Mortality within one year after intensive care unit (ICU) admission with Coronavirus disease 2019 (COVID-19) will be assessed. Risk and risk factors for one year mortality in ICU patients will be compared to patients admitted to hospital with COVID-19 and general population controls. The ICU population comprises all Swedish ICU patients with COVID-19 with at lease one year of follow up. The hospital admitted cohort comprises four hospital admitted patients with COVID-19 per ICU patient, matched on age, legal gender and region. The general population controls are matched to the ICU patients in a one to four fashion on age, legal gender and region. ICU patients are identified in the Swedish intensive care registry. The hospital admitted patients are identified in the national patient registry and the population controls are identified in the population registry. Data on socioeconomics and income are provided by the Statistics Sweden. Data on comorbidity, medications and death are provided from the National board of health and welfare.
Study Type
OBSERVATIONAL
Enrollment
13,537
Observational study. No intervention.
Uppsala University
Uppsala, Sweden
What factors have significant odds ratios in a logistic model of the risk of one year mortality?
Variables in a binary logistic model on mortality one year after ICU admission: age, legal gender, highest education, immigrant background, income previous year, martial status, ischemic heart disease, chronic renal failure, stroke, type 2 diabetes melitus, chronic obstructive pulmonary disease, asthma, hypertension, malignacy, treatment with renin angiotensin angiotensinogen inhibitors, treatment with statins
Time frame: One year
Is cohort an independent risk factor in a logistic model of one year mortality?
Binary logistic model, interaction with a variable denoting cohort (ICU, Hospital or General population). A significant interaction denotes a differential effect of a risk factor between cohorts. Variables in a binary logistic model on mortality one year after ICU admission: age, legal gender, highest education, immigrant background, income previous year, martial status, ischemic heart disease, chronic renal failure, stroke, type 2 diabetes melitus, chronic obstructive pulmonary disease, asthma, hypertension, malignancy, treatment with renin-angiotensin-angiotensinogen inhibitors and treatment with statins.
Time frame: One year
Does acute disease severity, hospital length of stay or ICU length of stay affect the significance of variables when added to the risk model in Outcome 1 for the ICU cohort?
Addition of Simplified Acute Physiology Score 3, hospital length of stay and ICU length of stay is added to the logistic model in Outcome 1.
Time frame: One year
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