Literature DB >> 32563688

Intermountain chronic disease risk score (ICHRON) validation for prediction of incident chronic disease diagnoses in an australian primary prevention population.

Heidi T May1, Jeffrey L Anderson2, Joseph B Muhlestein2, Kirk U Knowlton3, Benjamin D Horne4.   

Abstract

BACKGROUND: The Intermountain Chronic Disease Risk Score (ICHRON) is a primary prevention risk prediction tool that uses commonly ordered blood tests and is designed to be calculated by the electronic health record. ICHRON was highly predictive of 3-year chronic disease (ChrD) diagnosis in an internal validation; however, external validation is needed.
METHODS: ICHRON was calculated among patients from a region of Australia using sex-specific weightings of age and components of the comprehensive metabolic panel and the complete blood count. Original ICHRON weightings and risk stratification thresholds from the US-based derivation at Intermountain Healthcare were used. ICHRON was evaluated as a predictor of an incident 3-year ChrD diagnosis (coronary artery disease, myocardial infarction, heart failure, atrial fibrillation, stroke, dementia, diabetes, renal failure, chronic obstructive pulmonary disease, and peripheral vascular disease).
RESULTS: A total 5,512 females (49.6 ± 19.2) and 3,461 males (53.0 ± 18.6) were studied. Among females, 50.3%, 33.7% and 16.0% were low, moderate, and high-risk, respectively; and for males, 39.6%, 35.0%, and 25.4%. Frequency of a 3-year ChrD diagnosis among females was 2.2%, 8.5%, and 15.9% for low, moderate, and high-risk groups, respectively, and 4.7%, 9.7%, and 20.0% among males. C-statistics were 0.726 (0.700, 0.752) for females and 0.694 (0.665, 0.724) for males.
CONCLUSION: ICHRON predicted ChrD diagnosis at 3-years among an external, geographically distant validation cohort. These findings show the value of ICHRON for primary care patients in distinct locales. Additionally, electronic calculation of ICHRON empowers the clinical use of this tool to identify and differentially manage and treat high-risk patients.
Copyright © 2020 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Chronic disease; Clinical decision tool; Practical parsimonious model; Precision medicine; Risk score

Mesh:

Year:  2020        PMID: 32563688     DOI: 10.1016/j.ejim.2020.06.009

Source DB:  PubMed          Journal:  Eur J Intern Med        ISSN: 0953-6205            Impact factor:   4.487


  1 in total

1.  An Augmented Artificial Intelligence Approach for Chronic Diseases Prediction.

Authors:  Junaid Rashid; Saba Batool; Jungeun Kim; Muhammad Wasif Nisar; Amir Hussain; Sapna Juneja; Riti Kushwaha
Journal:  Front Public Health       Date:  2022-03-31
  1 in total

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