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Alzheimer disease (AD) is the most common form of age-related dementia. The etiology of AD is considered to be multifactorial as only a negligible percentage of cases have a familial or genetic origin. Glycogen synthase kinase-3 (GSK-3) is regarded as a critical molecular link between the two histopathological hallmarks of the disease, namely senile plaques and neurofibrillary tangles. In this review, we summarize current data regarding the involvement of this kinase in several aspects of AD development and progression, as well as key observations highlighting GSK-3 as one of the most relevant targets for AD treatment.
RESUMEN
PURPOSE: The purpose of the study was to evaluate the prevalence of cardiovascular disease (CVD), cardiovascular risk factors (CVRFs), and their control in patients with type 2 diabetes mellitus (T2DM) at primary care settings from the North Catalonia Diabetes Study (NCDS). DATA SOURCES: In this multicentre cross-sectional descriptive study, data were collected from a random sample of 307 patients with T2DM. The prevalence of CVD, CVRF, metabolic syndrome (MS), coronary heart disease (CHD) risk at 10 years (Framingham Point Scores), and CVRF control was evaluated. MS and lipid profiles were established according to Adult Treatment Panel III criteria. CONCLUSIONS: CVD prevalence was 22.0% (CHD: 18.9% and peripheral ischemia: 4.5%) and more frequent in men. The prevalence of selected CVRF was: hypertension: 74.5%; dyslipidemia: 77.7%; smoking: 14.9%; obesity 44.9%, and familial CVD: 38.4%. Three or more CVRFs, including T2DM, were observed in 91.3%. MS prevalence was 68.7%. Framingham score was 10.0%, higher in men than in women. CVD prevalence was related to: age, number of CVRFs, duration of diabetes, familial history of CVD, waist circumference, hypertension, lipid profile, kidney disease, and Framingham score, but not to MS by itself. Correct lipid profiles and blood pressure were only observed in 18.9% and 24.0%, respectively, whereas platelet aggregation inhibitors were only recorded in 16.1% of the patient cohort. MS presence was not an independent risk factor of CVD in our study. IMPLICATIONS FOR PRACTICE: The high prevalence of CVD and an inadequate control of CVRF, which were apparent in the NCDS population, would suggest that advanced practice nurses should consider incorporating specific cardiovascular assessment in their routine care of persons with T2DM.
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Enfermedades Cardiovasculares/epidemiología , Diabetes Mellitus Tipo 2/epidemiología , Conductas Relacionadas con la Salud , Población , Adulto , Anciano , Enfermedades Cardiovasculares/prevención & control , Colesterol/sangre , Comorbilidad , Estudios Transversales , Diabetes Mellitus Tipo 2/prevención & control , Femenino , Humanos , Hipertensión/epidemiología , Masculino , Síndrome Metabólico/epidemiología , Persona de Mediana Edad , Obesidad/epidemiología , Prevalencia , Factores de Riesgo , Distribución por Sexo , España/epidemiología , Tabaquismo/epidemiologíaRESUMEN
INTRODUCTION: In a previous study we developed a specific algorithm, the polyneuropathy selection method (PSM) with 4 parameters (age, HDL-C, HbA1c, and retinopathy), to select patients at risk of diabetic polyneuropathy (DPN). We also developed a simplified method for DPN diagnosis: outpatient polyneuropathy diagnosis (OPD), with 4 variables (symptoms and 3 objective tests). OBJECTIVES: To confirm the validity of conventional tests for DPN diagnosis; to validate the discriminatory power of the PSM and the diagnostic value of OPD by evaluating their relationship to electrodiagnosis studies and objective clinical neurological assessment; and to evaluate the correlation of DPN and pro-inflammatory status. DESIGN: Cross-sectional, crossed association for PSM validation. Paired samples for OPD validation. SETTING: Primary care in 3 counties. PARTICIPANTS: Random sample of 75 subjects from the type-2 diabetes census for PSM evaluation. Thirty DPN patients and 30 non-DPN patients (from 2 DM2 sub-groups in our earlier study) for OPD evaluation. METHODS: The gold standard for DPN diagnosis will be studied by means of a clinical neurological study (symptoms, physical examination, and sensitivity tests) and electrodiagnosis studies (sensitivity and motor EMG). Risks of neuropathy, macroangiopathy and pro-inflammatory status (PCR, TNF soluble fraction and total TGF-beta1) will be studied in every subject. EXPECTED RESULTS: Electrodiagnosis studies should confirm the validity of conventional tests for DPN diagnosis. PSM and OPD will be valid methods for selecting patients at risk and diagnosing DPN. There will be a significant relationship between DPN and pro-inflammatory tests.
