COVID-19 Salgınında Pnömonisi Olan Hastalarda Mortalite, Hastaneye Yatış ve Mekanik Ventilasyon Gereksinimlerinin Değerlendirilmesi

Yıl 2021, , 130 - 137, 29.05.2021

Nurettin Özgür Doğan , Sevtap Doğan , Murat Pekdemir , Serkan Yılmaz Duygu Ferek Emir Kutlu Barış Teke

https://doi.org/10.30934/kusbed.824886

Öz

Amaç: COVID-19 salgını, pnömoniye bağlı mortalite nedeniyle önemli kayıpları beraberinde getirmiştir. Bu araştırmada, COVID-19 salgını sırasında başvuran atipik pnömoni vakalarında mortalite ve diğer kötü sonlanım prediktörlerini bulmayı amaçladık.
Yöntem: Bu araştırma Mart ve Mayıs 2020 tarihleri arasında acil servisimizde yürütülen ileriye dönük kohort bir araştırmadır. Acil servise başvuran, toraks bilgisayarlı tomografisinde COVID-19 ilişkili atipik pnömoni patterni tespit edilen tüm erişkin hastalar araştırmaya dahil edildiler, bakteriyel pnömoni patterni olan hastalar ise dışlandılar. Araştırmanın primer sonlanım noktası; bir aylık süre içinde mortalite, yoğun bakım yatışı ve mekanik ventilasyon gereksinimi şeklinde birleşik sonlanım olarak planlandı. Bu hastalarda belirtilen kötü sonlanım prediktörlerinin araştırılması için bir lojistik regresyon modeli oluşturuldu.
Bulgular: Toplam 271 pnömoni olgusundan 146'sı son analize dahil edildi. Dahil edilen hastaların 31'inde (%21,2) birleşik sonlanım gerçekleşti, 17 hasta bir aylık dönem içinde öldü. Son regresyon modeline hastaların yaşları, kalp yetmezliği öyküsü bulunması, inme öyküsü bulunması, vücut sıcaklığı, dispne, öksürük, bilinç değişikliği, ciddi bronkospazm, tomografide bilateral akciğer bulgusu olması, hemoglobin, LDH, laktat, bikarbonat ve kreatinin düzeyleri dahil edildi. Buna göre; hastalarda bilinç değişikliği olmasının (odds oranı [OO]:15,7, %95'lik güven aralığı [GA]: 1,7-141,6), ciddi bronkospazmın (OO:12,4, %95 GA:1,6-97,9) ve laktat düzeyindeki artışın (OO:1,1, %95 GA: 1,0-1,2) kötü sonlanımın bağımsız prediktörleri olduğu bulundu.
Sonuç: Birçok klinik ve laboratuvar değişken arasından; bilinç değişikliği, ciddi bronkospazm ve laktat düzeylerinin kötü sonlanımı öngördüğü belirlenmiştir.

Anahtar Kelimeler

COVID-19, pandemi, mortalite, acil servis, pnömoni

Prediction of Mortality, Hospitalization and Mechanical Ventilation Needs of Patients with Pneumonia in COVID-19 Outbreak

Öz

Objective: The COVID-19 pandemic has brought considerable loss to the world by means of pneumonia related mortality. In the current study, we aimed to discover the predictors of mortality and other worse outcomes in atypical pneumonia cases during the COVID-19 outbreak.
Methods: A prospective cohort study was carried out in our emergency department (ED) between March and May, 2020. All adult patients presented to the ED with atypical pneumonia patterns related to COVID-19 based on a chest CT scan were included in the study, and patients with bacterial pneumonia patterns were excluded. The primary outcome measure was determined as the composite outcome, including mortality and intensive care unit admission or mechanical ventilation needs within a one-month period. A binary logistic regression model was constructed to predict the worse outcomes in those patients.
Results: Of the 271 suspected pneumonia cases, 146 patients were included in the final analysis. The composite outcome occurred in 31 patients (21.2%), 17 of whom died within one month. The patients’ age, history of heart failure, history of stroke, body temperature, dyspnea, cough, altered mental status, serious bronchospasm, bilateral lung involvement, hemoglobin level, LDH, lactate level, and bicarbonate and creatinine levels were added to the final model. Finally, patients’ altered mental status (OR:15.7, 95%CI:1.7-141.6), serious bronchospasm (OR:12.4, 95%CI:1.6-97.9), and lactate levels (OR:1.1, 95%CI:1.0-1.2) were found to be independent predictors for worse outcomes.
Conclusion: Among various clinical and laboratory variables, altered mental status, serious bronchospasm, and lactate levels can be used to predict worse outcomes.

