Theresa Koleck

Early Career Tenure-track Researcher, University of Pittsburgh

1 active project

Symptom Clusters in Chronic Conditions

Over half of all American adults ≥18 years of age are living with one or more chronic conditions such as cancer, heart failure, type 2 diabetes mellitus, or chronic obstructive pulmonary disease (COPD). Many experience multiple symptoms (e.g., pain, fatigue,…

Scientific Questions Being Studied

Over half of all American adults ≥18 years of age are living with one or more chronic conditions such as cancer, heart failure, type 2 diabetes mellitus, or chronic obstructive pulmonary disease (COPD). Many experience multiple symptoms (e.g., pain, fatigue, disturbed sleep, depressed mood, anxiety, nausea, shortness of breath) either related to the chronic condition and/or its treatment. Symptom clusters are defined as two or more co-occurring, related symptoms. Symptom clusters are challenging to manage and burden both the patient and healthcare system. However, symptom clusters in chronic conditions are understudied and poorly understood. We believe that we can generate new knowledge to improve patient symptom management by using All of Us data. We plan to perform data-driven characterization of symptom clusters in patients diagnosed with one or more chronic conditions and explore predictors (e.g., clinical, genetic, and environmental biomarkers) of different symptom clusters.

Project Purpose(s)

  • Disease Focused Research (Chronic conditions (e.g., cancer, heart failure, diabetes mellitus, COPD))

Scientific Approaches

We will use All of Us Research Program participant data, including electronic health record domains (e.g., conditions, drug exposures, labs & measurement), survey questions (e.g., basics, overall health, lifestyle, personal medical history, health care access & utilization), physical measurements, wearables, and genetic information, and statistical analysis methods (e.g., factor analysis, cluster analysis, regression) to characterize chronic condition symptom clusters and explore predictors of symptom clusters in patients diagnosed with chronic conditions.

Anticipated Findings

The anticipated findings from this study include symptom cluster(s) for various chronic conditions and predictors of the symptom clusters. We hypothesize that a core set of symptom clusters is shared among all common chronic conditions. We further hypothesize that distinct symptom clusters characterize specific conditions and/or treatments. We hope that this study will help us to understand physiological mechanisms underlying symptom development and lead to improved patient symptom management.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

  • Theresa Koleck - Early Career Tenure-track Researcher, University of Pittsburgh

Collaborators:

  • Alex Conway - Project Personnel, University of Pittsburgh
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