Prognostic value of right ventricular longitudinal strain in patients with pulmonary hypertension: a systematic review and meta-analysis.
until further notice
SourceEuropean Heart Journal Cardiovascular Imaging, 20, 4, (2019), pp. 475-484
Article / Letter to editor
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European Heart Journal Cardiovascular Imaging
SubjectRadboudumc 16: Vascular damage RIHS: Radboud Institute for Health Sciences
AIMS: Pulmonary hypertension (PH) is associated with high morbidity and mortality and the predictive capacity of traditional functional echocardiographic measures is poor. Recent studies assessed the predictive capacity of right ventricular longitudinal strain (RVLS). Diversity in methods between these studies resulted in conflicting outcomes. The purpose of this systematic review and meta-analysis was to determine the independent prognostic value of RVLS for PH-related events and all-cause mortality. METHODS AND RESULTS: A systematic search in Pubmed (MEDLINE), Embase, the Cochrane Library, and Web of Science was performed to identify studies that examined the prognostic value of RVLS in patients with PH. Studies reporting Cox regression based hazard ratios (HRs) for a combined endpoint of mortality and PH-related events or all-cause mortality for echocardiographic derived RVLS were included. A weighted mean of the multivariate HR was used to determine the independent predictive value of RVLS. Eleven studies met our criteria, including 1169 patients with PH (67% female, 0.6-3.8 years follow-up). PH patients with a relative reduction of RVLS of 19% had a significantly higher risk for the combined endpoint [HR 1.22, 95% confidence interval (CI) 1.07-1.40], while patients with a relative reduction of RVLS of 22% had a significantly higher risk for all-cause mortality (HR 2.96, 95% CI 2.00-4.38). CONCLUSION: This systematic review and meta-analysis showed that RVLS has independent prognostic value for a combined endpoint and all-cause mortality in patients with PH. Collectively, these findings emphasize that RVLS may have value for optimizing current predictive models for clinical events or mortality in patients with PH.
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