A long-term prognosis predictive model of ejection fraction preserved HF elderly patients using two-dimensional speckle tracking technology
10.3969/j.issn.1009-0126.2024.10.005
- VernacularTitle:基于二维斑点追踪技术构建老年射血分数保留的心力衰竭患者远期预后的预测模型
- Author:
Zhiyong LI
1
;
Huaping FENG
;
Shengfeng LAN
;
Xing LI
Author Information
1. 333000 景德镇市第二人民医院超声科
- Keywords:
heart failure;
prognosis;
nomograms;
forecasting;
logistic models
- From:
Chinese Journal of Geriatric Heart Brain and Vessel Diseases
2024;26(10):1138-1142
- CountryChina
- Language:Chinese
-
Abstract:
Objective To construct a prediction model for the long-term prognosis of elderly pa-tients heart failure with preserved ejection fraction(HFpEF)based on two-dimensional speckle tracking technology.Methods A total of 312 elderly HFpEF patients admitted in our hospital from January 2017 to December 2018 were prospectively enrolled,and then randomly divided into a training set(218 cases)and a validation set(94 cases)in a ratio of 7∶3.After 5 years of follow-up,they were divided into a death group(n=128)and a survival group(n=184)according to having experienced cardiovascular death events or not.The main clinical characteristics were com-pared between the two groups,and the risk factors for cardiovascular death events were analyzed.A clinical prediction model was constructed based on the relevant risk factors with R4.0.3 statisti-cal software.Results The age,age ≥80 years,atrial fibrillation,chronic obstructive pulmonary disease(COPD),and early strain rate of global systole(GSRs)in the death group were signifi-cantly higher than those in the survival group,with statistical significances[(76.68±8.73)years vs(70.98±7.74)years,P＜0.01;34.4％vs 20.7％,P＜0.01;25.0％vs 11.4％,P＜0.01;26.6％vs 9.2％,P＜0.01;(-0.84±0.24)/s vs(-1.24±0.31)/s,P＜0.01].Multivariate logistic regression analysis showed that age ≥80 years,atrial fibrillation,COPD and GSRs＞-1.035 1/s were inde-pendent risk factors for cardiovascular death events(RR=2.196,95％CI:1.217-3.962,P=0.009;RR=2.242,95％CI:1.136-4.424,P=0.020;RR=3.631,95％CI:1.787-7.377,P=0.000;RR=6.199,95％CI:3.624-10.602,P=0.000).The AUC value of the training set was 0.822(95％CI:0.765-0.879),and that of the validation set was 0.790(95％CI:0.698-0.882).Conclusion Our constructed nomogram prediction model has high predictive value and reliability in predicting cardiovascular death events.
