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1.
Clin Proteomics ; 20(1): 5, 2023 Jan 24.
Artigo em Inglês | MEDLINE | ID: mdl-36694116

RESUMO

BACKGROUND: We aimed to compare absolute plasma concentrations of N-terminal pro-brain natriuretic peptide (NT-proBNP) and growth differentiation factor 15 (GDF-15) obtained by a conventional immunoassay with the corresponding relative concentrations from a proximity extension assay (PEA) and compare the prognostic impact of the protein levels obtained from these assays. METHODS: We evaluated 437 patients with peripheral arterial disease (PAD) and a population-based cohort of 643 individuals without PAD. Correlations were calculated using Spearman's rank correlation coefficients (rho). The discriminatory accuracy of the protein levels to predict future cardiovascular events was analyzed with Cox regression and presented as time-dependent areas under the receiver-operator-characteristic curves (tdAUCs). RESULTS: For NT-proBNP, the two assays correlated with rho 0.93 and 0.93 in the respective cohort. The PEA values leveled off at higher values in both cohorts. The corresponding correlations for GDF-15 were 0.91 and 0.89. At 5 years follow-up, the tdAUCs in the patient cohort were similar for NT-proBNP and GDF-15 regardless of assay used (0.65-0.66). The corresponding tdAUCs in the population-based cohort were between 0.72 and 0.77. CONCLUSION: Except for the highest levels of NT-proBNP, we suggest that PEA data for NT-proBNP and GDF-15 reliably reflects absolute plasma levels and contains similar prognostic information.

2.
Ups J Med Sci ; 1262021.
Artigo em Inglês | MEDLINE | ID: mdl-33995892

RESUMO

BACKGROUND: Patients with peripheral arterial disease (PAD) are generally less intensively managed than patients with coronary heart disease (CHD), despite that their risk of complications is believed to be equivalent. Identification of PAD patients at risk of poorly controlled blood pressure (BP) could lead to improved treatment, thus lowering the risk of cardiovascular (CV) complications. We aimed to describe the prevalence of poorly controlled cardiovascular (CV) risk factors, focusing on BP, in outpatients with PAD diagnosed in a vascular ultrasound laboratory. METHODS: Consecutive outpatients with carotid and/or lower extremity PAD were included (n = 402) and examined with blood sampling, clinical BP, and 24-h ambulatory BP measurements. A poorly controlled clinical BP was defined as ≥140/90 mmHg, ambulatory BP ≥130/80 mmHg, low-density lipoprotein (LDL)-cholesterol level ≥2.5 mmol/L, and glycated hemoglobin (HbA1c) level >53 mmol/mol in those with diabetes. RESULTS: Most of the patients had poorly controlled clinical (76.6%) and ambulatory BP (51.7%) profiles. Antihypertensive medications were prescribed in 84% of the patients. However, >40% of them used only 0-1 medication, and <25% of them used three or more agents. Clinical BP, a low number of medications, body mass index, and the presence of diabetes independently predicted a poorly controlled ambulatory BP. Nearly one-third of the patients were smokers, and most of the cohort had an LDL-cholesterol level of ≥2.5 mmol/L. An HbA1c level of >53 mmol/mol was present in 55% of diabetic patients. CONCLUSION: Poorly controlled clinical and ambulatory systolic BP profiles were common. In addition, suboptimal control of other important CV risk factors was detected. The findings of this study highlight the need for better preventive efforts against CV risk factors in outpatients with PAD.


Assuntos
Hipertensão , Doença Arterial Periférica , Pressão Sanguínea , Monitorização Ambulatorial da Pressão Arterial , Humanos , Pacientes Ambulatoriais , Doença Arterial Periférica/complicações , Fatores de Risco
3.
Atherosclerosis ; 311: 143-149, 2020 10.
Artigo em Inglês | MEDLINE | ID: mdl-32711845

