Araştırma Makalesi
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Clinical and laboratory factors associated with hospitalization and mortality in the COVID-19 pandemic

Yıl 2023, Cilt: 8 Sayı: 3, 72 - 80, 29.05.2023

Dinçer Atila Vatan Barışık

https://doi.org/10.22391/fppc.1231219

Öz

Introduction: This study aimed to investigate the relationship between MPV and disease prognosis in patients with COVID-19, the chronic diseases that affect the prognosis of COVID-19, and the laboratory data that can help diagnose this disease and provide information about the course of the disease during the treatment process.
Methods: The study was conducted in a cross-sectional format. All participants gave written, informed consent to participate. A questionnaire consisting of two parts, including categorical (socio-demographic) data and laboratory data, was applied to people who had COVID-19 who applied to the internal medicine outpatient clinic of the hospital. The Pearson chi-squared test and Fisher exact test were used for comparing categorical variables. The Mann-Whitney U test, or Kruskal-Wallis test with Bonferroni post hoc comparisons, was used to compare numerical variables between the groups. All analyses were performed using the SPSS 25.0 (SPSS Inc., Chicago, IL, ‎USA) software package.
Results: The participants' mean (±SD) age was 40.8±13.7 years (median: 40, range: 18 – 72). Almost half of the participants (48.0%, n=98) were male, the majority (76.0%, n=155) were married, and 24.0% (n=49) were single. Of the 204 patients, 28 (13.7%) were hospitalized, and five died (2.5%). Of the five patients who died, three had chronic lung disease, one had diabetes and chronic lung disease, and one had no chronic disease.
Conclusion: Older age and the presence of chronic diseases are important factors affecting hospitalization in patients with COVID-19. LDH, CRP, and ferritin levels were high, and the mean platelet volume levels were significantly higher in hospitalized patients.
Keywords: COVID -19, pandemics, prognosis of COVID -19

