An 80-year-old man with a destination left ventricular assist device (LVAD) presented with decompensated heart failure. Evaluation demonstrated numerous LVAD high power spike events, significant ...aortic regurgitation, and hemolysis. He underwent successful aortic valve replacement with a novel transcatheter valve and LVAD pump exchange that resulted in an improvement in his clinical status. (Level of Difficulty: Advanced.)
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
We aim to evaluate the echocardiographic/hemodynamic effects of left ventricular assist devices in African American (AA) versus non-AA patients undergoing ramp speed optimization and its subsequent ...effect on readmissions. In 65 patients (26 AA), no differences in baseline echocardiographic/hemodynamic parameters were noted. During ramp testing, there was a significantly greater increase in cardiac output (slope0.29 ± 0.24 vs. 0.15 ± 0.12, p < 0.01) with more rapid decrease in left ventricular end-diastolic diameter (slope−0.21 ± 0.14 vs. −0.13 ± 0.07 L/min, p < 0.01) in the AA group. AAs had higher all-cause, but similar heart failure readmission rate as compared with the non-AA group.
Volume status assessment in left ventricular assist device (LVAD) patients remains challenging. Cardiac resynchronization therapy (CRT) devices are common in LVAD patients, and the impedance across ...the CRT leads may be associated with hemodynamics and serve as a tool for noninvasive estimation of volume status. Ninety-one sets of measurements including cardiac filling pressures and lead impedances were prospectively obtained during ramp tests from 11 LVAD patients (65.5 ± 9.7 years old; nine male) with CRT devices. Right atrial (RA), right ventricular (RV), and left ventricular (LV) lead impedances were all significantly associated with central venous pressure (CVP) (p < 0.05). We derived the following equationestimated CVP = 47.90–(0.086 × RA lead impedance) + (0.013 × RV lead impedance)–(0.020 × LV lead impedance). The estimated CVP had a significant correlation (r = 0.795) and good agreement with the measured CVP (mean difference –0.14 ± 1.77 mmHg). Applying the above equation on the validation cohort of twenty-one patients also maintained a strong association with measured CVP (r = 0.705). In conclusion, we have derived a novel equation to estimate CVP using lead impedance measurements. This finding may allow noninvasive monitoring of volume status in LVAD patients.
•A peak velocity of the LVAD outflow cannula of >2 m/s poorly predicts malfunction.•The HMII and HVAD have unique normal operating velocities in their outflow cannulas.•Peak velocities of 2.7 m/s ...(HMII) and 3.4 m/s (HVAD) have improved specificity for detecting malfunction.
Echocardiographic assessment of left ventricular assist devices (LVADs) is used as a screening tool to evaluate the integrity and mechanics of the pump and circuit. We aimed to 1) establish the normal range and upper reference limit of peak velocity of the outflow cannula for the modern era of LVADs and 2) assess the clinical performance of the currently cited and newly proposed reference limits in patients with continuous-flow LVADs as a screening tool for cannula malfunction.
LVAD outflow peak CW velocities were measured with the use of Doppler transthoracic echocardiography (TTE) in 57 patients with LVADs (44 with Heartmate II (HM2), 13 with Heartware (HW)). The average velocity and the upper and lower normal reference limits (defined as ±2 standard deviations from the mean) for each LVAD type was calculated. The upper reference limit was then used as a screening threshold for cannula malfunction.
The average outflow cannula peak velocity for the normal HM2 cohort was 1.86 ± 0.44 m/s with upper and lower reference limits of 2.73 m/s and 0.98 m/s, respectively. The average outflow cannula peak velocity for the normal HW cohort was 2.36 ± 0.53 m/s with upper and lower reference limits of 3.42 m/s and 1.3 m/s, respectively, which was significantly higher than the HM2 cohort (P = .004).
