1887
Research Open Access
Like 0

Abstract

Background

Determinants of hospitalisation, intensive care unit (ICU) admission and death are still unclear for COVID-19. Few studies have adjusted for confounding for different clinical outcomes including all reported cases within a country.

Aim

We used routine surveillance data from Portugal to identify risk factors for severe COVID-19 outcomes, and to support risk stratification, public health interventions, and planning of healthcare resources.

Methods

We conducted a retrospective cohort study including 20,293 laboratory-confirmed cases of COVID-19 reported between 1 March and 28 April 2020 through the national epidemiological surveillance system. We calculated absolute risk, relative risk (RR) and adjusted relative risk (aRR) to identify demographic and clinical factors associated with hospitalisation, ICU admission and death using Poisson regressions.

Results

Increasing age (≥ 60 years) was the major determinant for all outcomes. Age ≥ 90 years was the strongest determinant of hospital admission (aRR: 6.1), and 70–79 years for ICU (aRR: 10.4). Comorbidities of cardiovascular, immunodeficiency, kidney and lung disease (aRR: 4.3, 2.8, 2.4, 2.0, respectively) had stronger associations with ICU admission, while for death they were kidney, cardiovascular and chronic neurological disease (aRR: 2.9, 2.6, 2.0).

Conclusions

Older age was the strongest risk factor for all severe outcomes. These findings from the early stages of the COVID-19 pandemic support risk-stratified public health measures that should prioritise protecting older people. Epidemiological scenarios and clinical guidelines should consider this, even though under-ascertainment should also be considered.

Loading

Article metrics loading...

/content/10.2807/1560-7917.ES.2021.26.33.2001059
2021-08-19
2021-09-21
http://instance.metastore.ingenta.com/content/10.2807/1560-7917.ES.2021.26.33.2001059
Loading
Loading full text...

Full text loading...

/deliver/fulltext/eurosurveillance/26/33/eurosurv-26-33-3.html?itemId=/content/10.2807/1560-7917.ES.2021.26.33.2001059&mimeType=html&fmt=ahah

