Discussion:
The average 2D echocardiographic volume and pressure dimensions,
including EDV, ESV, LAVi, and RVSP, all significantly decreased after
Mitraclip placement, consistent with other studies. However, the LVEF
and GLS, as more discrete markers of LV function, demonstrate more
complex findings. Given that mean LVEF was 52% and only 25% of
patients had LVEF<40%, many of our patients did not have
signifanct LV dysfunction detectable by LVEF. LVEF showed less change
post clip than standard 2D estimating variation (about +/- 8%27). GLS, which detects earlier dysfunction and is
less load dependent28, likely offers amore sensitive
assessment of LV dysfunction in our patients , and our data suggests
more pronounced GLS associations at more extreme GLS values,
particularly severely impaired GLS.
Our population consisted largely of patients with abnormal pre-GLS,
51/57 (89%), abnormal as defined by ASE as GLS
<|18%|29. Notably, GLS
<│7%│ was recently showed to demonstrated worse all-cause
mortality outcomes than GLS>│7%│ among functional MR
patients28, and only six of our study patients were
below │7%│. In our study, the curvi-linear graph (Figure 2) shows that
among the lower, more abnormal │pre-GLS│ values on the left-side of the
graph, a higher │pre-GLS│ is associated with greater reductions in EDV
as depicted by the greater curvature. That pattern changes at higher,
more normal │pre-GLS│ values. If studied in a more abnormal GLS
population of <│7%│, the trend seen in the more left-sided
part of our curve may be more apparent. The left-sided curvilinear trend
is supported by findings in subgroups, where higher │pre-GLS│ sample
averages were noted in patients with at least 10% reduction in EDV
compared to those without, as seen in Table 4, though not statistically
significant odd ratios as seen in Table 3. In such, our data’s
association among more severely abnormal GLS values, although not
robust, may be more clinically useful.
In a study of 41 FMR patients in Italy, worse GLS was shown to predict
lack of reverse remodeling, as defined by 10% reduction in ESV at 6
months. GLS was the only independent correlate of reverse remodeling
(<p=0.01), and a GLS cut off of -9.25% (<0.01) was
associated with reverse remodeling on a ROC curve, 81% sensitivity and
74% specificity. 16 Our results likely differ because
our population was more heterogenous including FMR, DMR and mixed. This
seemingly prominent impact of etiology on GLS predictive ability may
reflect the inherent pathophysiologic relationship of functional MR with
LV dysfunction. Combining MR types may therefore be clinically
impractical. Also, our study allowed for a longer follow up, which may
have underestimated our observed effect as over time other cardiac
impairments could develop. Furthermore, we used EDV, where this study
used ESV. Our average LVEF and │pre-GLS│ values were higher at 52% vs
34.4% (SD5.4) LVEF and 12.5% (SD 4.2) vs 11.3% (SD 3.9) │pre-GLS│.16 The early, left-sided portion of our curvilinear
graph shows similar findings seen in this Italian study which addressed
patients with more severe LV dysfunction. Our finding that EDV was
stronger than ESV in the multivariable analysis supports our use of EDV
change as the volume dimension for evaluating reverse remodeling in our
population. To minimize type I error, we only looked at reverse
remodeling in terms of change of EDV but perhaps evaluating other
markers of reverse remodeling for correlation to GLS such as ESV, LAVi,
RVSP, or EF could have detected significant predictability.
Our study supports other studies in finding automated GLS highly
reproducible, despite needing practitioner edits. Inter and intra
reliability in our study, r=0.90 and r=0.95, respectively was similar
other mainstream studies (0.89 inter, 0.93 intra observer
reproducibility)28Limitation
and Hypothesis-generating considerations
A sample size of 641 patients would have been required to confidently
state GLS fails to predict reverse remodeling (avoiding type II error),
rendering our study significantly underpowered. Many of our limitations
stem from small sample size and our efforts to reduce type I error risk.
Our sample only had 7 FMR patients, and we therefore chose to combine
the clinically similar FMR and mixed MR subgroups. The combined group
better matches our larger proportion of DMR when performing statistical
comparisons.
With only 57 patients, the adjusted model significantly reduces the
power allotted to any regression co-efficient, and may explain the loss
of significance in GLS. Since ESV and EDV correlate clinically as heart
size changes and the crude regression values are very similar, and
multicollinearity likely explains the ESV change from negative to
positive regression coefficients seen in Table 5.
To be most generalizable, we looked at all MitraClip patients, rather
than selecting just those that demonstrated evidence of pre-clip
remodeling. Perhaps we would have seen more reverse remodeling if we
targeted just those with pre-clip remodeling. This is difficult to
identify clinically without a clear gold standard, particularly in FMR
patients where LV dilation may be due to reasons other than MR.
Our graph depicts four patients with particularly large EDV changes, and
while these patients are all DMR with at least moderately enlarged
pre-EDV (all >200ml) and │pre-GLS│ greater than │9.25│,
discrete factors affording specifically them major improvements are
unknown and warrant further study.
Tomtech software is unable to accurately calculate strain with heart
rate variability >10%, such as in atrial fibrillation or
arrythmia. We did not exclude patients based on heart rate or arrythmia
as we felt the GLS autostrain values were not grossly unexpected
compared to clinician visual estimates, and we favored including all
patients to increase sample size and generalizability. We avoided
additional adjusting as that further reduces power. However, the
precision in GLS measurement may have been compromised slightly.