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The largest study of healthy subjects were selected when there are multiple studies from the same authors. To be included, studies needed to report: (I) original data of the mean ± standard deviation or standard error, or median (lower quartile, upper quartile) (II) at least one of left ventricular global longitudinal, circumferential and/or radial strain measured by speckle tracking (III) in at least 50 healthy individuals (IV) and either sex must make up at least one third of the healthy cohort. The search terms used were (left ventricle) AND (echocardiography) AND (strain OR speckle tracking), with filters adult (age) and human (subject) applied. PubMed, Cochrane and Embase databases were searched for relevant studies with no restriction on start date until 31 December 2019. We present the following article in accordance with the PRISMA reporting checklist (available at ). Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist was followed and presented in the conduct of this meta-analysis, without a separate review protocol.
#Qlab 2 update
Our meta-analysis aims to pool the LLNs and update the pooled mean data for two-dimensional (2D-) and three dimensional (3D-) LVGLS, LVGCS and LVGRS by speckle tracking echocardiography in healthy subjects, in order to redefine thresholds of abnormal strains, as well as analyzing baseline parameters that could be associated with left ventricular (LV) strain measurements.
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It is important to note that the 95% CI of the pooled mean by meta-analysis does not accurately reflect the range of normal strain values and does not measure the LLN or its 95% CI, and therefore cannot be used in defining the cut-points for abnormal strain. When determining normal ranges of systolic function parameters in cardiac imaging, such as ejection fraction, fractional area change, tricuspid annular plane systolic excursion and of course strain, the focus is on the threshold at which the value measured becomes abnormally low in magnitude to reflect impaired systolic function, otherwise known as the lower limit of normal (LLN) ( 7). While meta-analyses of strain measurements have been reported ( 8- 10), they focused on the estimation of the pooled mean of the strain values with corresponding 95% confidence intervals (95% CI) for the mean alone. One way to overcome this problem is to perform a meta-analysis with both biologic and measuring system variability addressed. Yet it is close to impossible to perform a study in which both biologic and system variability are assessed. Measurement system variability can be addressed by having a small sample with repeated echocardiographic exams obtained using different ultrasound systems or software. Biologic variability can be resolved by appropriately large, multi-institutional samples of healthy individuals that take into account population diversity.
#Qlab 2 software
Strain measurement variability may stem from biologic variability (e.g., impact of gender, age, body size) or measurement system variability (echocardiographic image quality, software speckle detection, strain calculation). Despite significant investigation, there is no consensus of what constitutes normal variability and what is abnormal strain in an otherwise healthy patient ( 6, 7). Multiple studies have tested the prognostic utility of left ventricular global longitudinal (LVGLS), circumferential (LVGCS) and radial (LVGRS) strains in a wide range of clinical applications, including cardiomyopathies, coronary heart disease and valvular heart disease ( 1- 5).