Anahtar Kelimeler

COVID-19 pandemics prognosis of COVID -19

Kaynakça

  • 1. Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, et al. Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. JAMA 2020;323:1061-9. https://doi.org/10.1001/jama.2020.1585
  • 2. Aslan, R. Endemic diseases in history and today and COVID-19. Ayrinti J. 2020;8:38-44.
  • 3. Rothan HA, Byrareddy SN. The epidemiology and pathogenesis of coronavirus disease (COVID-19) outbreak. J Auto Immun. 2020;109:102433. https://doi.org/10.1016/j.jaut.2020.102433
  • 4. Tekin S, Demirturk N. Covid 19: Risk factors and scoring that increase the disease. Klimik J 2021;34:150-5.
  • 5. Giuseppe L, Brandon MH, Emmanuel JF. Mean platelet volume predicts severe COVID-19 illness. Semin Tromb Hemost 2021;47:456-9. https://doi.org/10.1055/s-0041-1727283
  • 6. Von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. PLoS Med 2007;4:1623–7. https://doi.org/10.1371/journal pmed.0040296
  • 7. Reese H, Iuliano AD, Patel NN, Garg S, Kim L, Silk BJ, et al. Estimated incidence of coronavirus disease 2019 (COVID-19) illness and hospitalization-United States, February-September 2020. Clin Infect Dis an Off Publ Infect Dis Soc Am 2021;72:e1010–7. https://doi.org/10.1093/cid/ciaa1780
  • 8. Lenth R. Java applets for power and sample size [Computer software] [Internet]. Available from: https://homepage.divms.uiowa.edu/~rlenth/Power/ (Access Date: May 24, 2023)
  • 9. Gandhi RT, Lynch JB, Del Rio C. Mild or moderate Covid-19. N Engl J Med 2020;383:1757-66. https://doi.org/10.1056/NEJMcp2009249
  • 10. Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med 2020;382:1708-20. https://doi.org/10.1056/NEJMoa2002032
  • 11. Xu J, Xiao W, Liang X, Shi L, Zhang P, Wang Y, et al. A meta-analysis on the risk factors adjusted association between cardiovascular disease and COVID-19 severity. BNC Public Health 2021;21(1):1533. https://doi.org/10.1186/s12889-021-11051-w
  • 12. World Health Organization. Noncommunicable diseases Available from: https://www.who.int/newsroom/fact-sheets/detail/noncommunicable-diseases. (Access Date: May 24, 2023)
  • 13. Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel corona virus pneumonia in Wuhan, China: a descriptive study. Lancet 2020;395:507-13. https://doi.org/10.1016/S0140-6736(20)30211-7
  • 14. Khan IH, Zahra SA, Zaim S, Harky A. At the heart of COVID-19. J Card Surg 2020;35:1287–94. https://doi.org/10.1111/jocs.14596
  • 15. Richardson S, Hirsch JS, Narasimhan M, Crawford JM, Mc-Ginn T, Davidson KW, et al. Presenting characteristics, comorbidities and outcomes among 5700 patients hospitalized with COVID-19 in the New York city area. JAMA 2020;323:2052-8. https://doi.org/10.1001/jama.2020.6775
  • 16. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 2020;395:1054-62. https://doi.org/10.1016/S0140-6736(20)30566-3
  • 17. Xie J, Tong Z, Guan X, Du B, Qiu H. Clinical characteristics of patients who died of coronavirus disease 2019 in China. JAMA Network Open 2020;3:e205619-e. https://doi.org/10.1001/jamanetworkopen.2020.5619
  • 18. Li B, Yang J, Zhao F, Zhi L, Wang X, Liu L, et al. Prevalence and impact of cardiovascular metabolic diseases on COVID-19 in China. Clin Res Cardiol 2020;109:531-8. https://doi.org/10.1007/s00392-020-01626-9
  • 19. Kornum JB, Thomsen RW, Riis A, Lervang HH, Schonheyder HC, Sorensen HT. Type 2 diabetes and pneumonia outcomes: A population-based cohort study. Diabetes Care 2007;30:2251-7. https://doi.org/10.2337/dc06-2417
  • 20. Singh AK, Gupta R, Ghosh A, Misra A. Diabetes in COVID-19: Prevalence, pathophysiology, prognosis and practical considerations. Diabetes Metab Syndr 2020;14:303-10. https://doi.org/10.1016/j.dsx.2020.04.004
  • 21. Yan Y, Yang Y, Wang F, Ren H, Zhang S, Shi X, et al. Clinical characteristics and outcomes of patients with severe covid-19 with diabetes. BMJ Open Diabetes Res Care 2020;8:e001343. https://doi.org/10.1136/bmjdrc-2020-001343
  • 22. Bhutani M, Hernandez P, Bourbeau J, Dechman G, Penz E, Aceron R, et al. Key highlights of the Canadian Thoracic Society’s position statement on the optimization of chronic obstructive pulmonary disease management during the COVID-19 pandemic. Chest 2020;158:869-72. https://doi.org/10.1016/j.chest.2020.05.530
