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Predictors of Co-occurring Cardiovascular and Gastrointestinal Disorders among Elderly with Osteoarthritis

OBJECTIVE: To identify the leading predictors of co-occurring cardiovascular or gastrointestinal disorders (CV-GID) in a real-world cohort of elderly with osteoarthritis (OA). METHOD: An observational retrospective cohort study using data from Optum’s deidentified Clinformatics® Data Mart was conduc...

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Autores principales: Patel, Jayeshkumar, Ladani, Amit, Sambamoorthi, Nethra, LeMasters, Traci, Dwibedi, Nilanjana, Sambamoorthi, Usha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9718072/
https://www.ncbi.nlm.nih.gov/pubmed/36474979
http://dx.doi.org/10.1016/j.ocarto.2021.100148
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author Patel, Jayeshkumar
Ladani, Amit
Sambamoorthi, Nethra
LeMasters, Traci
Dwibedi, Nilanjana
Sambamoorthi, Usha
author_facet Patel, Jayeshkumar
Ladani, Amit
Sambamoorthi, Nethra
LeMasters, Traci
Dwibedi, Nilanjana
Sambamoorthi, Usha
author_sort Patel, Jayeshkumar
collection PubMed
description OBJECTIVE: To identify the leading predictors of co-occurring cardiovascular or gastrointestinal disorders (CV-GID) in a real-world cohort of elderly with osteoarthritis (OA). METHOD: An observational retrospective cohort study using data from Optum’s deidentified Clinformatics® Data Mart was conducted. Elderly with OA were identified in 2015 and were followed for two years to identify co-occurring CV-GID including ischemic heart disease, stroke, heart failure, dyspepsia, gastroesophageal reflux disorder, and peptic ulcer disease. Random Forest (RF) and Partial Dependence Plots (PDP) were used to identify the leading predictors of CV-GID and to examine their associations. Multivariable logistic regression was also used to examine the association of the leading predictors with CV-GID. RESULTS: Our study cohort consisted of 45,385 elderly with OA (mean age 76.0 years). CV-GID were present in 59% of elderly. Using RF, age was found to be the strongest predictor of CV-GID followed by cardiac arrhythmia, duration of opioid use, number of orthopedist or physical therapy visits, number of intra-articular corticosteroid injections, polypharmacy, duration of non-selective nonsteroidal anti-inflammatory drugs or oral corticosteroids, and hypertension. The PDPs demonstrated that higher age, cardiac arrhythmia, longer durations of opioid or oral corticosteroids, higher number of physical therapy visits or intra-articular corticosteroid use, polypharmacy, and hypertension were associated with a higher risk of CV-GID. CONCLUSION: CV-GIDs are common among elderly with OA and can be predicted based on certain clinical factors. Machine learning methods with PDPs can be used to improve the interpretability and inform decision-making.
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spelling pubmed-97180722022-12-05 Predictors of Co-occurring Cardiovascular and Gastrointestinal Disorders among Elderly with Osteoarthritis Patel, Jayeshkumar Ladani, Amit Sambamoorthi, Nethra LeMasters, Traci Dwibedi, Nilanjana Sambamoorthi, Usha Osteoarthr Cartil Open ORIGINAL PAPER OBJECTIVE: To identify the leading predictors of co-occurring cardiovascular or gastrointestinal disorders (CV-GID) in a real-world cohort of elderly with osteoarthritis (OA). METHOD: An observational retrospective cohort study using data from Optum’s deidentified Clinformatics® Data Mart was conducted. Elderly with OA were identified in 2015 and were followed for two years to identify co-occurring CV-GID including ischemic heart disease, stroke, heart failure, dyspepsia, gastroesophageal reflux disorder, and peptic ulcer disease. Random Forest (RF) and Partial Dependence Plots (PDP) were used to identify the leading predictors of CV-GID and to examine their associations. Multivariable logistic regression was also used to examine the association of the leading predictors with CV-GID. RESULTS: Our study cohort consisted of 45,385 elderly with OA (mean age 76.0 years). CV-GID were present in 59% of elderly. Using RF, age was found to be the strongest predictor of CV-GID followed by cardiac arrhythmia, duration of opioid use, number of orthopedist or physical therapy visits, number of intra-articular corticosteroid injections, polypharmacy, duration of non-selective nonsteroidal anti-inflammatory drugs or oral corticosteroids, and hypertension. The PDPs demonstrated that higher age, cardiac arrhythmia, longer durations of opioid or oral corticosteroids, higher number of physical therapy visits or intra-articular corticosteroid use, polypharmacy, and hypertension were associated with a higher risk of CV-GID. CONCLUSION: CV-GIDs are common among elderly with OA and can be predicted based on certain clinical factors. Machine learning methods with PDPs can be used to improve the interpretability and inform decision-making. Elsevier 2021-03-11 /pmc/articles/PMC9718072/ /pubmed/36474979 http://dx.doi.org/10.1016/j.ocarto.2021.100148 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle ORIGINAL PAPER
Patel, Jayeshkumar
Ladani, Amit
Sambamoorthi, Nethra
LeMasters, Traci
Dwibedi, Nilanjana
Sambamoorthi, Usha
Predictors of Co-occurring Cardiovascular and Gastrointestinal Disorders among Elderly with Osteoarthritis
title Predictors of Co-occurring Cardiovascular and Gastrointestinal Disorders among Elderly with Osteoarthritis
title_full Predictors of Co-occurring Cardiovascular and Gastrointestinal Disorders among Elderly with Osteoarthritis
title_fullStr Predictors of Co-occurring Cardiovascular and Gastrointestinal Disorders among Elderly with Osteoarthritis
title_full_unstemmed Predictors of Co-occurring Cardiovascular and Gastrointestinal Disorders among Elderly with Osteoarthritis
title_short Predictors of Co-occurring Cardiovascular and Gastrointestinal Disorders among Elderly with Osteoarthritis
title_sort predictors of co-occurring cardiovascular and gastrointestinal disorders among elderly with osteoarthritis
topic ORIGINAL PAPER
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9718072/
https://www.ncbi.nlm.nih.gov/pubmed/36474979
http://dx.doi.org/10.1016/j.ocarto.2021.100148
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