P5739Venoarterial Extracorporeal Membrane Oxygenation in Cardiogenic Shock: exploring prognostic variables and risk prediction tools

Introduction

The use of venoarterial extracorporeal membrane oxygenation (VA-ECMO) to support patients in cardiogenic shock has been increasing in Portugal over the past few years. Nonetheless, epidemiologic, prognostic and clinical outcome data are scarce.

Purpose

We aim to identify clinical variables with prognostic significance in this challenging population, as well as the performance of various risk scores in mortality prediction.

Methods

All patients that underwent VA-ECMO support at our Cardiac ICU between 2011 and 2018 were included in the analysis. Logistic regression analysis was used to assess the relationship between clinical variables and outcomes.

Results

Short-term mechanical support with VA-ECMO was given to 40 patients, with a mean age of 52±11 years. At the time of the implant, the mean SOFA score was 11.2±4.0, and mean SAVE score was −4.75±4.6. Mean ECMO support duration was 116±96 hours. In 70% (N=28) of patients, VA-ECMO was successfully weaned. In-hospital mortality was observed in 52.5% of patients, which was in accordance with the predicted mortality by SOFA score (22.5% to 82% in our population risk range) and by SAVE score (60 to 70%). Those who placed the VA-ECMO as a bridge to transplant or to long-term mechanical LV assist device had greater in-hospital mortality rates (91.6 vs 41.9%, p=0.013), as well as those under ≥2 inotropic/vasopressors (69.2 vs 21.4%, p=0.012) or when adrenaline use was needed (100% vs 44.1%, p=0.01). No other between-group differences were observed in what concerns short-term mortality. After logistic regression analysis, independent predictors of in-hospital mortality included AMI setting, number of vasoactive amines used, and necessity of a LV venting device. SAVE score had the greater predictive ability in these patients (AUC = 0.638) among the most utilized clinical risk scores (SOFA score AUC = 0.37; APACHE II score AUC = 0.59; SAPS II score AUC = 0.54).

Conclusion

In our analysis, patients in profound cardiogenic shock on VA-ECMO support had slightly better survival rates than predicted by classical Risk Scores. The SAVE score may be the most accurate tool to predict in-hospital mortality in this specific, and yet heterogeneous, clinical subset. Other well recognized clinical markers of severity may also help refine short-term prognosis, and potentially improve organ transplant or other destination therapy prioritization.

P5270Impaired myocardial deformation assessed by cardiac magnetic resonance is associated with increased arrhythmic risk in hypertrophic cardiomyopathy

Background

Strain techniques, such as feature tracking cardiac magnetic resonance (FT-CMR), have emerged as a promise for more accurate evaluation of cardiac function compared to ejection fraction. In hypertrophic cardiomyopathy (HCM) patients, impaired myocardial deformation measured by FT-CMR has been associated with severity of hypertrophy and presence of late gadolinium enhancement (LGE) but associations with clinical severity and prognosis are scarce.

Purpose

To analyse the association between left ventricular strain measured by FT-CMR, morphologic features and prognostic markers in patients with HCM.

Methods

Retrospective analysis of clinical, echocardiography, Holter and CMR data of HCM patients aged ≥16 years followed at two referral centres. Ventricular arrhythmias (VA) were defined as non-sustained or sustained ventricular tachycardia or sudden cardiac arrest. Sudden cardiac death (SCD) risk was evaluated using the score proposed by the European Society of Cardiology. LGE extension was evaluated using the American Heart Association 17-segment model. FT-CMR was used to evaluate global peak systolic longitudinal (GLS), radial (GRS) and circumferential (GCS) strains - GLS was averaged from three standard longitudinal views while GRS and GCS were averaged from the basal, mid and apical LV short-axis planes.

Results

A total of 109 HCM patients (59.2±16.2 years old; 60.6% males) were included; mean follow-up was 39±25 months. Mean LV mass was 170.6±70.3g, LVEF was 63.7±10.0% and the number of segments with LGE was 3.14±3.32. Mean GLS, GRS and GCS were −14.8±4.0%, 34.4±13.3% and −17.5±4.8%, respectively. Impaired strain was associated with higher LV mass (GLS: r=0.46, GRS: r=−0.46, GCS: r=0.47, p<0.001 for all), reduced LVEF (GLS: r=−0,33, GRS: r=0,44, GCS: r=−0.41, p<0.003 for all) and LGE extension (GLS: r=0.26, GRS: r=−0.38, GCS: r=0.38, p<0.01 for all).

SCD risk score was 3.12%±2.98 (8 patients scored as high risk) and VA were documented in 26 patients (26%). Patients with VA had worse strain values than those without (GLS −13.2±4.12 vs −15.5±3.71, p=0.011; GCS −15,8±5.22 vs −18.3±4.24, p=0.017). Patients with high estimated risk of SCD also had worse strain values than those at low/intermediate risk (GLS −12.2±3.57 vs −15.1±3.83, p=0.048; GCS −14.5±4.26 vs −17.9±4.54, p=0.047). A correlation between SCD risk and GLS and GCS was observed (r=0.32, p=0.004; r=0.23, p=0.03, respectively).

Conclusions

In our population, worse strain measurements were associated with a more severe HCM phenotype, presence of VA and a higher estimated risk of SCD. Strain assessed by FT-CMR may improve risk stratification in HCM patients.

[Comparison of body fat using anthropometry bioelectrical impedance and DEXA in elderly women]

Verify correspondence and compare percentage body fat (%BF) estimates by skinfold thickness (SKT), bioelectrical impedance analysis (BIA) and DEXA. Twenty voluntaries women (aged 62-79 yr) were assessed. The body fat was estimated using two different equations of SKT(Jackson (19); Durning and Womersley, (20)), BIA using two-predictions formulas (23) and DEXA. To compare mean values of %BF was used analysis of variance for repeated measures (ANOVA--Bonferroni), the correlation of the inter-method was verified by Pearson correlation coefficients (r), and correspondence between prediction formulas was tested by using the approach by Bland and Altman (25). The %BF assessed by BIA (23) shown poor correlation (r < 0.5) with two SKT equations. The %BF ranged from 31.5 +/- 5.5 to 41.2 +/- 6.1 (mean +/- SD) for Jackson (19) e DEXA, respectively. The analysis of variance shown no significant differences (p > 0.05) between methods and/or equations by BIA (RJL-CompCorp) vs. DC-Jackson (19). There were observed significant differences (p < 0.001) between all comparisons. The correspondence between RJL-CompCorp vs. Deurenberg (23) was good and the same was observed for DEXA vs. Durning and Womersley (20). Although the methods and/or equations used in this study have been commonly utilized to estimate BF in elderly subjects, they neither must be used as a standard method. Each method has limitations and the comparison can be useful for interpretation of results.