  • 23. Fu L, Wang B, Yuan T, Chen X, Ao Y, Fitzpatrick T, et al. Clinical characteristics of coronavirus disease 2019 (COVID-19) in China: a systematic review and meta-analysis. J Infect 2020:S0163-4453:30170-5. https://doi.org/10.1016/j.jinf.2020.03.041
  • 24. Zhao Q, Meng M, Kumar R, Wu Y, Huang J, Lian N, et al. The impact of COPD and smoking history on the severity of Covid-19: a systemic review and meta-analysis. J Med Virol 2020; 92:1915-21. https://doi.org/10.1002/jmy.25889
  • 25. Ozer K.B, Cimenoglu B, Ozdemir A, Buz M, Koyuncu K, Geyik FD, et al. The effect of radiological and laboratory parameters on prognosis in COVID-19 Disease. South Clin Ist Euras 2020:31:203-5. https://doi.org/10.14744/scie.2020.87609
  • 26. Bohn MK, Lippi G, Horvath A, Sethi S, Koch D, Ferrari M, et al. Molecular, serological, and biochemical diagnosis and monitoring of COVID-19: IFCC task force evaluation of the latest evidence, Clin Chem Lab Med 2020;58:1037-52. https://doi.org/10.1515/cclm-2020-0722
  • 27. Wang T, Du Z, Zhu F, Cao Z, An Y, Gao Y, et al. Comorbidities and multi-organ injuries in the treatment of COVID-19. Lancet 2020;395: e52. https://doi.org/10.1016/S0140-6736(20)30558-4
  • 28. Ferrari D, Motta A, Strollo M, Banfi G, Locatelli M. Routine blood tests as a potential diagnostic tool for COVID-19. Clin Chem Lab Med 2020;58:1095-9. https://doi.org/10.1515/cclm-2020-0398
  • 29. Li Q, Ding X, Xia G, Chen HG, Chen F, Geng Z, et al. Eosinopenia and elevated C-reactive protein facilitate triage of COVID-19 patients in fever clinic: A retrospective case-control study. EClinicalMedicine 2020;23:100375. https://doi.org/10.1016/j.eclinm.2020.100375
  • 30. Qin C, Zhou L, Hu Z, Zhang S, Yang S, Tao Y, et al. Dysregulation of immune response in patients with Coronavirus 2019 (COVID-19) in Wuhan, China. Clin Infect Dis 2020;71:762-8. https://doi.org/10.1093/cid/ciaa248
  • 31. Chu H, Zhou J, Wong BH, Li C, Chan JF, Cheng ZS, et al. Middle East respiratory syndrome coronavirus efficiently infects human primary T lymphocytes and activates the extrinsic and intrinsic apoptosis pathways. J Infect Dis 2016;213:904-14. https://doi.org/10.1093/infdis/jiv380
  • 32. Lippi G, Plebani M. The critical role of laboratory medicine during corona virus disease 2019 (COVID-19) and other viral out breaks. Clin Chem Lab Med 2020;58:1063-7. https://doi.org/10.1515/cclm-2020-0240
  • 33. Sertbas Y, Sertbas M, Okuroglu N, Ozturk MA, Abacar KY, Ozdemir A. Mean platelet volume changes before and after glycated hemoglobin (HbA1c) improvement in a large study population. Arch Med Sci 2017;13(4):711–5. https://doi.org/10.5114/aoms.2016.61900
  • 34. Sertbas M, Dagci S, Kizilay V, Yazici Z, Elci E, Guduk O, et al. Mean platelet volume as an early predictor for the complication of coronavirus disease 19. Haydarpasa Numune Med J 2021;61:177–6. https://doi.org/10.14744/hnhj.2020.90582
  • 35. Ouyang SM, Zhu HQ, Xie YN, Zou ZS, Zuo HM, Rao YW, et al. Temporal changes in laboratory markers of survivors and non-survivors of adult in patients with COVID-19. BMC Infect Dis 2020;20:952. https://doi.org/10.1186/s12879-020-05678-0
  • 36. Bohn M.K, Lippi G, Horvath A, Sethi S, Koch D, Ferrari M, et al., Molecular, serological, and biochemical diagnosis and monitoring of COVID-19: IFCC task force evaluation of the latest evidence, Clin Chem Lab Med 2020;58:1037–52. https://doi.org/10.1515/cclm-2020-0722
  • 37. Guo T, Fan Y, Chen M, Wu X, Zhang L, He T, et al. Cardiovascular implications of fatal outcomes of patients with coronavirus disease 2019 (COVID-19). JAMA Cardiology 2020;5: 811-8. https://doi.org/10.1001/jamacardio.2020.1017
  • 38. Ruan Q, Yang K, Wang W, Jiang L, Song J. Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China. Intensive Care Med 2020;46:846-8. https://doi.org/10.1007/s00134-020-05991-x
  • 39. Sahin L, Gur A. The relationship between pro calcitonin, D-dimer, ferritin, troponin, and lactate levels with COVID-19. Acta Medica Alanya 2021;5:30-5. https://doi.org/10.30565/medalanya.808806
  • 40. Saygideger Y, Candevir A, Ozkan H, Komur S, Demir MS. The relationship of Eosinophil / Lymphocyte and D-Dimer / Fibrinogen ratios with the course of the disease in Covid-19 patients. Mersin Univ J Health Sci 2021;14:307-19. https://doi.org/10.26559/mersinsbd.952298

