Association of demographic, clinical, laboratory, and radiological characteristics with outcomes of COVID-19 patients: A systematic review and Meta-analysis

Abstract

Objectives: The aim of this meta-analysis was to assess association between a composite clinical outcome (severe infection/ required ICU admission/ death) of COVID-19 pneumonia and demographic, clinical, laboratory and radiological findings of these patients. Methods: A literature search was conducted using the databases PubMed, Medline, Scopus and Web of Science till July. Relative risk (RRs), standardized mean difference (SMDs) and 95% confidence intervals (CIs) were pooled using random-effects models. We described overall estimates of relevant data of clinical importance from 116,260 COVID-19 pneumonia patients including 19,628 with composite end points from 40 observational studies of 5 countries. Results: The result showed that male gender (RR=1.24, p <.001), older age (SMD= 3.19, P<.001) especially > 64 years (RR=2.52, P <.001) followed aggravated course. Delayed hospitalization (SMD=.75, p= 0.005), presence of co-morbidity (RR= 1.76, p<.001) and multiple co-morbidities (RR=1.50, p<.001) were associated with higher risk of fatal course. Pooled data reported significantly high neutrophil-lymphocyte ratio (SMD=10.79, p<.001), low lymphocyte-to-C-reactive protein ratio (SMD=-3.89, p<.001), low platelet count (SMD=-1.622, p<.001), prolonged prothrombin time (SMD=0.98, p<.001), high lactate dehydrogenase (SMD=6.260, p<.001), D-dimer (SMD=1.92, p<.001), creatine kinase (SMD=1.68, p= 0.001) and interleukin-6 level (SMD=2.84, P=.001) in patients with fatal outcome. Funnel plots and Egger’s tests did not reveal any significant publication bias. Conclusions: Features like older age, male gender, presence of co-morbidities and delayed hospitalization along with the laboratory findings consistent with infection, immune system activation, coagulation disorder and tissue damage could help clinicians to identify COVID-19 patients with poor prognosis at an early stage. J Microbiol Infect Dis 2019; 9(3):121-135.

Keywords

• COVID-19
• risk factors
• predictors
• statistical association
• outcome
• adversity
• death/ fatality
• laboratory results

References

1. 1. Ruan Q, Yang E, Wang W, et al. 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(5): 846-848.
2. 2. Zhang G, Hu C, Luo L, et al (2). Clinical features and short-term outcomes of 221 patients with COVID-19 in Wuhan, China. Journal of Clinical Virology 2020; 127: 104364.
3. 3. Parohana M, Yaghoubib S, Serajic A, et al. Risk factors for mortality in patients with Coronavirus disease 2019 (COVID-19) infection: a systematic review and meta-analysis of observational studies. The Aging Male 2020; 8: 1-9.
4. 4. Wang B, Li R, Lu Z, Huang Y (7). Does comorbidity increase the risk of patients with COVID-19: evidence from meta-analysis. Aging 2020; 12(7): 6049-6057.
5. 5. Sing AK, Gillies CL, Sing R, et al. Prevalence of comorbidities and their association with mortality in patients with COVID-19: A Systematic Review and Meta-analysis. Diabetes Obes Metab. 2020 Jun 23;10.1111/dom.14124. doi: 10.1111/dom.14124.
6. 6. Yang J, Zhenga Y, Goua X, et al (3). Prevalence of comorbidities and its effects in patients infected with SARS-CoV-2: a systematic review and meta-analysis. In J Infec Dis 2020; 94: 91–95.
7. 7. Emami A, Javanmardi F, Pirbonyeh N, et al. Prevalence of Underlying Diseases in Hospitalized Patients with COVID-19: a Systematic Review and Meta-Analysis. Arch Acad Emerg Med 2020; 8(1): e35.
8. 8. Zhou F, Yu T, Du R, et al. Clinical course and risk factors for mortality of adult in-patients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 2020; 395: 1054–62.

