663 resultados para emerging disease


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Deprivation assessed using the index of multiple deprivation (IMD) has been shown to be an independent risk factor for 1-year mortality in outpatients with chronic obstructive pulmonary disease; COPD (Collins et al, 2010). IMD combines a number of economic and social issues (eg, health, education, employment) into one overall deprivation score, the higher the score the higher an individual's deprivation. Whilst malnutrition in COPD has been linked to increased healthcare use it is not clear if deprivation is also independently associated. This study aimed to investigate the influence of deprivation on 1-year healthcare utilisation in outpatients with COPD. IMD was established in 424 outpatients with COPD according to the geographical location for each patient's address (postcode) and related to their healthcare use in the year post-date screened (Nobel et al, 2008). Patients were routinely screened in outpatient clinics for malnutrition using the ‘Malnutrition Universal Screening Tool’, ‘MUST’ (Elia 2003); mean age 73 (SD 9.9) years; body mass index 25.8 (SD 6.3) kg/m2 with healthcare use collected 1 year from screening (Abstract P147 Table 1). Deprivation assessed using IMD (mean 15.9; SD 11.1) was found to be a significant predictor for the frequency and duration of emergency hospital admissions as well as the duration of elective hospital admission. Deprivation was also linked to reduced secondary care outpatient appointment attendance but not an increase in failure to attend and deprivation was not associated with increased disease severity, as classified by the GOLD criteria (p=0.580). COPD outpatients residing in more deprived areas experience increased hospitalisation rates but decreased outpatient appointment attendance. The underlying reason behind this disparity in healthcare use requires further investigation.

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BACKGROUND: The efficacy of nutritional support in the management of malnutrition in chronic obstructive pulmonary disease (COPD) is controversial. Previous meta-analyses, based on only cross-sectional analysis at the end of intervention trials, found no evidence of improved outcomes. OBJECTIVE: The objective was to conduct a meta-analysis of randomized controlled trials (RCTs) to clarify the efficacy of nutritional support in improving intake, anthropometric measures, and grip strength in stable COPD. DESIGN: Literature databases were searched to identify RCTs comparing nutritional support with controls in stable COPD. RESULTS: Thirteen RCTs (n = 439) of nutritional support [dietary advice (1 RCT), oral nutritional supplements (ONS; 11 RCTs), and enteral tube feeding (1 RCT)] with a control comparison were identified. An analysis of the changes induced by nutritional support and those obtained only at the end of the intervention showed significantly greater increases in mean total protein and energy intakes with nutritional support of 14.8 g and 236 kcal daily. Meta-analyses also showed greater mean (±SE) improvements in favor of nutritional support for body weight (1.94 ± 0.26 kg, P < 0.001; 11 studies, n = 308) and grip strength (5.3%, P < 0.050; 4 studies, n = 156), which was not shown by ANOVA at the end of the intervention, largely because of bias associated with baseline imbalance between groups. CONCLUSION: This systematic review and meta-analysis showed that nutritional support, mainly in the form of ONS, improves total intake, anthropometric measures, and grip strength in COPD. These results contrast with the results of previous analyses that were based on only cross-sectional measures at the end of intervention trials.

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Introduction:  Smoking status in outpatients with chronic obstructive pulmonary disease (COPD) has been associated with a low body mass index (BMI) and reduced mid-arm muscle circumference (Cochrane & Afolabi, 2004). Individuals with COPD identified as malnourished have also been found to be twice as likely to die within 1 year compared to non-malnourished patients (Collins et al., 2010). Although malnutrition is both preventable and treatable, it is not clear what influence current smoking status, another modifiable risk factor, has on malnutrition risk. The current study aimed to establish the influence of smoking status on malnutrition risk and 1-year mortality in outpatients with COPD. Methods:  A prospective nutritional screening survey was carried out between July 2008 and May 2009 at a large teaching hospital (Southampton General Hospital) and a smaller community hospital within Hampshire (Lymington New Forest Hospital). In total, 424 outpatients with a diagnosis of COPD were routinely screened using the ‘Malnutrition Universal Screening Tool’, ‘MUST’ (Elia, 2003); 222 males, 202 females; mean (SD) age 73 (9.9) years; mean (SD) BMI 25.9 (6.4) kg m−2. Smoking status on the date of screening was obtained for 401 of the outpatients. Severity of COPD was assessed using the GOLD criteria, and social deprivation determined using the Index of Multiple Deprivation (Nobel et al., 2008). Results:  The overall prevalence of malnutrition (medium + high risk) was 22%, with 32% of current smokers at risk (who accounted for 19% of the total COPD population). In comparison, 19% of nonsmokers and ex-smokers were likely to be malnourished [odds ratio, 1.965; 95% confidence interval (CI), 1.133–3.394; P = 0.015]. Smoking status remained an independent risk factor for malnutrition even after adjustment for age, social deprivation and disease-severity (odds ratio, 2.048; 95% CI, 1.085–3.866; P = 0.027) using binary logistic regression. After adjusting for age, disease severity, social deprivation, smoking status, malnutrition remained a significant predictor of 1-year mortality [odds ratio (medium + high risk versus low risk), 2.161; 95% CI, 1.021–4.573; P = 0.044], whereas smoking status did not (odds ratio for smokers versus ex-smokers + nonsmokers was 1.968; 95% CI, 0.788–4.913; P = 0.147). Discussion:  This study highlights the potential importance of combined nutritional support and smoking cessation in order to treat malnutrition. The close association between smoking status and malnutrition risk in COPD suggests that smoking is an important consideration in the nutritional management of malnourished COPD outpatients. Conclusions:  Smoking status in COPD outpatients is a significant independent risk factor for malnutrition and a weaker (nonsignificant) predictor of 1-year mortality. Malnutrition significantly predicted 1 year mortality. References:  Cochrane, W.J. & Afolabi, O.A. (2004) Investigation into the nutritional status, dietary intake and smoking habits of patients with chronic obstructive pulmonary disease. J. Hum. Nutr. Diet.17, 3–11. Collins, P.F., Stratton, R.J., Kurukulaaratchym R., Warwick, H. Cawood, A.L. & Elia, M. (2010) ‘MUST’ predicts 1-year survival in outpatients with chronic obstructive pulmonary disease. Clin. Nutr.5, 17. Elia, M. (Ed) (2003) The ‘MUST’ Report. BAPEN. http://www.bapen.org.uk (accessed on March 30 2011). Nobel, M., McLennan, D., Wilkinson, K., Whitworth, A. & Barnes, H. (2008) The English Indices of Deprivation 2007. http://www.communities.gov.uk (accessed on March 30 2011).

