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Prehabilitation with Impella 5.5 offers hemodynamic support while allowing early mobilization, yet its overall effect on post-transplant recovery remains unclear. The aim was to assess recovery during Impella 5.5–supported prehabilitation and determine its association with early post-heart transplant outcomes, including a potential dose–response relationship with ambulatory activity. We conducted a single-center retrospective cohort study of adults bridged to transplant with Impella 5.5 between April 1, 2022 and September 30, 2024. Daily walking distance, recorded by nursing staff, served as the intervention. Primary outcome was postoperative hospital length of stay (LOS); the secondary outcome was time to extubation. Fine–Gray competing-risk models, adjusted for age, Sequential Organ Failure Assessment (SOFA) score, New York Heart Association (NYHA) class, and days of Impella support, assessed associations. Longitudinal recovery trajectories were analyzed with linear mixed-effects models incorporating restricted cubic splines. Among 82 eligible patients, 65 met the inclusion criteria. Patients who walked farther during Impella 5.5 support in the intensive care unit (ICU) had shorter hospital stays and were taken off the ventilator sooner after transplantation. The overall recovery peaked during the first 2–3 weeks of support, with smaller recovery thereafter, indicating that most functional recovery occurred early during prehabilitation.

Despite advances in drug and device technology, health care delivery, and research infrastructure, cardiogenic shock (CS) continues to have nearly 50% in‐hospital mortality. In patients with CS, both the initial severity of Society for Cardiovascular Angiography and Intervention CS and its subsequent trajectory predicts the clinical outcomes. Accordingly, delayed initial recognition and failure to escalate or deescalate treatment can significantly affect the outcomes of CS. Traditional assessment methods, with the exception of blood pressure measurement, require a high index of suspicion and frequent reassessment by the clinical team. Electronic medical record‐based detection has been successfully implemented in acute and critical care patients with septic shock and acute kidney injury. In CS, electronic medical record‐based studies have largely focused on using models to predict outcomes in patients with CS, with limited data on electronic medical record‐based tools to assist with either predicting CS or providing real time alerts when escalation or de‐escalation might be indicated. Early detection of CS may be associated with detection of earlier Society for Cardiovascular Angiography and Intervention stages of CS and potentially prevent deterioration to higher stages. In this review, we seek to highlight a blueprint for electronic medical record‐based detection of CS that focuses on reproducibility, convenience, clinical decision support, and research aspects.

Background. Acute cellular rejection (ACR) remains a major cause of morbidity after heart transplantation despite advances in immunosuppression. Whole genome transcriptomic profiling offers a systems-based, unbiased approach to elucidate the molecular mechanisms underlying ACR. However, noninvasive, longitudinal biomarker assessments capable of capturing the temporal dynamics of rejection biology remain scarce. Methods. RNA sequencing of peripheral blood from heart transplant recipients before, during, and after ACR was compared with nonrejection controls. Pathway analysis was conducted using differentially expressed genes (DEGs), and a machine learning approach was applied to assess gene-based prediction of ACR. Results. A total of 235 rejection-specific significant DEGs and 863 postrejection DEGs (false discovery rate < 0.05) were identified. During ACR, DEGs were enriched for T-cell activation/differentiation, apoptosis, and B-cell receptor signaling pathways. By combining the 2 sets of DEGs, a panel of 71 common genes was identified that reflected the significant, longitudinal transcriptomic dynamics of ACR. In an elastic net machine learning–based classifier, DYNLL1 and SERF2 were identified as ACR predictive genes, and achieved a cross-validated area under the receiver operating characteristic curve of 0.63. Conclusions. Peripheral blood transcriptomics identify dynamic temporal responses in ACR including T- and B-cell pathways with potential ACR predictive genes that warrant further investigation.

