Trajectories of Chronic Multimorbidity Patterns in Older Patients

Status Completed

Clinical Trial Summary

Following the MRisk-COVID project, MTOP (Multimorbidity Trajectories in Older Patients) study was developed. It is a retrospective observational study using Real World Data that aims to identify patterns of chronic multimorbidity in patients aged ≥65 years and their evolution and trajectories in the previous 10 years. The secondary objective is to identify the relationship between the trajectories of multimorbidity patterns in the previous 10 years and the severity of the infection by COVID-19.

Clinical Trial Description

Multimorbidity is associated with negative results and presents difficulties in clinical management. Recently, new methodologies are emerging based on the hypothesis that chronic conditions are associated in a non-random way forming multimorbidity patterns. However, there are few studies that study the temporal evolution and trajectories of these multimorbidity patterns, which could be associated with different prognoses and could allow better forecasting and planning. The primary objective of this analysis is to identify patterns of chronic multimorbidity in patients aged ≥65 years and their evolution and trajectories in the previous 10 years, using part of the MRisk-COVID project data. As a secondary objective, the investigators want to identify the relationship between the trajectories of multimorbidity patterns in the previous 10 years and the severity of the COVID-19 infection. This retrospective observational study has a historical cohort of 3958 patients ≥65 years of age suspected and confirmed of COVID-19 infection from February 1 to June 15, 2020 in the reference area of Parc Taulí University Hospital. The available data (real-world data) are socio-demographic and diagnostic variables provided by the Data Analytics Program for Research and Innovation in Health (PADRIS), which include sex, age and primary care diagnoses. To identify patterns of multimorbidity, the Clinical Classification Software, Chronic Condition Indicator, multiple correspondence analysis and cluster analysis using the fuzzy c-means algorithm will be used. Then, a clinical consensus process (Delphi-like) will be made of the clusters obtained. To identify the most probable trajectories along the three time points, each patient will be assigned to the cluster with the highest probability of membership. Descriptive and bivariate statistics will be performed. ;

Study Design

Related Conditions & MeSH terms

Chronic Disease

Clinical Trial Details

NCT number	NCT05717309
Study type	Observational
Source	Corporacion Parc Tauli
Contact
Status	Completed
Phase
Start date	February 10, 2022
Completion date	July 31, 2023

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Clinical trials are conducted in a series of steps, called phases - each phase is designed to answer a separate research question.

Phase 1: Researchers test a new drug or treatment in a small group of people for the first time to evaluate its safety, determine a safe dosage range, and identify side effects.
Phase 2: The drug or treatment is given to a larger group of people to see if it is effective and to further evaluate its safety.
Phase 3: The drug or treatment is given to large groups of people to confirm its effectiveness, monitor side effects, compare it to commonly used treatments, and collect information that will allow the drug or treatment to be used safely.
Phase 4: Studies are done after the drug or treatment has been marketed to gather information on the drug's effect in various populations and any side effects associated with long-term use.

Trajectories of Chronic Multimorbidity Patterns in Older Patients — MTOP

Clinical Trial Summary

Clinical Trial Description

Study Design

Related Conditions & MeSH terms