Risk Prediction Of Debility In Elderly Patients With Chronic Cardiac Insufficiency Research On Model Construction

Objective: To understand the current situation of senile chronic cardiac insufficiency patients and explore its influencing factors,and to establish a prediction model of senile chronic cardiac insufficiency patients’ asthenia nomogram;The prediction model was verified and evaluated internally and externally to judge its prediction ability and clinical efficacy,providing reference for clinical personnel to identify frailty in the early stage.Methods: In this cross-sectional study,525 elderly patients with chronic cardiac insufficiency from March 2022 to November 2022 in a Grade-A hospital in Wuhu from March 2022 to November 2022 as the survey objects.They were divided into a modeling group of 368 cases and a validation group of 157 cases.General information questionnaire,laboratory related indicators,Health Literacy Management Scale(He LMS),Self efficacy for Exercise(SEE),Family Care Index questionaire(APGAR),Hospital Anxiety and Depression Scale(HADS)was used to collect patient data.Single factor and Logistic regression analysis were used to analyze the data of the modeling group.R language software was used to select stepwise regression method to obtain the predictors and construct the line graph model.Hosmer-Lemeshow(H-L)chi-square test and Receiver Operating Characteristic Curve(ROC)were used to evaluate the calibration ability and differentiation ability of the model,and the calibration curve was drawn to evaluate the predictive performance of the model.Bootstrap method was used for internal verification of the model,and group data was used for external verification of the model.Results:(1)101 of 368 patients with chronic cardiac insufficiency in the modeling group developed asthenia,and the prevalence rate of asthenia was 27.4%.Univariate analysis showed that there were statistically significant differences between the frailty group and the non-frailty group in age,weekly exercise frequency,cardiac function classification,whether there was a risk of depression and anxiety,whether there was a risk of malnutrition,whether there were more than 4 types of chronic diseases,creatinine,exercise self-efficacy,and chronic disease health literacy(P<0.05).The results of binary logistic regression showed that the number of exercises per week,whether there was a risk of malnutrition,types of chronic diseases>4,chronic disease health literacy score and exercise self-efficacy score were independent influencing factors for the occurrence of cardiac insufficiency(P<0.05).The results of the prediction model showed that the area under ROC curve was 0.969,95%CI: 0.954 ～ 0.985,and the AUC after re-sampling was 0.965 after 1000 times of internal verification by strengthening the Bootstrap method,indicating good differentiation and stability of the model.When the optimal risk critical value of this model is 0.186,its sensitivity is 0.876,specificity is0.970,and Yoden index is 0.846.The Hosmer-Lemeshow χ2 test value was 1.134,P=0.768(>0.05),indicating that the calibration degree of the model was good.The calibration curve showed that the fissile risk predicted by the model was consistent with the actual risk in the elderly patients with chronic cardiac dysfunction.(2)In the 157 patients with cardiac insufficiency in the validation group,45 patients developed asthenia,and the prevalence rate of asthenia was 28.7%.In the verification group,45 of the 157 patients with cardiac insufficiency had fattening,and the prevalence of fattening was 28.7%.The verification results showed that the C index was 0.918,95%CI :0.873 ～ 0.964.Hosmer-Lemeshow χ 2 The test value is 7.564,P=0.056(P>0.05),Calibration curve display that the predicted incidence probability of senile chronic cardiac insufficiency is in good agreement with the actual incidence probability.Conclusion: The nomograph model of aging chronic cardiac insufficiency was constructed in this study.Through internal and external verification and efficacy evaluation,we know that this model has good predictive ability,which can provide reference for clinical prediction of frailty risk and targeted intervention.