmasıdır. Hasta grubu 1.09.2021-15.12.2021 tarihleri arasında pandemi servisine yatan hastalardan oluşmaktadır. İlgili tarih aralığında yatan 366 hastanın tamamı değerlendirildi, dışlama kriterleri sonrası 242 hasta çalışmaya alındı. Hastaların tamamının polimeraz zincir reaksiyon testleri pozitifti. Hastaların servise yatışlarının ilk günündeki kan parametreleri, yaş, boy, kilo, cinsiyet, kronik hastalıkları ve steroid tedavisi dosyalarından kaydedilerek incelendi. Servis çıkışlarına göre hastalar, yoğun bakıma devir (yoğun bakım tedavisinden sonra taburcu olanlar), ölüm ile sonuçlanan (servisten yoğun bakıma devredilen ve taburcu olmadan ölenler) ve eve taburcu (hiç yoğun bakım yatışı olmadan servisten eve taburcu olanlar) olarak üç gruba kategorize edildi. Bulgular: Çalışmaya alınan 242 hastanın 135’i (%55.8) kadın, 107’si (44.2%) erkektir. Hastaların 213’ü (%88) servisten eve taburcu edildi, 8’i (%3.3) yoğun bakıma devir edildi ve 21’i (%8.7) ölümle sonuçlandı. Ölümle sonuçlanan hastaların yaş ortalaması (69.6±13.14 yıl), yoğun bakıma devir edilenlerin yaş ortalamasından (61.25±15.75) ve servisten eve taburcu edilen hastaların yaş ortalamasından (68.91±12.97) anlamlı olarak daha büyüktür. Hastalar yaşayan ve ölümle sonuçlanan olarak iki gruba ayrılıp incelenince; yaş, lenfosit, kan üre azotu, glomerüler filtrasyon hızı, aspartat aminotransferaz, albumin, C reaktif protein, prokalsitonin, D-dimer, trombosit lenfosit oranı (TLO) ve nötrofil lenfosit oranı (NLO) değerlerinde iki grup arasında anlamlı farklılık vardı. Anlamlı değerlerle oluşturulan regresyon modeline göre yaş, NLO, D-dimer yüksekliği ve TLO düşüklüğü mortalite için bağımsız risk faktörleri olarak bulunmuştur. Sonuç: Sunulan çalışmada yaş, yatış günü alınan kandan ölçülen D-dimer, TLO ve NLO COVID-19 hastalarında mortalite için bağımsız prognostik belirteçler olarak bulunmuştur.

Keywords

• COVID-19
• trombosit-lenfosit oranı
• nötrofil-lenfosit oranı
• hemogramdan türetilen oranlar
• biyobelirteçler
• hastalık şiddeti

Supporting Institution

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Project Number

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Evaluation of the predictability of prognoses of COVID-19 patients hospitalized in the pandemic service by hospitalization blood values: A retrospective study

Abstract

Objectives: Prognostic predictors are important for the rapid response and optimal use of the health system during the ongoing COVID-19 pandemic. It has been reported that many hematological parameters may deteriorate starting from the early stages in COVID-19 patients. The aim of the present study was to determine the relationship between hematological and biochemical parameters of patients followed in the service, intensive care hospitalization, and mortality. Methods: The present study is a retrospective study. Participants consist of patients hospitalized in the pandemic service between 1.09.2021 and 15.12.2021. All 366 patients hospitalized in the relevant date range were evaluated, and after exclusion criteria, the study was conducted on 242 patients. Polymerase chain reaction tests of all patients were positive. The hematological and biochemical parameters of the patients on the first day of hospitalization, their age, height, weight, gender, chronic diseases, and steroid treatments were recorded. According to service exits, patients were categorized into three groups: transfer to intensive care (discharged after intensive care treatment), resulting in death (transferred from the ward to intensive care unit and died without discharge), and discharged home (discharged home from the ward without intensive care admission). Results: Of the 242 patients included in the study, 135 (55.8%) were female and 107 (44.2%) were male. Of the patients, 213 (88%) were discharged home from the ward, 8 (3.3%) were transferred to the intensive care unit, and 21 (8.7%) died. The mean age of the patients who died (69.6±13.14 years) was significantly higher than of those transferred to the intensive care unit (61.25±15.75) and discharged home from the service (68.91±12.97). When the patients were divided into two groups as survived and dead; age, lymphocyte, blood urea nitrogen, glomerular filtration rate, aspartate aminotransferase, albumin, C reactive protein, procalcitonin, D-dimer, platelet lymphocyte ratio (TLO) and neutrophil lymphocyte Ratio (NLO) values were significantly different between the two groups. According to the regression model created with significant values, age, high NLO and D-dimer, and low TLO were found to be independent risk factors for mortality. Conclusion: In the present study, age, D-dimer, TLO and NLO measured on the day of hospitalization were found to be independent prognostic markers for mortality in COVID-19 patients.

