ABSTRACT
BACKGROUND: Skeletal muscle loss has been associated with declining physical performance and a negative prognostic effect on falls, disability, and mortality risk in Parkinson's disease. OBJECTIVES: We aimed to analyze the clinical correlates associated with skeletal muscle wasting in Parkinson's disease. METHODS: This was a cross-sectional, case-control, observational study. We collected information on dietary intake with a 24-hour recall questionnaire, body composition with bioelectrical impedance, motor severity with the Unified Parkinson's disease Rating Scale, and physical activity with the Global Physical Activity Questionnaire. We used multivariate linear regression analysis to analyze the sociodemographic and clinical correlates associated with skeletal muscle loss after adjusting for confounding variables. RESULTS: Forty-three patients with Parkinson's disease and 21 matched family members were included. Patients and family members had similar body composition, anthropometrics, and nutritional parameters. Advanced patients had similar nutrient intakes compared to patients with mild-to-moderate Parkinson's disease. In the multivariate linear regression analysis, female patients with low physical activity and low energy intake were more likely to have skeletal muscle loss. CONCLUSIONS: Skeletal muscle wasting is a complex multifactorial problem. Dietary strategies and physical exercise should be recommended, especially to females with Parkinson's disease, to prevent significant skeletal muscle wasting.
ABSTRACT
BACKGROUND: Hospital administrative data have been suggested as a valuable cost-effective tool for providing information about the stroke burden. Nevertheless, the choice of the diagnosis codes has been a critical issue in the development of case ascertainment algorithms. METHODS: In this study, the Minimum Basic Data Set administrative database was used to analyze the accuracy of different ICD-9-CM algorithms based on the neurologist's clinical judgement as the 'gold standard'. RESULTS: The most accurate algorithm observed in our study involved the selection of ICD-9-CM codes 430-438 in the primary diagnosis. It yielded a sensitivity of 96.1%, a specificity of 87.5% and a positive predictive value of 82.5%. CONCLUSIONS: The Minimum Basic Data Set is a valuable source to evaluate stroke frequency when using an accurate algorithm to select events.
Subject(s)
Stroke/diagnosis , Stroke/epidemiology , Algorithms , Databases, Factual , HumansABSTRACT
BACKGROUND: Stroke is a public health concern and the availability of a stroke registry would provide valuable information. Administrative hospital data and mortality registries have been previously suggested as suitable sources of information. The aim of this study was to evaluate the utility of merging data from a hospital discharge database and the mortality registry (MR) to estimate the incidence of stroke in La Rioja, Spain. METHODS: A cross-sectional study about events of stroke occurred in our region in 2009 was carried out. Patients were selected among those registered in the discharge hospital database and in the MR, using the International Classification of Diseases. The databases were merged to detect duplicated occurrences and to estimate the number of cases identified by each source. Characteristics of the study population were analyzed and crude- and age-adjusted incidence rates were assessed. RESULTS: Using both databases, 1133 stroke events were detected, 153 (13.5%) representing coincident or recurrent cases. A total of 980 incident stroke cases were obtained, 150 provided by the MR (15.3%) and 830 by the hospital discharge database (84.7%). Incidence of stroke was similar in men than in women, the ischemic stroke being the major type. Most of the study population (66%) were older than 74 years. Crude incidence rate was 304.6 per 100,000, and age-adjusted rates were 171.1 per 100,000 (adjusted to the European population) and 107.9 per 100,000 (adjusted to the World population). CONCLUSIONS: Considering both the Minimum Basic Data Set and the MR as data sources appears advisable to build a stroke registry to evaluate the incidence and to perform epidemiological surveillance of stroke.
