Identifying Top Predictors of Change in Noncalcified Coronary Burden in Psoriasis by Machine Learning Over 1-Year
| Autor: | Marcus Y. Chen, Eric Munger, Amit K. Dey, Joel M. Gelfand, Justin A. Rodante, Xin Tian, Ahmed A. K. Hasan, Alexander V. Sorokin, Nehal N. Mehta, Colin O. Wu, Mohsin S. Jafri, Martin P. Playford |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
business.industry
Coronary computed tomography angiography Dermatology 030204 cardiovascular system & hematology Machine learning computer.software_genre medicine.disease Coronary artery disease 03 medical and health sciences 0302 clinical medicine Rheumatology Psoriasis medicine 030212 general & internal medicine Artificial intelligence business computer |
| Zdroj: | Journal of Psoriasis and Psoriatic Arthritis. 6:113-117 |
| ISSN: | 2475-5311 2475-5303 |
| DOI: | 10.1177/24755303211000757 |
| Popis: | Background: Psoriasis is associated with accelerated non-calcified coronary burden (NCB) by coronary computed tomography angiography (CCTA). Machine learning (ML) algorithms have been shown to effectively identify cardiometabolic variables with NCB in cross-sectional analysis. Objective: To use ML methods to characterize important predictors of change in NCB by CCTA in psoriasis over 1-year of observation. Methods: The analysis included 182 consecutive patients with 80 available variables from the Psoriasis Atherosclerosis Cardiometabolic Initiative, a prospective, observational cohort study at baseline and 1-year using the random forest regression algorithm. NCB was assessed at baseline and 1-year from CCTA. Results: Using ML, we identified variables of high importance in the context of predicting changes in NCB. For the cohort that improved NCB (n = 102), top baseline variables were cholesterol (total and HDL), white blood cell count, psoriasis area severity index score, and diastolic blood pressure. Top predictors of 1-year change were change in visceral adiposity, white blood cell count, total cholesterol, c-reactive protein, and absolute lymphocyte count. For the cohort that worsened NCB (n = 80), the top baseline variables were HDL cholesterol related including apolipoprotein A1, basophil count, and psoriasis area severity index score, and top predictors of 1-year change were change in apoA, apoB, and systolic blood pressure. Conclusion: ML methods ranked predictors of progression and regression of NCB in psoriasis over 1 year providing strong evidence to focus on treating LDL, blood pressure, and obesity; as well as the importance of controlling cutaneous disease in psoriasis. |
| Databáze: | OpenAIRE |
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