Effect of Intermittent Fasting on Glycaemic Control in Patients With Type 2 Diabetes Mellitus: A Systematic Review and Meta-analysis of Randomized Controlled Trials

Is Fasting Superior to Continuous Caloric Restriction for Weight Loss and Metabolic Outcomes in Obese Adults? A Systematic Review and Meta-Analysis of Randomized Clinical Trials

BACKGROUND

fasting-based strategies (FBS) and continuous caloric restriction (CCR) are popular methods for weight loss and improving metabolic health. FBS alternates between eating and fasting periods, while CCR reduces daily calorie intake consistently. Both aim to create a calorie deficit, but it is still uncertain as to which is more effective for short- and long-term weight and metabolic outcomes.

OBJECTIVES

this systematic review and meta-analysis aimed to compare the effectiveness of FBS and CCR on these parameters in obese adults.

METHODS

after screening 342 articles, 10 randomized controlled trials (RCTs) with 623 participants were included.

RESULTS

both interventions led to weight loss, with a reduction of 5.5 to 6.5 kg observed at the six-month mark. However, the results showed that FBS led to slightly greater short-term reductions in body weight (-0.94 kg, p = 0.004) and fat mass (-1.08 kg, p = 0.0001) compared to CCR, although these differences are not clinically significant. Both interventions had similar effects on lean mass, waist and hip circumference, blood pressure, lipid profiles, and glucose metabolism. However, FBS improved insulin sensitivity, with significant reductions in fasting insulin (-7.46 pmol/L, p = 0.02) and HOMA-IR (-0.14, p = 0.02).

CONCLUSIONS

despite these short-term benefits, FBS did not show superior long-term outcomes compared to CCR. Both strategies are effective for weight management, but more research is needed to explore the long-term clinical relevance of FBS in obese populations.

Challenges in Providing an Overview of Results of Intermittent Fasting Interventions on Diabetes Parameters. Comment on Silva et al. Effects of Intermittent Fasting on Regulation of Metabolic Homeostasis: A Systematic Review and Meta-Analysis in Health and Metabolic-Related Disorders. J. Clin. Med. 2023, 12, 3699

We hereby comment on the systematic review "Effects of Intermittent Fasting on Regulation of Metabolic Homeostasis: A Systematic Review and Meta-Analysis in Health and Metabolic-Related Disorders" by Silva et al [...].

Intermittent Fasting in Youth: A Scoping Review

Intermittent fasting (IF) focuses on the timing of eating rather than diet quality or energy intake, with evidence supporting its effects on weight loss and cardiometabolic outcomes in adults. However, there is limited evidence for its efficacy in adolescents and emerging adults. To address this, a scoping review examined IF regimens in individuals aged 10 to 25, focusing on methodology, intervention parameters, outcomes, adherence, feasibility, and efficacy. The review included 39 studies with 731 participants aged 15 to 25. Methodologies varied, with 18 studies on time-restricted eating and others requiring caloric restriction. Primary outcomes included cardiometabolic risk factors (11/29), body composition (9/29), anthropometric measurements (8/29), and feasibility (2/29). Most studies reported significant weight loss. This review underscores IF's potential in treating obesity in this age group but highlights the need for rigorous studies with standardized frameworks for feasibility to ensure comparability and determine IF's practicality in this age group.

Effectiveness of Stem Cell Therapy for Diabetic Foot Ulcers: A Systematic Review and GRADE Compliant Bootstrapped Meta-Analysis of Randomized Clinical Trials

