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Laboratory Parameters of Hospitalized COVID 19 (+) Patients and Factors Affecting Prognosis: Cross-Sectional Study

Year 2023, Volume: 49 Issue: 1, 43 - 48, 09.06.2023
https://doi.org/10.32708/uutfd.1210484

Abstract

In our study, it was aimed to evaluate the effect of PCR (+) COVID-19 patients' laboratory findings and sociodemographic data evaluated at hospitalization on mortality. The data of 1250 PCR (+) COVID-19 patients hospitalized between January 1, 2020 and January 1, 2022 were evaluated retrospectively. Parametric data were analyzed with Student's t-test and nonparametric data were analyzed with Mann-Whitney U test. Chi-square test was used in the comparison of categorical variables, and correlation analysis was used to determine the relationship between the parameters. A total of 1250 patients, 631 women (50.5%) and 619 men (49.5%) were included in the study. The mean age of the patients was 63.7. 1250 of patient 79.5% recovered and were discharged. The mean oxygen saturation (PO2) measured from the fingertips by pulse oximetry at the time of hospitalization was 93.5, and it was determined that low PO2, age, number of additional diseases, being unvaccinated, and having symptoms of shortness of breath increased mortality (p<0.001). From laboratory parameters; Leukocyte (WBC), Neutrophil, Neutrophil/Lymphocyte Ratio, CRP (C reaktif protein), Glucose, Urea, Creatinin, AST (Aspartat Aminotransferaz), Ferritin, Fibrinogen, INR (International Normalized Ratio), D-Dimer and Protrombin Time values were positively negatively correlated and significant with mortality, Hb (Hemoglobin), Hct (Hematocrit) %, Plt (Platelet) 103/μL, Lymphocyte, Monocyte, Basophil, Eosinophil %, Ca (Calcium) mg/dL ıt was found to be positively correlated and significant with eosinophil, ALT (Aspartate amino transferase) and Ca (p<0.001). It was determined that neutrophil/lymphocyte ratio, PO2 value, being over 65 years of age, having comorbid diseases and being unvaccinated were significant predictive factors for prognosis among the laboratory parameters of PCR (+) COVID-19 patients at the time of first admission.

