The Application of an AI-driven Multimodal Predictive Model for Cognitive Impairment in Patients With Type 2 Diabetes Mellitus

Обзор

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.

Вмешательства

• Другое follow-up observation
  In this study, no additional interventions were administered to any enrolled participants; only 3-5 years of follow-up observation were conducted, with cognitive status data collected at both baseline and endpoint.

Первичные конечные точки

• Early Identification Accuracy of the AI System [Срок оценки: From enrollment to the end of follow-up for 3-5 years]
• Cognitive Deterioration Rate [Срок оценки: From enrollment to the end of follow-up for 3-5 years]

Вторичные конечные точки (2)

• Association Between Diabetic Metabolic Indicators and Cognitive Decline [Срок оценки: From enrollment to the end of follow-up for 3-5 years]
• Predictive Value of Multimodal Data [Срок оценки: From enrollment to the end of follow-up for 3-5 years]

Критерии участия

Критерии включения

Критерии включения

• Diagnosed with type 2 diabetes mellitus (T2DM).
• Aged 40-75 years, with self-reported or informant-reported memory complaints.
• Cognitive assessment scores consistent with either:

• Cognitive Normal (CN) or
• Mild Cognitive Impairment (MCI).
• Preserved ability to perform basic activities of daily living (ADLs).
• Memory-specific deficits only (e.g., partial forgetfulness), with intact other cognitive domains (e.g., reasoning, judgment, attention, and executive function).

Критерии исключения

• Other types of diabetes (e.g., type 1 diabetes, gestational diabetes).
• Education level <6 years.
• 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.
• Neurological/psychiatric conditions that may impair cognition:

• History of head trauma, depression, anxiety, delirium, severe pulmonary/renal disease, heart failure, or malignancy.
• Substance abuse (past 2 years), including nicotine/alcohol dependence.
• Recent medication use (within 1 month):

• Anti-Parkinsonian drugs, antiepileptics, sedatives/hypnotics.
• Cognitive-enhancing drugs (e.g., donepezil, memantine).
• Inability to complete AI screening or follow-up due to:

• Speech/hearing/visual impairments or other disabilities

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Да

Дизайн исследования

Модель наблюдения

Когортное

Центры проведения

Китай · 21 центр

• Minda Hospital Affiliated to Hubei Minzu University — Enshi
• Huanggang Central Hospital — Huanggang
• Huangshi Central Hospital — Huangshi
• Jingzhou Central Hospital — Jingzhou
• Sinopharm Dongfeng General Hospital — Shiyan
• Suizhou Central Hospital — Suizhou
• Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology — Ухань
• China Resources & WISCO General Hospital — Ухань
• … и ещё 13 центров

Идентификаторы

NCT: NCT07128186 · TJ-IRB202503076

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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