9. 9. Yang X, Yu Y, Xu J, et al (1). 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: 475–81.
10. 10. Wu C, Chen X, Cai Y, 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.
11. 11. Colombi D, Bodini FC, Petrini M, et al. Well-aerated Lung on Admitting Chest CT to Predict Adverse Outcome in COVID-19 Pneumonia. Radiology 2020; 296(2):E86-E96.
12. 12. Petrilli CM, Jones SA, Yang J, Rajagopalan H, 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.
13. 13. Suleyman G, Fadel RA, Malette KA, et al. Clinical Characteristics and Morbidity Associated With Coronavirus Disease 2019 in a Series of Patients in Metropolitan Detroit. JAMA Network Open 2020; 3(6): e2012270. doi:10.1001/jamanetworkopen. 2020.12270.
14. 14. Huang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020; 395(10223):497-506.
15. 15. Lagunas-Rangel FA. Neutrophil to lymphocyte ratio and lymphocyte to C-reactive protein ratio in patients with severe coronavirus disease 2019 (COVID‐19): A meta-analysis. J Med Virol 2020; 127:104364
16. 16. Xu B, Xing Y, Peng J, et al (1). Chest CT for detecting COVID-19: a systematic review and meta-analysis of diagnostic accuracy. Eur Radiol 2020; 15;1-8. doi: 10.1007/s00330-020-06934-2.
17. 17. Stroup DF, Berlin JA, Morton SC, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA 2000; 283(15): 2008-2012.
18. 18. National Health Commission of the People’s Republic of China. Diagnosis and Treatment Protocol for Novel Coronavirus Pneumonia (Trial Version 6). Available from: http://www.nhc.gov.cn/yzygj/s7653p/202002/8334a8326dd94d329df351d7da8aefc2.shtml. [Accessed August 2, 2020]
19. 19. Hozo SP, Djulbegovic B, Hozo I. Estimating the mean and variance from the median, range, and the size of a sample. BMC Med Res Methodol 2005; 5(1):13. doi:10.1186/1471‐2288‐5‐13.
20. 20. Wang D, Hu B, Hu C, et al (1). Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA 2020 7; 323(11): 1061-1069. doi: 10.1001/jama.2020.1585.
21. 21. Wang X, Fang J, Zhu Y, et al (2). Clinical characteristics of non-critically ill patients with novel coronavirus infection (COVID-19) in a Fangcang Hospital. Clin Microbiol Infect 2020; 26(8):1063-1068. doi: 10.1016/j.cmi.2020.03.032.
22. 22. Guan W, Ni Z, Hu Y, et al (1). Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med 2020; 382:1708-20. doi: 10.1056/NEJMoa2002032
23. 23. Zhang JJ, Dong X, Cao YY, et al (1). Clinical characteristics of 140 patients infected with SARSCoV-2 in Wuhan, China Allergy 2020; 75(7):1730-1741. doi: 10.1111/all.14238.
24. 24. Liu Z, Xing B, Xue ZZ (3). The Epidemiological Characteristics of an Outbreak of 2019 Novel Coronavirus Diseases (COVID-19) in China. Epidemiology Working Group for NCIP Epidemic Response, Chinese Center for Disease Control and Prevention [Abstract in English]. Clin J Epidemiol 41(2): 145-151. doi:10.3760/cma.j.issn.0254-6450.2020.02. 003.
25. 25. Zhang G, Hu C, Luo L, et al. Clinical features and short-term outcomes of 221 patients with COVID-19 in Wuhan, China. Journal of Clinical Virology 2020; 127: 104364.
26. 26. Zhou F, Yu T, Du R, et al. Clinical course and risk factors for mortality of adult in-patients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 2020; 395: 1054–62
27. 27. Wu C, Chen X, Cai Y, 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 doi:10.1001/jamainternmed.2020.0994
28. 28. Tian S, Hu N, Lou J, et al. Characteristics of COVID-19 infection in Beijing. Journal of Infection 2020; 80: 401–406.
29. 29. Wang D, Yin Y, Hu C, et al (3). Clinical course and outcome of 107 patients infected with the novel coronavirus, SARS-CoV-2, discharged from two hospitals in Wuhan, China. Critical Care 2020; 24:188.
30. 30. Chen T, Wu D, Chen H, et al. Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study. BMJ 2020; 368: m1091. doi: 10.1136/bmj.m1091
31. 31. Deng Y, Liu W, Liu K, et al. Clinical characteristics of fatal and recovered cases of coronavirus disease 2019 in Wuhan, China: a retrospective study. Chinese Medical Journal 2020; 133(11)
32. 32. Argenziano MG, Bruce SL, Slater CL, et al. Characterization and clinical course of 1000 patients with coronavirus disease 2019 in New York: retrospective case series. BMJ 2020;369: m1996. doi: 10.1136/bmj.m1996.
33. 33. Cheng Y, Luo R, Wang K, et al. Kidney impairment is associated with in-hospital death of COVID-19 patients. Kidney Int 2020; 97(5):829-838. doi: 10.1016/j.kint.2020.03.005.
34. 34. Docherty AB, Harrison EM, Green CA, et al. Features of 20 133 UK patients in hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: prospective observational cohort study. BMJ 2020; 369: m1985. doi: 10.1136/bmj.m1985.
35. 35. Wang L, He W, Yu X, et al (4). Coronavirus disease 2019 in elderly patients: Characteristics and prognostic factors based on 4-week follow-up. Journal of Infection 2020; 80: 639–645.
36. 36. Long L, Zeng X, Zhang X, et al. Short-term outcomes of COVID-19 and risk factors for progression. Eur Respir J 2020; 55: 2000990. doi.org/10.1183/13993003.00990-2020.