References

  • 1. Yadaw AS, Li YC, Bose S, Iyengar R, Bunyavanich S, Pandey G. Clinical features of COVID-19 mortality: development and validation of a clinical prediction model. The Lancet Digital Health. 2020;2(10),e516-e525.
  • 2. Karvar Ş, Gülbudak H, Görgülü Y, Ülger ST, Ersöz G, Çalıkoğlu M, et al. SARS-Cov-2 pozitif hastaların klinik olarak sınıflandırılması; laboratuvar ve radyolojik bulgularının değerlendirilmesi. Flora İnfeksiyon Hastalıkları ve Klinik Mikrobiyoloji Dergisi. 2021;26(3), 401-409.
  • 3. Xie Y, Wang Z, Liao H, Marley G, Wu D, Tang W. Epidemiologic, clinical, and laboratory findings of the COVID-19 in the current pandemic: Systematic review and meta-analysis. BMC Infect Dis. 2020;20(1):640.
  • 4. Xie J, Tong Z, Guan X, Du B, Qiu H, Slutsky AS. Critical care crisis and some recommendations during the COVID-19 epidemic in China. Intensive Care Med. 2020;46(5):837-40
  • 5. Wu X, Liu L, Jiao J, Yang L, Zhu B, et al. Characterisation of clinical, laboratory and imaging factors related to mild vs. severe Covid-19 infection: A systematic review and meta-analysis. Ann Med. 2020;52(7):334-44.
  • 6. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors for mortality of adult in patients with COVID-19 in Wuhan, China: A retrospective cohort study. Lancet. 2020;395(10229):1054-1062
  • 7. Grasselli G, Pesenti A, Cecconi M. Critical care utilization for the COVID-19 outbreak in Lombardy, Italy: early experience and fore cast during an emergency response. Jama. 2020; 323(16),1545-1546.
  • 8. Kanya P, Rattarittamrong E, Wongtagan, O, Rattanathammethee, T, Chai-Adisaksopha C, Tantiworawit A, et al. Platelet function tests and inflammatory markers for the differentiation of primary thrombocytosis and secondary thrombocytosis. Asian Pacific journal of cancer prevention: APJCP. 2019;20,7:2079.
  • 9. Keleş GT, Bozkurt İ. COVID-19 hastalığı tanı ve tedavisinde kullanılan laboratuvar testleri. Celal Bayar Üniversitesi Sağlık Bilimleri Enstitüsü Dergisi. 2021; 8.2:380-387.
  • 10. Coronavirus disease (COVID-19) Pandemic [İnternet]. WHO. Erişim Tarihi: (29 Ocak 2021). Erişim Adresi: Https://Www.Who.İnt/Emergencies/Diseases/Novel-Coronavirus-2019
  • 11. Du RH, Liang LR, Yang CQ, Wang W, Cao TZ, Li M, et al. Predictors of mortality for patients with COVID-19 pneumonia caused by SARS-CoV-2: a prospective cohort study. European Respiratory Journal. 2020;55,5.
  • 12. Lıang WH, Guan WJ, Li CC, et al. Clinical characteristics and outcomes of hospitalised patients with COVID-19 treated in Hubei (epicentre) and outside Hubei (non-epicentre): a nationwide analysis of China. European Respiratory Journal.2020;55,6.
  • 13. Meng Y, Wu P, Lu W, Liu K, Ma K, Huang L, et al. Sex-specific clinical characteristics and prognosis of coronavirus disease-19 infection in Wuhan, China: A retrospective study of 168 severe patients. PLoS pathogens. 2020;16,4: e1008520.
  • 14. Galloway JB, Norton S, Barker RD, Brookes A, Carey I, Clarke BD, et al. A clinical risk scoreto identify patients with COVID-19 at high risk of critical care admission or death: an observational cohort study. Journal of Infection. 2020;81,2:282-288.
  • 15. Mudatsir M, Fajar JK, Wulandari L, Soegiarto G, Ilmawan M, Purnamasari Y, et al. Predictors of COVID-19 severity: a systematic review and meta-analysis. F1000Research. 2020; 9.
  • 16. Bulut Y, Özyılmaz E. COVID-19 hastasının yoğun bakım yönetimi. Arşiv Kaynak Tarama Dergisi. 2020;29.Özel Sayı: 54-59.
  • 17. Göçmen G, Akbaş D.B, Köksal N, Bayrakdar S, Bölük, G, Dinçer, F, et al. demographic factors affecting the attitudes of inegöl state hospital healthcare workers towards COVID-19 vaccine: Cross-Sectional Study. Türkiye Klinikleri Tip Bilimleri Dergisi. 2022; DOI:10.5336/medsci.2022-88614.
  • 18. 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. The lancet. 2020;395.10223:507-513.
  • 19. Liu Y, Yang Y, Zhang C, Huang F, Wang F, Yuan J, et al. Clinical and biochemical indexes from 2019-nCoV infected patients linked to viral loads and lung in jury. Science China Life Sciences. 2020;63.3: 364-374.
  • 20. Shang W, Dong J, Ren Y, Tian M, Li W, Hu J, et al. The value of clinical parameters in predicting these verity of COVID-19. Journal of medical virology. 2020;92.10:2188-2192.
  • 21. Liu Y, Du X, Chen J, et al. Neutrophil-to-lymphocyteratio as an independent risk factor formortality in hospitalized patients with COVID-19.J Infect. 2020;81(1):e6-e12 (PubMed).
  • 22. Yang A-P, Liu J, Tao W, Li H-M, et al. The diagnostic and predictive role of NLR, d-NLR and PLR in COVID-19 patients. International immuno pharmacology. 2020; 84: 106504.
  • 23. Kernan KF, Carcillo JA. Hyperferritinemia and inflammation. International immunology. 2017; 29,9:401-409.
  • 24. Wu C, Chen X, Cai Y, Xia J, Zhou X, Xu S, et al. Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China. JAMA internal medicine. 2020;180.7:934-943.
  • 25. Cecconi M, Piovani D, Brunetta E, Aghemo A, Greco M, Ciccarelli M, et al. Early predictors of clinical deterioration in a cohort of 239 patients hospitalized for Covid-19 infection in Lombardy, Italy. Journal of clinical medicine. 2020;9,5:1548.
  • 26. Cheng L, Li H, Li L, Liu C, Yan S, Chen H, et al. Ferritin in the coronavirus disease 2019 (COVID-19): a systematic review and meta-analysis. Journal of clinical laboratory analysis. 2020;34.10:e23618.
  • 27. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors formortality of adult in patients with COVID-19 in Wuhan, China: a retrospective cohort study. The lancet. 2020;395. 10229: 1054-1062.
  • 28. Nozari A, Mukerji S, Vora M, Garcia A, Park A, Flores N, et al. Postintubation decline in oxygen saturation index predicts mortality in COVID-19: A retrospective pilot study. Critical Care Research and Practice. 2021; https://doi.org/10.1155/2021/6682944
  • 29. Göçmen H, Çoban H, Yıldız A, Ursavaş A, Coşkun F, Ediger D, et al. KOAH akut atakta serum CRP düzeyi ve hematolojik parametreler ile hastalık şiddeti arasında korelasyon var mı? Solunum Hastalıkları. 2007;18, 141-7.

