DOI: http://dx.doi.org/10.18203/2394-6040.ijcmph20213218

The various prognostic scoring system used for predicting COVID-19 mortality

Khaled Mohamed Elsharkawy, Mohammed Abdulaziz Aljawi, Hani Helal Alhassani, Sadeen Essam Ezzat, Ziad Abdulmoti Alruwaithi, Murtadha Dhiya Alsultan, Amal Abdulmoniem Elimam, Amani Abdulmoniem Elimam, Ali Abdulrahman Alwehaibi, Shaher Musa Albakheet, Enass Farouk Aboshoushah

Abstract


The widespread pandemic of Coronavirus disease 2019 (COVID-19) has been reported to affect most countries all over the world, and burden all of the affected healthcare systems. COVID-19 has first emerged in December 2019 within the district of Wuhan which is located in China. Many prognostic scoring systems have been developed to predict severe disease and death for patients with COVID-19. In this literature review, the aim to discuss the various prognostic scoring system used for predicting COVID-19 mortality. It has mainly approached the prognostic scoring systems in two main ways: The clinical and biochemical ways. In addition, the research also investigates the chest X-ray imaging findings based on scoring systems for predicting mortality for patients with COVID-19. Many scoring systems have been reported based on the biochemical and clinical parameters as age, D-dimer, presence of comorbidities, procalcitonin, C-reactive protein (CRP) and other features. Some of the reported scoring systems were recently developed in the COVID-19 pandemic while others were just modified based on the fact that patients with COVID-19 are critically ill, and usually require the same medical attention as other conditions. These scoring systems should be considered by clinicians to early predict and intervene against severe COVID-19 that might cause death. As for the imaging modalities, we have also reported many of the reported systems in the literature, including the ones that are based on chest computed tomography and X-ray findings, and are discussed in detail within this study.


Keywords


Diagnosis, Mortality, Prognosis, COVID-19

Full Text:

PDF

References


Abbasi-Oshaghi E. Diagnosis and treatment of coronavirus disease 2019 (COVID-19): Laboratory, PCR, and chest CT imaging findings. Int J Surg. 2020;79:143-53.

Elezkurtaj S. Causes of death and comorbidities in hospitalized patients with COVID-19. Sci Rep. 2021;11(1):4263.

Ahmed N, Abdelaziz SG, Abbas AS, Reda A, El-Qushayri AE, Islam SMS. Full recovery of a patient with COVID-19-induced acute kidney injury. European Journal of Medical Case Report., 2021;5(1):26-30.

Elgamasy S. Epidemiologic features and clinical course of COVID-19: a retrospective analysis of 19 patients in Germany. Future Virol. 2021;10.2217.

Shi Q. Clinical Characteristics and Risk Factors for Mortality of COVID-19 Patients With Diabetes in Wuhan, China: A Two-Center, Retrospective Study. Diabetes Care. 2020;43(7):1382-91.

Ghozy S. COVID-19 and physical inactivity: Teetering on the edge of a deadlier pandemic? Journal of global health. 2021;11:03031.

Zhang L. D-dimer levels on admission to predict in-hospital mortality in patients with Covid-19. J Thromb Haemost. 2020;18(6):1324-9.

Simadibrata DM, Lubis AM. D-dimer levels on admission and all-cause mortality risk in COVID-19 patients: a meta-analysis. Epidemiol Infect. 2020;148:e202.

Shah S. Elevated D-Dimer Levels Are Associated With Increased Risk of Mortality in Coronavirus Disease 2019: A Systematic Review and Meta-Analysis. Cardiol Rev. 2020;28(6):295-302.

Wasilewski P. COVID-19 severity scoring systems in radiological imaging – A review. Polish Journal of Radiol. 2020;v85:e361-8.

Cuong VL. The first Vietnamese case of COVID-19 acquired from China. Lancet Infect Dis. 2020;20(4):408-9.

Hashan MR. Association of dengue disease severity and blood group: A systematic review and meta-analysis. Rev Med Virol. 2021;31(1):1-9.

El-Qushayri AE. Hyperimmunoglobulin therapy for the prevention and treatment of congenital cytomegalovirus: a systematic review and meta-analysis. Expert Rev Anti Infect Ther. 2020;1-9.

Shang Y. Scoring systems for predicting mortality for severe patients with COVID-19. EClinicalMedicine. 2020;24:100426.

Richardson D. Use of the first National Early Warning Score recorded within 24 hours of admission to estimate the risk of in-hospital mortality in unplanned COVID-19 patients: a retrospective cohort study. BMJ Open. 2021;11(2):e043721.

Bairwa M. Hematological profile and biochemical markers of COVID-19 non-survivors: A retrospective analysis. Clin Epidemiol Glob Health. 2021;11:100770.

Mo J. Predictive role of clinical features in patients with coronavirus disease 2019 for severe disease. Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2020;45(5):536-41.

Berenguer J. Development and validation of a prediction model for 30-day mortality in hospitalised patients with COVID-19: the COVID-19 SEIMC score. Thorax. 2021;thoraxjnl-2020-216001.

Zou X. Acute Physiology and Chronic Health Evaluation II Score as a Predictor of Hospital Mortality in Patients of Coronavirus Disease 2019. Critical care medicine. 2020;48(8):e657-65.

Sourij H. COVID-19 fatality prediction in people with diabetes and prediabetes using a simple score upon hospital admission. Diabetes Obes Metab. 2021;23(2):589-98.

Ai T. Correlation of Chest CT and RT-PCR Testing for Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases. Radiol. 2020;296(2):E32-e40.

Miao C. Early chest computed tomography to diagnose COVID-19 from suspected patients: A multicenter retrospective study. Am J Emerg Med. 2021;44:346-51.

Yang R. Chest CT Severity Score: An Imaging Tool for Assessing Severe COVID-19. Radiology: Cardiothoracic Imaging. 2020;2(2):e200047.

Chang YC. Pulmonary sequelae in convalescent patients after severe acute respiratory syndrome: evaluation with thin-section CT. Radiol. 2005;236(3):1067-75.

Li K. CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19). European Radiol. 2020;30.

Li K. The Clinical and Chest CT Features Associated With Severe and Critical COVID-19 Pneumonia. Invest Radiol. 2020;55(6):327-31.

Prokop M. CO-RADS: A Categorical CT Assessment Scheme for Patients Suspected of Having COVID-19-Definition and Evaluation. Radiol. 2020;296(2):E97-104.

Simpson S. 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.

Penha D. CO-RADS: Coronavirus Classification Review. Journal of clinical imaging science, 2021;11:9.

Taylor E. A chest radiograph scoring system in patients with severe acute respiratory infection: a validation study. BMC Med Imaging. 2015;15:61.

Yoon SH. Chest Radiographic and CT Findings of the 2019 Novel Coronavirus Disease (COVID-19): Analysis of Nine Patients Treated in Korea. Korean J Radiol. 2020;21(4):494-500.

Wong HYF. Frequency and Distribution of Chest Radiographic Findings in Patients Positive for COVID-19. Radiol. 2020;296(2):E72-8.

Warren MA. Severity scoring of lung oedema on the chest radiograph is associated with clinical outcomes in ARDS. Thorax. 2018;73(9):840-6.

Borghesi A, Maroldi R. COVID-19 outbreak in Italy: experimental chest X-ray scoring system for quantifying and monitoring disease progression. Radiol Med. 2020;125(5):509-13.

Tomo S. The Clinical Laboratory: A Key Player in Diagnosis and Management of COVID-19. Ejifcc. 2020;31(4):326-46.