Introduction: The use of intravascular ultrasound (IVUS) to guide lower extremity deep venous stent placement is associated with improved identification of the degree of maximal vessel stenosis, vessel obstruction, and thrombus burden, compared to venography alone. As the US medical system moves towards value-based care, the financial impact of interventional tools requires close consideration. Currently, there are limited evaluations of the cost effectiveness of IVUS during venous procedures. Research Question: This study seeks to examine the cost-effectiveness of IVUS in lower extremity deep venous interventions. Methods: Medicare fee-for-service claims data from 2016 through 2021 for beneficiaries aged ≥ 65 years undergoing lower extremity venous interventions with stent placement, thrombolysis, and/or thrombectomy were analyzed. Cost ratios between IVUS-guided and non-IVUS-guided procedures were assessed using gamma regression, adjusting for demographic and clinical variables. Results: A total of 52,610 patients were included, with 42.6% undergoing IVUS-guided procedures. IVUS utilization varied by setting, with higher usage in hospital-based outpatient centers (75.3%) and ambulatory surgical centers/outpatient-based laboratories (ASC/OBL; 86.4%) compared to inpatient hospitalizations (10.4%). Among inpatient procedures, IVUS-guided venous intervention was associated with greater cost than non-IVUS procedures at 90 days, with an adjusted cost ratio of 1.04 (95% CI 1.01-1.07), yet was associated with an average 0.6-day shorter hospitalization (p < 0.001; Figure 1, Figure 2 ). There were marginal increased costs associated with use of IVUS in inpatient procedures persisting through one- and three-years follow-up, with adjusted cost ratios of 1.05 (95% CI 1.02-1.08) and 1.05 (95% CI 1.02-1.09), respectively. In contrast, IVUS use was associated with significant cost savings in outpatient settings, with adjusted cost ratios of 0.71 (95% CI 0.69-0.73) in hospital-based outpatient settings and 0.75 (95% CI 0.73-0.78) in ASC/OBL at 90 days. These cost savings persisted at one- and three-year follow-up. Conclusions: IVUS-guided venous intervention was associated with cost savings in outpatient and ASC/OBL settings, while maintaining near cost equivalence in inpatient settings. These findings suggest that in addition to the clinical benefit of IVUS for venous intervention, IVUS is a cost-effective strategy, particularly in the outpatient setting.

Background: Impella 5.5 is a temporary MCS device FDA-approved for use up to 14 days. Limited data suggest it may be safe beyond this. We aim assess outcomes based on the duration of Impella 5.5 support in heart failure cardiogenic shock (HFCS) patients at our institution. Methods: We retrospectively reviewed all HFCS patients supported with Impella 5.5 at our institution between 2020-2024. Patients supported for >14 days were compared with those supported for ≤14 days. Categorical variables were analyzed with chi-square tests, continuous variables with t-tests or Mann-Whitney U. Logistic regression identified factors linked to clinical outcomes. Results: 154 patients were included: 38 (25%) with support ≤14 days, 116 (75%) with >14 days. Median support duration was 10 (6–12) vs 31 (22–45) days, respectively. Median support duration was 10 (6-12) days for the ≤14 cohort and 31 days (22-45) days for the >14 cohort. Baseline characteristics, comorbidities, LVEF 18% (15-23) and hemodynamics show no statistical differences. Patients supported for >14 days were more likely to undergo heart transplant compared to those supported ≤14 days (91% vs 74%, p=0.009). In contrast, myocardial recovery was more likely in the ≤14 day cohort (8% vs 1%, p=0.018). One patient suffered stroke post-transplant in the ≤14 day group and two had brachial plexus injuries in the >14 days group. Mortality during the impella-supported period was slightly higher in the ≤14 day group (8% vs 5%, p=0.535) but comparable overall, 13% in both groups, p=0.971. Support >14 days was associated with transplant outcome (OR 3.41, 95% CI 1.32–8.84, p=0.012), and remained significant after adjusting for age, gender, GFR, and EF (OR 4.05, 95% CI 1.31–12.54, p=0.015). Support duration <14 days was associated with recovery or LVAD outcomes (OR 5.01, 95% CI 1.49–16.89, p=0.009), and remained significant after adjustment (OR 5.43, 95% CI 1.11–26.45, p=0.036). No association was observed between duration of support and LVAD/mortality outcomes or with EcPella use. Conclusion: Shorter Impella support duration was independently associated with early myocardial recovery or LVAD candidacy, likely reflecting rapid clinical decision-making. Prolonged Impella support was associated with increased likelihood of transitioning to heart transplantation, likely reflecting clinical stabilization over time. Our multidisciplinary, single-center data suggests Impella 5.5 can be used beyond FDA-approved 14 days in HFCS patients.

