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Background: Heart failure is a prevailing diagnosis of hospitalization and readmission within 6 months, and nearly a quarter of these patients die within a year. Guideline-directed medication therapies reduce risk of mortality by 73% over 2 years; however, the implementation of these therapies to their target dose in clinical practice continues to be challenging. In 2020, the Veterans Affairs (VA) Health Care System developed a HF dashboard to monitor and improve outpatient HF management. The DASH-HF (Dashboard Activated Services and Telehealth for Heart Failure) study is a randomized, pragmatic clinical trial to evaluate proactive dashboard-directed telehealth clinics to improve the use and dosing of guideline-directed medication therapy for patients with heart failure with reduced ejection fraction not on optimal guideline-directed medication therapy within the VA., Methods: Three hundred veterans with heart failure with reduced ejection fraction met inclusion criteria with an optimization potential score (OPS) of 5 or less out of 10, representing nonoptimal guideline-directed medication therapy. The primary outcome was a composite score of guideline-directed medical therapy, the OPS, 6 months after the end of the intervention. Secondary outcomes included active prescriptions for each individual guideline-directed medical therapy class, HF-related hospitalizations, deaths, and clinician time per patient during the intervention clinics., Results: There was no significant difference between the intervention arm and usual care group in the primary outcome (OPS, 2.9; SD=2.1 versus OPS, 2.6, SD=2.1); adjusted mean difference 0.3 (95% CI, -0.1 to 0.7) or in the prespecified secondary outcomes for hospitalization and all-cause mortality for the intervention of proactive dashboard-based clinics., Conclusions: A dashboard-based clinic intervention did not improve the OPS or secondary outcomes of hospitalization and all-cause mortality. There remains a larger opportunity to better target patients and provide more intensive follow-up to further evaluate the utility of proactive dashboard-based clinics for HF management and quality improvement., Registration: URL: https://www., Clinicaltrials: gov; Unique identifier: NCT05001165., Competing Interests: Disclosures Dr Fonarow reports consulting for Abbott, Amgen, AstraZeneca, Bayer, Cytokinetics, Edwards, Janssen, Medtronic, Merck, and Novartis. There are no disclosures for the other authors.

Rationale: Mutations of the orphan transporter ABCC6 (ATP-binding cassette, subfamily C, member 6) cause the connective tissue disorder pseudoxanthoma elasticum. ABCC6 was thought to be located on the plasma membrane of liver and kidney cells., Objective: Mouse systems genetics and bioinformatics suggested that ABCC6 deficiency affects mitochondrial gene expression. We therefore tested whether ABCC6 associates with mitochondria., Methods and Results: We found ABCC6 in crude mitochondrial fractions and subsequently pinpointed its localization to the purified mitochondria-associated membrane fraction. Cell-surface biotinylation in hepatocytes confirmed that ABCC6 is intracellular. Abcc6-knockout mice demonstrated mitochondrial abnormalities and decreased respiration reserve capacity., Conclusions: Our finding that ABCC6 localizes to the mitochondria-associated membrane has implications for its mechanism of action in normal and diseased states.

Background: The total energy cost of pregnancy is largely due to an elevated basal metabolic rate (BMR). Large variations in the BMR response to pregnancy have been reported, but the factors associated with this variability are incompletely known., Objective: The objective was to identify factors associated with variability in the BMR response to pregnancy., Design: In 22 healthy women, BMR, body weight (BW), total body fat (TBF), fat-free mass (FFM), circulatory variables, serum concentrations of insulin-like growth factor I (IGF-I), and thyroid hormones were measured before pregnancy and in gestational weeks 14 and 32. BMR and BW were also measured in gestational weeks 8, 20, and 35. Fetal weight was estimated in gestational week 31., Results: In gestational week 14, the increase in BMR correlated significantly with the corresponding increase in BW and with the prepregnancy percentage of TBF. Together these variables explained approximately 40% of the variability in the BMR response. In gestational week 32, the increase in BMR correlated significantly with the corresponding changes in BW, TBF, FFM, IGF-I, cardiac output, and free triiodothyronine. The increase in BW in combination with fetal weight or with the elevated concentration of IGF-I in serum explained approximately 60% of the variability in the increase in BMR., Conclusions: Weight gain and the prepregnancy percentage of TBF-ie, factors related to the maternal nutritional situation-are important factors with regard to the variability in the BMR response to pregnancy. Thus, it is important to consider the nutritional situation before and during gestation when assessing pregnancy energy requirements.