Long Term Outcome in ICU Treated COVID-19: New Chronic Diseases

NCT05075096 | Completed

• 1 other identifier: U1111-1269-6916
• Study Type: observational
• Target: 60,000
• Locations: 1 country
• Sites: 1

Brief Summary

Additional chronic diseases one year after intensive care unit (ICU) admission with Coronavirus disease 2019 (COVID-19) will be assessed in comparison to two control cohorts. The ICU population comprises all Swedish ICU patients with COVID-19 with at least 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 comorbidity, medications and death are provided from the National board of health and welfare.

Conditions

Covid19

Keywords

Long term outcome; Mortality; COVID-19; Morbidity

Outcome Measures

Primary Outcomes (6)

• Is the illness severity in COVID-19 (according to level of care cohort) an independent risk factor for incident chronic renal failure within one year after inclusion?

  Variables in binary logistic model with the outcome incident chronic renal failure: On sick leave one year before ICU admission, age, legal gender, highest education, immigrant background, income the year before inclusion, marital status co-morbid diabetes mellitus. Interaction with a variable denoting cohort (ICU, Hospital or General population) is added to all variables. A significant interaction indicates a differential effect between cohorts.

  One year

• Is the illness severity in COVID-19 (according to level of care cohort) an independent risk factor for incident pulmonary disease within one year after inclusion?

  Variables in binary logistic model with the outcome incident pulmonary disease: On sick leave one year before ICU admission, age, legal gender, highest education, immigrant background, income the year before inclusion, marital status. Interaction with a variable denoting cohort (ICU, Hospital or General population) is added to all variables. A significant interaction indicates a differential effect between cohorts.

  One year

• Is the illness severity in COVID-19 (according to level of care cohort) an independent risk factor for incident cardiac failure within one year after inclusion?

  Variables in binary logistic model with the outcome incident cardiac failure: On sick leave one year before ICU admission, age, legal gender, highest education, immigrant background, income the year before inclusion, marital status co-morbid ischemic heart disease. Interaction with a variable denoting cohort (ICU, Hospital or General population) is added to all variables. A significant interaction indicates a differential effect between cohorts.

  One year

• Is the illness severity in COVID-19 (according to level of care cohort) an independent risk factor for incident pulmonary hypertension within one year after inclusion?

  Variables in binary logistic model with the outcome incident pulmonary hypertension: On sick leave one year before ICU admission, age, legal gender, highest education, immigrant background, income the year before inclusion, marital status co-morbid chronic obstructive pulmonary disease. Interaction with a variable denoting cohort (ICU, Hospital or General population) is added to all variables. A significant interaction indicates a differential effect between cohorts.

  One year

• Is the illness severity in COVID-19 (according to level of care cohort) an independent risk factor for being diagnosed with Post COVID (ICD-10, U09.9) within one year after inclusion?

  Variables in binary logistic model with the outcome Post COVID: On sick leave one year before ICU admission, age, legal gender, highest education, immigrant background, income the year before inclusion, marital status. Interaction with a variable denoting cohort (ICU, Hospital or General population) is added to all variables. A significant interaction indicates a differential effect between cohorts.

  One year

• Is the illness severity in COVID-19 (according to level of care cohort) an independent risk factor for incident psychiatric disease within one year after inclusion?

  Variables in binary logistic model with the outcome incident psychiatric disease: On sick leave one year before ICU admission, age, legal gender, highest education, immigrant background, income the year before inclusion, marital status. Interaction with a variable denoting cohort (ICU, Hospital or General population) is added to all variables. A significant interaction indicates a differential effect between cohorts.

  One year

Secondary Outcomes (1)

• Is the prevalence of pulmonary disease, chronic renal failure, pulmonary hypertension, cardiac failure or psychiatric diseases more common one year after than before ICU admission with COVID-19?

  One year

Study Arms (3)

COVID-19 ICU cohort

All patients admitted to a Swedish ICU with COVID-19 with at least one year of follow up. COVID-19 defined by the ICD-10 diagnosis U07.1 in the nationwide Swedish intensive care registry.

Other: No intervention.

COVID-19 hospital admission control cohort

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 defined by the ICD-10 diagnosis U07.1 in the nationwide Swedish national patient registry.

Other: No intervention.

General population control cohort

Four general population controls per ICU patient, matched on age, legal gender and region drawn from the total population register of Sweden. Not including ICU and hospital admitted COVID-19 patients.

Other: No intervention.

Interventions

No intervention. OTHER

No intervention observational study.

COVID-19 ICU cohort; COVID-19 hospital admission control cohort; General population control cohort

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

The study population consists of all patients a fulfilling the eligibility criteria.

You may qualify if:

• 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)

You may not qualify if:

• Missing a Swedish personal identification number

Sponsors & Collaborators

• Uppsala University: lead
• Dalarna County Council, Sweden: collaborator

Study Sites (1)

Uppsala University

Uppsala, 79182, Sweden

Location

MeSH Terms

Conditions

COVID-19

Condition Hierarchy (Ancestors)

Pneumonia, Viral; Pneumonia; Respiratory Tract Infections; Infections; Virus Diseases; Coronavirus Infections; Coronaviridae Infections; Nidovirales Infections; RNA Virus Infections; Lung Diseases; Respiratory Tract Diseases

Study Officials

• Miklos Lipcsey, Professor

  202100-2932

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: September 29, 2021
• First Posted: October 12, 2021
• Study Start: October 15, 2021
• Primary Completion: November 15, 2021
• Study Completion: November 15, 2021
• Last Updated: May 24, 2022

Record last verified: 2022-05

Data Sharing

• IPD Sharing: Will not share

Locations

SE (1)