LIST OF TABLES
Table 1.1 Meta-analyses of the prognostic role of sST2 in chronic heart failure...31 Table 1.2 Studies of the prognostic role of sST2 in heart failure 32
Table 2.1 Classification of body mass index according to Asia-Pacific standards
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Prognostic role of sST2 biomarker in heart failure - 1 -
The relationship between BMI and mortality and readmission in chronic heart failure patients treated as outpatients at Vietnam Heart Institute - 2 -
Clinical and paraclinical characteristics and treatment compliance in heart failure patients with reduced ejection fraction over 65 years old - 4 -
Unanimous Awareness of the Important Role of Fdi. -
The Nature and Role of the Internal Control System
Table 2.2 Diagnostic criteria for anemia according to the World Health Organization 225 44
Table 2.3 Values of variables used in the study 47
Table 3.1 Average values of heart rate and blood pressure 62
Table 3.2 Characteristics of hematological test values 62
Table 3.3 Biochemical test characteristics 63
Table 3.4 Characteristics of echocardiographic values 64
Table 3.5 Characteristics of medical treatment at admission and after 6 months 65
Table 3.6 Characteristics of sST2 in study 68
Table 3.7 Association between sST2 and clinical characteristics 69
Table 3.8 Differences in sST2 concentrations by gender and body mass index 69
Table 3.9 Differences in sST2 and NT-proBNP concentrations according to NYHA classification ...70 Table 3.10 sST2 concentrations according to the cause of heart failure 70
Table 3.11 Differences in sST2 concentrations in comorbidity groups 71
Table 3.12 Correlation between test parameters and sST2 concentration 72
Table 3.13 Correlation between sST2 and NT-proBNP with echocardiographic parameters
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Table 3.14 sST2 concentration according to number of hospitalizations 73
Table 3.15 sST2 concentration according to indications for treatment groups 74
Table 3.16 Univariate Cox regression analysis of all-cause mortality 75
Table 3.17 Multivariate Cox regression analysis of all-cause mortality 76
Table 3.18 Adjusted HR for all-cause mortality 76
Table 3.19 Univariate Cox regression analysis for cardiovascular mortality 77
Table 3.20 Multivariate Cox regression analysis of cardiovascular mortality 78
Table 3.21 Independent predictors of cardiovascular mortality .78 Table 3.22 Univariate Cox regression analysis of hospitalization for heart failure 79
Table 3.23 Multivariate Cox regression analysis of hospitalization for heart failure 80
Table 3.24 Comparison of cardiovascular event rates by sST2 concentration subgroups
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Table 3.25 Association between sST2 concentration and all-cause mortality 83
Table 3.26 Comparison of C statistical values of sST2 and NT-proBNP 86 values
Table 3.27 Comparison of prognostic models 87
Table 3.28 Comparison of combined prognostic models 87
Table 3.29 Group analysis of all-cause mortality 88
Table 4.1 Age characteristics in studies 90
Table 4.2 Characteristics of comorbidities in studies 94
Table 4.3 PSTM characteristics in studies 99
Table 4.4 Characteristics of echocardiographic parameters in 100 studies
Table 4.5 Characteristics of medical treatment in studies 102
Table 4.6 Characteristics of sST2 concentrations in studies 103
Table 4.7 Correlation between sST2 and biochemical indices in studies 111 Table 4.8 Correlation between sST2 and NT-proBNP in studies 111
Table 4.9 Correlation between sST2 and PSTM, TTTTTTg, and DKNT in studies
rescue 112
Table 4.10 Frequency of events in studies 114
Table 4.11 sST2 cutoff points in 119 studies
LIST OF CHARTS
Figure 1.1 Prevalence of chronic heart failure by age and sex 5
Figure 1.2 Survival rate after diagnosis of chronic heart failure 6
Figure 1.3 Prognostic value of sST2 according to cut-off point 28 ng/ml 30
Figure 1.4 Comparison of prognosis of sST2, NT-proBNP and troponin T 30
Figure 3.1 Gender distribution by age groups 59
Figure 3.2 Distribution of physical characteristics of the study population 59
Figure 3.3 NYHA functional classification 60
Figure 3.4 Distribution of causes of chronic heart failure in the study of 60
Figure 3.5 Rate of comorbidities 61
Figure 3.6 Distribution of the number of comorbidities 61
Figure 3.7 Percentage (%) of functional and physical symptoms 62
Figure 3.8 Distribution of chronic anemia 63
Figure 3.9 Distribution of estimated glomerular filtration rate 63
Figure 3.10 Radiographic characteristics of the study population 64
Figure 3.11 Correlation chart between echocardiographic indices 64
