| Objectives:This study used the holistic model of cardiovascular health as a theoretical framework to explore the incidence of cognitive frailty in hospitalized elderly patients with chronic heart failure and analyze its related influencing factors.A questionnaire survey was used to collect relevant information to explore the correlation between age,gender and other variables and cognitive frailty and its mechanism.Based on the above factors,a model was developed to predict the risk of cognitive frailty in hospitalized elderly patients with chronic heart failure,aiming to provide a new tool for clinical medical staff and social workers.Through this screening tool,the signs of cognitive frailty can be detected as early as possible,and scientific interventions can be developed based on potential reversible risk factors to reduce its incidence.So as to provide decision support for improving the poor clinical outcomes of patients.Methods:In this study,convenience sampling was used to select elderly patients with chronic heart failure who met the inclusion criteria in a hospital in Shandong Province as the research objects,and the time span was from August 2021 to September 2022,and a cross-sectional study was conducted.Clinical observation and medical record information were collected.FRAIL frailty scale and MoCA scale were used to evaluate the physical and cognitive function of patients to assess their cognitive frailty status.Questionnaire survey was conducted and the results were recorded.By using the self-designed general information questionnaire,Mini nutritional Assessment-short form(MNA-SF),Athens Insomnia Scale(AIS),Scale of Loneliness(ULCA),Geriatric Depression Scale(GDS-5),Social support rating scale(SSRS)and modified Barthel index(MBI),The related influencing factors of cognitive frailty were evaluated.For the statistical analysis part,we used SPSS 26.0 and R 4.1.2 software for detailed data analysis.Firstly,the subjects were classified into two different groups of cognitive frailty and non-cognitive frailty,and descriptive statistical analysis was carried out.Secondly,univariate and multivariate regression analyses were performed for variables that might have a negative impact on cognitive frailty,and variables with significant differences between the two groups(P<0.05)were included in the risk prediction model;Finally,R 4.1.2 software was used to generate a Nomogram,and the area under the receiver operating characteristic curve(AUC)and Bootstrap method were used to evaluate the goodness of fit and prediction performance of the model.Results:1.The incidence of cognitive frailty is high in hospitalized elderly patients with chronic heart failureThe results showed that 165 hospitalized elderly patients with chronic heart failure had cognitive frailty,with an incidence of 50.5%.There were 162 patients(49.5%)without cognitive frailty.There were 195 patients(59.6%)with physical frailty,90 patients(27.5%)with pre-frailty,and 42 patients(12.8%)without physical frailty.A total of 244 patients(74.6%)were judged to have mild cognitive impairment,while only 83 patients(25.4%)did not have mild cognitive impairment.2.There are many factors leading to the occurrence of cognitive frailty in hospitalized elderly patients with chronic heart failureAfter univariate analysis,18 variables were identified,Age,weekly physical activity,weekly intellectual activity,daily sleep duration,NYHA class,chronic pain,chewing ability,body mass index,serum albumin,lymphocyte count,N-terminal pro-brain natriuretic peptide,left ventricular ejection fraction,nutritional status,sleep status,loneliness,depression,social support,and activities of daily living Mobility,had a significant difference in influencing cognitive frailty(P<0.05);Through multivariate regression analysis,the scores of NYHA cardiac function classification,chewing ability,nutritional status,loneliness and sleep were statistically different(P<0.05).3.To develop and evaluate a model to predict the risk of cognitive frailty in older hospitalized patients with chronic heart failureThe regression model based on the above five variables showed that the AUC was 0.804(95%CI=0.756～0.851,P<0.001).Hosmer-Lemeshow test showed that there was no statistical difference,and the Brier score was 0.188,indicating that the constructed model fitted the actual data well.The cognitive frailty risk prediction model constructed by Nomogram showed a sensitivity of 77.2%and a specificity of 70.3%.After internal validation with 2000 Bootstrap samples,the AUC reached 0.788.The above results show that the model has good fitting degree and prediction performance,and can effectively predict the risk of cognitive frailty in hospitalized elderly patients with chronic heart failure.Conclusions:The incidence of cognitive frailty is high in hospitalized elderly patients with chronic heart failure,which is affected by many factors.The main influencing factors included NYHA cardiac function classification,chewing ability,nutritional status,loneliness,and sleep quality,which all affected the occurrence of cognitive frailty.The Nomogram risk prediction model constructed based on the above predictive factors has been verified to have good fitting degree and prediction performance,which can be used to early predict the risk of cognitive frailty in elderly patients with chronic heart failure and provides a new tool.The use of this tool helps clinical medical staff and social workers to quickly and intuitively identify patients at high risk of cognitive frailty at admission,so as to provide evidence support for the early development and implementation of personalized strategies. |
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