Predictive value of nutritional status and serological indicators in elderly patients with mild cognitive impairment

Area of Science:

• Gerontology
• Neurology
• Epidemiology

Background:

• Mild cognitive impairment (MCI) represents a critical transitional phase between normal aging and dementia in older adults.
• Understanding MCI risk factors is vital for timely intervention and improving quality of life in the elderly population.

Purpose of the Study:

• To investigate the diverse risk factors associated with mild cognitive impairment (MCI) in an elderly cohort.
• To develop and validate a clinical prediction model for identifying individuals at high risk of MCI.

Main Methods:

• A cohort of 295 elderly individuals with memory loss was analyzed.
• Demographic, clinical, and serological data were collected and assessed using the Montreal Cognitive Assessment Scale.
• A predictive model for MCI likelihood was developed and evaluated for accuracy and calibration.

Main Results:

• Identified risk factors for MCI include advanced age, hypertension, diabetes, hyperlipidemia, smoking, and specific dietary habits (high-salt, high-cholesterol).
• Protective factors identified were a high-vitamin diet and elevated high-density lipoprotein cholesterol.
• The developed clinical prediction model demonstrated good differentiation and calibration capabilities.

Conclusions:

• Mild cognitive impairment (MCI) in the elderly is influenced by a multifactorial array of risk and protective elements.
• Early identification of high-risk individuals through predictive modeling is essential for effective intervention strategies.
• Improving the quality of life for elderly individuals affected by MCI can be achieved through proactive risk management.