Anahtar Kelimeler

COVID-19, pandemics, mortality, emergency department, pneumonia

Kaynakça

• World Health Organization. Coronavirus (COVID-19) outbreak situation. URL: https://www.who.int/emergencies/diseases/novel-coronavirus-2019 (Accessed on: October 15, 2020).
• Yang X, Yu Y, Xu J, Shu H, Xia J, Liu H, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir Med 2020;8:475-481.
• 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. Lancet 2020;395:507-513.
• Bhargava A, Fukushima EA, Levine M, Zhao W, Tanveer F, Szpunar SM, et al. Predictors for Severe COVID-19 Infection. Clin Infect Dis 2020 May 30;ciaa674. doi: 10.1093/cid/ciaa674. Online ahead of print.
• 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. J Clin Med 2020;9:E1548.
• 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. Eur Respir J 2020;55:2000524.
• Petrilli CM, Jones SA, Yang J, Rajagopalan H, O'Donnell L, Chernyak Y, et al. Factors Associated With Hospital Admission and Critical Illness Among 5279 People With Coronavirus Disease 2019 in New York City: Prospective Cohort Study. BMJ 2020;369:m1966.
• 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;46:846-848.
• Rothe C, Schunk M, Sothmann P, Bretzel G, Froeschl G, Wallrauch C, et al. Transmission of 2019-nCoV Infection From an Asymptomatic Contact in Germany. N Engl J Med 2020;382:970-971.
• Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, Heet JX, et al. Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med 2020;382:1708-1720.
• Zhao J, Yuan Q, Wang H, Liu W, Liao X, Suet Y, et al. Antibody responses to SARS-CoV-2 in patients of novel coronavirus disease 2019. Clin Infect Dis 2020. DOI: 10.1093/cid/ciaa344.
• Sethuraman N, Jeremiah SS, Ryo A. Interpreting Diagnostic Tests for SARS-CoV-2. JAMA [In Press] 2020 May 6. doi: 10.1001/jama.2020.8259.
• Watson J, Whiting PF, Brush JE. Interpreting a COVID-19 Test Result. BMJ 2020;369:m1808.
• Wang W, Xu Y, Gao R, Lu R, Han K, Wu G, et al. Detection of SARS-CoV-2 in Different Types of Clinical Specimens. JAMA 2020;323:1843-1844.
• Ye Z, Zhang Y, Wang Y, Huang Z, Song B. Chest CT manifestations of new coronavirus disease 2019 (COVID-19): a pictorial review. Eur Radiol 2020;30:4381-4389.
• Ai T, Yang Z, Hou H, Zhan C, Chen C, Lv W, et al. Correlation of Chest CT and RT-PCR Testing in Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases. Radiology 2020;296:E32-E40.
• Bai HX, Hsieh B, Xiong Z, Halsey K, Choi JW, Tran TML, et al. Performance of Radiologists in Differentiating COVID-19 From Viral Pneumonia on Chest CT. Radiology 2020;296:E46-E54.
• Simpson S, Kay FU, Abbara S, et al. Radiological Society of North America Expert Consensus Statement on Reporting Chest CT Findings Related to COVID-19. J Thorac Imaging. 2020 Mar 25. [In Press] doi: 10.1148/ryct.2020200152
• Magnani C, Azzolina D, Gallo E, Ferrante D, Gregori D. How Large Was the Mortality Increase Directly and Indirectly Caused by the COVID-19 Epidemic? An Analysis on All-Causes Mortality Data in Italy. Int J Environ Res Public Health 2020;17:E3452.
• 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;395:1054-1062.
• Aggarwal S, Garcia-Telles N, Aggarwal G, Lavie C, Lippi G, Henry BM, et al. Clinical Features, Laboratory Characteristics, and Outcomes of Patients Hospitalized With Coronavirus Disease 2019 (COVID-19): Early Report From the United States. Diagnosis 2020;7:91-96.
• Hong KS, Lee KH, Chung JH, Shin KC, Choi EY, Jin HJ, et al. Clinical Features and Outcomes of 98 Patients Hospitalized With SARS-CoV-2 Infection in Daegu, South Korea: A Brief Descriptive Study. Yonsei Med J 2020;61:431-437.
• Imam Z, Odish F, Gill I, O'Connor D, Armstrong J, Vanood A, et al. Older Age and Comorbidity Are Independent Mortality Predictors in a Large Cohort of 1305 COVID-19 Patients in Michigan, United States. J Intern Med 2020 Jun 4. doi: 10.1111/joim.13119. Online ahead of print.
• Argenziano MG, Bruce SL, Slater CL, Tiao JR, Baldwin MR, Barr RG, et al. Characterization and Clinical Course of 1000 Patients With Coronavirus Disease 2019 in New York: Retrospective Case Series. BMJ 2020;369:m1996.
• Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA 2016;315:801-10.