Wheelchair basketball improves the treatment of urinary tract infection in people with motor disabilities: a clinical trial

SUMMARY OBJECTIVE: Few studies on physical medicine and rehabilitation analyze the benefit of wheelchair basketball in people with motor disabilities. Given these, this study aimed to investigate the effect of the intervention of wheelchair basketball on urinary tract infection in people with motor disabilities. METHODS: A 12-month experimental follow-up was conducted in a single-center study. A total of 48 male individuals aged 18-55 years were allocated to the control group and experimental group. The experimental group practiced wheelchair basketball for 2 h, twice a week. Intra- and intergroup comparisons were made pre- and post-interventions over urinary tract infection. RESULTS: There was a significant improvement in urinary tract infection and urine culture in pre- and post-intervention antibiograms, respectively. Moreover, the intergroup comparison presented a decrease in infection caused by Klebsiella pneumoniae, as well as an increase in the time variability of partially activated thromboplastin, average corpuscular hemoglobin, and hemoglobin and platelets. In the experimental group, there was an increase in hemoglobin and hematocrit and a decrease in glycated hemoglobin (%HbA1C). On the intragroup comparison, there was a reduction of triiodothyronine (T3), %HbA1C, interleukin-6 pre-intervention, and C-reactive protein post-intervention. CONCLUSIONS: There was a decrease in urinary tract infection and improvement in biochemical, immunological, and microbiological biomarkers evaluated with physical exercise practice by wheelchair basketball, as well as by multiprofessional follow-up and health guidance.

Gasto energético de repouso medido vs. estimado e relação com a composição corporal de mulheres / Resting energy expenditure measured vs. estimated and this relationship with body composition in women / Resting energy expenditure measured vs. estimated and this relationship with body composition in women

OBJETIVOS: Medir o gasto energético de repouso (GER, kcal/d), comparar as equações de predição disponíveis na literatura e associar a composição corporal. MÉTODOS: Vinte e oito sedentárias foram voluntárias [peso: 79 ± 12 kg; estatura: 164 ± 5 cm; idade: 36 ± 11 anos; índice de massa corporal (IMC): 29 ± 4 kg/m²]. A composição corporal foi estimada por antropometria, o GER foi medido por calorimetria indireta e estimado pelas principais equações da literatura. Foram desenvolvidas equações para estimativa do GER sendo a melhor a GER-Nosso. RESULTADOS: Diferentes tempos de coleta produziram resultados similares para o GER medido. O GER estimado pelas fórmulas de Harris & Benedict, FAO/WHO/UNO somente peso e peso mais altura, Schofield e GER-Nosso foram estatisticamente iguais ao GER medido. As equações do Siervo & Falconi, Schofield e Henry & Rees não foram correlacionadas ao GER medido. O melhor preditor isolado do GER foi a massa corporal e a melhor associação quando ajustado por unidade (kg) foi a massa magra. A equação desenvolvida no presente trabalho foi: GER(kcal/d)= 21837 - 14,448 * Peso(kg) + 54,963 * Massa Magra(kg) - 9,341 * Estatura(cm) - 4,349 * Idade(anos) - 19753 * Densidade Corporal(g/ml). CONCLUSÃO: As equações de predição do GER podem induzir a erros de predição e parecem ser população-específicas. O melhor resultado de predição foi para fórmula desenvolvida com os dados antropométricos das voluntárias (medido= 1617 ± 237 kcal/d; GER-Nosso= 1616 ± 167 kcal/d).

OBJECTIVES: To compare the resting energy expenditure (REE, kcal/d) measured to the disposable equation of literature and to associate this to body composition. METHODS: Twenty-eight sedentary women were volunteers [weight: 79 ± 12 kg; stature: 164 ± 5 cm; age: 36 ± 11 years; body mass index (BMI, kg/m²): 29 ± 4]. The body composition was estimated with anthropometry methods; REE was measured by indirect calorimetry and was estimated by the main equations of the literature. Equations were developed to estimate REE and the best of them was REE-Our. RESULTS: The different time of harvest produced a similar result to REE measured. The Harris & Benedict, FAO/WHO/UNO only weight, and weight plus height, Schofield and REE-Our equations results were statistically similar to REE measured. The Siervo & Falconi, Schofield and Henry & Rees equations did not have correlation with the measured calorimetry. The best-isolated predictor of the REE was the body mass and the best association when adjusted to unit (kg) was lean body mass. The equation developed in the present work was: REE(kcal/d)= 21837 - 14,448 * Weight(kg) + 54,963 * Lean Mass(kg) - 9,341 * Stature(cm) - 4,349 * Age(years) - 19753 * Body Density(g/ml). CONCLUSION: The REE prediction equations can prompt to errors and seem to be population specific. The best prediction result was with the equation developed with anthropometrics variables of the volunteers (measured= 1617 ± 237 kcal/d; REE-Our= 1616 ± 167 kcal/d).