Objective To analyze the risk factors of heart failure in patients with coronary heart disease(CHD),and to construct and verify a nomogram prediction model for the risk of heart failure in patients with CHD.Methods The clinical data of 453 patients with CHD who were hospitalized in the Second Affiliated Hospital of Shenyang Medical College from January to December 2022 were retrospectively analyzed,including 278 patients with CHD combined with heart failure and 175 patients without heart failure.The patients were divided into training group(318 cases)and validation group(135 cases)according to the ratio of 7:3.R software was applied to perform LASSO regression to screen the risk factors,and Logistic regression to establish a prediction model and construct a nomogram.The calibration curve and receiver operating characteristic(ROC)curve were used to evaluate the calibration and discrimination of the model.Results LASSO regression analysis ultimately screened five risk factors from 22 variables,and Logistic regression results showed that age,smoking,history of myocardial infarction,New York Heart Association(NYHA)cardiac function class Ⅳ,and left ventricular ejection fraction(LVEF)were all independent risk factors for heart failure in CHD patients(P＜0.05).The model formula was Z=-2.927+0.045 × age+0.886 × smoking+0.808 × history of myocardial infarction-2.829 × NYHA cardiac function class Ⅳ+0.037×LVFF.Internal validation of the model showed that area under the curve was 0.727(95％CI:0.588-0.752),the sensitivity was 40.4％,the specificity was 84.3％,and the Youden index was 0.247.According to the calibration curve,the predicted value of the calibration curve was highly consistent with the actual value,and the Brier score was 0.106.Conclusion The risk prediction model for heart failure in patients with CHD based on LASSO regression has good discrimination and prediction efficiency,which can be used as an evaluation tool for medical staff to predict the risk of patients.

Objective:To understand the current situation of nurses in 52 hospitals in China on mastery of knowledge about skin injury in the elderly based on the background of mixed-mode homogenization training.Methods:Using the convenient sampling method, a total of 1 067 nurses from 52 hospitals in China were selected as the research objects in January 2021. A self-designed questionnaire on knowledge of skin injury in the elderly was used to investigate the nurses through the questionnaire star and univariate analysis was used to analyze the influencing factors. A total of 1 067 questionnaires were distributed and 1 067 valid questionnaires were recovered, and the effective recovery rate was 100%.Results:The knowledge scores of pressure injury, incontinence-associated dermatitis, skin tear and xerosis cutis among 1067 nurses were (95.66±7.37) , (95.65±9.15) , (91.37±15.45) and (87.67±15.91) , respectively. The results of univariate analysis showed that hospital grade was the influencing factor of nurses' knowledge score of pressure injury, skin tear and incontinence-associated dermatitis ( P<0.05) , educational background was the influencing factor of nurses' knowledge score of skin tear ( P<0.05) , professional title was the influencing factor of nurses' knowledge scores of pressure injury, incontinence-associated dermatitis and xerosis cutis ( P<0.05) . Conclusions:Hospitals at all levels need to strengthen the theoretical and practical knowledge training for nurses on skin xerosis and skin tear in the elderly, especially for nurses with primary titles and lower education in grassroots hospitals.