References

  1. Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. 2020;382(18):1708-20.  https://doi.org/10.1056/NEJMoa2002032  PMID: 32109013 
  2. 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):1775-6.  https://doi.org/10.1001/jama.2020.4683  PMID: 32203977 
  3. Livingston E, Bucher K. Coronavirus Disease 2019 (COVID-19) in Italy. JAMA. 2020;323(14):1335.  https://doi.org/10.1001/jama.2020.4344  PMID: 32181795 
  4. Bialek S, Boundy E, Bowen V, Chow N, Cohn A, Dowling N, et al. Severe outcomes among patients with coronavirus disease 2019 (COVID-19) - United States, February 12-March 16, 2020. MMWR Morb Mortal Wkly Rep. 2020;69(12):343-6.  https://doi.org/10.15585/mmwr.mm6912e2  PMID: 32214079 
  5. Grasselli G, Zangrillo A, Zanella A, Antonelli M, Cabrini L, Castelli A, et al. Baseline characteristics and outcomes of 1591 patients infected with SARS-CoV-2 admitted to ICUs of the Lombardy Region, Italy. JAMA. 2020;323(16):1574-81.  https://doi.org/10.1001/jama.2020.5394  PMID: 32250385 
  6. Korean Society of Infectious Diseases and Korea Centers for Disease Control and Prevention. Analysis on 54 mortality cases of Coronavirus disease 2019 in the Republic of Korea from January 19 to March 10, 2020. J Korean Med Sci. 2020;35(12):e132.  https://doi.org/10.3346/jkms.2020.35.e132  PMID: 32233161 
  7. 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(10229):1054-62.  https://doi.org/10.1016/S0140-6736(20)30566-3  PMID: 32171076 
  8. 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.  https://doi.org/10.1136/bmj.m1966  PMID: 32444366 
  9. Docherty AB, Harrison EM, Green CA, Hardwick HE, Pius R, Norman L, 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.  https://doi.org/10.1136/bmj.m1985  PMID: 32444460 
  10. Williamson EJ, Walker AJ, Bhaskaran K, Bacon S, Bates C, Morton CE, et al. Factors associated with COVID-19-related death using OpenSAFELY. Nature. 2020;584(7821):430-6.  https://doi.org/10.1038/s41586-020-2521-4  PMID: 32640463 
  11. Russell TW, Golding N, Hellewell J, Abbott S, Wright L, Pearson CAB, et al. Reconstructing the early global dynamics of under-ascertained COVID-19 cases and infections. BMC Med. 2020;18(1):332.  https://doi.org/10.1186/s12916-020-01790-9  PMID: 33087179 
  12. Center for Global Infectious Disease Analysis - Imperial College London (ICL). Short-term forecasts of COVID-19 deaths in multiple countries. London: ICL. [Accessed: 13 May 2020]. Available from: https://mrc-ide.github.io/covid19-short-term-forecasts/index.html#analysis-of-trends-in-reporting
  13. Statista. COVID-19 testing rate by country. Statista. [Accessed: 13 May 2020]. Available from: https://www.statista.com/statistics/1104645/covid19-testing-rate-select-countries-worldwide
  14. Statista. Coronavirus case incidence in Europe, by country 2020. Statista. [Accessed: 13 May 2020]. Available from: https://www.statista.com/statistics/1110187/coronavirus-incidence-europe-by-country
  15. Textor J, van der Zander B, Gilthorpe MS, Liśkiewicz M, Ellison GT. Robust causal inference using directed acyclic graphs: the R package ‘dagitty’. Int J Epidemiol. 2016;45(6):1887-94.  https://doi.org/10.1093/ije/dyw341  PMID: 28089956 
  16. Morrison KE, Colón-González FJ, Morbey RA, Hunter PR, Rutter J, Stuttard G, et al. Demographic and socioeconomic patterns in healthcare-seeking behaviour for respiratory symptoms in England: a comparison with non-respiratory symptoms and between three healthcare services. BMJ Open. 2020;10(11):e038356.  https://doi.org/10.1136/bmjopen-2020-038356  PMID: 33158821 
  17. República Portuguesa XXII Governo. Relatório sobre a aplicação da 3a declaração do estado de emergência. [Report on the application of the 3rd declaration of the state of emergency]. Lisbon: Government of the Portuguese Republic; 2020. Portuguese. Available from: https://www.portugal.gov.pt/pt/gc22/comunicacao/documento?i=relatorio-sobre-a-aplicacao-da-3-declaracao-do-estado-de-emergencia
  18. Direção-Geral da Saúde (DGS). Norma no 004/2020 de 23/03/2020 atualizada a 25/04/2020 - COVID-19: FASE DE MITIGAÇÃO – Abordagem do Doente com Suspeita ou Infeção por SARS-CoV-2. [Guideline No. 004/2020 of 03/23/2020 updated to 04/25/2020 - COVID-19: MITIGATION PHASE - Approach to patients with suspected or confirmed Infection by SARS-CoV-2]. Lisbon, DGS. [Accessed: 27 May 2020]. Portuguese.
  19. Martínez A, Soldevila N, Romero-Tamarit A, Torner N, Godoy P, Rius C, et al. Risk factors associated with severe outcomes in adult hospitalized patients according to influenza type and subtype. PLoS One. 2019;14(1):e0210353.  https://doi.org/10.1371/journal.pone.0210353  PMID: 30633778 
  20. Taylor G, Mitchell R, McGeer A, Frenette C, Suh KN, Wong A, et al. Healthcare-associated influenza in Canadian hospitals from 2006 to 2012. Infect Control Hosp Epidemiol. 2014;35(2):169-75.  https://doi.org/10.1086/674858  PMID: 24442080 
