São Paulo medical journal = Revista paulista de medicina
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Dementia is a highly prevalent condition worldwide. Its chronic and progressive presentation has an impact on physical and psychosocial characteristics and on public healthcare. Our aim was to summarize evidence from Cochrane reviews on non-pharmacological treatments for cognitive disorders and dementia. ⋯ Many non-pharmacological interventions for patients with cognitive impairment and dementia have been studied and potential benefits have been shown. However, the strength of evidence derived from these studies was considered low overall, due to the methodological limitations of the primary studies.
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Aging causes changes in men and women. Studies have shown that women have worse postural balance and greater functional dependence than men, but there is no consensus regarding this. The aim of this study was to compare the balance and functional independence of elderly people according to sex and age, and to evaluate the association between postural balance and the number of drugs taken. ⋯ There was no sexual difference in relation to postural balance. However, people who were more elderly presented a high risk of falling. Functional dependence was worse among females. There was an association between the number of medication drugs and risk of falling.
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It has been suggested in the literature that periodontal disease (PD) is associated with cardiovascular risk. The objective of this study was to appraise the relationship between periodontal disease (gingivitis and periodontitis) and traditional cardiovascular risk factors (obesity, hypertension, dyslipidemia, diabetes and metabolic syndrome) among young and middle-aged adults attended at a health promotion and check-up center in the city of São Paulo, Brazil. ⋯ We did not find any significant associations between cardiovascular risk factors and periodontal disease in this sample.
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Comparative Study
Comparison of machine-learning algorithms to build a predictive model for detecting undiagnosed diabetes - ELSA-Brasil: accuracy study.
Type 2 diabetes is a chronic disease associated with a wide range of serious health complications that have a major impact on overall health. The aims here were to develop and validate predictive models for detecting undiagnosed diabetes using data from the Longitudinal Study of Adult Health (ELSA-Brasil) and to compare the performance of different machine-learning algorithms in this task. ⋯ Most of the predictive models produced similar results, and demonstrated the feasibility of identifying individuals with highest probability of having undiagnosed diabetes, through easily-obtained clinical data.