Extracellular cardiac matrix biomarkers in patients with reduced ejection fraction heart failure as predictors of response to cardiac resynchronisation therapy: a systematic review

细胞外心肌基质生物标志物在射血分数降低型心力衰竭患者中作为心脏再同步治疗反应预测指标:系统评价

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Abstract

OBJECTIVE: Cardiac resynchronisation therapy (CRT) is an effective therapy for selected patients with heart failure (HF); however, a significant non-response rate exists. We examined current evidence on extracellular cardiac matrix (ECM) biomarkers in predicting response following CRT. METHODS: Complete literature review of PubMed, Ovid SP MEDLINE, Cochrane Library and TRIP, reference lists, international cardiology conferences and ongoing studies between December 1999 and December 2015 conducted according to prospectively registered study selection and analysis criteria (PROSPERO:CRD42016025864) was performed. All observational and randomised control trials (RCT) were included if they tested prespecified ECM biomarkers' ability to predict CRT response. Risk of bias assessment and data extraction determined pooling of included studies was not feasible due to heterogeneity of the selected studies. RESULTS: A total of 217 studies were screened; six (five prospective cohort and one RCT substudy) were included in analysis with 415 participants in total. Study sizes varied (n=55-260), cohort characteristics contrasted (male: 67.8%-83.6%, ischaemic aetiology: 40.2%-70.3%) and CRT response definitions differed (three clinical/functional, three echocardiographic). Consistent observation in all ECM biomarker behaviour before and after CRT implantation was not observed between studies. Lower type I and type III collagen synthesis biomarkers (N-terminal propeptides of type I and III procollagens) expression demonstrated replicated ability to predict reverse left ventricular remodelling. CONCLUSION: Collagen synthesis biomarkers offer the most potential as ECM biomarkers for predicting CRT response. Heterogeneity between these studies was large and limited the ability to pool and compare results numerically. Use of different response definitions was one of the biggest challenges.

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