Primary Care Relevant Risk Factors for Adverse Outcomes in Patients With COVID-19 Infection: A Systematic Review

References

1. 1.↵
   1. Yi Y,
   2. Lagniton PNP,
   3. Ye S,
   4. Li E,
   5. Xu R-H

   . COVID-19: what has been learned and to be learned about the novel coronavirus disease. Int J Biol Sci 2020;16:1753–66.

   OpenUrlCrossRefPubMed
2. 2.↵
   World Health Organization. Coronavirus Disease (COVID-19) Situation Report-127. World Health Organization.
3. 3.↵
   Centers for Disease Control and Prevention. Cases in the U.S.|CDC. https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/cases-in-us.html.
4. 4.↵
   1. Stringhini S,
   2. Wisniak A,
   3. Piumatti G,
   4. et al

   . Seroprevalence of anti-SARS-CoV-2 IgG antibodies in Geneva, Switzerland (SEROCoV-POP): a population-based study. Lancet 2020.
5. 5.↵
   1. Havers FP,
   2. Reed C,
   3. Lim TW

   . Seroprevalence of antibodies to SARS-CoV-2 in six sites in the United States, March 23–May 3, 2020. medRxiv.org 2020.
6. 6.↵
   Centers for Disease Control and Prevention. Interim clinical guidance for management of patients with confirmed 2019-nCoV|CDC. https://www.cdc.gov/coronavirus/2019-ncov/hcp/clinical-guidance-management-patients.html.
7. 7.↵
   1. Horby P,
   2. Lim WS,
   3. Emberson J

   . Effect of dexamethasone in hospitalized patients with COVID-19—preliminary report. medRxiv.org 2020.
8. 8.↵
   1. Beigel JH,
   2. Tomashek KM,
   3. Dodd LE,
   4. et al

   . Remdesivir for the treatment of Covid-19—preliminary report. N Engl J Med 2020;383:1813–26.

   OpenUrlCrossRefPubMed
9. 9.↵
   1. Ferguson NM,
   2. Laydon D,
   3. Nedjati-Gilani G,
   4. et al

   . Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand.
10. 10.↵
    1. Xie J,
    2. Tong Z,
    3. Guan X,
    4. Du B,
    5. Qiu H,
    6. Slutsky AS

    . Critical care crisis and some recommendations during the COVID-19 epidemic in China. Intensive Care Med 2020;46:837–40.

    OpenUrlCrossRefPubMed
11. 11.↵
    1. Moutchia J,
    2. Pokharel P,
    3. Kerri A,
    4. et al

    . Clinical laboratory parameters associated with severe or critical novel coronavirus disease 2019 (COVID-19): a systematic review and meta-analysis. medrxiv.org 2020.
12. 12.↵
    1. Do NT,
    2. Ta NT,
    3. Tran NT,
    4. et al

    . Point-of-care C-reactive protein testing to reduce inappropriate use of antibiotics for non-severe acute respiratory infections in Vietnamese primary health care: a randomised controlled trial. Lancet Glob Heal 2016;4:e633-41–e641.

    OpenUrl
13. 13.↵
    1. Howick J,
    2. Cals JWL,
    3. Jones C,
    4. et al

    . Current and future use of point-of-care tests in primary care: an international survey in Australia, Belgium, The Netherlands, the UK and the USA. BMJ Open 2014;4:e005611–e005611.

    OpenUrlAbstract/FREE Full Text
14. 14.↵
    1. Huang DT,
    2. Yealy DM,
    3. Filbin MR,
    4. et al

    . Procalcitonin-guided use of antibiotics for lower respiratory tract infection. N Engl J Med 2018;379:236–49.

    OpenUrlCrossRefPubMed
15. 15.↵
    1. Waterfield T,
    2. Maney JA,
    3. Hanna M,
    4. Fairley D,
    5. Shields MD

    . Point-of-care testing for procalcitonin in identifying bacterial infections in young infants: a diagnostic accuracy study. BMC Pediatr 2018;18.
16. 16.↵
    1. Wan X,
    2. Wang W,
    3. Liu J,
    4. Tong T

    . Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC Med Res Methodol 2014;14.
17. 17.↵
    1. Hayden JA,
    2. van der Windt DA,
    3. Cartwright JL,
    4. Côté P,
    5. Bombardier C

    . Assessing bias in studies of prognostic factors. Ann Intern Med 2013;158:280–6.