In both HM2 and HW LVADs, the average peak outflow velocity and reference limit for the normal population, as measured by Doppler TTE, was markedly higher than the currently used LVAD reference limits of 2 m/s and are significantly different between devices. Patients with peak outflow velocities above our upper reference limits should be evaluated for LVAD outflow cannula malfunction.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Hemocompatibility-related adverse events affect patients after left ventricular assist device (LVAD) implantation but are hard to predict.BACKGROUNDHemocompatibility-related adverse events affect ...patients after left ventricular assist device (LVAD) implantation but are hard to predict.Dynamic risk modeling with a multistate model can predict risk of gastrointestinal bleeding (GIB), stroke, or death in ambulatory patients.OBJECTIVESDynamic risk modeling with a multistate model can predict risk of gastrointestinal bleeding (GIB), stroke, or death in ambulatory patients.This was a secondary analysis of the MOMENTUM 3 (Multicenter Study of MagLev Technology in Patients Undergoing Mechanical Circulatory Support Therapy with HeartMate 3) trial. HeartMate 3 LVAD recipients who survived to hospital discharge and were followed for up to 2 years. A total of 145 variables were included in the multistate model with multivariate logistic regression. Model performance was assessed with the area under the curve in a holdout validation cohort. A risk stratification tool was created by dividing patients into categories of predicted risk using the final model variables and associated OR.METHODSThis was a secondary analysis of the MOMENTUM 3 (Multicenter Study of MagLev Technology in Patients Undergoing Mechanical Circulatory Support Therapy with HeartMate 3) trial. HeartMate 3 LVAD recipients who survived to hospital discharge and were followed for up to 2 years. A total of 145 variables were included in the multistate model with multivariate logistic regression. Model performance was assessed with the area under the curve in a holdout validation cohort. A risk stratification tool was created by dividing patients into categories of predicted risk using the final model variables and associated OR.Among 2,056 LVAD patients, the median age was 59.4 years (20.4% women, 28.6% Black). At 2 years, the incidence of GIB, stroke, and death was 25.6%, 6.0%, and 12.3%, respectively. The multistate model included 39 total variables to predict risk of GIB (16 variables), stroke (10 variables), and death (19 variables). When ambulatory patients were classified according to their risk category, the 30-day observed event rate in the highest risk group for GIB, stroke, or death was 26.9%, 1.8%, and 4.8%, respectively. The multistate model predicted GIB, stroke, and death at any 30-day period with an area under the curve of 0.70, 0.69, and 0.86, respectively.RESULTSAmong 2,056 LVAD patients, the median age was 59.4 years (20.4% women, 28.6% Black). At 2 years, the incidence of GIB, stroke, and death was 25.6%, 6.0%, and 12.3%, respectively. The multistate model included 39 total variables to predict risk of GIB (16 variables), stroke (10 variables), and death (19 variables). When ambulatory patients were classified according to their risk category, the 30-day observed event rate in the highest risk group for GIB, stroke, or death was 26.9%, 1.8%, and 4.8%, respectively. The multistate model predicted GIB, stroke, and death at any 30-day period with an area under the curve of 0.70, 0.69, and 0.86, respectively.The multistate model informs 30-day risk in ambulatory LVAD recipients and allows recalculation of risk as new patient-specific data become available. The model allows for accurate risk stratification that predicts impending adverse events and may guide clinical decision making. (MOMENTUM 3 IDE Clinical Study Protocol; NCT02224755).CONCLUSIONSThe multistate model informs 30-day risk in ambulatory LVAD recipients and allows recalculation of risk as new patient-specific data become available. The model allows for accurate risk stratification that predicts impending adverse events and may guide clinical decision making. (MOMENTUM 3 IDE Clinical Study Protocol; NCT02224755).
The clinical implications of the discrepancy between cystatin C (cysC)- and serum creatinine (Scr)-estimated glomerular filtration rate (eGFR) in patients with heart failure (HF) and reduced ejection ...fraction (HFrEF) are unknown.
Post-hoc analysis of randomized trial data.
1,970 patients with HFrEF enrolled in PARADIGM-HF with available baseline cysC and Scr measurements.
Intraindividual differences between eGFR based on cysC (eGFR
) and Scr (eGFR
; eGFRdiff
).
Clinical outcomes included the PARADIGM-HF primary end point (composite of cardiovascular CV mortality or HF hospitalization), CV mortality, all-cause mortality, and worsening kidney function. We also examined poor health-related quality of life (HRQoL), frailty, and worsening HF (WHF), defined as HF hospitalization, emergency department visit, or outpatient intensification of therapy between baseline and 8-month follow-up.
Fine-Gray subdistribution hazard models and Cox proportional hazards models were used to regress clinical outcomes on baseline eGFRdiff
. Logistic regression was used to investigate the association of baseline eGFRdiff
with poor HRQoL and frailty. Linear regression models were used to assess the association of WHF with eGFR
, eGFR
, and eGFRdiff
at 8-month follow-up.
Baseline eGFRdiff
was higher than +10 and lower than-10mL/min/1.73m
in 13.0% and 35.7% of patients, respectively. More negative values of eGFRdiff
were associated with worse outcomes (subhazard ratio per standard deviation: PARADIGM-HF primary end point, 1.18; P=0.008; CV mortality, 1.34; P=0.001; all-cause mortality, 1.39; P<0.001; worsening kidney function, 1.31; P=0.05). For a 1-standard-deviation decrease in eGFRdiff
, the prevalences of poor HRQoL and frailty increased by 29% and 17%, respectively (P≤0.008). WHF was associated with a more pronounced decrease in eGFR
than in eGFR
, resulting in a change in 8-month eGFRdiff
of-4.67mL/min/1.73m
(P<0.001).
Lack of gold-standard assessment of kidney function.
In patients with HFrEF, discrepancies between eGFR
and eGFR
are common and are associated with clinical outcomes, HRQoL, and frailty. The decline in kidney function associated with WHF is more marked when assessed with eGFR
than with eGFR
.
Kidney function assessment traditionally relies on serum creatinine (Scr) to establish an estimated glomerular filtration rate (eGFR). However, this has been challenged with the introduction of an alternative marker, cystatin C (cysC). Muscle mass and nutritional status have differential effects on eGFR based on cysC (eGFR
) and Scr (eGFR
). Among ambulatory patients with heart failure enrolled in PARADIGM-HF, we investigated the clinical significance of the difference between eGFR
and eGFR
. More negative values (ie, eGFR
>eGFR
) were associated with worse clinical outcomes (including mortality), poor quality of life, and frailty. In patients with progressive heart failure, which is characterized by muscle loss and poor nutritional status, the decline in kidney function was more pronounced when eGFR was estimated using cysC rather than Scr.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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