Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 7 de 7
Filtrar
1.
Diabet Med ; 36(9): 1118-1124, 2019 09.
Artículo en Inglés | MEDLINE | ID: mdl-30575096

RESUMEN

AIM: To assess if latent autoimmune diabetes of adulthood (LADA) is associated with small fibre neuropathy. METHODS: Participants with LADA (n=31), Type 2 diabetes (n=31) and healthy control participants without diabetes (n=31) underwent a detailed assessment of neurologic deficits, quantitative sensory testing, electrophysiology, skin biopsy and corneal confocal microscopy. RESULTS: The groups were matched for age (healthy control without diabetes: 53.5±9.1 vs. Type 2 diabetes: 58.0±6.5 vs. LADA: 53.2±11.6 years), duration of diabetes (Type 2 diabetes: 10.0±8.3 vs. LADA: 11.0±9.1 years) and blood pressure. However, BMI (P=0.01) and triglycerides (P=0.0008) were lower and HbA1c (P=0.0005), total cholesterol (P=0.01) and HDL (P=0.002) were higher in participants with LADA compared with Type 2 diabetes. Peroneal motor nerve conduction velocity (P=0.04) and sural sensory nerve conduction velocity (P=0.008) were lower in participants with latent autoimmune diabetes in adults compared with Type 2 diabetes. Intra-epidermal nerve fibre density (P=0.008), corneal nerve fibre density (P=0.003) and corneal nerve branch density (P=0.006) were significantly lower in participants with LADA compared with Type 2 diabetes. There were no significant differences in the other neuropathy parameters. CONCLUSIONS: Despite comparable age and duration of diabetes, participants with LADA demonstrate more severe neuropathy and particularly small fibre neuropathy, compared with participants with Type 2 diabetes.


Asunto(s)
Diabetes Autoinmune Latente del Adulto/complicaciones , Diabetes Autoinmune Latente del Adulto/epidemiología , Neuropatía de Fibras Pequeñas/epidemiología , Neuropatía de Fibras Pequeñas/etiología , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Estudios de Casos y Controles , Diabetes Mellitus Tipo 2/complicaciones , Diabetes Mellitus Tipo 2/diagnóstico , Diabetes Mellitus Tipo 2/epidemiología , Neuropatías Diabéticas/diagnóstico , Neuropatías Diabéticas/epidemiología , Neuropatías Diabéticas/etiología , Diagnóstico Diferencial , Femenino , Humanos , Diabetes Autoinmune Latente del Adulto/diagnóstico , Masculino , Persona de Mediana Edad , Factores de Riesgo , Índice de Severidad de la Enfermedad , Neuropatía de Fibras Pequeñas/diagnóstico , Adulto Joven
2.
Diabet Med ; 34(4): 478-484, 2017 04.
Artículo en Inglés | MEDLINE | ID: mdl-27917530

RESUMEN

Diabetic retinopathy is the most common cause of vision loss in people with diabetes mellitus; however, other causes of visual impairment/loss include other retinal and non-retinal visual problems, including glaucoma, age-related macular degeneration, non-arteritic anterior ischaemic optic neuropathy and cataracts. Additionally, when a person with diabetes complains of visual disturbance despite a visual acuity of 6/6, abnormalities in refraction, contrast sensitivity, straylight and amplitude of accommodation should be considered. We review and highlight these visual problems for physicians who manage people with diabetes to ensure timely referral and treatment to limit visual disability, which can have a significant impact on daily living, especially for those participating in sports and driving.


Asunto(s)
Catarata/complicaciones , Complicaciones de la Diabetes/complicaciones , Diabetes Mellitus , Glaucoma/complicaciones , Degeneración Macular/complicaciones , Trastornos de la Visión/etiología , Catarata/fisiopatología , Sensibilidad de Contraste , Complicaciones de la Diabetes/fisiopatología , Retinopatía Diabética/complicaciones , Retinopatía Diabética/fisiopatología , Glaucoma/fisiopatología , Humanos , Degeneración Macular/fisiopatología , Presbiopía/complicaciones , Presbiopía/fisiopatología , Errores de Refracción/complicaciones , Errores de Refracción/fisiopatología , Trastornos de la Visión/fisiopatología
3.
Diabetes Res Clin Pract ; 113: 101-7, 2016 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-26830855

RESUMEN

AIMS: Sensory neuropathy is central to the development of painful neuropathy, and foot ulceration in patients with diabetes. Currently, available QST devices take considerable time to perform and are expensive. NerveCheck is the first inexpensive ($500), portable QST device to perform both vibration and thermal testing and hence evaluate diabetic peripheral neuropathy (DPN). This study was undertaken to establish the reproducibility and diagnostic validity of NerveCheck for detecting neuropathy. METHODS: 130 subjects (28 with DPN, 46 without DPN and 56 control subjects) underwent QST assessment with NerveCheck; vibration perception and thermal testing. DPN was defined according to the Toronto criteria. RESULTS: NerveCheck's intra correlation coefficient for vibration, cold and warm sensation testing was 0.79 (95% LOA: -4.20 to 6.60), 0.86 (95% LOA: -1.38 to 2.72) and 0.71 (95% LOA: -2.36 to 3.83), respectively. The diagnostic accuracy (AUC) for vibration, cold and warm sensation testing was 86% (SE: 0.038, 95% CI 0.79-0.94), 79% (SE: 0.058, 95% CI 0.68-0.91) and 72% (SE: 0.058, 95% CI 0.60-0.83), respectively. CONCLUSIONS: This study shows that NerveCheck has good reproducibility and comparable diagnostic accuracy to established QST equipment for the diagnosis of DPN.


