RESUMO
Spirometry is a pulmonary function test where correct interpretation of the results is crucial for accurate diagnosis of disease. There are online tools to assist in the interpretation of spirometry results; however, as yet none are validated. We evaluated the interpretation accuracy of the Espiro app using pulmonologist interpretations as the gold standard. This is an observational descriptive study in which 118 spirometry results were interpreted by the Espiro app, two pulmonologists, two primary care physicians, and two residents of a primary care training program. We determined the interpretation accuracy of the Espiro app and the concordance of the pattern and severity interpretation between the Espiro app and each of the observers using Cohen's kappa coefficient (k). We obtained a sensitivity and specificity for the Espiro app of 97.5% (95% confidence interval (CI): 86.8-99.9%) and 94.9% (95%CI: 87.4-98.6%) with pulmonologist 1 and 100% (95%CI: 91.6-100%) and 98.7% (95%CI: 92.9-99.9%) with pulmonologist 2. The concordance for the pattern interpretation was greater than k 0.907, representing almost perfect agreement. The concordance of the severity interpretation was greater than k 0.807, representing substantial to almost perfect agreement. We concluded that the Espiro app is a valid tool for spirometry interpretation.
RESUMO
PURPOSE: To assess the association between the consumption of non-soy legumes and different subtypes of non-soy legumes and serum uric acid (SUA) or hyperuricemia in elderly individuals with overweight or obesity and metabolic syndrome. METHODS: A cross-sectional analysis was conducted in the framework of the PREDIMED-Plus study. We included 6329 participants with information on non-soy legume consumption and SUA levels. Non-soy legume consumption was estimated using a semi-quantitative food frequency questionnaire. Linear regression models and Cox regression models were used to assess the associations between tertiles of non-soy legume consumption, different subtypes of non-soy legume consumption and SUA levels or hyperuricemia prevalence, respectively. RESULTS: Individuals in the highest tertile (T3) of total non-soy legume, lentil and pea consumption, had 0.14 mg/dL, 0.19 mg/dL and 0.12 mg/dL lower SUA levels, respectively, compared to those in the lowest tertile (T1), which was considered the reference one. Chickpea and dry bean consumption showed no association. In multivariable models, participants located in the top tertile of total non-soy legumes [prevalence ratio (PR): 0.89; 95% CI 0.82-0.97; p trend = 0.01, lentils (PR: 0.89; 95% CI 0.82-0.97; p trend = 0.01), dry beans (PR: 0.91; 95% C: 0.84-0.99; p trend = 0.03) and peas (PR: 0.89; 95% CI 0.82-0.97; p trend = 0.01)] presented a lower prevalence of hyperuricemia (vs. the bottom tertile). Chickpea consumption was not associated with hyperuricemia prevalence. CONCLUSIONS: In this study of elderly subjects with metabolic syndrome, we observed that despite being a purine-rich food, non-soy legumes were inversely associated with SUA levels and hyperuricemia prevalence. TRIAL REGISTRATION: ISRCTN89898870. Registration date: 24 July 2014.