COVID-19 pandemisinde hastaneye yatış ve mortalite ile ilişkili klinik ve laboratuvar faktörleri

Yıl 2023, Cilt: 8 Sayı: 3, 72 - 80, 29.05.2023

Dinçer Atila Vatan Barışık

https://doi.org/10.22391/fppc.1231219

Öz

Giriş: Bu çalışmada COVID-19 hastalarında MPV ile hastalık prognozu arasındaki ilişkinin araştırılması ve COVID-19'un prognozunu etkileyen kronik hastalıklar ile bu hastalığın teşhisine yardımcı olabilecek ve tedavi sürecinde hastalığın seyri hakkında bilgi sağlayabilecek laboratuvar verilerinin araştırılması amaçlandı.
Yöntem: Çalışma kesitsel bir düzlemde gerçekleştirilmiştir. Tüm katılımcılar yazılı bireysel bilgilendirilmiş onay verdi. Hastanenin dahiliye polikliniğine başvuran COVID-19 tanılı kişilere kategorik (sosyo-demografik) veriler ve laboratuvar verileri olmak üzere iki bölümden oluşan anket uygulandı. Kategorik değişkenlerin karşılaştırılmasında Pearson ki-kare testi ve Fisher Exact testi kullanıldı. Gruplar arasında sayısal değişkenleri karşılaştırmak için Mann-Whitney U testi veya Bonferroni post hoc karşılaştırmalı Kruskal-Wallis testi kullanıldı. Tüm analizler SPSS 25.0 (SPSS Inc., Chicago, IL, ABD) paket programı kullanılarak yapılmıştır.
Bulgular: Katılımcıların ortalama (± SS) yaşı 40,8±13,7 idi (medyan: 40, aralık:18-72). Yaklaşık yarısı (%48,0, n=98) erkek, çoğunluğu (%76,0, n=155) evli ve %24,0' ı (n=49) bekardı. 204 hastanın 28' I (%13,7) hastaneye yatırıldı ve beşi öldü (%2,5). Ölen 5 kişiden 3'ünde kronik akciğer hastalığı, 1'inde diyabet ve kronik akciğer hastalığı saptanırken, 1'inde ise kronik hastalık saptanmadı.
Sonuç: Yaşlılık ve kronik hastalıkların varlığı COVID-19 hastalarında hastaneye yatışı etkileyen önemli faktörlerdir. LDH, CRP, ferritin ve bunlara ek olarak hastaneye yatanlarda ortalama trombosit hacim düzeyleri anlamlı olarak yüksekti.
Anahtar kelimeler: COVID -19, pandemi, COVID-19 prognozu

