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

Abstract

Gou et al. (2024) recently conducted a cross-sectional study to systematically investigate the factors contributing to cognitive frailty in older adults diagnosed with chronic heart failure. Utilising advanced statistical techniques, notably LASSO-logistic regression, the researchers identified a range of predictive variables significantly associated with cognitive decline within this population. The study revealed that factors such as advancing age, lower monthly income, alcohol consumption, higher New York Heart Association (NYHA) classification, prolonged hospital stays, depression and malnutrition risk or malnutrition were among the most prominent predictors of cognitive frailty. The multifactorial nature of cognitive frailty, as demonstrated by these findings, underscores the critical need for a comprehensive approach to managing older patients with chronic heart failure. Addressing both physical and psychological health factors is essential, given their combined impact on cognitive outcomes. By identifying these specific risk factors, the study offers valuable insights that can guide healthcare providers in designing and implementing targeted interventions. Such interventions could potentially slow or prevent cognitive decline, ultimately improving the overall quality of life and clinical outcomes for this vulnerable patient group. Furthermore, this research contributes to the growing body of literature emphasising the relationship between physical health, mental well-being and cognitive function in geriatric populations with chronic illnesses. The findings of this study are both interesting and significant, as they contribute to reducing the risk of cognitive frailty in older people with chronic heart failure. We congratulate the authors on their contribution and would like to offer some of our perspectives to further elucidate the risks of cognitive frailty in this population.

Firstly, it is important to note that Gou et al. (2024) study included a cohort of 421 patients, of whom 134 (31.8%) were diagnosed with comorbid depression. Their study revealed that depression is independently associated with cognitive frailty among older individuals suffering from chronic heart failure. However, it is crucial to recognise that depression itself predisposes individuals to an increased risk of cognitive frailty, which complicates the interpretation of the observed associations (Arts et al. 2016; Kwan et al. 2019). For instance, a comprehensive meta-analysis (Zou et al. 2023) encompassing 15 studies reported an overall prevalence of depression of 46% (95% CI, 30%–62%; p < 0.0001) among patients with cognitive frailty. This meta-analysis underscores the complex relationship between cognitive frailty and depression, suggesting that these two conditions may mutually exacerbate each other. Therefore, the increased risk of cognitive frailty observed in Gou et al. study may be more attributable to the presence of depression rather than solely to the effects of chronic heart failure. This potential confounding factor necessitates a careful reevaluation of the study's conclusions, as failing to account for the influence of depression could lead to an overestimation of the role that chronic heart failure plays in the development of cognitive frailty. To address this issue and derive more precise conclusions, it would be advisable to conduct sensitivity and subgroup analyses. A sensitivity analysis could involve the exclusion of patients diagnosed with depression to isolate the effect of chronic heart failure on cognitive frailty. Alternatively, a subgroup analysis stratified by the presence or absence of depression could be performed. This approach would enable us to separate the independent contributions of depression and chronic heart failure to cognitive frailty, as well as explore the possibility of an interaction between these two conditions. By doing so, we can more accurately determine whether the observed cognitive frailty is primarily driven by depression, chronic heart failure or a synergistic effect of both conditions.

Secondly, it is widely accepted that haemoglobin and albumin are critical parameters utilised in clinical practice for assessing the nutritional status of patients. These biomarkers serve as essential indicators for indirectly evaluating the risk of malnutrition and provide a basis for clinical decision-making. However, as described in Table 1 of the study by Gou et al. (2024), there is no significant difference in the levels of haemoglobin (p = 0.790) and albumin (p = 0.132) between patients with non-cognitive frailty and those with cognitive frailty. In contrast, there is a significant difference in the proportion of malnutrition risk/malnutrition between these two groups (p < 0.001). This observation suggests a complex relationship between conventional nutritional parameters and the risk of malnutrition in older adults with chronic heart failure. The lack of correlation between traditional nutritional biomarkers like haemoglobin and albumin with malnutrition risk in this population highlights a critical gap in our current assessment tools. This finding underscores the challenges inherent in accurately evaluating the nutritional status of this vulnerable population, where conventional markers may fail to capture the multifaceted nature of malnutrition and its implications for cognitive health. Consequently, these results point to an urgent need for the identification and validation of more accurate and reliable nutritional biomarkers that can better predict both malnutrition risk and the onset of cognitive frailty in older people with chronic heart failure. The development of such biomarkers would not only improve clinical outcomes but also enhance our understanding of the underlying mechanisms linking nutritional status with frailty and cognitive decline in this vulnerable population.

The authors declare no conflicts of interest.