    OpenUrlCrossRefPubMedWeb of Science
18. 18.↵
    1. Xie J,
    2. Hungerford D,
    3. Chen H,
    4. et al

    . Development and external validation of a prognostic multivariable model on admission for hospitalized patients with COVID-19. SSRN Electron J 2020.
19. 19.↵
    1. Liang W,
    2. Liang H,
    3. Ou L,
    4. 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;180:1081.

    OpenUrl
20. 20.↵
    1. Kaeuffer C,
    2. Ruch Y,
    3. et al

    . The BAS²IC score: a useful tool to identify patients at high risk of early progression to severe COVID-19. Open Forum Infect Dis 2020.
21. 21.↵
    1. Knight SR,
    2. Ho A,
    3. Pius R

    , ISARIC4C investigatorset al. Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: development and validation of the 4C Mortality Score. BMJ 2020;370:m3339.

    OpenUrlAbstract/FREE Full Text
22. 22.↵
    1. Cals JWL,
    2. Ebell MH

    . C-reactive protein: Guiding antibiotic prescribing decisions at the point of care. Br J Gen Pract 2018;68:112–3.

    OpenUrlFREE Full Text
23. 23.↵
    1. Hardy V,
    2. Thompson M,
    3. Keppel GA,
    4. et al

    . Qualitative study of primary care clinicians’ views on point-of-care testing for C-reactive protein for acute respiratory tract infections in family medicine. BMJ Open 2017;7:e012503.

    OpenUrlAbstract/FREE Full Text
24. 24.↵
    World Health Organization. R & D blueprint and COVID-19. World Health Organization—WHO Web Site. https://www.who.int/teams/blueprint/covid-19.
25. 25.↵
    1. Foy BH,
    2. Carlson JCT,
    3. Reinertsen E,
    4. et al

    . Association of red blood cell distribution width with mortality risk in hospitalized adults with SARS-CoV-2 Infection. JAMA Netw open 2020;3:e2022058.

    OpenUrl
26. 26.↵
    1. Galloway JB,
    2. Norton S,
    3. Barker RD,
    4. et al

    . A clinical risk score to identify patients with COVID-19 at high risk of critical care admission or death: an observational cohort study. J Infect 2020.
27. 27.↵
    1. Stiell I

    . Ottawa ankle rules. Can Fam Physician 1996.
28. 28.↵
    1. Ebell MH,
    2. Smith MA,
    3. Barry HC,
    4. Ives K,
    5. Carey M

    . The rational clinical examination. Does this patient have strep throat? JAMA 2000;284:2912–8. http://www.ncbi.nlm.nih.gov/pubmed/11147989.

    OpenUrlCrossRefPubMedWeb of Science
29. 29.↵
    1. Centor RM,
    2. Witherspoon JM,
    3. Dalton HP,
    4. Brody CE,
    5. Link K

    . The diagnosis of strep throat in adults in the emergency room. Med Decis Making 1981;1:239–46.

    OpenUrlCrossRefPubMed
30. 30.↵
    1. British Thoracic S,
    2. Myint PK,
    3. Kamath AV,
    4. Vowler SL,
    5. Maisey DN,
    6. Harrison BD

    , British Thoracic Society. Severity assessment criteria recommended by the British Thoracic Society (BTS) for community-acquired pneumonia (CAP) and older patients. Should SOAR (systolic blood pressure, oxygenation, age and respiratory rate) criteria be used in older people? A compilation of two prospective cohorts. Age Ageing 2006;35:286–91.

    OpenUrlCrossRefPubMedWeb of Science
31. 31.↵
    1. Ebell MH,
    2. Walsh ME,
    3. Fahey T,
    4. Kearney M,
    5. Marchello C

    . Meta-analysis of calibration, discrimination, and stratum-specific likelihood ratios for the CRB-65 Score. J Gen Intern Med 2019;34:1304–13.

    OpenUrlPubMed
32. 32.↵
    1. Yu Q,
    2. Wang Y,
    3. Huang S,
    4. et al

    . Multicenter cohort study demonstrates more consolidation in upper lungs on initial CT increases the risk of adverse clinical outcome in COVID-19 patients. Theranostics 2020;10:5641–8.

    OpenUrlCrossRef
33. 33.
    1. Wang D,
    2. Yin Y,
    3. Hu C,
    4. et al

    . Clinical course and outcome of 107 patients infected with the novel coronavirus, SARS-CoV-2, discharged from two hospitals in Wuhan, China. Crit Care 2020;24.
34. 34.
    1. Chen T,
    2. Wu D,
    3. Chen H,
    4. et al

    . Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study. BMJ 2020;368.
35. 35.
    1. Zhou F,
    2. Yu T,
    3. Du R,
    4. et al

    . Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 2020.
36. 36.
    1. Liu W,
    2. Tao ZW,
    3. Wang L,
    4. et al

    . Analysis of factors associated with disease outcomes in hospitalized patients with 2019 novel coronavirus disease. Chin Med J (Engl) 2020;133:1032–8.