Anahtar Kelimeler

COVID-19 pandemi COVID-19 prognozu

Kaynakça

  • 1. Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, et al. Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. JAMA 2020;323:1061-9. https://doi.org/10.1001/jama.2020.1585
  • 2. Aslan, R. Endemic diseases in history and today and COVID-19. Ayrinti J. 2020;8:38-44.
  • 3. Rothan HA, Byrareddy SN. The epidemiology and pathogenesis of coronavirus disease (COVID-19) outbreak. J Auto Immun. 2020;109:102433. https://doi.org/10.1016/j.jaut.2020.102433
  • 4. Tekin S, Demirturk N. Covid 19: Risk factors and scoring that increase the disease. Klimik J 2021;34:150-5.
  • 5. Giuseppe L, Brandon MH, Emmanuel JF. Mean platelet volume predicts severe COVID-19 illness. Semin Tromb Hemost 2021;47:456-9. https://doi.org/10.1055/s-0041-1727283
  • 6. Von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. PLoS Med 2007;4:1623–7. https://doi.org/10.1371/journal pmed.0040296
  • 7. Reese H, Iuliano AD, Patel NN, Garg S, Kim L, Silk BJ, et al. Estimated incidence of coronavirus disease 2019 (COVID-19) illness and hospitalization-United States, February-September 2020. Clin Infect Dis an Off Publ Infect Dis Soc Am 2021;72:e1010–7. https://doi.org/10.1093/cid/ciaa1780
  • 8. Lenth R. Java applets for power and sample size [Computer software] [Internet]. Available from: https://homepage.divms.uiowa.edu/~rlenth/Power/ (Access Date: May 24, 2023)
  • 9. Gandhi RT, Lynch JB, Del Rio C. Mild or moderate Covid-19. N Engl J Med 2020;383:1757-66. https://doi.org/10.1056/NEJMcp2009249
  • 10. Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med 2020;382:1708-20. https://doi.org/10.1056/NEJMoa2002032
  • 11. Xu J, Xiao W, Liang X, Shi L, Zhang P, Wang Y, et al. A meta-analysis on the risk factors adjusted association between cardiovascular disease and COVID-19 severity. BNC Public Health 2021;21(1):1533. https://doi.org/10.1186/s12889-021-11051-w
  • 12. World Health Organization. Noncommunicable diseases Available from: https://www.who.int/newsroom/fact-sheets/detail/noncommunicable-diseases. (Access Date: May 24, 2023)
  • 13. Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel corona virus pneumonia in Wuhan, China: a descriptive study. Lancet 2020;395:507-13. https://doi.org/10.1016/S0140-6736(20)30211-7
  • 14. Khan IH, Zahra SA, Zaim S, Harky A. At the heart of COVID-19. J Card Surg 2020;35:1287–94. https://doi.org/10.1111/jocs.14596
  • 15. Richardson S, Hirsch JS, Narasimhan M, Crawford JM, Mc-Ginn T, Davidson KW, et al. Presenting characteristics, comorbidities and outcomes among 5700 patients hospitalized with COVID-19 in the New York city area. JAMA 2020;323:2052-8. https://doi.org/10.1001/jama.2020.6775
  • 16. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 2020;395:1054-62. https://doi.org/10.1016/S0140-6736(20)30566-3
  • 17. Xie J, Tong Z, Guan X, Du B, Qiu H. Clinical characteristics of patients who died of coronavirus disease 2019 in China. JAMA Network Open 2020;3:e205619-e. https://doi.org/10.1001/jamanetworkopen.2020.5619
  • 18. Li B, Yang J, Zhao F, Zhi L, Wang X, Liu L, et al. Prevalence and impact of cardiovascular metabolic diseases on COVID-19 in China. Clin Res Cardiol 2020;109:531-8. https://doi.org/10.1007/s00392-020-01626-9
  • 19. Kornum JB, Thomsen RW, Riis A, Lervang HH, Schonheyder HC, Sorensen HT. Type 2 diabetes and pneumonia outcomes: A population-based cohort study. Diabetes Care 2007;30:2251-7. https://doi.org/10.2337/dc06-2417
  • 20. Singh AK, Gupta R, Ghosh A, Misra A. Diabetes in COVID-19: Prevalence, pathophysiology, prognosis and practical considerations. Diabetes Metab Syndr 2020;14:303-10. https://doi.org/10.1016/j.dsx.2020.04.004
  • 21. Yan Y, Yang Y, Wang F, Ren H, Zhang S, Shi X, et al. Clinical characteristics and outcomes of patients with severe covid-19 with diabetes. BMJ Open Diabetes Res Care 2020;8:e001343. https://doi.org/10.1136/bmjdrc-2020-001343
  • 22. Bhutani M, Hernandez P, Bourbeau J, Dechman G, Penz E, Aceron R, et al. Key highlights of the Canadian Thoracic Society’s position statement on the optimization of chronic obstructive pulmonary disease management during the COVID-19 pandemic. Chest 2020;158:869-72. https://doi.org/10.1016/j.chest.2020.05.530
