TÜRKİYE’NİN MUŞ İLİNDEKİ COVID-19 PNÖMONİSİ NEDENİYLE HASTANEYE YATIRILAN HASTALARIN ÖZELLİKLERİ VE KLİNİK SONUÇLARININ DEĞERLENDİRİLMESİ: İKİNCİ BASAMAK HASTANE DENEYİMİ

Year 2021, Volume: 84 Issue: 2, 149 - 157, 25.04.2021

Aysun Benli , Emir Resuloğlu İlke Karadağlı Ayşe Nur Ceylan Mustafa Taner Yeler Gürkan Danışan , Cihan Büyüksütçü , Mehmet Balcı Şinasi Korkmaz Bilal Akdemir Adil Akın Yıldıran Cemal Yaşar

https://doi.org/10.26650/IUITFD.2021.812574

Abstract

Amaç: Bu çalışmada COVID-19 pnömonili hastalarının özelliklerini ve aynı zamanda hastalığın şiddetini etkileyen faktörleri belirlemeyi amaçladık. Gereç ve Yöntem: Çalışmamız tek merkezli, retrospektif bir çalışmadır. Çalışmaya 19 Mart - 19 Mayıs 2020 tarihlerinde hastanede yatan, 18 yaş ve üstü, COVID-19 pnömonili hasta dahil edildi. Hastaların demografik, klinik özellikleri ve şiddetli COVID-19 ile ilişkili faktörler analiz edildi. Şiddetli COVID-19’u öngören faktör leri değerlendirmek için çok değişkenli lojistik regresyon analizi yapıldı. Bulgular: COVID-19 pnömonisi olan toplam 228 hasta kaydedildi. Hastaların ortalama yaşı 51±19 yıldı, 136'sı (%59,6) erkekti. Hastaların %47,4'ünde en az bir komorbidite vardı. Yoğun bakım ünitesine (YBÜ) yatış ve ölüm sırasıyla 29 (%12,7) ve 17 (%7,5) hastada tespit edildi. Ağır olmayan hastalıkta ölüm tespit edilmedi. Başvuru anındaki dispne (OR:7,449 %95 CI 2,444-22,708, p<0,001), halsizlik (OR:5,968 %95 CI 2,155- 16,526, p:0,001), LDH yüksekliği (OR:4,288 %95 CI 1,109- 16,584, p:0,035) ve D-dimer yüksekliği (OR:3,242 %95 CI 1,106-9,501, p:0,032) şiddetli COVID-19 hastalığı için başlıca bağımsız öngörücü faktörlerdi. Sonuç: Dispne, halsizlik, LDH ve D-dimer seviyelerinin yükselmesi şiddetli COVID-19 ile yakından ilişkilidir. Tipik pnömoni belirtilerine ek olarak, ağır COVID-19 pnömonili hastaları erken evrede ayırt etmek için başvuru sırasındaki halsizlik, LDH ve D-dimer değerli göstergeler olarak kullanılabilir Başvuruda bu göstergeleri değerlendirmek COVID-19 ile hastaneye yatırılan hastalarda daha iyi sonuçlara yol açabilir.

Keywords

COVID-19, pnömoni, klinik özellikler, hastalık şiddeti, belirleyici faktörler

EVALUATION OF THE CHARACTERISTICS AND CLINICAL RESULTS OF THE PATIENTS HOSPITALIZED WITH COVID-19 PNEUMONIA IN THE PROVINCE OF MUS: A STATE HOSPITAL EXPERIENCE

Abstract

Objective: In this study, we aimed to determine the characteristics of COVID-19 pneumonia patients, and also predict factors affecting the severity of the disease. Methods: This is a retrospective, single-center study. Hospitalized COVID-19 pneumonia patients aged over 18 years between March 19th 2020, and May 19th 2020 were included in the study. The demographic, and clinical characteristics of patients, and factors associated with severe COVID-19 were analyzed. Multivariate logistic regression analysis was performed to evaluate the factors predicting the severity of COVID-19. Results: A total of 228 patients with COVID-19 pneumonia were recorded. The mean age of the patients was 51±19 years, and 136 (59.6%) were men. Of the patients, 47.4% had at least one comorbidity. Intensive care unit (ICU) admission, and mortality were detected in 29 (12.7%), and in 17 (7.5%) patients respectively. No mortality was detected in non-severe disease. Our results revealed that dyspnea (OR:7.449 95% CI 2.444-22.708, p<0.001), fatigue (OR:5.968 96% CI 2.155-16.526, p:0.001), elevation of LDH (OR: 4.288 95% CI 1.109-16.584, p:0.035) and elevation of D-dimer (OR:3.242 95% CI 1.106-9.501, p:0.032) levels at admission were major independent predicting factors for severe COVID-19 disease. Conclusion: Dyspnea, fatigue, elevation of LDH and D-dimer levels are closely related to severe disease in COVID-19. In addition to typical pneumonia signs, fatigue, LDH, and D-dimer can be used as valuable indicators at admission for distinguishing severe COVID-19 pneumonia patients in the early stage. Therefore, this may lead to improved outcomes in patients hospitalized with COVID-19.