    OpenUrl
37. 37.
    1. Xie J,
    2. Hungerford D,
    3. Chen H,
    4. et al

    . Development and external validation of a prognostic multivariable model on admission for hospitalized patients with COVID-19. medRxiv April 2020;2020.03.28.20045997.
38. 38.
    1. Yan L,
    2. Zhang H-T,
    3. Xiao Y,
    4. et al

    . Prediction of criticality in patients with severe Covid-19 infection using three clinical features: a machine learning-based prognostic model with clinical data in Wuhan. medRxiv March 2020;2020.02.27.20028027.
39. 39.
    1. Cao M,
    2. Zhang D,
    3. Wang Y,
    4. et al

    . Clinical features of patients infected with the 2019 novel coronavirus (COVID-19) in Shanghai, China. medRxiv 2020;2020.03.04.20030395. March.
40. 40.
    1. Hu L,
    2. Chen S,
    3. Fu Y,
    4. et al

    . Risk factors associated with clinical outcomes in 323 COVID-19 patients in Wuhan, China. medRxiv March 2020;2020.03.25.20037721.
41. 41.
    1. Luo X,
    2. Zhou W,
    3. Yan X,
    4. et al

    . Prognostic value of C-reactive protein in patients with COVID-19. Clin Infect Dis 2020.
42. 42.
    1. Petrilli CM,
    2. Jones SA,
    3. Yang J,
    4. 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.
43. 43.
    1. Wu C,
    2. Chen X,
    3. Cai Y,
    4. 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;180:934.

    OpenUrlPubMed
44. 44.
    1. Li K,
    2. Chen D,
    3. Chen S,
    4. et al

    . Radiographic findings and other predictors in adults with Covid-19. medRxiv 2020;2:2020.03.23.20041673.

    OpenUrl
45. 45.
    1. Jang JG,
    2. Hur J,
    3. Choi EY,
    4. Hong KS,
    5. Lee W,
    6. Ahn JH

    . Prognostic factors for severe coronavirus disease 2019 in Daegu, Korea. J Korean Med Sci 2020;35:e209.

    OpenUrlPubMed
46. 46.
    1. Xu PP,
    2. Tian RH,
    3. Luo S,
    4. et al

    . Risk factors for adverse clinical outcomes with COVID-19 in China: a multicenter, retrospective, observational study. Theranostics 2020;10:6372–83.

    OpenUrlCrossRefPubMed
47. 47.
    1. Zhou Y,
    2. He Y,
    3. Yang H,
    4. et al

    . Development and validation a nomogram for predicting the risk of severe COVID-19: a multi-center study in Sichuan, China. PLoS One 2020;15:e0233328.

    OpenUrlCrossRefPubMed
48. 48.
    1. Hou W,
    2. Zhang W,
    3. Jin R,
    4. Liang L,
    5. Xu B,
    6. Hu Z

    . Risk factors for disease progression in hospitalized patients with COVID-19: a retrospective cohort study. Infect Dis (Auckl) 2020;52:498–505.

    OpenUrl
49. 49.
    1. Zhang J,
    2. Yu M,
    3. Tong S,
    4. Liu LY,
    5. Tang LV

    . Predictive factors for disease progression in hospitalized patients with coronavirus disease 2019 in Wuhan, China. J Clin Virol 2020;127:104392.

    OpenUrlCrossRefPubMed
50. 50.
    1. Liu F,
    2. Li L,
    3. Xu MD,
    4. et al

    . Prognostic value of interleukin-6, C-reactive protein, and procalcitonin in patients with COVID-19. J Clin Virol 2020;127:104370.

    OpenUrlCrossRefPubMed
51. 51.
    1. Zhu Z,
    2. Cai T,
    3. Fan L,
    4. et al

    . Clinical value of immune-inflammatory parameters to assess the severity of coronavirus disease 2019. Int J Infect Dis 2020;95:332–9.

    OpenUrlCrossRefPubMed
52. 52.
    1. Hu H,
    2. Yao N,
    3. Qiu Y

    . Comparing rapid scoring systems in mortality prediction of critically ill patients with novel coronavirus disease. Burton JH, ed. Acad Emerg Med 2020;27:461–8.

    OpenUrlPubMed