  • 23. Fu L, Wang B, Yuan T, Chen X, Ao Y, Fitzpatrick T, et al. Clinical characteristics of coronavirus disease 2019 (COVID-19) in China: a systematic review and meta-analysis. J Infect 2020:S0163-4453:30170-5. https://doi.org/10.1016/j.jinf.2020.03.041
  • 24. Zhao Q, Meng M, Kumar R, Wu Y, Huang J, Lian N, et al. The impact of COPD and smoking history on the severity of Covid-19: a systemic review and meta-analysis. J Med Virol 2020; 92:1915-21. https://doi.org/10.1002/jmy.25889
  • 25. Ozer K.B, Cimenoglu B, Ozdemir A, Buz M, Koyuncu K, Geyik FD, et al. The effect of radiological and laboratory parameters on prognosis in COVID-19 Disease. South Clin Ist Euras 2020:31:203-5. https://doi.org/10.14744/scie.2020.87609
  • 26. Bohn MK, Lippi G, Horvath A, Sethi S, Koch D, Ferrari M, et al. Molecular, serological, and biochemical diagnosis and monitoring of COVID-19: IFCC task force evaluation of the latest evidence, Clin Chem Lab Med 2020;58:1037-52. https://doi.org/10.1515/cclm-2020-0722
  • 27. Wang T, Du Z, Zhu F, Cao Z, An Y, Gao Y, et al. Comorbidities and multi-organ injuries in the treatment of COVID-19. Lancet 2020;395: e52. https://doi.org/10.1016/S0140-6736(20)30558-4
  • 28. Ferrari D, Motta A, Strollo M, Banfi G, Locatelli M. Routine blood tests as a potential diagnostic tool for COVID-19. Clin Chem Lab Med 2020;58:1095-9. https://doi.org/10.1515/cclm-2020-0398
  • 29. Li Q, Ding X, Xia G, Chen HG, Chen F, Geng Z, et al. Eosinopenia and elevated C-reactive protein facilitate triage of COVID-19 patients in fever clinic: A retrospective case-control study. EClinicalMedicine 2020;23:100375. https://doi.org/10.1016/j.eclinm.2020.100375
  • 30. Qin C, Zhou L, Hu Z, Zhang S, Yang S, Tao Y, et al. Dysregulation of immune response in patients with Coronavirus 2019 (COVID-19) in Wuhan, China. Clin Infect Dis 2020;71:762-8. https://doi.org/10.1093/cid/ciaa248
  • 31. Chu H, Zhou J, Wong BH, Li C, Chan JF, Cheng ZS, et al. Middle East respiratory syndrome coronavirus efficiently infects human primary T lymphocytes and activates the extrinsic and intrinsic apoptosis pathways. J Infect Dis 2016;213:904-14. https://doi.org/10.1093/infdis/jiv380
  • 32. Lippi G, Plebani M. The critical role of laboratory medicine during corona virus disease 2019 (COVID-19) and other viral out breaks. Clin Chem Lab Med 2020;58:1063-7. https://doi.org/10.1515/cclm-2020-0240
  • 33. Sertbas Y, Sertbas M, Okuroglu N, Ozturk MA, Abacar KY, Ozdemir A. Mean platelet volume changes before and after glycated hemoglobin (HbA1c) improvement in a large study population. Arch Med Sci 2017;13(4):711–5. https://doi.org/10.5114/aoms.2016.61900
  • 34. Sertbas M, Dagci S, Kizilay V, Yazici Z, Elci E, Guduk O, et al. Mean platelet volume as an early predictor for the complication of coronavirus disease 19. Haydarpasa Numune Med J 2021;61:177–6. https://doi.org/10.14744/hnhj.2020.90582
  • 35. Ouyang SM, Zhu HQ, Xie YN, Zou ZS, Zuo HM, Rao YW, et al. Temporal changes in laboratory markers of survivors and non-survivors of adult in patients with COVID-19. BMC Infect Dis 2020;20:952. https://doi.org/10.1186/s12879-020-05678-0
  • 36. Bohn M.K, Lippi G, Horvath A, Sethi S, Koch D, Ferrari M, et al., Molecular, serological, and biochemical diagnosis and monitoring of COVID-19: IFCC task force evaluation of the latest evidence, Clin Chem Lab Med 2020;58:1037–52. https://doi.org/10.1515/cclm-2020-0722
  • 37. Guo T, Fan Y, Chen M, Wu X, Zhang L, He T, et al. Cardiovascular implications of fatal outcomes of patients with coronavirus disease 2019 (COVID-19). JAMA Cardiology 2020;5: 811-8. https://doi.org/10.1001/jamacardio.2020.1017
  • 38. Ruan Q, Yang K, Wang W, Jiang L, Song J. Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China. Intensive Care Med 2020;46:846-8. https://doi.org/10.1007/s00134-020-05991-x
  • 39. Sahin L, Gur A. The relationship between pro calcitonin, D-dimer, ferritin, troponin, and lactate levels with COVID-19. Acta Medica Alanya 2021;5:30-5. https://doi.org/10.30565/medalanya.808806
  • 40. Saygideger Y, Candevir A, Ozkan H, Komur S, Demir MS. The relationship of Eosinophil / Lymphocyte and D-Dimer / Fibrinogen ratios with the course of the disease in Covid-19 patients. Mersin Univ J Health Sci 2021;14:307-19. https://doi.org/10.26559/mersinsbd.952298
Toplam 40 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular İç Hastalıkları
Bölüm Araştırma Makalesi (Original Article)
Yazarlar