Figure 3.12 Distribution chart of NT-proBNP 65
Figure 3.13 Cumulative event rates after 3, 6, 12 months of follow-up 66
Figure 3.14 Distribution chart of causes of death 66
Figure 3.15 Hospitalization frequency rate in 12 months 67
Figure 3.16 Distribution of sST2 concentration 67
Figure 3.17 Distribution of sST2 and NT-proBNP concentrations according to functional classification
NYHA 70
Figure 3.18 sST2 and NT-proBNP concentrations according to the number of comorbidities 71
Figure 3.19 Correlation chart between sST2 and NT-proBNP concentrations 72
Figure 3.20 Graph of sST2 and all-cause mortality over time 81
Figure 3.21 ROC curve showing the predictive value of all-cause mortality of sST2 82
Figure 3.22 All-cause mortality curve according to sST2 concentration
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Figure 3.23 ROC curve comparing sST2 and NT-proBNP values according to all-cause mortality 84
Figure 3.24 ROC curve comparing sST2 and NT-proBNP values according to cardiovascular death events 84
Figure 3.25 ROC curve comparing sST2 and NT-proBNP values according to heart failure hospitalization events 85
Figure 3.26 Rate of cardiovascular events according to subgroups of sST2 and NT-proBNP 86
LIST OF DIAGRAM
Figure 1.1 Pathophysiological mechanism of heart failure 7
Figure 1.2 Heart failure diagnosis diagram 10
Figure 1.3 Schematic diagram of the ST2 18 gene promoter regions
Figure 1.4 Structure of the two main ST2 isoforms: ST2L and sST2 19
Figure 1.5 Local regulatory mechanism and cytokine function of IL-33 20
Figure 1.6 Dynamic inflammatory and immune functions of the IL-33/ST2L system 23
Figure 2.1 Research diagram 54
Figure 3.1 Research procedure diagram 58
LIST OF FIGURES
Figure 1.1 Frequency of chronic heart failure in the world 4
Figure 1.2 Biomarkers according to the pathophysiological mechanism of heart failure 13
Figure 1.3 Location of ST2 gene on chromosome 2 17
Figure 1.4 Anti-fibrotic and anti-remodeling functions of the IL-33/ST2 system 24
Figure 1.5 Role of the IL33/ST2 system in normal and failing hearts 25
Figure 1.6 Sources of sST2 protein production in heart failure 26
INTRODUCTION
Chronic heart failure is a common health problem, increasing and associated with significant morbidity, mortality, and health care costs 1-3 . Chronic heart failure is not only a burden in Europe and the United States but is also increasing and has a great impact in Asia in general and Southeast Asian countries in particular 2,4,5,6 . Despite many advances in treatment, the mortality and hospitalization rates of patients with chronic heart failure with PSTM ≤ 40% remain high 4,7,8,9,10 , the mortality rate due to chronic heart failure and hospitalization in Southeast Asia is generally higher than in the world 11,12 . There are not many published epidemiological statistics on heart failure in Vietnam, the number of people with chronic heart failure is estimated at 1.5 to 3.5 million and the rate of hospitalization due to chronic heart failure is still high 12 . This increases the economic and social burden 12,13 . Predicting patients at high risk of hospitalization and death is of great importance in patient care and treatment to identify patients who need close monitoring and intensive care.
Natriuretic peptides (BNP and NT-proBNP) are biomarkers that have been developed and widely applied. NT-proBNP is recommended as Class I in the diagnosis, prognosis and risk stratification of patients with chronic heart failure with PSTM ≤ 40% in recent guidelines of major associations such as the European Society of Cardiology, the American Heart Association or the Vietnam Cardiology Association 14-16 . NT-proBNP reflects the mechanical stress on the heart wall and the state of congestion, so it plays an important role in the diagnosis of heart failure 17. In clinical practice, natriuretic peptides are affected by many individual factors (such as age, sex, body mass index and glomerular filtration rate) 18,19 . NT-proBNP also increases in many diseases that are common co-morbidities in chronic heart failure and changes with different treatments 17 . Therefore, the use of NT-proBNP for prognosis in patients with chronic heart failure is still limited because NT-proBNP does not reflect myocardial remodeling, changes according to many factors or changes according to treatment, so it needs to be quantified many times 20,21,22, 23,24 . Developing and evaluating new factors or tools in combination with NT-proBNP to predict and stratify the risk of patients with chronic heart failure more accurately and effectively is an urgent need in the current management of chronic heart failure.