Hastaneye Yatırılan COVID 19 (+) Hastaların Laboratuvar Parametreleri ve Prognoza Etki Eden Faktörler: Kesitsel Çalışma

Year 2023, Volume: 49 Issue: 1, 43 - 48, 09.06.2023
https://doi.org/10.32708/uutfd.1210484

Abstract

Çalışmamızda; PCR (+) COVID-19 hastaların yatışta değerlendirilen laboratuvar bulgularının ve sosyo-demografik verilerinin mortaliteye etkisinin değerlendirilmesi amaçlandı. 1 Ocak 2020- 1 Ocak 2022 tarihleri arasında hastanede yatan PCR (+) COVID-19 1250 hastanın verileri retrospektif olarak değerlendirildi. Parametrik veriler Student’s t-test ile nonparametrik veriler ise Mann-Whitney U testi ile analiz edildi. Kategorik değişkenlerin karşılaştırmasında ise Ki-kare testi kullanıldı ve parametrelerin birbirleri ile olan ilişkisinin saptanmasında korelasyon analizinden faydalanıldı. Çalışmaya 631’i kadın (%50,5) 619’u erkek (%49,5) toplam 1250 hasta dâhil edildi. Hastaların ortalama yaşı 63,7 idi. 1250 hastanın %79,5’i iyileşerek taburcu oldu. Hastaların yatış anında pulse oksimetre ile parmak ucundan ölçülen oksijen satürasyonu (PO2 ) ortalaması 93,5 şeklindeydi ve PO2’nin düşük olması, yaş, ek hastalık sayısı, aşısız olmak, nefes darlığı semptomunun olması mortaliteyi arttırdığı tespit edildi (p<0,001). Laboratuvar parametrelerinden; WBC (Beyaz küre) 103/μL, Nötrofil 103/μL, Nötrofil/Lenfosit Oranı, CRP (C reaktif protein), Glukoz mg/dL, Üre mg/dL, Kreatinin mg/dL, AST (Aspartat Aminotransferaz) IU/L, Ferritin ml/ng, Fibrinojen mg/dl, INR (International Normalized Ratio), D-Dimer mg/L ve Protrombin zamanı değerlerinin mortalite ile negatif yönde korele ve anlamlı olduğu, Hb (Hemoglobin) g/dL, Hct (Hematokrit) %, Plt (Platelet) 103/μL, Lenfosit % ve Lenfosit 103/μL, Monosit %, Bazofil %, Eozinofil %, Ca (Kalsiyum) mg/dL ile pozitif yönde korele ve anlamlı olduğu tespit edildi (p<0,001). PCR (+) COVID-19 hastaların ilk başvuru anında ki laboratuvar parametrelerinden nötrofil/lenfosit oranı, PO2 değeri, 65 yaş üstü olma ve komorbit hastalıklara sahip olma ve aşısız olmanın prognoz açısından anlamlı prediktif faktörler olduğu saptanmıştır.

