COVID-GRAM risk score used in determining the critically ill patients in the Covid 19 patients validation in Turkey populations.

Yıl 2021, Cilt: 7 Sayı: 3, 35 - 51, 30.12.2021

Hasan Burak Toprak , Gökhan Ersunan , Özlem Bilir , Mehmet Altuntaş , Özcan Yavaşi , Gürkan Altuntaş , Ali Çelik

Öz

Objective: A pathogen called novel coronavirus was identified as the cause of pneumonia in the city of Wuhan, Hubei province of China. It spread rapidly and caused an epidemic in China and a pandemic in the world in the ongoing process. In February 2020, the World Health Organization (WHO) named this disease Covid-19 disease, meaning 2019 coronavirus disease.To validate the “COVID-GRAM” critical illness risk scoring system used to detect critically ill patients in hospitalized Covid-19 patients in the Turkish population.
Materials and Methods: This research is a retrospective analysis of computer-based patient records of patients who were admitted to the Emergency Service of Recep Tayyip Erdoğan University Training and Research Hospital between 01.08.2020 and 31.01.2021 were hospitalized due to Covid-19 and was made with with the approval of the ethics committee (2021/51).Patients' age, gender, vital values at admission, complaints at admission, chest X-ray, laboratory tests, comorbid diseases and outcome patterns were used in the study.
Results: This study was conducted by retrospectively examining 299 Covid-19 patients, 164 of them (54.8 %) and 135 (45.2 %) of women. The median age of the patients was 69 (22-96). Chest X-ray (OR:9.72, 95% CI: 4.06 – 23.3), age (OR:1.05, 95% CI: 1.03 – 1.08), dyspnea (OR:10.3, 95% CI: 5.03 – 21.0) ), altered consciousness (OR:77.91, 95% CI: 1.03 - 5870.48), and the number of comorbidities (OR: 1.64, 95% CI: 1.32 - 2.05) found in the COVID-GRAM risk scoring, between critical and non-critical patient groups appeared as independent predictors. Lactate dehydrogenase (OR:1.002, 95% CI: 1.001 - 1.004) and direct bilirubin (OR: 1.04, 95% CI: 1.01 - 1.07) were similarly independent predictors of laboratory parameters. In our study, no significant difference was found between the groups for hemoptysis and cancer history in the scoring (p>0.05). In the ROC curve analysis of the scoring, the area under the curve (AUC) was found to be 0.874 with a 95% confidence interval.
Conclusion: As validated in our study; the COVID-GRAM risk scoring has had satisfactory success in detecting critical illness in patients hospitalized for Covid-19.

Anahtar Kelimeler

Covid-19, Risk score, Emergency Service

COVID-19 Hastalarında Kritik Hastaların Saptanmasında Kullanılan COVID-Gram Risk Skorlamasının Türkiye Popülasyonunda Validasyonu

