Recruitment

Recruitment Status
Active, not recruiting
Estimated Enrollment
Same as current

Summary

Conditions
  • COVID-19
  • Death
  • Elderly Infection
  • Epidemic Disease
  • Infection Viral
  • Infection, Coronavirus
  • Infections, Respiratory
  • Old Age; Dementia
Type
Observational
Design
Observational Model: CohortTime Perspective: Retrospective

Participation Requirements

Age
Younger than 125 years
Gender
Both males and females

Description

A lot has been written about individual risk factors for COVID-19 death, mostly in the hospitalized population. However, even though most deaths around the world have occurred among the frail and elderly, little is known about the risk factors specific to the long-term care population. In this retro...

A lot has been written about individual risk factors for COVID-19 death, mostly in the hospitalized population. However, even though most deaths around the world have occurred among the frail and elderly, little is known about the risk factors specific to the long-term care population. In this retrospective cohort study, the investigators will review the medical charts of all COVID-19 cases (n=1200) from 17 long-term care facilities in Montreal, Canada, to compare patients who survived to patients who did not survive. Through multilevel logistic regression, the risk of death will be estimated for institutional predictors of mortality, while controlling for individual risk factors. The objective is to influence local and national policies in long-term care facilities, in the hopes of avoiding the tragic spring 2020 outcomes during subsequent waves of COVID-19 or future pandemics. Covariates in the models will be drawn from a review of the medical literature and known risk factors for COVID-19 death. Individual-level covariates include clinical features (age, sex, Charlston comorbidity index, SMAF autonomy score, severity criteria) as well as medical treatments (IV fluids, anticoagulation, oxygen, regular opiates, corticosteroids). Aggregate-level covariates include epidemiological data (attack rates, timing of outbreak) and institutional characteristics (number of beds, air exchange per hour, presence of a dedicated COVID-19 unit at the time of outbreak, staff compliance to infection control measures, staff infection rates, understaffing, proportion of semi-private rooms, proportion of wandering wards and other special units).

Tracking Information

NCT #
NCT04782427
Collaborators
Université de Montréal
Investigators
Principal Investigator: Sophie Zhang, M.D. Université de Montréal