References

  • 1. Yadaw AS, Li YC, Bose S, Iyengar R, Bunyavanich S, Pandey G. Clinical features of COVID-19 mortality: development and validation of a clinical prediction model. The Lancet Digital Health. 2020;2(10),e516-e525.
  • 2. Karvar Ş, Gülbudak H, Görgülü Y, Ülger ST, Ersöz G, Çalıkoğlu M, et al. SARS-Cov-2 pozitif hastaların klinik olarak sınıflandırılması; laboratuvar ve radyolojik bulgularının değerlendirilmesi. Flora İnfeksiyon Hastalıkları ve Klinik Mikrobiyoloji Dergisi. 2021;26(3), 401-409.
  • 3. Xie Y, Wang Z, Liao H, Marley G, Wu D, Tang W. Epidemiologic, clinical, and laboratory findings of the COVID-19 in the current pandemic: Systematic review and meta-analysis. BMC Infect Dis. 2020;20(1):640.
  • 4. Xie J, Tong Z, Guan X, Du B, Qiu H, Slutsky AS. Critical care crisis and some recommendations during the COVID-19 epidemic in China. Intensive Care Med. 2020;46(5):837-40
  • 5. Wu X, Liu L, Jiao J, Yang L, Zhu B, et al. Characterisation of clinical, laboratory and imaging factors related to mild vs. severe Covid-19 infection: A systematic review and meta-analysis. Ann Med. 2020;52(7):334-44.
  • 6. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors for mortality of adult in patients with COVID-19 in Wuhan, China: A retrospective cohort study. Lancet. 2020;395(10229):1054-1062
  • 7. Grasselli G, Pesenti A, Cecconi M. Critical care utilization for the COVID-19 outbreak in Lombardy, Italy: early experience and fore cast during an emergency response. Jama. 2020; 323(16),1545-1546.
  • 8. Kanya P, Rattarittamrong E, Wongtagan, O, Rattanathammethee, T, Chai-Adisaksopha C, Tantiworawit A, et al. Platelet function tests and inflammatory markers for the differentiation of primary thrombocytosis and secondary thrombocytosis. Asian Pacific journal of cancer prevention: APJCP. 2019;20,7:2079.
  • 9. Keleş GT, Bozkurt İ. COVID-19 hastalığı tanı ve tedavisinde kullanılan laboratuvar testleri. Celal Bayar Üniversitesi Sağlık Bilimleri Enstitüsü Dergisi. 2021; 8.2:380-387.
  • 10. Coronavirus disease (COVID-19) Pandemic [İnternet]. WHO. Erişim Tarihi: (29 Ocak 2021). Erişim Adresi: Https://Www.Who.İnt/Emergencies/Diseases/Novel-Coronavirus-2019
  • 11. Du RH, Liang LR, Yang CQ, Wang W, Cao TZ, Li M, et al. Predictors of mortality for patients with COVID-19 pneumonia caused by SARS-CoV-2: a prospective cohort study. European Respiratory Journal. 2020;55,5.
  • 12. Lıang WH, Guan WJ, Li CC, et al. Clinical characteristics and outcomes of hospitalised patients with COVID-19 treated in Hubei (epicentre) and outside Hubei (non-epicentre): a nationwide analysis of China. European Respiratory Journal.2020;55,6.
  • 13. Meng Y, Wu P, Lu W, Liu K, Ma K, Huang L, et al. Sex-specific clinical characteristics and prognosis of coronavirus disease-19 infection in Wuhan, China: A retrospective study of 168 severe patients. PLoS pathogens. 2020;16,4: e1008520.
  • 14. Galloway JB, Norton S, Barker RD, Brookes A, Carey I, Clarke BD, et al. A clinical risk scoreto identify patients with COVID-19 at high risk of critical care admission or death: an observational cohort study. Journal of Infection. 2020;81,2:282-288.