Keywords

COVID-19, Turkey, pneumonia, clinical characteristics, severity, predicting factors

References

• 1. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020;395:497-506. [CrossRef]
• 2. World Health Organization (2020). WHO Director-General’s opening remarks at the media briefing on COVID-19 - 11 March 2020 (cited 2020 September 3). [CrossRef]
• 3. Fahrettin Koca. Turkey remains firm, calm as first coronavirus case confirmed. Daily Sabah (cited 2020 September 3). [CrossRef]
• 4. World Health Organization (2020). WHO Coronavirus Disease (COVID-19) Dashboard (cited 2020 October 12). [CrossRef]
• 5. T.C. Sağlık Bakanlığı (2020). Türkiye COVID-19 Hasta Tablosu (cited 2020 October 12). [CrossRef]
• 6. Wu Z, McGoogan JM. Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72314 Cases From the Chinese Center for Disease Control and Prevention. JAMA 2020;323(13):1239-42. [CrossRef]
• 7. Richardson S, Hirsch JS, Narasimhan M. Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area. JAMA 2020;323(20):2052-9.
• 8. T.C. Sağlık Bakanlığı, Halk Sağlığı Genel Müdürlüğü, COVID-19 (SARS-CoV-2 ENFEKSİYONU) GENEL BİLGİLER, EPİDEMİOLOJİ VE TANI, 29 June 2020 (cited 2020 July 3). Available from: URL: https://covid19.saglik. gov.tr/Eklenti/39060/0/covid19rehberigenelbilgiler epidemiyolojivetanipdf.pdf
• 9. World Health Organization (2020). Clinical management of COVID-19: Interim guidance (cited 2020 July 3). [CrossRef]
• 10. Simpson S, Kay FU, Abbara S, Bhalla S, Chung JH, Chung M, et al. Radiological Society of North America Expert Consensus Statement on Reporting Chest CT Findings Related to COVID-19. Endorsed by the Society of Thoracic Radiology, the American College of Radiology, and RSNA – Secondary Publication. J Thorac Imaging 2020;35(4):219-27. [CrossRef]
• 11. Zhang G, Hu C, Luo L, Fang F, Chen Y, Li J, et al. Clinical features and short-term outcomes of 221 patients with COVID-19 in Wuhan, China. J Clin Virol 2020 Apr 9. [CrossRef]
• 12. Güner R, Hasanoğlu İ, Kayaaslan B, Aypak A, Kaya Kalem A, Eser F, et al. COVID-19 experience of the major pandemic response center in the capital: Results of the pandemic’s first month in Turkey. Turk J Med Sci 2020;50(8):1801-9. [CrossRef]
• 13. Başaran NÇ, Uyaroğlu OA, Dizman GT, Özişik L, Şahin TK, Taş Z, et al. Outcome of Non-Critical COVID-19 Patients with Early Hospitalization and Early Antiviral Treatment Outside the ICU. Turk J Med Sci 2020 Jul 28. [CrossRef]
• 14. Guan W, Ni Z, Hu Y, Liang W, Ou C, He J, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med 2020 Feb 28. [CrossRef]
• 15. Zhang J, Wang X, Jia X, Li J, Hu K, Chen G, et al. Risk factors for disease severity, unimprovement, and mortality in COVID-19 patients in Wuhan, China. Clin Microbiol Infect 2020;26(6):767-72. [CrossRef]
• 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. [CrossRef]
• 17. Pollitt KJG, Peccia J, Ko AI, Kaminski N, Cruz CSD, Nebert DW, et al. COVID-19 vulnerability: the potential impact of genetic susceptibility and airborne transmission. Human Genomics 2020 May 12 [CrossRef]
• 18. Guan W, Liang W, Zhao Y, Liang H, Chen Z, Li Y, et al. Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis. Eur Respir J 2020 May 14 [CrossRef]
• 19. Xu PP, Tian RH, Luo S, Zu ZY, Fan B, Wang XM, et al. Risk factors for adverse clinical outcomes with COVID-19 in China: a multicenter, retrospective, observational study. Theranostics 2020;10(14): 6372-83. [CrossRef]