Background: Renal dysfunction is a known prognostic factor in advanced heart failure and among patients receiving temporary mechanical circulatory support (tMCS). However, the predictive value of post-Impella creatinine in determining healthcare resource utilization in patients bridged to transplant with Impella 5.5 remains unclear. This study aimed to evaluate the association between post-Impella creatinine and key hospitalization metrics in this population. Methods: We performed a retrospective cohort study of patients who received Impella 5.5 as a bridge-to-transplant between January 2020 and January 2025. Serum creatinine was collected 72 hours after Impella placement. The primary outcome was device-to-discharge time. Secondary outcomes included transplant-to-discharge time, post-transplant ICU length of stay (LOS), and total LOS (admission-discharge). Univariate and multivariable linear regressions were used to examine the association between post-Impella creatinine and each outcome, adjusting for age, gender, BMI, and LVEF. Results: 133 patients were supported with the Impella 5.5 as BTT and were included (median age 58 years (51–65), 82.7% were male, and 71.4% presented with non-ischemic cardiomyopathy. The median BMI was 27.7 (24.3–32.3), LVEF 17% (15–22), and post-Impella creatinine 1.32 mg/dL (0.96–1.71). The median device-to-discharge time was 45 days (29-64), transplant-to-discharge time was 14 days (12–19), ICU LOS post-transplant was 6 days (4–8), and total LOS was 58 days (42–76). Higher post-Impella creatinine was significantly associated with longer device-to-discharge time (β = 6.67, p = 0.004), longer transplant-to-discharge duration (β = 3.42 p = 0.003), longer ICU LOS (β = 2.19, p = 0.007), and longer total LOS (β = 7.24, p = 0.002) on univariate analysis. Post-impella creatinine remained significantly associated with device-to-discharge time in the multivariate model after adjusting for confounders (β = 6.33, p = 0.006). Importantly, this suggests that patients with lower post-Impella creatinine levels may experience shorter hospitalizations and faster recovery trajectories following transplant. Conclusions: Post-Impella creatinine is a significant predictor of prolonged hospitalization in patients supported with Impella 5.5 as a bridge to transplant. These findings emphasize the prognostic importance of early renal function assessment and may guide risk stratification and resource planning in advanced heart failure care.

Background: Progressive heart failure cardiogenic shock (HFCS) often requires escalation to temporary or durable mechanical circulatory support (MCS) as a bridge to transplant (BTT). Following the 2018 UNOS allocation changes, our center revised its BTT strategy to optimize support and shorten wait times. At our institution, the Impella 5.5 with SmartAssist via the axillary approach was selectively used for patients who remained refractory to guideline-directed medical therapy, failed single-inotrope therapy, and were not considered suitable durable LVAD candidates by our multidisciplinary heart team. We compared transplant-related outcomes of BTT patients supported with Impella 5.5 versus durable LVAD. Methods: We performed a single-center retrospective review of all heart and heart/kidney transplant candidates at Mayo Clinic Florida from October 2018 to February 2021. INTERMACS profile, baseline characteristics, and perioperative data were collected at the time of device implantation and throughout the transplant hospitalization. Results: A total of 87 heart and 4 heart–kidney transplants were completed. Forty-five patients (49%) required MCS as BTT: 27 (60%) with a durable LVAD and 18 (40%) with an Impella 5.5. All eighteen patients with Impella 5.5 as BTT (100%) were transplanted compared to nineteen patients with durable LVAD (70%), p = 0.001. The median time from listing to transplant was substantially shorter with Impella (32 vs. 696 days, p < 0.001), and this difference persisted across INTERMACS profiles. UNOS status at transplant was more urgent for Impella than LVAD (p < 0.001). Transplant surgery following Impella support required shorter cardiopulmonary bypass time (181 vs. 219 min, p < 0.001) and resulted in lower postoperative vasoactive-inotropic requirements (7.9 vs. 13, p = 0.003). No patients in the Impella group died or were delisted while awaiting transplant, whereas 5 LVAD patients (26%) died or were removed due to LVAD complications (p < 0.001). Conclusions: Our data demonstrates that the use of the Impella 5.5 as BTT was associated with significantly shorter waitlist time, higher transplantation rates, reduced perioperative morbidity, and lower postoperative vasoactive support compared with durable LVAD as BTT. These benefits were achieved despite a higher severity of illness at transplantation in the Impella cohort.