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Predicting glucose levels in individuals with diabetes offers potential improvements in glucose control. However, not all patients exhibit predictable glucose dynamics, which may lead to ineffective treatment strategies. We sought to investigate the efficacy of a 7-day blinded screening test in identifying diabetes patients suitable for glucose forecasting. Participants with type 1 diabetes (T1D) were stratified into high and low initial error groups based on screening results (eligible and non-eligible). Long-term glucose predictions (30/60 min lead time) were evaluated among 334 individuals who underwent continuous glucose monitoring (CGM) over a total of 64,460,560 min. A strong correlation was observed between screening accuracy and long-term mean absolute relative difference (MARD) (0.661–0.736; p < 0.001), suggesting significant predictability between screening and long-term errors. Group analysis revealed a notable reduction in predictions falling within zone D of the Clark Error Grid by a factor of three and in zone C by a factor of two. The identification of eligible patients for glucose prediction through screening represents a practical and effective strategy. Implementation of this approach could lead to a decrease in adverse glucose predictions. • Some patients may have glucose dynamics not suitable for glucose forecasting. • Screening is a novel approach to identify eligible and non-eligible patients. • The correlation between screening and long-term performance was high. • Results show the approach could lead to fewer adverse glucose forecasting. [ABSTRACT FROM AUTHOR]

Aim: To investigate the cognitive function in people without diabetes, with prediabetes and with diabetes.Methods/design: The study design used was a cross-sectional analysis of data in people above 60 years registered in NHANES from 2011 to 2014.Three assessments were used to characterize cognitive function: (a) CERAD Word Learning subtest assessing immediate and delayed learning ability, (b) The Animal Fluency test assesing categorical verbal fluency, and (c) The Digit Symbol Substitution test assessing processing speed, sustained attention, and working memory.Results: (A) Memory recall (-0.19, [-0.34; -0.039], p = 0.014) and Delayed memory recall decline was associated with diabetes (-0.285, [-0.503; -0.067], p = 0.01), but not in an adjusted analysis. (B) Animal Fluency score decline was associated with diabetes (-1.185, [-1.688; -0.682], p < 0.001). (C) Digit Symbol score decline was associated with diabetes (-6.897, [-8.491; -5.302], p < 0.001). Prediabetes was not associated with cognitive function.Conclusions: This study demonstrates an association between cognitive dysfunction and diabetes. Results may also indicate that cognitive decline is not yet present in people with mild impairments of glucose homeostasis. [ABSTRACT FROM AUTHOR]

Aim: This study investigates the prevalence of smell and taste impairment in adults with diabetes and potential risk factors for sense deterioration and its influence of daily food intake.Methods: Data from the NHANES 2013-2014 were analyzed. Smell impairment was defined as failing to identify ≥3 of 8 odors in NHANES Pocket Smell Test. Taste impairment was defined as being unable to identify quinine or NaCl in NHANES Tongue Tip and Whole-mouth Test.Results: A total of 3204 people (428 patients with diabetes, 2776 controls) were suitable to be included. The prevalence of smell impairment in patients with diabetes was higher compared to the controls: 22% versus 15% (p<0.001). The difference prevailed after adjustment for age, BMI, alcohol misuse and smoking status. Taste was not impaired in patients with diabetes (p=0.29). Patients with diabetes and smell impairment had a lower daily calorie intake compared to patients with diabetes and normal smell function. The duration of diabetes, diabetic complications and other potential risk factors were not associated with smell dysfunction.Conclusions: Smell dysfunction appears with a higher prevalence in patients with diabetes, and this seems to negatively affect daily food intake. [ABSTRACT FROM AUTHOR]

Aim: This study investigates the role of muscle strength as a predictive factor for reduced pulmonary function in diabetes.Methods: Data from the NHANES 2011-2012 were analyzed. Lung function was assessed with spirometry (FEV1, FVC). Diabetes was assessed with an oral glucose tolerance test (OGTT), glycated hemoglobin (HbA1c), or fasting plasma glucose (FPG). Muscle strength was measured by a grip test using a handgrip dynamometer.Results: A total of 3521 people were suitable to be included for analysis in this study. Lung function was reduced in diabetes-after adjustment for covariates, the impact of diabetes on FVC was estimated as -331mL (SE 48) for known diabetes and -282mL (SE 41) for undiagnosed diabetes (P<0.001). Grip strength was also reduced in diabetes. After adjustment for covariates, the impact of diabetes was estimated as -5.9kg (SE 0.8) for known diabetes (P<0.001). An association between lung capacity and grip strength in people with known diabetes was observed (R=0.7, P<0.001). The adjusted impact on FVC from grip strength was estimated as 13.1mL (SE 3.4) per kg (P<0.001).Conclusions: Muscle strength appears to be reduced in people with known diabetes, and this seems to affect the respiratory muscles as an independent factor. [ABSTRACT FROM AUTHOR]

New methods to estimate body-composition have recently been proposed, but their relation to diseases, such as diabetes and coronary heart disease, needs further investigation. The purpose of this study was to investigate the association between proposed prediction of body-composition (PBC); Relative Fat Mass (RFM), Body Mass Index (BMI), Waist Circumference (WC) and disease. In a cross-sectional cohort (NHANES) the association between the four body measures and diabetes, high blood pressure, coronary heart disease, cancer, arthritis, and hospitalization were assessed. A total of 13,348 people was included in this study. Receiver operating characteristic (ROC), Area Under Curve (AUC) and statistical testing were used to evaluate the differences. PBC/RFM had significant higher AUC than BMI or WC for diabetes, high blood pressure, hospitalization, and arthritis. PBC had a significant higher AUC than RFM, BMI, WC for Cancer and coronary heart disease. RFM and PBC could be a better indicator to distinguish amongst people with a risk of diseases compared to traditional measures such as BMI and WC. However, future studies need to investigate the longitudinal association between RFM, PBC and the risk of disease development to assess if these measures are better suited for risk-stratification. • Relative Fat Mass (RFM) & Prediction of Body-Composition (PBC) serve as an alternate for estimation of body-composition. • RFM and PBC were associated with various diseases and hospitalization. • RFM and PBC help to predict risk of diseases among individuals. [ABSTRACT FROM AUTHOR]