Öz

Amaç: Bu çalışmanın amacı acil servisten hastaneye yatış verilen Covid-19 hastalarında kritik hastaları saptamak için kullanılan “COVID-GRAM” kritik hastalık risk skorlamasının Türkiye popülasyonundaki validasyonu yapmaktır.
Gereç ve Yöntem: Bu çalışma 01.08.2020 ile 31.01.2021 tarihleri arasında Recep Tayyip Erdoğan Üniversitesi Eğitim ve Araştırma Hastanesi Acil Servisi’ne başvurup Covid-19 nedeniyle yatış verilen 299 COVID-19 hastasının bilgisayar tabanlı hasta kayıtlarının geriye dönük incelenmesi ile yapılmıştır. Söz konusu incelemelerde hastaların yaş, cinsiyet, başvuru vital değerleri, başvuru şikayeti, akciğer grafisi, laboratuvar tetkikleri, komorbid hastalıkları ve sonlanım şekilleri kullanılmıştır.
Bulgular: Hastaların yaş ortanca değeri 69 (22-96) bulunmuştur. COVID-GRAM risk skorlamasında bulunan akciğer grafisi (OO:9.72, %95 GA: 4.06 – 23.3), yaş (OO:1.05, %95 GA: 1.03 – 1.08), dispne (OO:10.3, %95 GA: 5.03 – 21.0), bilinç değişikliği (OO:77.91, %95 GA: 1.03 – 5870.48), komorbidite sayısını (OO:1.64, %95 GA: 1.32–2.05) kritik ve kritik olmayan hasta grupları arasında karşılaştırdığımızda bağımsız prediktör olarak karşımıza çıkmıştır. Laboratuvar parametrelerinden laktat dehidrogenaz (OO:1.002, %95 GA: 1.001 – 1.004) ve direkt bilurubin de (OO: 1.04, %95 GA: 1.01– 1.07) benzer şekilde bağımsız prediktör olarak karşımıza çıkmıştır. Çalışmamızda skorlamada bulunan hemoptizi, kanser öyküsü için gruplar arası anlamlı fark bulunamamıştır (p>0.05). Skorlamanın ROC eğrisi analizinde eğri altında kalan alan (AUC) %95 güven aralığı ile 0.874 bulunmuştur.
Sonuç: Çalışmamızda valide edildiği gibi COVID-GRAM risk skorlaması Covid-19 nedeniyle yatış verilen hastalarda kritik hastalığı saptamada tatmin edici bir başarıya sahiptir.

Anahtar Kelimeler

Covid-19, Risk skoru, Acil Servis

Kaynakça

• 1. Zhu N, Zhang D, Wang W, Li X, Yang B, Song J, et al. A Novel Coronavirus from Patients with Pneumonia in China, 2019. N Engl J Med. 2020;382(8):727–33.
• 2. Lu R, Zhao X, Li J, Niu P, Yang B, Wu H, et al. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. Lancet [Internet]. 2020 Feb 22 [cited 2021 Mar 5];395(10224):565–74. Available from: https://www.ncbi.com
• 3. World Health Organization. Novel coronavirus situation report [Internet]. [cited 2021 Jan 23]. Available from: https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200122-sitrep-2-2019-ncov.pdf
• 4. COVID-19 (SARS-CoV-2 Enfeksiyonu) Genel Bilgiler, Epidemiyoloji ve Tanı [Internet]. [cited 2021 Jun 28]. Available from: https://covid19.saglik.gov.tr/Eklenti/39551/0/covid-19rehberigenelbilgilerepidemiyolojivetanipdf.pdf
• 5. Covid-19, Sağlık Bakanlığı [Internet]. [cited 2021 Jul 5]. Available from: https://covid19.saglik.gov.tr/
• 6. 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 [Internet]. 2020 Feb 15 [cited 2021 Mar 15];395(10223):497–506. Available from: https://isaric.tghn.org/protocols/
• 7. 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 - J Am Med Assoc [Internet]. 2020 Apr 7 [cited 2021 Mar 5];323(13):1239–42. Available from: https://jamanetwork.com/
• 8. 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 Mar 28;395(10229):1054–62.
• 9. Li Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, et al. Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia. N Engl J Med [Internet]. 2020 Mar 26 [cited 2021 Mar 15];382(13):1199–207. Available from: https://pubmed.ncbi.nlm.nih.gov/31995857/
• 10. Wynants L, Van Calster B, Collins GS, Riley RD, Heinze G, Schuit E, et al. Prediction models for diagnosis and prognosis of covid-19: Systematic review and critical appraisal. BMJ [Internet]. 2020 Apr 7 [cited 2021 Mar 15];369. Available from: https://pubmed.ncbi.nlm.nih.gov/32265220/
• 11. Liang W, Liang H, Ou L, Chen B, Chen A, Li C, et al. Development and validation of a clinical risk score to predict the occurrence of critical illness in hospitalized patients with COVID-19. JAMA Intern Med. 2020;180(8):1081–9.
• 12. 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 Intern Med. 2020 Jul 1;180(7):934–43.
• 13. Liu Y, Du X, Chen J, Jin Y, Peng L, Wang HHX, et al. Neutrophil-to-lymphocyte ratio as an independent risk factor for mortality in hospitalized patients with COVID-19. J Infect. 2020;81(1):e6–12.