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Diabetes Mellitus Tipo 2/complicaciones , Neuropatías Diabéticas/diagnóstico , Algoritmos , Estudios Transversales , Interpretación Estadística de Datos , Neuropatías Diabéticas/prevención & control , Electromiografía , Humanos , Consentimiento Informado , Examen Neurológico , Selección de Paciente , Examen Físico , Proyectos Piloto , Atención Primaria de Salud , Curva ROC , Factores de Riesgo , MuestreoRESUMEN
Introducción. En una investigación previa hemos desarrollado un algoritmo: polyneuropathy selection method (PSM) con 4 parámetros (edad, cHDL, HbA1c y retinopatía diabética) para seleccionar a los pacientes con riesgo de presentar polineuropatía diabética (PND), y un método simplificado para su diagnóstico: outpatient polyneuropathy diagnosis (OPD) con 4 variables (síntomas y 3 pruebas objetivas). Objetivos. Confirmar la validez de las pruebas convencionales para diagnosticar la PND. Validar el poder discriminatorio del PSM y el poder diagnóstico del OPD mediante la evaluación de su relación con estudios de electrodiagnóstico y la valoración neurológica clínica objetiva. Evaluar la correlación entre la PND y la situación proinflamatoria. Diseño. Transversal de asociación cruzada para validar el PSM; muestras emparejadas para validar el OPD. Ámbito. Atención primaria de 3 comarcas. Sujetos. Para validar el PSM: muestra aleatoria de 75 pacientes del censo de diabéticos tipo 2. Para validar el OPD, 30 pacientes con PND y 30 sin PND seleccionados entre 2 subgrupos de diabéticos no insulinodependientes de nuestro estudio previo. Método. El diagnóstico de PND se realizará mediante valoración clínica neurológica (síntomas, exploración física y pruebas de sensibilidad) y estudios de electrodiagnóstico (electromiografía [EMG] sensitiva y motora) como «pruebas de referencia». Se determinarán factores de riesgo de neuropatía, macroangiopatía y citocinas proinflamatorias (PCR, TNF fracción soluble,TGF-ß1 total) en todos los sujetos. Resultados esperados. Las pruebas de EMG confirman la capacidad de las pruebas convencionales para diagnosticar la PND. El PSM y el OPD son métodos válidos para seleccionar a los pacientes con riesgo y para diagnosticar la PND. Hay una relación significativa entre PND y las pruebas proinflamatorias
Introduction. In a previous study we developed a specific algorithm, the polyneuropathy selection method (PSM) with 4 parameters (age, HDL-C, HbA1c, and retinopathy), to select patients at risk of diabetic polyneuropathy (DPN). We also developed a simplified method for DPN diagnosis: outpatient polyneuropathy diagnosis (OPD), with 4 variables (symptoms and 3 objective tests). Objectives. To confirm the validity of conventional tests for DPN diagnosis; to validate the discriminatory power of the PSM and the diagnostic value of OPD by evaluating their relationship to electrodiagnosis studies and objective clinical neurological assessment; and to evaluate the correlation of DPN and pro-inflammatory status. Design. Cross-sectional, crossed association for PSM validation. Paired samples for OPD validation. Setting. Primary care in 3 counties. Participants. Random sample of 75 subjects from the type-2 diabetes census for PSM evaluation. Thirty DPN patients and 30 non-DPN patients (from 2 DM2 sub-groups in our earlier study) for OPD evaluation. Methods. The gold standard for DPN diagnosis will be studied by means of a clinical neurological study (symptoms, physical examination, and sensitivity tests) and electrodiagnosis studies (sensitivity and motor EMG). Risks of neuropathy, macroangiopathy and pro-inflammatory status (PCR, TNF soluble fraction and total TGF-ß1) will be studied in every subject. Expected results. Electrodiagnosis studies should confirm the validity of conventional tests for DPN diagnosis. PSM and OPD will be valid methods for selecting patients at risk and diagnosing DPN. There will be a significant relationship between DPN and pro-inflammatory tests