Machine Learning-Assisted Analysis of Sublingual Microcirculatory Dysfunction for Early Cardiovascular Risk Evaluation and Cardiovascular-Kidney-Metabolic Syndrome Stage in Patients With Type 2 Diabetes Mellitus.

Autor: Liu W; Department of Hypertension and Endocrinology, Daping Hospital, Center for Hypertension and Metabolic Diseases, Army Medical University of PLA, Chongqing Institute of Hypertension, Chongqing, China., Wang W; Department of Hypertension and Endocrinology, Daping Hospital, Center for Hypertension and Metabolic Diseases, Army Medical University of PLA, Chongqing Institute of Hypertension, Chongqing, China., Sun F; Department of Hypertension and Endocrinology, Daping Hospital, Center for Hypertension and Metabolic Diseases, Army Medical University of PLA, Chongqing Institute of Hypertension, Chongqing, China., Jiang N; Department of Hypertension and Endocrinology, Daping Hospital, Center for Hypertension and Metabolic Diseases, Army Medical University of PLA, Chongqing Institute of Hypertension, Chongqing, China., Yuan L; Department of Hypertension and Endocrinology, Daping Hospital, Center for Hypertension and Metabolic Diseases, Army Medical University of PLA, Chongqing Institute of Hypertension, Chongqing, China., Bu X; Department of Hypertension and Endocrinology, Daping Hospital, Center for Hypertension and Metabolic Diseases, Army Medical University of PLA, Chongqing Institute of Hypertension, Chongqing, China., Shu W; Department of Hypertension and Endocrinology, Daping Hospital, Center for Hypertension and Metabolic Diseases, Army Medical University of PLA, Chongqing Institute of Hypertension, Chongqing, China., Li Q; Department of Hypertension and Endocrinology, Daping Hospital, Center for Hypertension and Metabolic Diseases, Army Medical University of PLA, Chongqing Institute of Hypertension, Chongqing, China., Zhu Z; Department of Hypertension and Endocrinology, Daping Hospital, Center for Hypertension and Metabolic Diseases, Army Medical University of PLA, Chongqing Institute of Hypertension, Chongqing, China.
Jazyk: angličtina
Zdroj: Diabetes/metabolism research and reviews [Diabetes Metab Res Rev] 2024 Sep; Vol. 40 (6), pp. e3835.
DOI: 10.1002/dmrr.3835
Abstrakt: Aims: To examine whether sublingual microcirculation can be used as an effective and noninvasive method for assessing cardiovascular, kidney, and metabolic risks in patients with type 2 diabetes mellitus (T2DM).
Materials and Methods: This cross-sectional observational study enrolled 186 patients with T2DM. All patients were evaluated using the Framingham General Cardiovascular Risk Score (FGCRS) and cardiovascular-kidney-metabolic (CKM) syndrome stage. Side-stream dark-field microscopy was used for sublingual microcirculation, including total and perfused vessel density (TVD and PVD). Multiple machine-learning prediction models have been developed for CKM risk and stage assessment in T2DM patients. Receiver operating characteristic (ROC) curves were generated to determine cutoff points.
Results: Compared to patients with T2DM, diabetic patients with subclinical atherosclerosis (SA) had a greater CV risk, as measured by the FGCRS, accompanied by markedly decreased microcirculation perfusion. Microcirculatory parameters (TVD and PVD), including carotid intima-media thickness (IMT), brachial-ankle pulse wave velocity (ba-PWV), and FGCRS, were closely associated with SA incidence. Microcirculatory parameters, Index (DM SA screen ), and cut-off points were used to screen for SA in patients with T2DM. Furthermore, a new set of four factors identified through machine learning showed optimal sensitivity and specificity for detecting CKM risk in patients with T2DM. Decreased microcirculatory perfusion served as a useful early marker for CKM syndrome risk stratification in patients with T2DM without SA.
Conclusions: Sublingual microcirculatory dysfunction is closely correlated with the risk of SA and CKM risk in T2DM patients. Sublingual microcirculation could be a novel tool for assessing the CKM syndrome stage in patients with T2DM.
(© 2024 John Wiley & Sons Ltd.)
Databáze: MEDLINE
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