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Deprivation is linked to increased incidence in a number of chronic diseases but its relationship to chronic obstructive pulmonary disease (COPD) is uncertain despite suggestions that the socioeconomic gradient seen in COPD is as great, if not greater, than any other disease (Prescott and Vestbo).1 There is also a need to take into account the confounding effects of malnutrition which have been shown to be independently linked to increased mortality (Collins et al).2 The current study investigated the influence of social deprivation on 1-year survival rates in COPD outpatients, independently of malnutrition. 424 outpatients with COPD were routinely screened for malnutrition risk using the ‘Malnutrition Universal Screening Tool’; ‘MUST’ (Elia),3 between July and May 2009; 222 males and 202 females; mean age 73 (SD 9.9) years; body mass index 25.8 (SD 6.3) kg/m2. Each individual's deprivation was calculated using the index of multiple deprivation (IMD) which was established according to the geographical location of each patient's address (postcode). IMD includes a number of indicators covering economic, housing and social issues (eg, health, education and employment) into a single deprivation score (Nobel et al).4 The lower the IMD score, the lower an individual's deprivation. The IMD was assigned to each outpatient at the time of screening and related to1-year mortality from the date screened. Outpatients who died within 1-year of screening were significantly more likely to reside within a deprived postcode (IMD 19.7±SD 13.1 vs 15.4±SD 10.7; p=0.023, OR 1.03, 95% CI 1.00 to 1.06) than those that did not die. Deprivation remained a significant independent risk factor for 1-year mortality even when adjusted for malnutrition as well as age, gender and disease severity (binary logistic regression; p=0.008, OR 1.04, 95% CI 1.04 to 1.07). Deprivation was not associated with disease-severity (p=0.906) or body mass index, kg/m2 (p=0.921) using ANOVA. This is the first study to show that deprivation, assessed using IMD, is associated with increased 1-year mortality in outpatients with COPD independently of malnutrition, age and disease severity. Deprivation should be considered in the targeted management of these patients.

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Deprivation assessed using the Index of Multiple Deprivation (IMD) has been shown to be an independent risk factor for both malnutrition and mortality in outpatients with chronic obstructive pulmonary disease (COPD) (Collins et al., 2010a, b). IMD consists of a range of different deprivation domains, although it is unclear which ones are most closely linked to malnutrition. The aim of the current study was to investigate whether the relationship between malnutrition and deprivation was a general one, affecting all domains in a consistent manner, or specific, affecting only certain domains.

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Objective To identify the spatial and temporal clusters of Barmah Forest virus (BFV) disease in Queensland in Australia, using geographical information systems (GIS) and spatial scan statistic (SaTScan). Methods We obtained BFV disease cases, population and statistical local areas boundary data from Queensland Health and Australian Bureau of Statistics respectively during 1992-2008 for Queensland. A retrospective Poisson-based analysis using SaTScan software and method was conducted in order to identify both purely spatial and space-time BFV disease high-rate clusters. A spatial cluster size of a proportion of the population and a 200km circle radius and varying time windows from 1 month to 12 months were chosen (for the space-time analysis). Results The spatial scan statistic detected a most likely significant purely spatial cluster (including 23 SLAs) and a most likely significant space-time cluster (including 24 SLAs) in approximately the same location. Significant secondary clusters were also identified from both the analyses in several locations. Conclusions This study provides evidence of the existence of statistically significant BFV disease clusters in Queensland, Australia. The study also demonstrated the relevance and applicability of SaTScan in analysing on-going surveillance data to identify clusters to facilitate the development of effective BFV disease prevention and control strategies in Queensland, Australia.