37. 37. Xu PP, Tian R, Luo S, et al. Risk factors for adverse clinical outcomes with COVID-19 in China: a multicenter, retrospective, observational study. Theranostics 2020; 10(14): 6372- 6383. doi: 10.7150/thno.46833
38. 38. Guan W, Liang W, Zhao Y, et al (2). Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis. Eur Respir J 2020; 55: 2000547. doi.org/10.1183/13993003.00547-2020.
39. 39. Nikpouraghdam M, Farahani AJ, Alishiri GH, et al. Epidemiological characteristics of coronavirus disease 2019 (COVID-19) patients in IRAN: A single center study. Journal of Clinical Virology 2020;127: 104378.
40. 40. Shi s, Qin m, Shen b, Cai y, Liu t, Yang F, Gong W, Liu X et al. Association of Cardiac Injury with Mortality in Hospitalized Patients With COVID-19 inWuhan, China. JAMA Cardiol doi:10.1001/jamacardio.2020.0950
41. 41. Tan T, Khoo B, Mills EG, et al. Association between high serum total cortisol concentrations and mortality from COVID-19. Lancet Diabetes Endocrinol 2020. doi.org/10.1016/S2213-8587(20)30216-3.
42. 42. Wang K, Zuo P, Liu Y, et al (6). Clinical and laboratory predictors of in-hospital mortality in patients with COVID-19: a cohort study in Wuhan, China. Clin Infect Dis 2020; 3(538). doi: 10.1093/cid/ciaa538.
43. 43. Yanga AP, Liub JP, Taoc WQ, et al (2). The diagnostic and predictive role of NLR, d-NLR and PLR in COVID-19 patients. International Immunopharmacology 2020; 84: 106504.
44. 44. Liu Y, Du X, Chen J, et al. Neutrophil-to-lymphocyte ratio as an independent risk factor for mortality in hospitalized patients with COVID-19. Journal of Infection. 2020; 81: e6–e12.
45. 45. Richardson S, Hirsch JS, Narasimhan M, et al. Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the NewYork City Area. JAMA. doi:10.1001/jama.2020.6775
46. 46. Gao Y, Li T, Han M, et al. Diagnostic utility of clinical laboratory data determinations for patients with the severe COVID-19. J Med Virol 2020;92:c791–796.
47. 47. Li K, Wu J, Wu F, et al. The Clinical and Chest CT Features Associated With Severe and Critical COVID-19 Pneumonia. Investigative Radiology 2020; 55(6): 327-331.
48. 48. Qin C, Zhou L, Hu Z, et al. Dysregulation of Immune Response in Patients With Coronavirus 2019 (COVID-19) in Wuhan, China. Clin Infect Dis 2020; 71(15):762-768. doi: 10.1093/cid/ciaa248.
49. 49. Wang Z, Yang B, Li Q, et al (5). Clinical Features of 69 Cases With Coronavirus Disease 2019 in Wuhan, China. Clin Infect Dis. 2020; 71(15):769-777. doi: 10.1093/cid/ciaa272.
50. 50. Onder G, Rezza G, Brusaferro S. Case-Fatality Rate and Characteristics of Patients Dying in Relation to COVID-19 in Italy. JAMA 2020; 323(18): 1775-1776.
51. 51. Lewnard JA, Liu VX, Jackson ML, et al. Incidence, clinical outcomes, and transmission dynamics of severe coronavirus disease 2019 in California and Washington: prospective cohort study. BMJ 2020; 369: m1923.
52. 52. Du RH, Liang LR, Yang CQ, et al. Predictors of mortality for patients with COVID-19 pneumonia caused by SARSCoV-2: a prospective cohort study. Eur Respir J 2020; 55: 2000524. doi.org/10.1183/13993003.00524-2020.
53. 53. Ye C, Zhang S, Zhang X, et al. Impact of comorbidities on patients with COVID‐19: A large retrospective study in Zhejiang, China. J Med Virol 2020; 1–9.
54. 54. Wells G, Shea B, O’Connell D, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of non-randomised studies in meta-analyses. 2013, http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp,
55. 55. Dooley KE, Chaisson RE. Tuberculosis and diabetes mellitus: convergence of two epidemics. Lancet Infect Dis 2009; 9: 737–46.
56. 56. Badawi A, Ryoo SG. Prevalence of comorbidities in the Middle East respiratory syndrome coronavirus (MERS-CoV): a systematic review and meta-analysis. Int J Infect Dis 2016; 49:129–33.
57. 57. Hong KH, Choi JP, Hong SH, et al. Predictors of mortality in Middle East respiratory syndrome (MERS). Thorax 2018; 73: 286–289.
58. 58. Opal SM, Girard TD, Ely EW. The immunopathogenesis of sepsis in elderly patients. Clin Infect Dis 2005; 41(7): S504–S512.
59. 59. Jaillon S, Berthenet K, Garlanda C. Sexual dimorphism in innate immunity. Clin Rev Allergy Immunol 2019; 56:308–321.
60. 60. Kim ES, Choe PG, Park WB, et al. Clinical progression and cytokine profiles of Middle East respiratory syndrome coronavirus infection. J Korean Med Sci 2016; 31:1717–1725.
61. 61. Guo L, Wei D, Zhang X, et al. Clinical features predicting mortality risk in patients with viral pneumonia: the MuLBSTA Score. Front Microbiol 2019; 10: 2752.
62. 62. Sun Z, Zhang N, Li Y, Xu X. A systematic review of chest imaging findings in COVID-19. Quant Imaging Med Surg 2020; 10(5):1058-1079. doi.org/10.21037/qims-20-564
63. 63. Ferreira FL, Bota DP, Bross A, et al. Serial evaluation of the SOFA score to predict outcome in critically ill patients. JAMA 2001; 286: 1754–58.