Cardiovascular disease is the main cause of hospitalization and death, which has a serious impact on the health of the elderly and is a huge public health burden. The overall health and prognosis of elderly people are influenced by frailty, comorbidity, general health status, and cardiovascular disease. As the aging population in China gradually intensifies, the number of elderly patients with coronary heart disease also increases. Frailty as a predictive indicator of adverse outcomes and healthy life expectancy in elderly patients with coronary heart disease, early and effective identification is of great significance for improving patient prognosis. According to data from the European Heart Rehabilitation Center, the incidence of frailty in elderly patients with coronary heart disease ranges from 10–48%[15]. This study found that the incidence of frailty is 30.07%, which is similar to previous domestic studies (33.48%) [8]. Due to the decline in physiological reserve function of various organ systems in the elderly, coupled with the interaction between frailty and coronary heart disease, the mechanism of occurrence is relatively complex, causing the body to continue to be in a state of continuous consumption, reducing the ability to maintain stability of various organ systems, reducing tolerance, and increasing susceptibility. This may be the reason for the higher incidence of frailty in elderly patients with coronary heart disease. A large cohort study in the United States showed a 33% decrease in heart disease mortality rate at 5 years after percutaneous coronary intervention, but an increase of 57% in non cardiac mortality[16], suggesting that predictive factors for non cardiac mortality are related to the quality of life of cardiovascular disease patients. And previous studies have confirmed that frailty is closely related to the prognosis of patients[17]. Although frailty has important predictive value for prognosis, it is rarely evaluated in clinical practice. Therefore, it is necessary to improve awareness of frailty, and strengthen the management of frailty in elderly CHD, as early as possible to be identified, and appropriate intervention measures should be given to reduce the occurrence of frailty and improve patient prognosis.
In 2012, the International Weakness Working Group emphasized that physiological frailty can be reversed and recommended clinical frailty assessment for individuals aged ≥ 70 years old. The most commonly used evaluation method currently is the frailty phenotype, according to the frailty phenotype, frailty can be divided into three states based on phenotype: non frailty, pre frailty, and frailty. Different states exhibit dynamic changes in the development of the disease. Therefore, identifying high-risk populations for frailty as early as possible and taking intervention measures can delay or reverse the frailty state. Due to the higher risk of frailty in pre frail patients and their sensitivity to intervention measures[18], this highlights the necessity of screening for frailty and early intervention measures to reverse the progression of frailty. Due to the late start of frailty assessment for coronary heart disease patients in China and the lack of routine screening in clinical practice, it is recommended to establish identification and management standards for frailty in coronary heart disease patients, attach importance to comprehensive assessment of frailty in elderly coronary heart disease patients, regularly use accurate and reliable tools for frailty screening in coronary heart disease patients, and actively treat the disease, Combining individualized characteristics to screen specific risk factors for optimization and management, providing health education and lifestyle guidance to coronary heart disease patients at risk of frailty, in order to improve patient prognosis.
Health status is an important indicator that affects patient recovery and is related to disease prognosis. The poorer the health status, the greater the risk of weakness. The WHO recommends it as a comprehensive indicator for measuring human health status[19]. This study found through multivariate logistic regression analysis that elderly coronary heart disease patients with poor health conditions have a higher risk of frailty (OR = 70.885, 95% CI: 9.259–142.710), which is consistent with the research results of CURCIO et al[20]. Due to the poorer self perceived health status of elderly patients, they are more likely to adopt negative self-protection or ineffective coping behaviors, which can accelerate the deterioration of their health status and lead to various frailty issues. This result suggests that medical personnel should pay attention to screening for frailty in patients with poor self-evaluation of health, adopt intervention measures to improve individual health status and prevent frailty. At the same time, for patients with low self-efficacy, they should assist them in actively coping and establishing and enhancing confidence in overcoming the disease, and timely targeted interventions should be carried out to prevent further deterioration of frailty. This study's univariate analysis found that comorbidities have a statistically significant impact on patient frailty (P < 0.05), which is consistent with previous studies [21]. This study found that comorbidities are an independent risk factor for frailty, and elderly patients with ≥ 4 diseases have a 27-fold increased risk of frailty. This is because when there are more chronic diseases, the body is in a chronic consumption state, and tolerance is reduced, and various chronic diseases also have a certain promoting effect on the occurrence of frailty, Therefore, elderly coronary heart disease patients with multiple coexisting diseases are more likely to experience frailty, which suggests that medical staff should pay special attention to coronary heart disease patients with multiple coexisting diseases and appropriately increase the frequency of frailty screening.