Dinçer Atila 0000-0003-0835-2740

Vatan Barışık 0000-0003-1100-6961

Yayımlanma Tarihi 29 Mayıs 2023
Gönderilme Tarihi 8 Ocak 2023
Kabul Tarihi 24 Nisan 2023
Yayımlandığı Sayı Yıl 2023Cilt: 8 Sayı: 3

Kaynak Göster

APA Atila, D., & Barışık, V. (2023). Clinical and laboratory factors associated with hospitalization and mortality in the COVID-19 pandemic. Family Practice and Palliative Care, 8(3), 72-80. https://doi.org/10.22391/fppc.1231219
AMA Atila D, Barışık V. Clinical and laboratory factors associated with hospitalization and mortality in the COVID-19 pandemic. Fam Pract Palliat Care. Mayıs 2023;8(3):72-80. doi:10.22391/fppc.1231219
Chicago Atila, Dinçer, ve Vatan Barışık. “Clinical and Laboratory Factors Associated With Hospitalization and Mortality in the COVID-19 Pandemic”. Family Practice and Palliative Care 8, sy. 3 (Mayıs 2023): 72-80. https://doi.org/10.22391/fppc.1231219.
EndNote Atila D, Barışık V (01 Mayıs 2023) Clinical and laboratory factors associated with hospitalization and mortality in the COVID-19 pandemic. Family Practice and Palliative Care 8 3 72–80.
IEEE D. Atila ve V. Barışık, “Clinical and laboratory factors associated with hospitalization and mortality in the COVID-19 pandemic”, Fam Pract Palliat Care, c. 8, sy. 3, ss. 72–80, 2023, doi: 10.22391/fppc.1231219.
ISNAD Atila, Dinçer - Barışık, Vatan. “Clinical and Laboratory Factors Associated With Hospitalization and Mortality in the COVID-19 Pandemic”. Family Practice and Palliative Care 8/3 (Mayıs 2023), 72-80. https://doi.org/10.22391/fppc.1231219.
JAMA Atila D, Barışık V. Clinical and laboratory factors associated with hospitalization and mortality in the COVID-19 pandemic. Fam Pract Palliat Care. 2023;8:72–80.
MLA Atila, Dinçer ve Vatan Barışık. “Clinical and Laboratory Factors Associated With Hospitalization and Mortality in the COVID-19 Pandemic”. Family Practice and Palliative Care, c. 8, sy. 3, 2023, ss. 72-80, doi:10.22391/fppc.1231219.
Vancouver Atila D, Barışık V. Clinical and laboratory factors associated with hospitalization and mortality in the COVID-19 pandemic. Fam Pract Palliat Care. 2023;8(3):72-80.
 Kapak Resmi İndir

Family Practice and Palliative Care      ISSN 2458-8865       E-ISSN 2459-1505