BackgroundThe study objectives were to identify the main predictive factors for long hospital stays and to propose new and improved methods of risk assessment.MethodsThis prospective cohort study was conducted in the clinics and surgical wards of a tertiary hospital and involved 523 elderly patients over 60 years of age. Demographic, clinical, functional, and cognitive characteristics assessed between 48 and 72 h after admission were analyzed to investigate correlations with lengths of stay greater than 10 days. Univariate and multivariate analyses were performed, and in the final model, long-term probability scores were estimated for each variable.ResultsOf the 523 patients studied, 33 (6.3%) remained hospitalized for more than 10 days. Multiple regression analysis revealed that both the presence of diabetes and the inability to perform chair-to-bed transfers (Barthel Index) remained significant risk predictors. Diabetes doubled the risk of prolonged hospital stays, while a chair-to-bed transfer score of 0 or 5 led to an eight-fold increase in risk. Conclusions: In this study, we propose an easy method that can be used, after external validation, to screen for long-term risk (using diabetes and bed/chair transfer) as a first step in identifying hospitalized elderly patients who will require comprehensive assessment to guide prevention plans and rehabilitation programs.Electronic supplementary materialThe online version of this article (10.1186/s12877-019-1104-4) contains supplementary material, which is available to authorized users.
INTRODUÇÃO: A dor pélvica crônica (DPC) é uma condição comum, complexa e pouco compreendida. Há evidências de que o sistema musculoesquelético esteja comprometido, embora estudos que avaliem o padrão de movimento deste grupo ainda sejam escassos. OBJETIVO: Avaliar objetivamente a marcha de mulheres com DPC. MÉTODOS: Estudo transversal, incluindo 20 mulheres com DPC e 20 saudáveis. Utilizou-se a análise tridimensional para obtenção dos dados referente a marcha. Foi obtido variáveis espaço-temporais. Além disso foram coletados dados para caracterização da amostra sobre idade, dados antropométricos, cinesiofobia, nível de atividade física, qualidade de vida e estado de humor. O teste não paramétrico de Mann-Whitney comparou as variáveis quantitativas, e a correlação de Spearman comparou as variáveis da marcha com cinesiofobia, dor, ansiedade e depressão. RESULTADOS: Mulheres com DPC apresentaram alterações na marcha quando comparadas às saudáveis. Os movimentos comprometidos foram redução na velocidade da marcha e comprimento do passo. Não notamos ocorrência de correlação entre as variáveis da marcha com dor, cinesiofobia e depressão. CONCLUSÃO: Mulheres com DPC apresentam alterações na marcha quando comparadas a mulheres saudáveis. Estes achados sugerem a necessidade de uma avaliação mais detalhada deste grupo, para que se obtenha melhores diagnósticos e tratamentos mais eficazes.
Objective: To develop and validate a high-risk predictive model that identifies, at least, one common adverse event in older population: early readmission (up to 30 days after discharge), long hospital stays (10 days or more) or in-hospital deaths. Methods: This was a retrospective cohort study including patients aged 60 years or older (n=340) admitted at a 630-beds tertiary hospital, located in the city of São Paulo, Brazil. A predictive model of high-risk indication was developed by analyzing logistical regression models. This model prognostic capacity was assessed by measuring accuracy, sensitivity, specificity, and positive and negative predictive values. Areas under the receiver operating characteristic curve with 95% confidence intervals were also obtained to assess the discriminatory power of the model. Internal validation of the prognostic model was performed in a separate sample (n=168). Results: Statistically significant predictors were identified, such as current Barthel Index, number of medications in use, presence of diabetes mellitus, difficulty chewing or swallowing, extensive surgery, and dementia. The study observed discrimination model acceptance in the construction sample 0.77 (95% confidence interval: 0.71-0.83) and good calibration. The characteristics of the validation samples were similar, and the receiver operating characteristic curve area was 0.687 (95% confidence interval: 0.598-0.776). We could assess an older patient's adverse health events during hospitalization after admission. Conclusion: A predictive model with acceptable discrimination was obtained, with satisfactory results for early readmission (30 days), long hospital stays (10 days), or in-hospital death.
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