Keywords

• COVID-19
• platelet-to-lymphocyte ratio
• neutrophil-to-lymphocyte ratio
• hemogram-derived-ratios
• biomarkers
• disease severity
• mortality

Project Number

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References

1. 1. WHO. 14.9 million excess deaths associated with the COVID-19 pandemic in 2020 and 2021. https://www.who.int/news/item/05-05-2022-14.9-million-excess-deaths-were-associated-with-the-covid-19-pandemic-in-2020-and-2021. Accessed on May 13, 2022.
2. 2. Guan W-J, Liang W-H, Zhao Y, et al. Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis. Eur Respir J 2020;55(5).
3. 3. Levi M, Thachil J, Iba T, Levy JH. Coagulation abnormalities and thrombosis in patients with COVID-19. Lancet Haematol 2020;7(6):438–40.
4. 4. Sriram K, Insel PA. Inflammation and thrombosis in COVİD-19 pathophysiology: Proteinase-activated and purinergic receptors as drivers and candidate therapeutic targets. Physiol Rev 2021;101(2):545-67.
5. 5.Ünver Ulusoy T, Demirköse M, Bilek H. C. COVID-19'da temel laboratuvar parametrelerinin tanısal faydası ve prognostik değeri. Klimik Dergisi 2021;34(3):174-81.
6. 6. Algın A, Özdemir S. Evaluation of the predictability of platelet mass ındex for short-term mortality in patients with COVID 19: A retrospective cohort study. J Contemp Med 2021;11(5):728-33.
7. 7. Yaşar C. Türkiye’nin Muş ilindeki COVID-19 pnömonisi nedeniyle hastaneye yatırılan hastaların özellikleri ve klinik sonuçlarının değerlendirilmesi: ikinci basamak hastane deneyimi. İstanbul Tıp Fakültesi Dergisi 2021;84(2):149-57.
8. 8. T.C. Sağlık Bakanlığı. Antisitokin-antiinflamatuar tedaviler, koagülopati yönetimi. https://covid19.saglik.gov.tr/Eklenti/39296/0/covid-19rehberiantisitokin-antiinflamatuartedavilerkoagulopatiyonetimipdf.pdf. Accessed on May 13, 2022.

9. 9. Miller LE, Bhattacharyya R, Miller AL. Diabetes mellitus increases the risk of hospital mortality in patients with COVID-19: systematic review with meta-analysis. Medicine (Baltimore) 2020;99(40):e22439.
10. 10. WHO. COVID-19 dashboard with vaccination data. https://covid19.who.int/. Accessed on May 15, 2022.
11. 11 Zhou F, Yu T, Du R, et al. Clinical course and risk factors formortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 2020;395(10229):1054-62.
12. 12. Liu J, Liu Y, Xiang P, et al. Neutrophil-to-lymphocyte ratio predicts critical illness patients with 2019 coronavirus disease in the early stage. J Transl Med 2020;18(1):1–12.
13. 13. Yang A-P, Liu J-P, Tao W-Q, Li H-M. The diagnostic and predictive role of NLO, d-NLO and PLR in COVID-19 patients. Int Immunopharmacol 2020;84:106504.
14. 14. Henry BM, de Oliveira MHS, Benoit S, Plebani M, Lippi G. Hematologic, biochemical and immune biomarker abnormalities associated with severe illness and mortality in coronavirus disease 2019 (COVID-19): a meta-analysis. Clin Chem Lab Med 2020;58(7):1021-8.
15. 15. Sarkar S, Kannan S, Khanna P, Singh AK. Role of platelet-to-lymphocyte count ratio (PLR), as a prognostic indicator in COVID-19: a systematic reviewand meta-analysis. J Med Virol 2022;94(1):211-21.
16. 16. Simadibrata DM, Pandhita BAW, Ananta ME, Tango T. Platelet-to-lymphocyte ratio, a novel biomarker to predict the severity of COVID-19 patients: a systematic review and meta-analysis. Journal of the Intensive Care Society 2022;20:20-6.
17. 17. Mousavi SA, Rad S, Rostami T, et al. Hematologic predictors of mortality in hospitalized patients with COVID-19: a comparative study. Hematology 2020;25(1):383-8.
18. 18. Zhao Y, Yu C, Ni W, Shen H, Qiu M, Zhao Y. Peripheral blood inflammatory markers in predicting prognosis in patients with COVID-19; some differences with influenza A. J Clin Lab Anal 2021;35(1):e23657.
19. 19. Seyit M, Avci E, Nar R, et al. Neutrophil to lymphocyte ratio, lymphocyte to monocyte ratio and platelet to lymphocyte ratio to predict the severity of COVID-19. Am J Emerg Med 2021;40:110-4.
20. 20. Guan W-J, Ni Z-Y, Hu Y, et al. Clinical characteristics of coronavirus disease2019 in China. N Engl J Med 2020; 382(18):1708-20.
21. 21. Kwaan HC, Mazar AP. More on the Source of D-Dimer in COVID-19. Thrombosis and haemostasis 2022;122:158–9.
22. 22. Aziz M, Fatima R, Lee-Smith W, Assaly R. The association of low serum albumin level with severe COVID-19: a systematic review and meta-analysis. Critical care 2020.;24:255.
23. 23. 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.
24. 24. Lippi G, Plebani M. Procalcitonin in patients with severe coronavirus disease 2019 (COVID-19): a meta-analysis. Clinicachimicaacta; international journal of clinical chemistry 2020;505:190-1.
25. 25. Koyasu S, Moro K. Role of innate lymphocytes in infection and inflammation. Front Immunol 2012;3.
26. 26. Niu J, Sareli C, Mayer D, Visbal A, Sareli A. Lymphopenia as a predictor for adverse clinical outcomes in hospitalized patients with COVID-19: a single center retrospective study of 4485 Cases. J Clin Med 2022;11(3).
27. 27. Young B, Gleeson M, Cripps AW. C-reactive protein: a critical review. Pathology 1991;23(2):118-24.
28. 28. Keski H. Hematological and inflammatory parameters to predict the prognosis in COVID-19. Indian J Hematol Blood Transfus 2021;37(4):534-42.