Determinants for hospitalisations, intensive care unit admission and death among 20,293 reported COVID-19 cases in Portugal, March to April 2020

  1. Vasco Ricoca Peixoto
  2. André Vieira
  3. Pedro Aguiar
  4. Paulo Sousa
  5. Carlos Carvalho
  6. Daniel Thomas
  7. Alexandre Abrantes
  8. Carla Nunes

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Abstract

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.

Article activity feed

  1. Version published to 10.2807/1560-7917.es.2021.26.33.2001059
  2. ScreenIT

    SciScore for 10.1101/2020.05.29.20115824: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    ) The regression models were analyzed in STATA 14, All analyses used 95% Cl and < 0.05 as statistically significant.
    STATA
    suggested: (Stata, RRID:SCR_012763)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    The study has some limitations. The extracted data is related to an early phase of the epidemic in Portugal and as such, risks associated may still change with increased testing and detection of mild and asymptomatic infection, changes in Regional epidemic behaviour and further data validation. There are relevant comorbidities that we could not adjust for that have been previously found to be of relevance for the COVID-19 severity outcomes, such as obesity9,10,11, economic deprivation and black and minority ethnic groups. Hypertension is also not included since it was not available in SINAVEmed dataset, although recent evidence form the largest cohort to date suggest that controlled Hypertension (HT) alone does not increase the risk of death of COVID-19 patients11. A study that found increased risk for Hypertension did not adjust for age, which we know is strongly associated with risk of death and severe disease29. In our study no data on smoking was available but, as with hypertension, it does not seem to be a relevant factor for poorer outcomes in the OpenSafely Project Cohort, where some evidence of increased risks in former smokers was found but no effect for actual smokers.11 Cardiovascular disease small numbers are probably related to the fact that, contrary to other Comorbidities, Cardiac Disease is not in a specific field in the SINAVEmed notification form. As such physicians would need to describe that condition on the field “others chronic conditions”. This may intr...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.05.29.20115824v1 on medRxiv