RESUMEN
BACKGROUND: Coronary atherosclerosis detected by imaging is a marker of elevated cardiovascular risk. However, imaging involves large resources and exposure to radiation. The aim was, therefore, to test whether nonimaging data, specifically data that can be self-reported, could be used to identify individuals with moderate to severe coronary atherosclerosis. METHODS AND RESULTS: We used data from the population-based SCAPIS (Swedish CardioPulmonary BioImage Study) in individuals with coronary computed tomography angiography (n=25 182) and coronary artery calcification score (n=28 701), aged 50 to 64 years without previous ischemic heart disease. We developed a risk prediction tool using variables that could be assessed from home (self-report tool). For comparison, we also developed a tool using variables from laboratory tests, physical examinations, and self-report (clinical tool) and evaluated both models using receiver operating characteristic curve analysis, external validation, and benchmarked against factors in the pooled cohort equation. The self-report tool (n=14 variables) and the clinical tool (n=23 variables) showed high-to-excellent discriminative ability to identify a segment involvement score ≥4 (area under the curve 0.79 and 0.80, respectively) and significantly better than the pooled cohort equation (area under the curve 0.76, P<0.001). The tools showed a larger net benefit in clinical decision-making at relevant threshold probabilities. The self-report tool identified 65% of all individuals with a segment involvement score ≥4 in the top 30% of the highest-risk individuals. Tools developed for coronary artery calcification score ≥100 performed similarly. CONCLUSIONS: We have developed a self-report tool that effectively identifies individuals with moderate to severe coronary atherosclerosis. The self-report tool may serve as prescreening tool toward a cost-effective computed tomography-based screening program for high-risk individuals.
Asunto(s)
Angiografía por Tomografía Computarizada , Angiografía Coronaria , Enfermedad de la Arteria Coronaria , Autoinforme , Humanos , Enfermedad de la Arteria Coronaria/diagnóstico por imagen , Enfermedad de la Arteria Coronaria/epidemiología , Enfermedad de la Arteria Coronaria/diagnóstico , Persona de Mediana Edad , Femenino , Masculino , Suecia/epidemiología , Angiografía Coronaria/métodos , Medición de Riesgo , Calcificación Vascular/diagnóstico por imagen , Calcificación Vascular/epidemiología , Valor Predictivo de las Pruebas , Índice de Severidad de la Enfermedad , Reproducibilidad de los ResultadosRESUMEN
BACKGROUND: Selenoprotein P (SELENOP) is a transporter for selenium and has been shown to protect selenium-status maintenance in the brain against deficiency and to support neuronal development, neurogenesis and neurocognitive function. Selenium deficiency has previously been associated with cognitive impairment in various populations, but no studies have been carried out in subjects with heart failure (HF). PURPOSE: To explore whether SELENOP deficiency in subjects with acute HF is associated with cognitive impairment. METHODS: Plasma SELENOP, as measured by an immunoassay analysis, is a well-validated marker of plasma selenium status and has the benefit of providing information on the bioavailable fraction of selenium to preferentially supplied cells equipped with receptors for SELENOP uptake. SELENOP was measured in 320 subjects hospitalized for HF. Of the subjects, 187 also underwent 4 cognitive tests assessing global cognitive function: Montreal Cognitive Assessment (MoCA); information processing (Symbol Digit Modalities Test [SDMT]); visual attention and task switching (Trailmaking Test A [TMT-A]); and executive speed (A Quick Test of Cognitive Speed [AQT] form and color). Appropriate cutoffs were used for each cognitive test to define cognitive impairment. Cross-sectional associations between SELENOP concentrations and cognitive impairment, as defined by each cognitive test, were explored using multivariable logistic models. Further, multivariable logistic models exploring associations between selenium deficiency, defined as the lowest quartile of SELENOP levels, and cognitive impairment, defined by each cognitive test, were carried out. RESULTS: The 187 participants had a mean age of 73 (± 11.9) years; 31% were female and had a mean body mass index of 28.1 (± 5.6) kg/m2. Each 1 standard deviation increment in SELENOP concentrations was associated with lower odds of cognitive impairment, defined as a MoCA cut-off score < 23 (odds ratio [OR] 0.60; 95% CI 0.40-0.91; Pâ¯=â¯0.017). Further, SELENOP concentrations in the lowest quartile (≤ 2.3 mg/L) were associated with cognitive impairment as measured by MoCA (OR 3.10; 95% CI 1.38-6.97; Pâ¯=â¯0.006), SDMT (OR 2.26; 95% CI 1.10-4.67; Pâ¯=â¯0.027) and TMT-A (OR 3.40; 95% CI 1.47-7.88; Pâ¯=â¯0.004) but not by AQT form and color. CONCLUSIONS: In subjects admitted for HF, higher SELENOP concentrations were associated with better performance on the MoCA test, reflecting global cognition, and SELENOP deficiency was associated with cognitive impairment as defined by 3 cognitive tests.
RESUMEN
AIMS: Heart failure (HF) patients with anaemia tend to have a worse outcome, with increased hospitalization rates, decreased exercise tolerance, and higher mortality compared to those without anaemia. Limited research exists on the association between selenium deficiency and anaemia specifically in HF patients, despite previous findings of a correlation in different populations. The BIOSTAT-CHF study demonstrated that higher selenium levels in HF patients were associated to a lower risk of anaemia and iron deficiency. This study investigates the relationship between selenoprotein P (SELENOP) concentrations, a major contributor and functional biomarker of selenium transport, and anaemia, Hb levels, and iron status in hospitalized HF patients. METHODS AND RESULTS: SELENOP was analysed in 320 hospitalized HF subjects, with complete data available for 310 subjects. The relationships between continuous SELENOP concentrations and 1) Hb concentrations, 2) anaemia (Hb < 115 g/L (women), <130 g/L (men)), and 3) iron status (as measured by transferrin receptor 1 (TfR1) which increases in iron deficiency) were evaluated using multivariable logistic and linear regression models. Additionally, SELENOP concentrations in the lowest quartile were related to anaemia, haemoglobin, and iron state in multivariable logistic and linear models. The mean age of the study population was 75.0 ± 11.6 years, and 30% were women. Anaemia was present in 133 subjects (42.9%). SELENOP concentrations were positively correlated with haemoglobin concentrations (0.238; P < 0.001) and negatively with TfR1 concentrations (-0.238, P < 0.001). In multivariable regression models, higher SELENOP concentrations were associated with higher Hb concentrations (B = 3.23; P = 0.002) and lower TfR1 concentrations (B = -0.20; P < 0.001). Furthermore, SELENOP deficiency was associated with lower Hb concentrations (B = -7.64: P = 0.001), higher TfR1 concentrations (B = 0.31; P = 0.003), and higher odds of anaemia in HF patients (odds ratio 2.17; 95% confidence interval 1.23-3.82; P = 0.008). CONCLUSIONS: In hospitalized heart failure patients, lower concentrations of SELENOP were associated with higher prevalence of anaemia.