Assessing the impact of COVID-19 on the health of geriatric patients: The European GeroCovid Observational Study.

2021
ABSTRACT Background : Despite the growing evidence on Covid-19, there are still many gaps in the understanding of this disease, especially in individuals in advanced age. We describe the study protocol of GeroCovid Observational, a multi-purpose, multi-setting and multicenter initiative that aims at investigating: risk factors, clinical presentation and outcomes of individuals affected by Covid-19 in acute and residential care settings; best strategies to prevent infection in long-term care facilities; and, impact of the pandemic on neuropsychologic, functional and physical health, and on medical management in outpatients and home care patients at risk of Covid-19, with a special focus on individuals with dementia. Methods : GeroCovid involves individuals aged ≥60 years, at risk of or affected by Covid-19, prospectively or retrospectively observed since March 1st, 2020. Data are collected in multiple investigational sites across Italy, Spain and Norway, and recorded in a de-identified clinical e-Registry. A common framework was adapted to different care settings: acute wards, long-term care facilities, geriatric outpatient and home care, and outpatient memory clinics. Results : At September 16th, 2020, 66 investigational sites obtained their Ethical Committee approval and 1618 cases (mean age 80.6 [SD=9.0] years; 45% men) have been recorded in the e-Registry. The average inclusion rate since the study start on April 25th is 11.2 patients/day. New cases enrollment will end on December 31st and the clinical follow-up on June 30th, 2021. Conclusion : GeroCovid will explore relevant aspects of Covid-19 in adults aged ≥60 years with high-quality and comprehensive data, which will help to optimize Covid-19 prevention and management, with practical implications for ongoing and possible future pandemics. Trial registration : NCT04379440 (clinicaltrial.gov).
    • Correction
    • Source
    • Cite
    • Save
    47
    References
    7
    Citations
    NaN
    KQI
    []
    Baidu
    map