Comment on ‘Associating Factors of Cognitive Frailty Among Older People With Chronic Heart Failure: Based on LASSO‐Logistic Regression’

We read with great interest the recent study on the association between cognitive frailty and chronic heart failure (CHF) in older adults (Gou et al. 2024). The study aimed to identify key factors contributing to cognitive frailty using LASSO-logistic regression. The authors analysed a cohort of older individuals with CHF and assessed various clinical and demographic factors, including comorbidities, biomarkers and functional assessments. Using LASSO-logistic regression, they identified significant associations between cognitive frailty and several factors, such as advanced age, alcohol consumption, NYHA classification and malnutrition risk/malnutrition. The study provides valuable insights into the complex relationship between CHF and cognitive decline in older adults, highlighting potential risk factors that could inform clinical care and interventions aimed at improving outcomes for this population. It is worth noting that this study found that malnutrition risk/malnutrition, a modifiable factor, is associated with an increased risk of cognitive frailty. Moreover, various strategies can be employed to improve the nutritional status of CHF patients, thereby reducing their risk of cognitive frailty. Therefore, we propose improving the nutritional status of CHF patients from the following perspectives. Firstly, healthcare professionals should conduct a thorough nutritional assessment for CHF patients, identifying any signs of malnutrition or nutritional deficiencies. This assessment should include evaluating dietary habits, weight history, body mass index (BMI) and laboratory markers such as serum albumin and cholesterol levels. Based on this assessment, a personalised nutritional plan should be developed, which may involve recommending nutrient-dense foods that are easy to digest, while also addressing specific deficiencies (e.g., protein, vitamins and minerals). For example, increasing the intake of foods rich in omega-3 fatty acids, antioxidants and high-quality protein can help manage both malnutrition and inflammation (Block et al. 2019; Djoussé et al. 2012). Given the fluid retention associated with CHF, healthcare professionals must ensure that the patient's fluid intake is balanced. An individualised fluid management plan, including monitoring and adjusting fluid restrictions as necessary, can help prevent further complications while promoting proper nutrition. To ensure the effectiveness of nutritional interventions, healthcare providers should regularly monitor the patient's weight, dietary intake and laboratory results. Follow-up appointments should be scheduled to assess progress and make any necessary adjustments to the nutrition plan. In addition, educating CHF patients and their families about the importance of nutrition and dietary choices is essential. Healthcare professionals should offer clear guidance on meal planning, cooking tips and the use of supplements if necessary. Encouraging patients to adhere to their nutrition plans and providing support through regular counselling can improve adherence. Secondly, family members can encourage CHF patients to follow a balanced diet by providing nutritious, easily accessible meals. This includes preparing meals rich in vegetables, fruits, whole grains, lean proteins and healthy fats. Family members can also tailor meals to the patient's specific needs, such as increasing protein intake or incorporating foods high in omega-3 fatty acids. Preparing meals that meet the patient's dietary requirements can be challenging, especially if the patient is fatigued or has limited mobility. In such cases, family members can take on the responsibility of meal planning and cooking, ensuring that the meals are both nutritious and within any necessary fluid restrictions. Additionally, family members should assist in monitoring the patient's food and fluid intake to ensure the right balance of nutrients and fluids. They can track daily meals, snacks and beverages, helping the patient adhere to any prescribed fluid restrictions. It is also crucial for CHF patients to eat regularly to maintain energy levels and prevent malnutrition. Family members can ensure that the patient eats small, frequent meals throughout the day, which are often easier to manage than larger meals. Thirdly, artificial intelligence (AI) (Khan et al. 2023; Averbuch et al. 2022) is a current research focus and plays an important role in improving the nutritional status of patients with CHF. AI can analyse vast amounts of patient data, including clinical history, laboratory results and dietary patterns, to generate personalised nutritional plans for CHF patients. By integrating data from electronic health records (EHRs) and real-time health monitoring, AI algorithms can identify nutrient deficiencies and suggest dietary adjustments tailored to each patient's unique needs. AI-driven predictive models can help identify patients at risk of malnutrition or cognitive frailty before it becomes clinically evident. These models can analyse trends in a patient's weight, fluid balance and other biomarkers over time, providing early warnings and enabling timely interventions to prevent the worsening of nutritional status. The use of wearable devices powered by AI could provide real-time monitoring of CHF patients' vital signs, including fluid retention and activity levels, which can directly impact nutritional needs. AI-powered devices could alert caregivers or healthcare providers to any changes in a patient's condition, allowing for prompt adjustments to nutrition plans or fluid restrictions. AI can assist in meal planning by suggesting recipes based on the patient's dietary restrictions and preferences. It can also be integrated with smart kitchen technology to automate meal preparation, ensuring that CHF patients receive meals that meet their specific nutritional requirements. Furthermore, AI-enabled food delivery services could ensure that meals are delivered on time and adhere to the patient's dietary needs. Moreover, AI can also assist in determining the optimal types and dosages of nutritional supplements for CHF patients. By analysing a patient's individual health data and deficiencies, AI can recommend the most effective supplements, improving the overall management of their nutritional needs. The authors declare no conflicts of interest. The authors have nothing to report.