RESUMO

BACKGROUND AND AIMS: Patients with peripheral arterial disease (PAD) are at high risk for fatal events. We aimed to investigate the ability among several serum proteins to predict all-cause mortality in outpatients with PAD. METHODS: Consecutive outpatients with carotid and/or lower extremity PAD were included in the discovery cohort (n = 436), and subjects with PAD from a population-based sample in the validation cohort (n = 129). Blood samples were analyzed for 81 proteins by a proximity extension assay. The proteins best predicting incident all-cause mortality were identified using L1-regularized Cox regression. The added value of the identified proteins to clinical risk markers was evaluated by Cox regression models and presented by the area under the receiver operator characteristics curves (AUC). RESULTS: In the discovery cohort (mean age 70 years; 59% men), 195 died (4.8 events per 100 person-years) during a 10.3 years median follow-up. The clinical risk markers generated an AUC of 0.70 (95% confidence interval [95%CI] 0.65-0.76). The two serum protein biomarkers with best prediction of all-cause mortality were growth differentiation factor 15 and tumor necrosis factor-related apoptosis-inducing ligand receptor 2. Adding these proteins to the clinical risk markers significantly improved prediction (p < 0.001) and yielded an AUC of 0.76 (95%CI 0.71-0.80). A higher discriminatory performance was observed in the validation cohort (AUC 0.84; 95% CI 0.76-0.92). CONCLUSIONS: In a large-sample targeted proteomics assay, we identified two proteins that improved risk prediction beyond the COPART risk score. The use of high-throughput proteomics assays may identify potential biomarkers for improved risk prediction in patients with PAD.


Assuntos
Doença Arterial Periférica , Proteômica , Idoso , Biomarcadores , Feminino , Seguimentos , Humanos , Masculino , Pacientes Ambulatoriais , Doença Arterial Periférica/diagnóstico , Medição de Risco , Fatores de Risco
4.
Eur J Prev Cardiol ; 24(15): 1576-1583, 2017 10.
Artigo em Inglês | MEDLINE | ID: mdl-28762762

RESUMO

Background The Proximity Extension Assay proteomics chip provides a large-scale analysis of 92 biomarkers linked to cardiovascular disease or inflammation. We aimed to identify the biomarkers that best predicted long-term all-cause mortality in patients with acute myocardial infarction. Methods In this prospective cohort study, 92 biomarkers were analysed in 847 consecutive patients from the Västmanland Myocardial Infarction Study with a median follow-up of 6.9 years. Results The mean (± standard deviation) age of the patients was 70 (11.8) years and 32.7% were female. Two hundred and seven patients had died after follow-up. The biomarkers most strongly linked to all-cause mortality were growth differentiation factor 15 (GDF-15) and tumour necrosis factor-related apoptosis-inducing ligand receptor 2 (TRAIL-R2). Cox regression analysis showed that GDF-15 (hazard ratio 1.25 per unit change, 95% confidence interval, 1.02-1.53, p = 0.031) and TRAIL-R2 (hazard ratio 1.37 per unit change, 95% confidence interval 1.12-1.67, p = 0.002) were independent predictors of long-term all-cause mortality after adjusting for age, gender, diabetes, previous myocardial infarction, stroke, heart failure, hypertension, smoking, hypercholesterolaemia, body mass index, ST-elevation myocardial infarction, left ventricular ejection fraction, troponin I, estimated glomerular filtration rate, N-terminal pro-brain natriuretic peptide and C-reactive protein. The combination of GDF-15 and TRAIL-R2 with established risk factors and biomarkers showed a discriminating accuracy of separating survivors from non-survivors with a cross-validated area under the receiving operating characteristics curve of 0.88 within five years. Conclusion GDF-15 and TRAIL-R2 were the most powerful Proximity Extension Assay chip biomarkers in predicting long-term all-cause mortality in patients with acute myocardial infarction.


Assuntos
Fator 15 de Diferenciação de Crescimento/sangue , Infarto do Miocárdio/sangue , Infarto do Miocárdio/mortalidade , Receptores do Ligante Indutor de Apoptose Relacionado a TNF/sangue , Idoso , Idoso de 80 Anos ou mais , Área Sob a Curva , Biomarcadores/sangue , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Infarto do Miocárdio/diagnóstico , Valor Preditivo dos Testes , Prognóstico , Modelos de Riscos Proporcionais , Estudos Prospectivos , Análise Serial de Proteínas , Proteômica/métodos , Curva ROC , Reprodutibilidade dos Testes , Fatores de Risco , Suécia , Fatores de Tempo
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