Asunto(s)
Neuropatías Diabéticas/diagnóstico , Técnicas de Diagnóstico Neurológico/instrumentación , Adulto , Anciano , Estudios de Casos y Controles , Femenino , Humanos , Masculino , Persona de Mediana Edad , Dolor , Enfermedades del Sistema Nervioso Periférico , Reproducibilidad de los Resultados , Vibración
4.
Handb Clin Neurol ; 126: 275-90, 2014.
Artículo en Inglés | MEDLINE | ID: mdl-25410229

RESUMEN

Small fiber neuropathy represents a significant component of diabetic sensorimotor polyneuropathy (DSPN) which has to date been ignored in most recommendations for the diagnosis of DSPN. Small fibers predominate in the peripheral nerve, serve crucial and highly clinically relevant functions such as pain, and regulate microvascular blood flow, mediating the mechanisms underlying foot ulceration. An increasing number of diagnostic tests have been developed to quantify small fiber damage. Because small fiber damage precedes large fiber damage, diagnostic tests for DSPN show good sensitivity but moderate specificity, because the gold standard which is used to define DSPN is large fiber-weighted. Hence new diagnostic algorithms for DSPN should acknowledge this emerging data and incorporate small fiber evaluation as a key measure in the diagnosis of DSPN, especially early neuropathy.


Asunto(s)
Diabetes Mellitus/diagnóstico , Neuropatías Diabéticas/diagnóstico , Eritromelalgia/diagnóstico , Fibras Nerviosas/patología , Animales , Diabetes Mellitus/epidemiología , Neuropatías Diabéticas/epidemiología , Diagnóstico Diferencial , Eritromelalgia/epidemiología , Humanos , Piel/inervación
5.
Diabet Med ; 31(12): 1673-80, 2014 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-24975286

RESUMEN

AIMS: Neuropad is a simple visual indicator test, with moderate diagnostic performance for diabetic peripheral neuropathy. As it assesses sweating, which is a measure of cholinergic small nerve fibre function, we compared its diagnostic performance against established measures of both large and, more specifically, small fibre damage in patients with diabetes. METHODS: One hundred and twenty-seven participants (89 without diabetic peripheral neuropathy and 38 with) aged 57 ± 9.7 years underwent assessment with Neuropad, large nerve fibre assessments: Neuropathy Disability Score, vibration perception threshold, peroneal motor nerve conduction velocity; small nerve fibre assessments: neuropathy symptoms (Diabetic Neuropathy Symptoms score) corneal nerve fibre length and warm perception threshold. RESULTS: Neuropad has a high sensitivity but moderate specificity against large fibre neuropathy assessments: Neuropathy Disability Score (> 2) 70% and 50%, vibration perception threshold (> 14 V) 83% and 53%, and peroneal motor nerve conduction velocity (< 42 m/s) 81% and 54%, respectively. However, the diagnostic accuracy of Neuropad was significantly improved against corneal nerve fibre length (< 14 mm/mm2) with a sensitivity and specificity of 83% and 80%, respectively. Furthermore, the area under the curve for corneal nerve fibre length (85%) was significantly greater than with the Neuropathy Disability Score (66%, P = 0.01) and peroneal motor nerve conduction velocity (70%, P = 0.03). For neuropathic symptoms, sensitivity was 78% and specificity was 60%. CONCLUSIONS: The data show the improved diagnostic performance of Neuropad against corneal nerve fibre length. This study underlines the importance of Neuropad as a practical diagnostic test for small fibre neuropathy in patients with diabetes.


Asunto(s)
Neuropatías Diabéticas/diagnóstico , Glándulas Sudoríparas/inervación , Adulto , Anciano , Estudios de Casos y Controles , Diabetes Mellitus Tipo 1/complicaciones , Diabetes Mellitus Tipo 2/complicaciones , Neuropatías Diabéticas/etiología , Neuropatías Diabéticas/fisiopatología , Femenino , Humanos , Masculino , Persona de Mediana Edad , Conducción Nerviosa/fisiología , Percepción/fisiología , Nervio Peroneo/fisiopatología , Sensibilidad y Especificidad , Glándulas Sudoríparas/fisiopatología , Sudoración/fisiología , Vibración
7.
Med Image Anal ; 15(5): 738-47, 2011 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-21719344

RESUMEN

Diabetic peripheral neuropathy (DPN) is one of the most common long term complications of diabetes. Corneal confocal microscopy (CCM) image analysis is a novel non-invasive technique which quantifies corneal nerve fibre damage and enables diagnosis of DPN. This paper presents an automatic analysis and classification system for detecting nerve fibres in CCM images based on a multi-scale adaptive dual-model detection algorithm. The algorithm exploits the curvilinear structure of the nerve fibres and adapts itself to the local image information. Detected nerve fibres are then quantified and used as feature vectors for classification using random forest (RF) and neural networks (NNT) classifiers. We show, in a comparative study with other well known curvilinear detectors, that the best performance is achieved by the multi-scale dual model in conjunction with the NNT classifier. An evaluation of clinical effectiveness shows that the performance of the automated system matches that of ground-truth defined by expert manual annotation.


Asunto(s)
Algoritmos , Córnea/inervación , Córnea/patología , Retinopatía Diabética/patología , Interpretación de Imagen Asistida por Computador/métodos , Microscopía Confocal/métodos , Fibras Nerviosas/patología , Reconocimiento de Normas Patrones Automatizadas/métodos , Humanos , Aumento de la Imagen/métodos , Modelos Biológicos , Oftalmoscopía/métodos , Sensibilidad y Especificidad
SELECCIÓN DE REFERENCIAS
DETALLE DE LA BÚSQUEDA
...