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Chronic Multimorbidity Patterns in Relation to COVID-19 Severe Infection (Mrisk-COVID)

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details. Identifier: NCT04981249
Recruitment Status : Completed
First Posted : July 28, 2021
Last Update Posted : August 4, 2021
Agència de Qualitat i Avaluació Sanitàries
Instituto Aragones de Ciencias de la Salud
Information provided by (Responsible Party):
Marisa Baré, MD, MPH, PhD, Corporacion Parc Tauli

Brief Summary:
The aim of the study was to analyze the patterns of chronic multimorbidity of a cohort of Covid-19 patients, and to assess the relation between the patterns and the development of severe infection or mortality.

Condition or disease
Covid-19 Chronic Disease

Detailed Description:
This is a Big Data study that aims to establish the multimorbidity (MM) clusters of a cohort of Covid-19 patients, and assess their potential relation with severe infection or mortality. Databases of demographic information and complete medical records from the cohort will be provided by the Agency for Health Quality and Assessment of Catalonia (AQuAS). Data will be collected and integrated in a complete database in order to define the study variables: multimorbidity patterns, COVID-19 severe infection and COVID-19 associated mortality. The population will be stratified by sex and age (21-45, 46-65, 66-80 and 81-95 years). Diagnoses from primary care and hospitals will be filtered and classified using the Chronic Condition Indicator v.2021 and the Clinical Classification Software v.2021 [1], in order to identify the Chronic Conditions (CC) of the patients. CC with prevalence >2% in each age-sex strata will be subjected to a fuzzy c-means clustering analysis. The final number of clusters in each age-sex group will be determined under the clinical criteria of the research group members. Percentages of patients that suffered severe Covid-19 infection or death in each cluster will be calculated. Bivariate statistical analysis comparing the demographic data and the cluster distribution with severe infection and mortality will be performed.

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Study Type : Observational
Actual Enrollment : 14286 participants
Observational Model: Cohort
Time Perspective: Retrospective
Official Title: Risk of Severe COVID-19, Taking Into Account Multimorbidity Patterns, as Well as Other Clinical and Sociodemographic Variables. Big Data Mrisk-COVID Project
Actual Study Start Date : January 1, 2021
Actual Primary Completion Date : January 31, 2021
Actual Study Completion Date : May 31, 2021

Primary Outcome Measures :
  1. Covid-19 severe infection [ Time Frame: From 27-February-2020 to 15-June-2020 ]
    Severe COVID-19 infection was defined as the occurrence of at least one of the following conditions during any of the registered COVID-19 episodes: severe respiratory affection (including insufficiency, failure, or distress); use of respiratory support (including mechanical ventilation or oxygen therapy); septic shock; multiple organ failure (the combination of respiratory failure and any other organ failure); inflammatory response; admission to intensive care unit; and mortality.

  2. Covid-19 mortality [ Time Frame: From 27-February-2020 to 15-June-2020 ]
    Death associated to COVID-19 infection episode

Information from the National Library of Medicine

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Ages Eligible for Study:   21 Years to 95 Years   (Adult, Older Adult)
Sexes Eligible for Study:   All
Sampling Method:   Non-Probability Sample
Study Population
Confirmed or suspected Covid-19 patients from the first wave of the pandemic, aged >20 years, residing in a healthcare region of about 400.000 inhabitants in a Northeast region of Spain (Vallès Occidental Est, Catalonia, Spain).

Inclusion Criteria:

  • Positive results of Covid-19 laboratory tests
  • Covid-19 related clinical profile verified by healthcare professionals

Exclusion Criteria:

  • Male >90 years
  • Females >95 years

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its identifier (NCT number): NCT04981249

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Corporacio Parc Taulí
Sabadell, Spain, 08208
Sponsors and Collaborators
Corporacion Parc Tauli
Agència de Qualitat i Avaluació Sanitàries
Instituto Aragones de Ciencias de la Salud
Additional Information:
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Responsible Party: Marisa Baré, MD, MPH, PhD, Coordinator, Corporacion Parc Tauli Identifier: NCT04981249    
Other Study ID Numbers: CIR 2020/023
First Posted: July 28, 2021    Key Record Dates
Last Update Posted: August 4, 2021
Last Verified: July 2021

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Keywords provided by Marisa Baré, MD, MPH, PhD, Corporacion Parc Tauli:
Cluster analysis
Additional relevant MeSH terms:
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Chronic Disease
Disease Attributes
Pathologic Processes