| Objective:Left ventricular reverse remodeling(LVRR)is characterized by a decrease in chamber volume and normalization of shape associated with improvements in both systolic and diastolic function.LVRR might occur spontaneously or more often in response to therapeutic interventions that either re-move the initial stressor or alleviate some of the mechanisms that contribute to further deterioration of the failing heart.It serves as an independent predictor of heart failure treatment and prognosis,making it a crucial factor in determining the outcome of heart failure.However,predicting LVRR is currently limited due to a lack of predictive factors in the early stages of heart failure.This study aims to explore the role of circulating inflammatory and fibrotic factors in predicting LVRR and prognosis in early heart failure with reduced ejection fraction(HFrEF),as inflammation and fibrosis are critical components of cardiac remodeling.Methods:This study aims to investigate the potential of common inflammation-fibrosis indexes to predict LVRR in HFrEF patients.The study is divided into two parts: a retrospective cohort study and a prospective cohort study.In the retrospective cohort study,the predictive ability of the systemic inflammatory immune index and Fibrosis-4 index for left ventricular reverse remodeling is evaluated using receiver operating characteristic curves and areas under the curves.The Delong test is used to compare the predictive ability of each index.Univariate and multivariate logistic regression analysis is conducted to observe the relationship between left ventricular remodeling and circulating inflammation-fibrosis biomarker-related indicators.The Cox regression model is used to analyze the prognostic factors for adverse events after left ventricular remodeling in heart failure patients.Transcriptome sequencing of peripheral blood mononuclear cells of 14 HFrEF patients are included to explore novel inflammation-fibrosis biomarkers through screening differentially expressed genes and functional enrichment analysis.The sample size is expanded in a prospective cohort study,and the expression of inflammation-fibrosis biomarkers in peripheral blood is detected through ELISA and RT-q PCR methods to predict the ability of LVRR based on their expression levels.Finally,a clinical prediction model is constructed based on clinical indicators and previous inflammation-fibrosis biomarkers.Overall,this study aims to provide insights into the potential of inflammation-fibrosis biomarkers as predictors of LVRR in HFrEF patients and to identify novel biomarkers for future research.Results:(1)In summary,this study indicated that decreased FIB-4,SII and FIB4-SII indexes at admission offer good predictability regarding LVRR.After adjusting for potential risks,the FIB4-SII index exhibited the best performance in estimating LVRR and predicting the risk of all-cause mortality and composite cardiovascular events due to HFrEF patients and could be used as a novel index.(2)This section presents a transcriptomics-based approach for screening and predicting factors associated with LVRR.Through differential gene expression and functional gene enrichment analysis,this study identified IL1 B,MMP9 and NLRP3 as potential inflammation-fibrosis indicators.The diagnostic and predictive abilities of these indicators were validated by expanding the sample size in a prospective cohort study.The combination of these three indicators demonstrated high accuracy in predicting LVRR and has the potential to serve as a biological marker for adverse prognosis in HFrEF patients.These findings provide further evidence for the role of inflammation and fibrosis in heart failure and can guide clinical prognosis and treatment decisions.(3)This part is based on the special inflammation-fibrosis indicators that were chosen to build a prediction model in the second part.In HFrEF patients,this model can precisely predict LVRR and also predict their poor prognosis.These practical and succinct prognostic criteria make them easier to use in clinical settings and aid in the early detection of high-risk groups of heart failure patients.This provides a theoretical foundation for proactive intervention strategies and adverse prognosis alarms,which can lessen the probability of poor prognosis in patients with end-stage heart failure.Conclusion:After a multilevel study in this study,it was concluded that,first,the clinical test FIB4-SII index performed best in assessing LVRR and predicting the all-cause mortality and composite cardiovascular events in HFrEF patients and could be used as a novel index.Secondly,the novel inflammation-fibrosis indicators screened by high-throughput sequencing was used to construct a prediction model that could accurately predict not only LVRR but also a poor prognosis in HFrEF patients.These predictors are more concise and practical,easy for clinical promotion,and help to identify the high-risk group of heart failure patients at an early stage,providing a theoretical basis for their active interventions and early warning of poor prognosis. |
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