The Application of an AI-driven Multimodal Predictive Model for Cognitive Impairment in Patients With Type 2 Diabetes Mellitus
Trial Parameters
Brief Summary
The objective of this observational study is to evaluate the accuracy and feasibility of an artificial intelligence-based multimodal cognitive screening system in early identification of diabetes-related mild cognitive impairment (MCI) among type 2 diabetes mellitus (T2DM) patients through a 3-5 year follow-up. It also aims to analyze the correlation between diabetic metabolic indicators (such as glycemic variability and HbA1c levels) and cognitive function changes, thereby determining the value of this intelligent screening system in early detection and intervention of cognitive impairment in T2DM patients, which constitutes the key focus of this research.
Eligibility Criteria
Inclusion Criteria: Inclusion Criteria 1. Diagnosed with type 2 diabetes mellitus (T2DM). 2. Aged 40-75 years, with self-reported or informant-reported memory complaints. 3. Cognitive assessment scores consistent with either: * Cognitive Normal (CN) or * Mild Cognitive Impairment (MCI). 4. Preserved ability to perform basic activities of daily living (ADLs). 5. Memory-specific deficits only (e.g., partial forgetfulness), with intact other cognitive domains (e.g., reasoning, judgment, attention, and executive function). Exclusion Criteria: 1. Other types of diabetes (e.g., type 1 diabetes, gestational diabetes). 2. Education level \<6 years. 3. Metabolic disorders that may affect cognition, including: * Acute carbohydrate metabolism events within 3 months (e.g., severe hypoglycemia, diabetic ketoacidosis, hyperglycemic hyperosmolar state). * Hypothyroidism or other endocrine disorders. 4. Neurological/psychiatric conditions that may impair cognition: * History of head trauma, depression