Long Term Outcome in ICU Treated COVID-19: Risk Factors for 1-year Mortality

Study Overview
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Brief Summary
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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.

Official Title
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Long Term Outcome in ICU Treated COVID-19: Risk Factors for 1-year Mortality

Conditions
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Covid19

Intervention / Treatment
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* Other: No intervention.


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Admitted to a Swedish ICU and registered in the Swedish intensive care registry with the ICD 10 diagnosis U07.1 before 1 July 2020. ICU-cohort. or randomly selected from all patients admitted to hospital but not ICU with the ICD 10 diagnosis U07.1 in the national patient registry, matched on age, legal gender and region (four per ICU patient) before 1 July 2020. Hospital cohort. or randomly selected from the general population (and not included in the ICU or hospital admitted cohorts), matched on age, legal gender and region (four per ICU patient) Exclusion Criteria: Missing a Swedish personal identification number

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| COVID-19 ICU cohort<br>All patients admitted to a Swedish ICU with COVID-19 with at least one year of follow up. COVID-19 is defined by the International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10) diagnosis U07.1 in the nationwide Swedish intensive care registry. | Other: No intervention.<br>* Observational study. No intervention.<br>|
| COVID-19 hospital admission control cohort<br>Four random control patients per ICU patient matched on age legal gender and region. Controls selected from all patients admitted to a Swedish hospital with COVID-19 with at least one year of follow up not including patients in the COVID-19 ICU cohort. COVID-19 is defined by the ICD-10 diagnosis U07.1 in the nationwide Swedish national patient registry. | Other: No intervention.<br>* Observational study. No intervention.<br>|
| General population control cohort<br>Four general population controls per ICU patient, matched on age, legal gender and region drawn from the total population register of Sweden. ICU and hospital admitted COVID-19 patients are not included. | Other: No intervention.<br>* Observational study. No intervention.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| 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 | 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. | One year | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| 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. | One year | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Long term outcome, Mortality, COVID-19, Risk factors, Critical care