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BACKGROUND & AIMS: Weight loss in individuals with obesity and overweight leads to metabolic and health benefits but also poses the risk of muscle mass reduction. This systematic review and meta-analysis of randomized controlled trials aims to determine the initial protein amount necessary for achieving weight loss while maintaining muscle mass, strength, and physical function in adults with overweight and obesity. METHODS: Relevant literature databases, including Medical Literature Analysis and Retrieval System Online (Medline), Excerpta Medica (Embase), the Cumulative Index to Nursing and Allied Health Literature (CINHAL), and Web of Science, were electronically searched up to 15 March 2023. We examined the effect of additional protein intake on muscle mass, strength, and physical function in adults with overweight or obesity targeting weight loss. The risk of bias was assessed using the Cochrane RoB 2.0 tool. Results were synthesized using standardized mean differences (SMD) and 95% confidence intervals (CI) via a random-effects model. RESULTS: Forty-seven studies (n = 3218) were included. In the muscle mass analysis, twenty-eight trials with 1989 participants were encompassed. Results indicated that increased protein intake significantly prevents muscle mass decline in adults with overweight or obesity aiming for weight loss (SMD 0.75; 95% CI 0.41 to 1.10; p < 0.001). Enhanced protein intake did not significantly prevent decreases in muscle strength and physical function. An intake exceeding 1.3 g/kg/day is anticipated to increase muscle mass, while an intake below 1.0 g/kg/day is associated with a higher risk of muscle mass decline. The risk of bias in studies regarding muscle mass ranged from low to high. CONCLUSIONS: Adults with overweight or obesity and aim for weight loss can more effectively retain muscle mass through higher protein intake, as opposed to no protein intake enhancement.
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OBJECTIVE: The clinical impact of malnutrition based on the Global Leadership Initiative on Malnutrition (GLIM) criteria in patients with kidney dysfunction remains poorly understood. This study investigated the usefulness of GLIM criteria for malnutrition in predicting mortality in patients with kidney dysfunction and different clinical renal states, including no kidney disease (NKD), acute kidney injury (AKI), and chronic kidney disease (CKD). METHODS: This single-center retrospective cohort study included 6,712 patients aged ≥18 admitted between 2018 and 2019. The relationship between the estimated glomerular filtration rate (eGFR) groups, nutritional status based on the GLIM criteria, and the incidence of all-cause mortality was evaluated using a multivariate Cox proportional hazards model. Malnutrition was defined as at least one phenotype (weight loss, low body mass index, or reduced muscle mass) and one etiological criterion (reduced intake/assimilation or disease burden/inflammation). RESULTS: Multivariate Cox proportional hazards model showed that eGFR ≤29 (vs. eGFR: 60-89, adjusted hazard ratio [HR] = 1.84, 95% confidence interval [CI]: 1.52-2.22), 30-59 (vs. eGFR: 60-89, adjusted HR = 1.40, 95% CI: 1.20-1.64), and ≥90 (vs. eGFR: 60-89, adjusted HR = 1.40, 95% CI: 1.14-1.71), moderate and severe malnutrition (vs. without malnutrition, adjusted HR = 1.38 [1.18-1.62] and 2.18 [1.86-2.54], respectively) were independently associated with the incidence of death. The all-cause mortality rate was higher in patients with malnutrition or eGFR ≤29 (adjusted HR, 3.31; 95% CI: 2.51-4.35) than in patients without malnutrition or eGFR 60-89. Furthermore, moderate and severe malnutrition (vs. no malnutrition) was independently associated with death in patients with NKD, AKI, and CKD. CONCLUSION: Malnutrition based on the GLIM criteria was associated with increased all-cause mortality in inpatients, and malnutrition combined with kidney dysfunction was associated with a higher risk of mortality. Furthermore, patients with NKD, AKI, and CKD showed an association between malnutrition based on GLIM criteria and mortality.
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Aim: A testing method for early diagnosis of Mild cognitive dementia (MCI) that can be easily applied in clinical practice was investigated in this study. We examined whether MCI risk can be determined through finger movements. Methods: Between 2013 and 2020, 1097 individuals were screened. After applying propensity-score matching to adjust for variability between the groups, 173 individuals each in the mild cognitive impairment and control groups were selected. Thereafter, differences between groups in mean values of parameters extracted from finger tap movements were determined using unpaired t-test and effect size. Furthermore, area under the curve, sensitivity, and specificity were calculated from the receiver operating characteristic curve for parameters with significant difference. Results: A significant difference was observed, especially in the number of taps in the MCI group compared with that in the control group (p < .001; 95% CI, -12.7 to -8.8; r = 0.51). A cut-off value of 30 taps was applied (sensitivity, 0.77; specificity, 0.67; AUC, 0.79). Significant differences were also observed in rhythm-related parameters. Conclusions: These parameters might be useful for capturing MCI risk. Finger taps are easily measured and may be suitable for screening large populations. This tool might be used as a supplemental method to increase the sensitivity of traditional cognitive tests.