  21. Nguyen Y-L, Angus DC, Boumendil A, Guidet B. The challenge of admitting the very elderly to intensive care. Ann Intensive Care. 2011;1(1):29.  https://doi.org/10.1186/2110-5820-1-29  PMID: 21906383 
  22. Monteiro F. Ventilação mecânica e obstinação terapêutica ou distanásia, a dialéctica da alta tecnologia em medicina intensive. [Mechanical ventilation and medical futility or dysthanasia, the dialectic of high technology in intensive medicine]. Rev Port Pneumol. 2006;12(3):281-91. Portuguese.  https://doi.org/10.1016/S0873-2159(15)30431-1  PMID: 16967178 
  23. Lima C. Medicina High Tech, obstinação terapêutica e distanasia. [“High Tech” medicine, excessive therapy and undignified death]. Med Interna. 2006;13(2):79-82. Portuguese. https://www.spmi.pt/revista/vol13/vol13_n2_2006_079_082.pdf
  24. Ranzani OT, Besen BAMP, Herridge MS. Focus on the frail and elderly: who should have a trial of ICU treatment? Intensive Care Med. 2020;46(5):1030-2.  https://doi.org/10.1007/s00134-020-05963-1  PMID: 32123988 
  25. Guidet B, Leblanc G, Simon T, Woimant M, Quenot JP, Ganansia O, et al. Effect of systematic intensive care unit triage on long-term mortality among critically ill elderly patients in France a randomized clinical trial. JAMA. 2017;318(15):1450-9.  https://doi.org/10.1001/jama.2017.13889  PMID: 28973065 
  26. Feigin VL, Nichols E, Alam T, Bannick MS, Beghi E, Blake N, et al. Global, regional, and national burden of neurological disorders, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019;18(5):459-80.  https://doi.org/10.1016/S1474-4422(18)30499-X  PMID: 30879893 
  27. Khunti K, Singh AK, Pareek M, Hanif W. Is ethnicity linked to incidence or outcomes of covid-19? BMJ. 2020;369:m1548.  https://doi.org/10.1136/bmj.m1548  PMID: 32312785 
  28. McNutt LA, Wu C, Xue X, Hafner JP. Estimating the relative risk in cohort studies and clinical trials of common outcomes. Am J Epidemiol. 2003;157(10):940-3.  https://doi.org/10.1093/aje/kwg074  PMID: 12746247 
  29. Aguiar P, Nunes B. Odds ratio: Reflexão sobre a validade de uma medida de referência em epidemiologia. [Odds Ratio: review about the meaning of an epidemiological measure]. Acta Med Port. 2013;26(5):505-10. Portuguese. PMID: 24192088 
  30. Knol MJ. Weg met oddsratio’s: risicoratio’s in cohortonderzoek en gerandomiseerd gecontroleerd onderzoek. [Down with odds ratios: risk ratios in cohort studies and randomised clinical trials]. Ned Tijdschr Geneeskd. 2012;156(28):A4775. Dutch. PMID: 22805792 
  31. European Centre for Disease Prevention and Control (ECDC). Guidance for discharge and ending isolation in the context of widespread community transmission of COVID-19, 8 April 2020. Stockholm: ECDC; 2020. https://www.ecdc.europa.eu/en/publications-data/covid-19-guidance-discharge-and-ending-isolation
  32. Presidência do Conselho de Ministros. Decreto-Lei 20/2020, Altera as medidas excecionais e temporárias relativas à pandemia da doença COVID-19, Diário da República n.o 85-A/2020, Série I de 2020-05-01. [Decree-Law No. 20/2020: Changes the exceptional and temporary measures related to the COVID-19 disease pandemic. Diário da República No. 85-A/2020, Series I of 2020-05-01]. Lisbon: Diário da República Eletrónico. [Accessed: 13 May 2020]. Portuguese. Available from: https://dre.pt/web/guest/home/-/dre/132883356/details/maximized
  33. Ricoca Peixoto V, Nunes C, Abrantes A. Epidemic surveillance of covid-19: considering uncertainty and under-ascertainment. Port J Public Health. 2020;38(1):23-9.  https://doi.org/10.1159/000507587 
  34. Davies NG, Klepac P, Liu Y, Prem K, Jit M, Eggo RM, CMMID COVID-19 working group. Age-dependent effects in the transmission and control of COVID-19 epidemics. Nat Med. 2020;26(8):1205-11.  https://doi.org/10.1038/s41591-020-0962-9  PMID: 32546824 
  35. Serviço Nacional De Saúde (SNS). Plano de vacinação contra a Covid-19. [Covid-19 vaccination plan]. Lisbon: SNS. [Accessed: 17 Jan 2021]. Portuguese. Available from: https://www.sns.gov.pt/wp-content/uploads/2020/12/Plano_Vacinacao_COVID-19.pdf/
  36. Acemoglu D, Chernozhukov V, Werning I, Whinston M. A multi-risk SIR model with optimally targeted lockdown; cemmap working paper CWP14/20. London: The Institute for Fiscal Studies; 2020.  https://doi.org/10.1920/WP.CEM.2020.1420 
  37. Savulescu J, Cameron J. Why lockdown of the elderly is not ageist and why levelling down equality is wrong. J Med Ethics. 2020;46(11):717-21.  https://doi.org/10.1136/medethics-2020-106336  PMID: 32561661 
  38. Del Rio C, Collins LF, Malani P. Long-term health consequences of COVID-19. JAMA. 2020;324(17):1723-4.  https://doi.org/10.1001/jama.2020.19719  PMID: 33031513 
/content/10.2807/1560-7917.ES.2021.26.33.2001059
Loading

Data & Media loading...

Supplementary data

Submit comment
Close
Comment moderation successfully completed
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error