Kanwar, Manreet

Abstract Aims Cardiogenic shock (CS) is often treated with catecholamines titrated to an adequate target mean arterial pressure (MAP) while minimizing adverse effects. We aim to assess the optimal catecholamine dose/MAP balance in heart failure-associated CS (HF-CS). Methods Patients with HF-CS were retrospectively enrolled from 16 tertiary centres in 5 European countries (2016–2021; NCT03313687). Dosage was quantified by inotropic scores (epinephrine, norepinephrine, and dobutamine). Associations of baseline and seven-day summarized dosage with intensive care unit (ICU) discharge (mixed-effects logistic regression) and 30-day mortality (Cox regression) were analysed. Potential catecholamine/MAP target ratios for optimized outcomes were assessed in models adjusted for age, sex, pH, lactate and prior resuscitation, stratified by centre. Results N = 704 patients: median age 63 years, 74% male, 34% post-resuscitation, median lactate 5.2 mmol/l. Of these, 53% were discharged from ICU, 48% died within 30 days. Higher inotropic scores independently predicted a lower probability of ICU discharge (baseline score: OR 0.78 [95%-CI 0.69–0.88]; summarized score: OR 0.46 [0.38–0.56]; both P < .001) and higher risk of 30-day mortality (baseline score: HR 1.27 [1.15–1.40], summarized score HR 1.83 [1.60–2.09]; both P < .001). A score/MAP ratio <0.403 µg/kg/min/mmHg was associated with higher ICU discharge odds (ceiling effect); a < 0.426 µg/kg/min/mmHg with lower 30-day mortality hazards (no ceiling effect). Lowering catecholamine doses by accepting reduced MAP targets was linked to better outcomes. Conclusion In HF-CS, higher catecholamine support independently associates with worse outcomes. Accepting lower blood pressure targets to reduce catecholamine dosage may improve outcomes. Validation in randomized controlled trials is urgently needed.

ImportanceThe advanced ambulatory heart failure (HF) population comprises patients who have progressed beyond the pillars of recommended stage C HF therapies but can still find meaningful life-years ahead. Although these patients are commonly encountered in practice, national databases selectively capture the small groups accepted for heart transplant listing or left ventricular assist devices. The epidemiology, trajectories, and therapies for other ambulatory patients with advanced HF are poorly understood.ObservationsIn December 2022, the National Heart, Lung and Blood Institute convened a team of experts to identify knowledge gaps and research priorities for the ambulatory population with limiting daily symptoms and transition toward refractory end-stage D HF, designated as stage C2D. This article summarizes the findings from that 3-day workshop. Workshop participants surveyed the initial challenges and knowledge gaps for (1) recognition of ambulatory C2D HF, (2) estimation of the magnitude of the affected population and identifiable subpopulations, and (3) physiologic phenotypes, such as low cardiac output, right HF, cardiorenal syndromes, congestive hepatopathy and frailty, which offer distinct targets for existing and emerging therapies. Social drivers of HF and patient preferences for quality/length of survival were highlighted as essential modifiers for personalization of therapies.Conclusions and RelevanceTen key points summarized workshop findings, with target cohorts for study proposed as a crucial next step. This workshop summary is intended as a call for action to address knowledge gaps and develop new strategies to improve outcomes in the large ambulatory population with C2D HF.

Right ventricular pressure-volume (PV) analysis characterizes ventricular systolic and diastolic properties independent of loading conditions like volume status and afterload. While long-considered the gold-standard method for quantifying myocardial chamber performance, it was traditionally only performed in highly specialized research settings. With recent advances in catheter technology and more sophisticated approaches to analyze PV data, it is now more commonly used in a variety of clinical and research settings. Herein, we review the basic techniques for PV loop measurement, analysis, and interpretation with the aim of providing readers with a deeper understanding of the strengths and limitations of PV analysis. In the second half of the review, we detail key scenarios in which right ventricular PV analysis has influenced our understanding of clinically relevant topics and where the technique can be applied to resolve additional areas of uncertainty. All told, PV analysis has an important role in advancing our understanding of right ventricular physiology and its contribution to cardiovascular function in health and disease.

AbstractBackgroundCardiac allograft vasculopathy (CAV) remains an important cause of graft failure after heart transplantation (HT). Although many risk factors for CAV have been identified, there are no clinical prediction models that enable clinicians to determine each recipient's risk of CAV.MethodsWe studied a cohort of 14 328 heart transplant recipients whose data were reported to the International Society for Heart and Lung Transplantation Registry between 2000 and 2010. The cohort was divided into training (75%) and test (25%) sets. Multivariable modeling was performed in the test set using variables available at the time of heart transplant using three methods: (i) stepwise Cox proportional hazard, (ii) regularized Cox proportional hazard, and (iii) Bayesian network.ResultsCardiac allograft vasculopathy developed in 4259 recipients (29.7%) at a median time of 3.0 years after HT. The regularized Cox proportional hazard model yielded the optimal performance and was also the most parsimonious. We deployed this model as an Internet‐based risk calculator application.ConclusionsWe have developed a clinical prediction model for assessing a recipient's risk of CAV using variables available at the time of HT. Application of this model may allow clinicians to determine which recipients will benefit from interventions to reduce the risk of development and progression of CAV.