This study of hospital inpatients demonstrated a high burden of malnutrition at the time of hospital admission, which negatively impacted LOS and mortality and increased the costs of hospitalization. These findings underscore the need for improved diagnosis and treatment of hospital malnutrition to improve patient outcomes and reduce healthcare costs.
Physical exercise (PE) is a strong stimulant of glucose absorption by the skeletal muscles, a phenomenon that results from an increase in the rates of glucose release, transmembranal transport of glucose, and substrate flow at the intracellular level through glycolysis. 1 Although PE is an important tool for maintaining or improving cardiovascular fitness, most studies on the impact of PE on DM1 have not shown objective improvements on glycemic control. 2 It has been described that type 1 diabetic athletes show alterations in their metabolic control compared to sedentary type 1 diabetics.2 The fear of a hypoglycemic event underlies this finding because overcompensation generally occurs in terms of additional carbohydrate intake prior to exercise and excessive reductions to insulin dosages. 2 In fact, in a pediatric population, hypoglycemia during or after exercise is the most frequent specific cause of severe hypoglycemia, with most of the severe events occurring at night. 3It has been established that hypoglycemia associated with exercise is determined by an increase in glucose absorption, the inability of PE per se to decrease insulin levels, and the presence of autonomous diabetic neuropathy. 4 A history of hypoglycemia can deteriorate even further the adrenergic activity in response to hypoglycemia caused by exercise. Abstract Background: Although physical exercise (PE) is recommended for individuals with type 1 diabetes (DM1), participation in exercise is challenging because it increases the risk of severe hypoglycemia and the available therapeutic options to prevent it frequently result in hyperglycemia. There is no clear recommendation about the best timing for exercise. The aim of this study was to compare the risk of hypoglycemia after morning or afternoon exercise sessions up to 36 hours postworkout. Methods: This randomized crossover study enrolled subjects with DM1, older than 18 years of age, on sensor-augmented insulin pump (SAP) therapy. Participants underwent 2 moderate-intensity exercise sessions; 1 in the morning and 1 in the afternoon, separated by a 7 to 14 day wash-out period. Continuous glucose monitoring (CGM) data were collected 24 hours before, during and 36 hours after each session. Results: Thirty-five subjects (mean age 30.31 ± 12.66 years) participated in the study. The rate of hypoglycemia was significantly lower following morning versus afternoon exercise sessions (5.6 vs 10.7 events per patient, incidence rate ratio, 0.52; 95% CI, 0.43-0.63; P < .0001). Most hypoglycemic events occurred 15-24 hours after the session. On days following morning exercise sessions, there were 20% more CGM readings in near-euglycemic range (70-200 mg/dL) than on days prior to morning exercise (P = .003). Conclusions: Morning exercise confers a lower risk of late-onset hypoglycemia than afternoon exercise and improves metabolic control on the subsequent day.
Social factors, such as social cognition skills (SCS) and social determinants of health (SDH), may be vital for mental health, even when compared with classical psycho-physical predictors (demographic, physical, psychiatric, and cognitive factors). Although major risk factors for psychiatric disorders have been previously assessed, the relative weight of SCS and SDH in relation to classical psycho-physical predictors in predicting symptoms of mental disorders remains largely unknown. In this study, we implemented multiple structural equation models (SEM) from a randomized sample assessed in the Colombian National Mental Health Survey of 2015 (CNMHS, n = 2947, females: 1348) to evaluate the role of SCS, SDH, and psycho-physical factors (totaling 17 variables) as predictors of mental illness symptoms (anxiety, depression, and other psychiatric symptoms). Specifically, we assessed the structural equation modeling of (a) SCS (emotion recognition and empathy skills); (b) SDH (including the experience of social adversities and social protective factors); (c) and classical psycho-physical factors, including psychiatric antecedents, physical-somatic factors (chronic diseases), and cognitive factors (executive functioning). Results revealed that the emotion recognition skills, social adverse factors, antecedents of psychiatric disorders and chronic diseases, and cognitive functioning were the best predictors of symptoms of mental illness. Moreover, SCS, particularly emotion recognition skills, and SDH (experiences of social adversities, familial, and social support networks) reached higher predictive values of symptoms than classical psycho-physical factors. Our study provides unprecedented evidence on the impact of social factors in predicting symptoms of mental illness and highlights the relevance of these factors to track early states of disease.
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