Study On Assessment Model For Heart Failure

Heart failure is a serious stage of various heart diseases. Due to its high morbidity and mortality, heart failure has become a worldwide public health problem. However, the diagnostic rate and the control rate of heart failure in clinic are very low, which is mainly ascribed to the lack of effective assessment methods for heart failure.By means of engineering technology and medical knowledge, a heart failure disease assessment model based on physiological parameters was established. This model is able to stratify heart failure into ACC/AHA stages and give comprehensive quantitative scores. The main work and achievements are summarized as follows:1) Analyze clinical data, and obtain heart failure characteristic parameters.2) Stratify heart failure with the aid of support vector machine algorithm (SVM).3) Utilize fuzzy multi-level analysis to assess heart failure:firstly, employ cluster analysis to classify physiological parameters into seven catalogs, apply membership function to obtain fuzzy membership of physiological parameters, then produce grade indexes through a weighted sum of fuzzy membership, finally calculate the weighted sum of the grade indexes to gain a comprehensive score. The involved physiological parameters and a target weights are achieved by Matrix methods and principal component analysis.4) Use the established model to classify and score heart failure, apply and verify the model in clinical cases.The results show that, the cataloged seven indexes, i.e. cardiac function, cardiac structure, fluid overload, exercise tolerance, electronic physiology parameters, biochemistry parameters and neural activity have distinguished physiological and clinical meanings. The total stratification accuracy in 108 cases is 81.5%, and the accuracies for Health/A stage, B and C stage are 83.9%,82.9% and 75.8%, respectively. Furthermore, the model successfully detected 20 cases, which are misclassified in clinic. Tested in 237 cases, the given scores for the three stages of ACC/ACH are significantly different.In conclusion, the developed model achieved effective stratification in heart failure and the scores indicate the severity of heart failure properly. Since the model is quantitative and objective, it helps reduce the subjective errors in clinical assessment. The model provides a new approach for the valuation of heart failure and has a great prospect in clinical application.