The period following heart failure hospitalization (HFH) is a vulnerable time with high rates of death or recurrent HFH.OBJECTIVE To evaluate clinical characteristics, outcomes, and treatment response to vericiguat according to prespecified index event subgroups and time from index HFH in the Vericiguat Global Study in Subjects With Heart Failure With Reduced Ejection Fraction (VICTORIA) trial. DESIGN, SETTING, AND PARTICIPANTSAnalysis of an international, randomized, placebo-controlled trial. All VICTORIA patients had recent (<6 months) worsening HF (ejection fraction <45%). Index event subgroups were less than 3 months after HFH (n = 3378), 3 to 6 months after HFH (n = 871), and those requiring outpatient intravenous diuretic therapy only for worsening HF (without HFH) in the previous 3 months (n = 801). Data were analyzed between May 2, 2020, and May 9, 2020.INTERVENTION Vericiguat titrated to 10 mg daily vs placebo. MAIN OUTCOMES AND MEASURESThe primary outcome was time to a composite of HFH or cardiovascular death; secondary outcomes were time to HFH, cardiovascular death, a composite of all-cause mortality or HFH, all-cause death, and total HFH. RESULTS Among 5050 patients in the VICTORIA trial, mean age was 67 years, 24% were women, 64% were White, 22% were Asian, and 5% were Black. Baseline characteristics were balanced between treatment arms within each subgroup. Over a median follow-up of 10.8 months, the primary event rates were 40.9, 29.6, and 23.4 events per 100 patient-years in the HFH at less than 3 months, HFH 3 to 6 months, and outpatient worsening subgroups, respectively. Compared with the outpatient worsening subgroup, the multivariable-adjusted relative risk of the primary outcome was higher in HFH less than 3 months (adjusted hazard ratio, 1.48; 95% CI, 1.27-1.73), with a time-dependent gradient of risk demonstrating that patients closest to their index HFH had the highest risk. Vericiguat was associated with reduced risk of the primary outcome overall and in all subgroups, without evidence of treatment heterogeneity. Similar results were evident for all-cause death and HFH. Addtionally, a continuous association between time from HFH and vericiguat treatment showed a trend toward greater benefit with longer duration since HFH. Safety events (symptomatic hypotension and syncope) were infrequent in all subgroups, with no difference between treatment arms.CONCLUSIONS AND RELEVANCE Among patients with worsening chronic HF, those in closest proximity to their index HFH had the highest risk of cardiovascular death or HFH, irrespective of age or clinical risk factors. The benefit of vericiguat did not differ significantly across the spectrum of risk in worsening HF.
Background Keratoconus is a disorder characterized by progressive thinning and distortion of the cornea. If detected at an early stage, corneal collagen cross-linking can prevent disease progression and further visual loss. Although advanced forms are easily detected, reliable identification of subclinical disease can be problematic. Several different machine learning algorithms have been used to improve the detection of subclinical keratoconus based on the analysis of multiple types of clinical measures, such as corneal imaging, aberrometry, or biomechanical measurements. Objective The aim of this study is to survey and critically evaluate the literature on the algorithmic detection of subclinical keratoconus and equivalent definitions. Methods For this systematic review, we performed a structured search of the following databases: MEDLINE, Embase, and Web of Science and Cochrane Library from January 1, 2010, to October 31, 2020. We included all full-text studies that have used algorithms for the detection of subclinical keratoconus and excluded studies that did not perform validation. This systematic review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) recommendations. Results We compared the measured parameters and the design of the machine learning algorithms reported in 26 papers that met the inclusion criteria. All salient information required for detailed comparison, including diagnostic criteria, demographic data, sample size, acquisition system, validation details, parameter inputs, machine learning algorithm, and key results are reported in this study. Conclusions Machine learning has the potential to improve the detection of subclinical keratoconus or early keratoconus in routine ophthalmic practice. Currently, there is no consensus regarding the corneal parameters that should be included for assessment and the optimal design for the machine learning algorithm. We have identified avenues for further research to improve early detection and stratification of patients for early treatment to prevent disease progression.
Discovery of disease-causing structural variants (dcSV) from whole genome sequencing data is difficult due to high number of false positives and a lack of efficient way to estimate allele frequency. Here we introduce SVRare, an application that aggregates structural variants (SV) called by other tools, and efficiently annotates rare SVs to aid dcSVs discovery. Applied in the Genomics England (GEL) research environment to data from the 100K Genomes Project, SVRare aggregated 554,060,126 SVs called by Manta and Canvas in all the 71,408 participants in the rare-disease arm. From a pilot study of 4313 families, SVRare identified 36 novel protein-coding disrupting SVs on diagnostic grade genes that may explain proband's phenotype. It is estimated that SVRare can increase SV-based diagnosis yield by at least 4-fold. We also performed a genome-wide association study, and uncovered clusters of dcSVs in genes with known pathogenicity, such as PKD1/2 - cystic kidney diseases and LDLR - familial hypercholesterolaemia.
The glucocorticoid betamethasone (BM) has potent anti-inflammatory and immunosuppressive effects; however, it increases the susceptibility of patients to superficial Candida infections. Previously we found that this disadvantageous side effect can be counteracted by menadione sodium bisulfite (MSB) induced oxidative stress treatment. The fungus specific protein phosphatase Z1 (CaPpz1) has a pivotal role in oxidative stress response of Candida albicans and was proposed as a potential antifungal drug target. The aim of this study was to investigate the combined effects of CaPPZ1 gene deletion and MSB treatment in BM pre-treated C. albicans cultures. We found that the combined treatment increased redox imbalance, enhanced the specific activities of antioxidant enzymes, and reduced the growth in cappz1 mutant (KO) strain. RNASeq data demonstrated that the presence of BM markedly elevated the number of differentially expressed genes in the MSB treated KO cultures. Accumulation of reactive oxygen species, increased iron content and fatty acid oxidation, as well as the inhibiting ergosterol biosynthesis and RNA metabolic processes explain, at least in part, the fungistatic effect caused by the combined stress exposure. We suggest that the synergism between MSB treatment and CaPpz1 inhibition could be considered in developing of a novel combinatorial antifungal strategy accompanying steroid therapy.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.