Diabetic foot (DF) represents a severe complication of diabetes mellitus, imposing substantial psychological and economic burdens on affected individuals. This investigation sought to assess the therapeutic efficacy of stem cell interventions in the management of DF complications. A comprehensive systematic search across PubMed, Embase, CINAHL, Scopus, and the Cochrane library databases was conducted to identify pertinent studies for meta-analysis. Outcome measures encompassed ulcer or wound healing rates, amputation rates, angiogenesis, ankle-brachial index (ABI), and pain-free walking distance. Dichotomous outcomes were expressed as risk differences (RDs) with 95% confidence intervals (CIs), while continuous data were articulated as standardized mean differences (SMDs) with corresponding 95% CIs. Statistical analyses were executed using RevMan 5.3 and Open Meta, with bootstrapped meta-analysis conducted through OpenMEE software. A total of 20 studies, comprising 24 arms and involving 1304 participants, were incorporated into the meta-analysis. The findings revealed that stem cell therapy exhibited superior efficacy compared to conventional interventions in terms of ulcer or wound healing rate [RD = 0.36 (0.28, 0.43)], pain-free walking distance [SMD = 1.27 (0.89, 1.65)], ABI [SMD = 0.61 (0.33, 0.88)], and new vessel development [RD = 0.48 (0.23, 0.78)], while concurrently reducing the amputation rate significantly [RD = -0.19 (-0.25, -0.12)]. Furthermore, no statistically significant difference in adverse events was observed [RD -0.07 (-0.16, 0.02)]. The Grading of Recommendations, Assessment, Development, and Evaluation assessment indicated varying levels of evidence certainty, ranging from very low to moderate, for different outcomes. Bootstrapping analysis substantiated the precision of the results. The meta-analysis underscores the significant superiority of stem cell therapy over conventional approaches in treating DF complications. Future investigations should prioritize large-scale, randomized, double-blind, placebo-controlled, multicenter trials, incorporating rigorous long-term follow-up protocols. These studies are essential for elucidating the optimal cell types and therapeutic parameters that contribute to the most effective treatment strategies for DF management.

Precision Medicine in Type 2 Diabetes Mellitus: Utility and Limitations

Type 2 diabetes mellitus (T2DM) is one of the most widespread diseases in Western countries, and its incidence is constantly increasing. Epidemiological studies have shown that in the next 20 years. The number of subjects affected by T2DM will double. In recent years, owing to the development and improvement in methods for studying the genome, several authors have evaluated the association between monogenic or polygenic genetic alterations and the development of metabolic diseases and complications. In addition, sedentary lifestyle and socio-economic and pandemic factors have a great impact on the habits of the population and have significantly contributed to the increase in the incidence of metabolic disorders, obesity, T2DM, metabolic syndrome, and liver steatosis. Moreover, patients with type 2 diabetes appear to respond to antihyperglycemic drugs. Only a minority of patients could be considered true non-responders. Thus, it appears clear that the main aim of precision medicine in T2DM is to identify patients who can benefit most from a specific drug class more than from the others. Precision medicine is a discipline that evaluates the applicability of genetic, lifestyle, and environmental factors to disease development. In particular, it evaluated whether these factors could affect the development of diseases and their complications, response to diet, lifestyle, and use of drugs. Thus, the objective is to find prevention models aimed at reducing the incidence of pathology and mortality and therapeutic personalized approaches, to obtain a greater probability of response and efficacy. This review aims to evaluate the applicability of precision medicine for T2DM, a healthcare burden in many countries.

Understanding Type 2 Diabetes Mellitus Risk Parameters through Intermittent Fasting: A Machine Learning Approach

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterized by elevated blood glucose levels. Despite the availability of pharmacological treatments, dietary plans, and exercise regimens, T2DM remains a significant global cause of mortality. As a result, there is an increasing interest in exploring lifestyle interventions, such as intermittent fasting (IF). This study aims to identify underlying patterns and principles for effectively improving T2DM risk parameters through IF. By analyzing data from multiple randomized clinical trials investigating various IF interventions in humans, a machine learning algorithm was employed to develop a personalized recommendation system. This system offers guidance tailored to pre-diabetic and diabetic individuals, suggesting the most suitable IF interventions to improve T2DM risk parameters. With a success rate of 95%, this recommendation system provides highly individualized advice, optimizing the benefits of IF for diverse population subgroups. The outcomes of this study lead us to conclude that weight is a crucial feature for females, while age plays a determining role for males in reducing glucose levels in blood. By revealing patterns in diabetes risk parameters among individuals, this study not only offers practical guidance but also sheds light on the underlying mechanisms of T2DM, contributing to a deeper understanding of this complex metabolic disorder.