IADL is used to evaluate patients' self-care ability, which focuses on the ability of elderly people to live independently and engage in social interaction activities, including multiple daily living abilities such as shopping, cooking, taking medication, and taking transportation. A decrease in IADL is more common among elderly people. Weakness is a state that lies between health and disability. Impairment of self-care ability can lead to frailty, and disability is also one of the adverse consequences for frail patients. This study shows that IADL is an independent risk factor for frailty in elderly patients with coronary heart disease (OR = 3.131, 95% CI: 1.560–6.287), which suggests that impaired IADL assessment function is a risk factor for frailty in the elderly, and foreign scholar Atkins [22] has also confirmed this viewpoint. Impaired ability to live assessment is a common phenotype in frail patients. A decrease in IADL indicates physical weakness and decreased autonomous activity in elderly patients. Impaired IADL promotes the occurrence and development of frailty, which can further exacerbate dysfunction, and the two interact with each other. Therefore, routine assessment of IADL is of great significance for early detection of frailty. Medical staff should strengthen their attention to frailty in elderly patients with coronary heart disease, and guide them to improve or prevent frailty through daily life exercise. However, as the occurrence of frailty is the result of multiple factors working together, in clinical work, we cannot only focus on physical disorders and functional impairment, but also ignore the importance of other factors for the occurrence of frailty. Therefore, a comprehensive evaluation of multiple factors should be combined.
This study suggests that frequent social activity is a protective factor for frailty in elderly patients with coronary heart disease (OR = 0.169, 95% CI: 0.110–0.261), indicating that social participation reduces the risk of frailty in patients with coronary heart disease, consistent with the results of Bunt et al[23]. The reason for this is that social status, as one of the main factors affecting the physical and mental health of elderly people, often participating in social activities can stimulate intelligence and obtain emotional support. Lack of communication or communication barriers with others, social skill deficiencies, lack of companionship, and other factors can easily lead to loneliness and lack of security, thereby losing confidence in recovery, and to some extent, promoting the occurrence of frailty. Lack of social participation is considered a lack of resources to meet a person's basic social needs, and meeting social needs is necessary for fully unleashing self-efficacy. For patients with coronary heart disease who lack social participation, attention should be paid to cultivating their sense of self-efficacy and encouraging them to participate in social activities appropriately based on their actual physical conditions. Previous studies[24]have shown that social activities can not only promote appropriate physical activity, strengthen physical fitness, improve sleep quality, and improve health status in elderly patients with coronary heart disease; It can also promote the harmonious development of body and mind, and enrich the daily life of patients. Therefore, medical staff should develop a gradual social activity plan based on the patient's age, physical condition, exercise habits, etc., which is of great significance for improving patient health and delaying frailty.
Model validation usually requires evaluating the discrimination and calibration dimensions of the model, and the accuracy of risk prediction results will directly affect the selection and effectiveness of preventive measures. This study evaluated the distinguishability and calibration of the predictive model through ROC curves and Hosmer Lemeshow tests. The results showed that the area under the ROC curve was 0.837, the sensitivity was 0.798, the specificity was 0.792, and the accuracy was 80.4%. It has good distinguishability and accuracy, which is conducive to identifying high-risk individuals with weakness. In the internal validation of the model, the C-value is 0.8367, and a value greater than 0.7 indicates good model resolution. The uncorrected and corrected calibration curves in the classification calibration curve are closely aligned with the reference line, indicating that the probability of predicting patient weakness is close to the actual incidence rate, indicating that the column chart has a high degree of calibration. A column chart is a flat graph with graduated line segments based on multivariate regression results. Its essence is a simple visual chart of the regression equation[25]. A vertical line is drawn for each variable towards the scoring standard, and the total score corresponding to the risk value obtained by adding the scores of each variable is the predicted probability value of the frailty risk of elderly coronary heart disease patients. For example, a certain smoking elderly coronary heart disease patient (26 points) has average health status (50 points), No social activity (58 points), impaired IADL function (38 points), a total score of 172 points, corresponding to a frailty risk value of 0.55. The higher the score, the higher the risk of frailty. Therefore, the frailty risk prediction model for elderly coronary heart disease patients based on column charts can provide personalized, high-precision, and quantifiable frailty risk assessment for such patients, which has clinical practicality. Due to the multifactorial impact of frailty, the model constructed in this study covers four aspects of patients' individual health status, social participation, personal lifestyle habits, and IADL. Medical staff can use this model to assess the risk of frailty in patients, screen high-risk populations early, take effective prevention and care measures as soon as possible, achieve early prevention and intervention, and reduce the incidence of frailty.
The incidence of frailty in elderly patients with coronary heart disease is high, and medical staff should pay attention to it. They should actively carry out screening for frailty in elderly patients with coronary heart disease, conduct early assessment and intervention based on risk factors, strengthen knowledge education, and develop intervention plans to reduce the occurrence of frailty. The predictive model of frailty risk column chart based on logistic regression results has good discrimination and calibration, providing a visual quantitative risk assessment tool for medical staff to evaluate frailty, which can be used for clinical reference. The drawback is that although this study is a multicenter study, due to limited sample size, only internal validation was conducted during model validation. The external efficacy of the model needs further revision and validation in the future to better apply to clinical practice and be widely used in patients with coronary heart disease.