Mudatsir Mudatsir1, Jonny Karunia Fajar1,2, Laksmi Wulandari3, Gatot Soegiarto4, Muhammad Ilmawan5, Yeni Purnamasari5, Bagus Aulia Mahdi4, Galih Dwi Jayanto2, Suhendra Suhendra5, Yennie Ayu Setianingsih6, Romi Hamdani7, Daniel Alexander Suseno8, Kartika Agustina9, Hamdan Yuwafi Naim10, Muchamad Muchlas11, Hamid Hunaif Dhofi Alluza5, Nikma Alfi Rosida5, Mayasari Mayasari5, Mustofa Mustofa5, Adam Hartono12, Richi Aditya5, Firman Prastiwi5, Fransiskus Xaverius Meku5, Monika Sitio5, Abdullah Azmy7, Anita Surya Santoso13, Radhitio Adi Nugroho5, Camoya Gersom2, Ali A Rabaan14, Sri Masyeni15, Firzan Nainu16, Abram L Wagner17, Kuldeep Dhama18, Harapan Harapan1,19. 1. Department of Microbiology, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Aceh, 23111, Indonesia. 2. Brawijaya Internal Medicine Research Center, Department of Internal Medicine, Faculty of Medicine, Universitas Brawijaya, Malang, East Java, 65145, Indonesia. 3. Department of Pulmonology and Respiratory Medicine, Faculty of Medicine, Universitas Airlangga, Surabaya, East Java, 60286, Indonesia. 4. Department of Internal Medicine, Faculty of Medicine, Universitas Airlangga, Surabaya, Easy Java, 60286, Indonesia. 5. Faculty of Medicine, Universitas Brawijaya, Malang, East Java, 65145, Indonesia. 6. Department of Urology, Faculty of Medicine, Universitas Airlangga, Surabaya, East Java, 60285, Indonesia. 7. Department of Orthopedic Surgery, Faculty of Medicine, Universitas Brawijaya, Malang, East Java, 65145, Indonesia. 8. Department of Obstetry and Gynecology, Faculty of Medicine, Universitas Brawijaya, Malang, East Java, 65145, Indonesia. 9. Department of Neurology, Faculty of Medicine, Universitas Brawijaya, Malang, East Java, 65145, Indonesia. 10. Department of Urology, Faculty of Medicine, Universitas Brawijaya, Malang, East Java, 65145, Indonesia. 11. Faculty of Animal Science, Universitas Brawijaya, Malang, East Java, 65145, Indonesia. 12. Faculty of Medicine, Universitas Negeri Sebelas Maret, Surakarta, Surakarta, 57126, Indonesia. 13. Department of Cardiology and Vascular Medicine, Faculty of Medicine, Universitas Brawijaya, Malang, East Java, 65145, Indonesia. 14. Molecular Diagnostic Laboratory, Johns Hopkins Aramco Healthcare, Dhahran, Dhahran, 31311, Saudi Arabia. 15. Department of Internal Medicine, Faculty of Medicine and Health Science, Universitas Warmadewa, Denpasar, Bali, 80235, Indonesia. 16. Faculty of Pharmacy, Hasanuddin University, Makassar, Makassar, 90245, Indonesia. 17. Department of Epidemiology, University of Michigan, Ann Arbor, MI, 48109, USA. 18. Division of Pathology, Indian Veterinary Research Institute, Izatnagar, Uttar Pradesh, 243 122, India. 19. Medical Research Unit, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Aceh, 23111, Indonesia.
Abstract
Background: The unpredictability of the progression of coronavirus disease 2019 (COVID-19) may be attributed to the low precision of the tools used to predict the prognosis of this disease. Objective: To identify the predictors associated with poor clinical outcomes in patients with COVID-19. Methods: Relevant articles from PubMed, Embase, Cochrane, and Web of Science were searched as of April 5, 2020. The quality of the included papers was appraised using the Newcastle-Ottawa scale (NOS). Data of interest were collected and evaluated for their compatibility for the meta-analysis. Cumulative calculations to determine the correlation and effect estimates were performed using the Z test. Results: In total, 19 papers recording 1,934 mild and 1,644 severe cases of COVID-19 were included. Based on the initial evaluation, 62 potential risk factors were identified for the meta-analysis. Several comorbidities, including chronic respiratory disease, cardiovascular disease, diabetes mellitus, and hypertension were observed more frequent among patients with severe COVID-19 than with the mild ones. Compared to the mild form, severe COVID-19 was associated with symptoms such as dyspnea, anorexia, fatigue, increased respiratory rate, and high systolic blood pressure. Lower levels of lymphocytes and hemoglobin; elevated levels of leukocytes, aspartate aminotransferase, alanine aminotransferase, blood creatinine, blood urea nitrogen, high-sensitivity troponin, creatine kinase, high-sensitivity C-reactive protein, interleukin 6, D-dimer, ferritin, lactate dehydrogenase, and procalcitonin; and a high erythrocyte sedimentation rate were also associated with severe COVID-19. Conclusion: More than 30 risk factors are associated with a higher risk of severe COVID-19. These may serve as useful baseline parameters in the development of prediction tools for COVID-19 prognosis. Copyright:
Background: The unpredictability of the progression of coronavirus disease 2019 (COVID-19) may be attributed to the low precision of the tools used to predict the prognosis of this disease. Objective: To identify the predictors associated with poor clinical outcomes in patients with COVID-19. Methods: Relevant articles from PubMed, Embase, Cochrane, and Web of Science were searched as of April 5, 2020. The quality of the included papers was appraised using the Newcastle-Ottawa scale (NOS). Data of interest were collected and evaluated for their compatibility for the meta-analysis. Cumulative calculations to determine the correlation and effect estimates were performed using the Z test. Results: In total, 19 papers recording 1,934 mild and 1,644 severe cases of COVID-19 were included. Based on the initial evaluation, 62 potential risk factors were identified for the meta-analysis. Several comorbidities, including chronic respiratory disease, cardiovascular disease, diabetes mellitus, and hypertension were observed more frequent among patients with severe COVID-19 than with the mild ones. Compared to the mild form, severe COVID-19 was associated with symptoms such as dyspnea, anorexia, fatigue, increased respiratory rate, and high systolic blood pressure. Lower levels of lymphocytes and hemoglobin; elevated levels of leukocytes, aspartate aminotransferase, alanine aminotransferase, blood creatinine, blood ureanitrogen, high-sensitivity troponin, creatine kinase, high-sensitivity C-reactive protein, interleukin 6, D-dimer, ferritin, lactate dehydrogenase, and procalcitonin; and a high erythrocyte sedimentation rate were also associated with severe COVID-19. Conclusion: More than 30 risk factors are associated with a higher risk of severe COVID-19. These may serve as useful baseline parameters in the development of prediction tools for COVID-19 prognosis. Copyright:
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