• 20. Cummings MJ, Baldwin MR, Abrams D, Jacobson SD, Meyer BJ, Balough EM, et al. Epidemiology, clinical course, and outcomes of critically ill adults with COVID-19 in New York City: a prospective cohort study. Lancet 2020;395:1763- 70. [CrossRef]
• 21. Karakoç ZÇ, Pınarbaşı-Şimşek B, Asil R, Dodurgalı R, Calışkaner F, Özsarı A, et al. First wave in COVID-19 pandemic: A single center experience. Klimik Dergisi 2020;33(3):223-9. [CrossRef]
• 22. Sümer Ş, Ural O, Aktuğ-Demir N, Çifci Ş, Türkseven B, Kılınçer A, et al. Clinical and laboratory characteristics of COVID-19 cases followed in Selçuk University Faculty of Medicine. Klimik Dergisi 2020;33(2):122-7. [CrossRef]
• 23. Gold JAW, Wong KK, Szablewski CM, Patel PR, Rossow J, Silva J, et al. Characteristics and Clinical Outcomes of Adult Patients Hospitalized with COVID-19 — Georgia, March 2020. MMWR Morb Mortal Wkly Rep 2020 May 8 [CrossRef]
• 24. Grasselli G, Zangrillo A, Zanella A, Antonelli M, Cabrini L, Castelli A, et al. Baseline Characteristics and Outcomes of 1591 Patients Infected With SARS-CoV-2 Admitted to ICUs of the Lombardy Region, Italy. JAMA 2020;323(16):1574-81. [CrossRef]
• 25. Özger HS, Yıldız PA, Gaygısız Ü, Dikmen AU, Gülmez ZD, Yıldız M, et al. The factors predicting pneumonia in COVID-19 patients: preliminary results of a university hospital in Turkey. Turk J Med Sci 2020;50(8):1810-6. [CrossRef]
• 26. Tomlins J, Hamilton F, Gunning S, Sheehy C, Moran E et al. Clinical features of 95 sequential hospitalised patients] with novel coronavirus 2019 disease (COVID-19), the first UK cohort. J Infect 2020 Aug 8 [CrossRef]
• 27. Nguyen Y, Corre F, Honsel V, Curac S, Zarrouk V, Fantin B, et al. Applicability of the CURB-65 pneumonia severity score for outpatient treatment of COVID-19. J Infect 2020 Sep [CrossRef]
• 28. Characteristics of SARS-CoV-2 patients dying in Italy Report based on available data on October 4th, 2020 (cited 2020 October 6). [CrossRef]
• 29. Henry BM, 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. [CrossRef]
• 30. Han Y, Zhang H, Mu S, Wei W, Jin C, Tong C, et al. Lactate dehydrogenase, an independent risk factor of severe COVID-19 patients: a retrospective and observational study. Aging 2020;12(12):11245-58. [CrossRef]
• 31. Henry BM, Aggarwal G, Wong J, Benoit S, Vikse J, Plebani M, et al. Lactate dehydrogenase levels predict coronavirus disease 2019 (COVID-19) severity and mortality: A pooled analysis. Am J Emerg Med 2020;38(9):1722-6. [CrossRef]
• 32. Wu M, Yao L, Wang Y, Zhu X, Wang X, Tang P, et al. Clinical evaluation of potential usefulness of serum lactate dehydrogenase (LDH) in 2019 novel coronavirus (COVID-19) pneumonia. Respir Res 2020 Jul 6 [CrossRef]
• 33. Li J, Chen Z, Nie Y, Ma Y, Guo Q, Dai X, et al. Identification of Symptoms Prognostic of COVID-19 Severity: Multivariate Data Analysis of a Case Series in Henan Province. J Med Internet Res 2020 Jun 30 [CrossRef]
• 34. Jain V, Yuan J. Predictive symptoms and comorbidities for severe COVID-19 and intensive care unit admission: a systematic review and meta-analysis. Int J Public Health 2020 May 25 [CrossRef]
• 35. Hu C, Su F, Dai J, Lu S, Wu L, Chen D, et al. Prediction Model of Severe Coronavirus Disease 2019 (COVID-19) Cases Shows the Leading Risk Factor of Hypocalcemia. Research Square 2020 Jul 14 [CrossRef]
• 36. Rod JE, Trespalacios OO, Ramirez JC. A brief-review of the risk factors for covid-19 severity. Rev Saude Publica. 2020;54:60. [CrossRef]
• 37. Yao Y, Cao J, Wang Q, Shi Q, Liu K, Luo Z, et al. D-dimer as a biomarker for disease severity and mortality in COVID-19 patients: A case control study. J Intensive Care 2020 Jul 10 [CrossRef]