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

Yıl 2021, , 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

Öz

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.

Anahtar Kelimeler

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

Öz

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.

Anahtar Kelimeler

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

Kaynakça

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