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1.
J Cardiovasc Transl Res ; 16(6): 1343-1348, 2023 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-37191882

RESUMO

BACKGROUND: Recent advances in multi-marker platforms offer faster data generation, but the fidelity of these methods compared to the ELISA is not established. We tested the correlation and predictive performance of SOMAscan vs. ELISA methods for NTproBNP and ST2. METHODS: Patients ≥ 18 years with heart failure and ejection fraction < 50% were enrolled. We tested the correlation between SOMA and ELISA for each biomarker and their association with outcomes. RESULTS: There was good correlation of SOMA vs. ELISA for ST2 (ρ = 0.71) and excellent correlation for NTproBNP (ρ = 0.94). The two versions of both markers were not significantly different regarding survival association. The two ST2 assays and NTproBNP assays were similarly associated with all-cause mortality and cardiovascular mortality. These associations remained statistically significant when adjusted for MAGGIC risk score (all p < 0.05). CONCLUSION: SOMAscan quantifications of ST2 and NTproBNP correlate to ELISA versions and carry similar prognosis.


Assuntos
Insuficiência Cardíaca , Peptídeo Natriurético Encefálico , Humanos , Proteína 1 Semelhante a Receptor de Interleucina-1 , Prognóstico , Insuficiência Cardíaca/diagnóstico , Fragmentos de Peptídeos , Biomarcadores
2.
Front Hum Neurosci ; 14: 108, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32477079

RESUMO

Introduction/Purpose: Cardiovascular disease (CVD) is the leading cause of death worldwide, and in the United States alone, CVD causes nearly 840,000 deaths annually. Using functional magnetic resonance imaging (fMRI), a tool to assess brain activity, researchers have identified some brain-behavior connections and predicted several self-management behaviors. The purpose of this study was to examine the sample characteristics of individuals with CVD who participated in fMRI studies. Methods: A literature search was conducted in PubMed, CINAHL, and Scopus. No date or language restrictions were applied and research methodology filters were used. In October 2017, 1659 titles and abstracts were identified. Inclusion criteria were: (1) utilized an empirical study design, (2) used fMRI to assess brain activity, and (3) focused on patients with CVD-related chronic illness. Articles were excluded if they: were theory or opinion articles, focused on mental or neuropathic illness, included non-human samples, or were not written in English. After duplicates were removed (230), 1,429 titles and abstracts were reviewed based on inclusion criteria; 1,243 abstracts were then excluded. A total of 186 studies were reviewed in their entirety; after additional review, 142 were further excluded for not meeting the inclusion criteria. Forty-four articles met criteria and were included in the final review. An evidence table was created to capture the demographics of each study sample. Results: Ninety eight percent of the studies did not report the racial or ethnic composition of their sample. Most studies (66%) contained more men than women. Mean age ranged from 38 to 78 years; 77% reported mean age ≥50 years. The most frequently studied CVD was stroke (86%), while hypertension was studied the least (2%). Conclusion: Understanding brain-behavior relationships can help researchers and practitioners tailor interventions to meet specific patient needs. These findings suggest that additional studies are needed that focus on populations historically underrepresented in fMRI research. Researchers should thoughtfully consider diversity and purposefully sample groups by including individuals that are: women, from diverse backgrounds, younger, and diagnosed with a variety of CVD-related illnesses. Identifying and addressing these gaps by studying more representative samples will help healthcare providers reduce disparities and tailor interventions for all CVD populations.

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