  • 15. Mudatsir M, Fajar JK, Wulandari L, Soegiarto G, Ilmawan M, Purnamasari Y, et al. Predictors of COVID-19 severity: a systematic review and meta-analysis. F1000Research. 2020; 9.
  • 16. Bulut Y, Özyılmaz E. COVID-19 hastasının yoğun bakım yönetimi. Arşiv Kaynak Tarama Dergisi. 2020;29.Özel Sayı: 54-59.
  • 17. Göçmen G, Akbaş D.B, Köksal N, Bayrakdar S, Bölük, G, Dinçer, F, et al. demographic factors affecting the attitudes of inegöl state hospital healthcare workers towards COVID-19 vaccine: Cross-Sectional Study. Türkiye Klinikleri Tip Bilimleri Dergisi. 2022; DOI:10.5336/medsci.2022-88614.
  • 18. 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. The lancet. 2020;395.10223:507-513.
  • 19. Liu Y, Yang Y, Zhang C, Huang F, Wang F, Yuan J, et al. Clinical and biochemical indexes from 2019-nCoV infected patients linked to viral loads and lung in jury. Science China Life Sciences. 2020;63.3: 364-374.
  • 20. Shang W, Dong J, Ren Y, Tian M, Li W, Hu J, et al. The value of clinical parameters in predicting these verity of COVID-19. Journal of medical virology. 2020;92.10:2188-2192.
  • 21. Liu Y, Du X, Chen J, et al. Neutrophil-to-lymphocyteratio as an independent risk factor formortality in hospitalized patients with COVID-19.J Infect. 2020;81(1):e6-e12 (PubMed).
  • 22. Yang A-P, Liu J, Tao W, Li H-M, et al. The diagnostic and predictive role of NLR, d-NLR and PLR in COVID-19 patients. International immuno pharmacology. 2020; 84: 106504.
  • 23. Kernan KF, Carcillo JA. Hyperferritinemia and inflammation. International immunology. 2017; 29,9:401-409.
  • 24. Wu C, Chen X, Cai Y, Xia J, Zhou X, Xu S, et al. Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China. JAMA internal medicine. 2020;180.7:934-943.
  • 25. Cecconi M, Piovani D, Brunetta E, Aghemo A, Greco M, Ciccarelli M, et al. Early predictors of clinical deterioration in a cohort of 239 patients hospitalized for Covid-19 infection in Lombardy, Italy. Journal of clinical medicine. 2020;9,5:1548.
  • 26. Cheng L, Li H, Li L, Liu C, Yan S, Chen H, et al. Ferritin in the coronavirus disease 2019 (COVID-19): a systematic review and meta-analysis. Journal of clinical laboratory analysis. 2020;34.10:e23618.
  • 27. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors formortality of adult in patients with COVID-19 in Wuhan, China: a retrospective cohort study. The lancet. 2020;395. 10229: 1054-1062.
  • 28. Nozari A, Mukerji S, Vora M, Garcia A, Park A, Flores N, et al. Postintubation decline in oxygen saturation index predicts mortality in COVID-19: A retrospective pilot study. Critical Care Research and Practice. 2021; https://doi.org/10.1155/2021/6682944
  • 29. Göçmen H, Çoban H, Yıldız A, Ursavaş A, Coşkun F, Ediger D, et al. KOAH akut atakta serum CRP düzeyi ve hematolojik parametreler ile hastalık şiddeti arasında korelasyon var mı? Solunum Hastalıkları. 2007;18, 141-7.
There are 29 citations in total.

Details

Primary Language Turkish
Subjects Respiratory Diseases, Infectious Diseases
Journal Section Research Article
Authors

Hayrettin Göçmen 0000-0001-8265-6860

Gülçin Bölük 0000-0003-3587-6910

Demet Büyük Akbaş 0000-0001-9593-4276

Nurhan Köksal 0000-0002-6285-6117

Serap Bayrakdar 0000-0002-6706-4725

Filiz Dinçer 0000-0002-3179-5702

Publication Date June 9, 2023
Acceptance Date March 3, 2023
Published in Issue Year 2023 Volume: 49 Issue: 1

Cite

APA Göçmen, H., Bölük, G., Büyük Akbaş, D., Köksal, N., et al. (2023). Hastaneye Yatırılan COVID 19 (+) Hastaların Laboratuvar Parametreleri ve Prognoza Etki Eden Faktörler: Kesitsel Çalışma. Uludağ Üniversitesi Tıp Fakültesi Dergisi, 49(1), 43-48. https://doi.org/10.32708/uutfd.1210484
AMA Göçmen H, Bölük G, Büyük Akbaş D, Köksal N, Bayrakdar S, Dinçer F. Hastaneye Yatırılan COVID 19 (+) Hastaların Laboratuvar Parametreleri ve Prognoza Etki Eden Faktörler: Kesitsel Çalışma. Uludağ Tıp Derg. June 2023;49(1):43-48. doi:10.32708/uutfd.1210484
Chicago Göçmen, Hayrettin, Gülçin Bölük, Demet Büyük Akbaş, Nurhan Köksal, Serap Bayrakdar, and Filiz Dinçer. “Hastaneye Yatırılan COVID 19 (+) Hastaların Laboratuvar Parametreleri Ve Prognoza Etki Eden Faktörler: Kesitsel Çalışma”. Uludağ Üniversitesi Tıp Fakültesi Dergisi 49, no. 1 (June 2023): 43-48. https://doi.org/10.32708/uutfd.1210484.
EndNote Göçmen H, Bölük G, Büyük Akbaş D, Köksal N, Bayrakdar S, Dinçer F (June 1, 2023) Hastaneye Yatırılan COVID 19 (+) Hastaların Laboratuvar Parametreleri ve Prognoza Etki Eden Faktörler: Kesitsel Çalışma. Uludağ Üniversitesi Tıp Fakültesi Dergisi 49 1 43–48.
IEEE H. Göçmen, G. Bölük, D. Büyük Akbaş, N. Köksal, S. Bayrakdar, and F. Dinçer, “Hastaneye Yatırılan COVID 19 (+) Hastaların Laboratuvar Parametreleri ve Prognoza Etki Eden Faktörler: Kesitsel Çalışma”, Uludağ Tıp Derg, vol. 49, no. 1, pp. 43–48, 2023, doi: 10.32708/uutfd.1210484.
ISNAD Göçmen, Hayrettin et al. “Hastaneye Yatırılan COVID 19 (+) Hastaların Laboratuvar Parametreleri Ve Prognoza Etki Eden Faktörler: Kesitsel Çalışma”. Uludağ Üniversitesi Tıp Fakültesi Dergisi 49/1 (June 2023), 43-48. https://doi.org/10.32708/uutfd.1210484.
JAMA Göçmen H, Bölük G, Büyük Akbaş D, Köksal N, Bayrakdar S, Dinçer F. Hastaneye Yatırılan COVID 19 (+) Hastaların Laboratuvar Parametreleri ve Prognoza Etki Eden Faktörler: Kesitsel Çalışma. Uludağ Tıp Derg. 2023;49:43–48.
MLA Göçmen, Hayrettin et al. “Hastaneye Yatırılan COVID 19 (+) Hastaların Laboratuvar Parametreleri Ve Prognoza Etki Eden Faktörler: Kesitsel Çalışma”. Uludağ Üniversitesi Tıp Fakültesi Dergisi, vol. 49, no. 1, 2023, pp. 43-48, doi:10.32708/uutfd.1210484.
Vancouver Göçmen H, Bölük G, Büyük Akbaş D, Köksal N, Bayrakdar S, Dinçer F. Hastaneye Yatırılan COVID 19 (+) Hastaların Laboratuvar Parametreleri ve Prognoza Etki Eden Faktörler: Kesitsel Çalışma. Uludağ Tıp Derg. 2023;49(1):43-8.

ISSN: 1300-414X, e-ISSN: 2645-9027

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