Clinical evidence for high-risk CE-marked medical devices for glucose management: A systematic review and meta-analysis.

AIMS To conduct a systematic review and meta-analysis, within the Coordinating Research and Evidence for Medical Devices (CORE-MD) project, evaluating CE-marked high-risk devices for glucose management. MATERIALS AND METHODS We identified interventional and observational studies evaluating the efficacy and safety of eight automated insulin delivery (AID) systems, two implantable insulin pumps, and three implantable continuous glucose monitoring (CGM) devices. We meta-analysed randomized controlled trials (RCTs) comparing AID systems with other treatments. RESULTS A total of 182 studies published between 2009 and 2024 were included, comprising 166 studies on AID systems, six on insulin pumps, and 10 on CGM devices; 26% reported industry funding; 18% were pre-market; 37% had a comparator group. Of the studies identified, 29% were RCTs, 24% were non-randomized trials, and 47% were observational studies. The median (interquartile range) sample size was 48 (28-102), age 34.8 (14-44.2) years, and study duration 17.5 (12-26) weeks. AID systems lowered glycated haemoglobin by 0.5 percentage points (absolute mean difference [MD] = -0.5; 21 RCTs; I2 = 86%) and increased time in target range for sensor glucose level by 13.4 percentage points (MD = 13.4; 14 RCTs; I2 = 90%). At least one safety outcome was assessed in 71% of studies. CONCLUSIONS High-risk devices for glucose monitoring or insulin dosing, in particular AID systems, improve glucose control safely, but evidence on diabetes-related end-organ damage is lacking due to short study durations. Methodological heterogeneity highlights the need for developing standards for future pre- and post-market investigations of diabetes-specific high-risk medical devices

Agreement between Mega-Trials and Smaller Trials: A Systematic Review and Meta-Research Analysis

Importance: Mega-trials can provide large-scale evidence on important questions. Objective: To explore how the results of mega-trials compare with the meta-analysis results of trials with smaller sample sizes. Data Sources: ClinicalTrials.gov was searched for mega-trials until January 2023. PubMed was searched until June 2023 for meta-analyses incorporating the results of the eligible mega-trials. Study Selection: Mega-trials were eligible if they were noncluster nonvaccine randomized clinical trials, had a sample size over 10000, and had a peer-reviewed meta-analysis publication presenting results for the primary outcome of the mega-trials and/or all-cause mortality. Data Extraction and Synthesis: For each selected meta-analysis, we extracted results of smaller trials and mega-trials included in the summary effect estimate and combined them separately using random effects. These estimates were used to calculate the ratio of odds ratios (ROR) between mega-trials and smaller trials in each meta-analysis. Next, the RORs were combined using random effects. Risk of bias was extracted for each trial included in our analyses (or when not available, assessed only for mega-trials). Data analysis was conducted from January to June 2024. Main Outcomes and Measures: The main outcomes were the summary ROR for the primary outcome and all-cause mortality between mega-trials and smaller trials. Sensitivity analyses were performed with respect to the year of publication, masking, weight, type of intervention, and specialty. Results: Of 120 mega-trials identified, 41 showed a significant result for the primary outcome and 22 showed a significant result for all-cause mortality. In 35 comparisons of primary outcomes (including 85 point estimates from 69 unique mega-trials and 272 point estimates from smaller trials) and 26 comparisons of all-cause mortality (including 70 point estimates from 65 unique mega-trials and 267 point estimates from smaller trials), no difference existed between the outcomes of the mega-trials and smaller trials for primary outcome (ROR, 1.00; 95% CI, 0.97-1.04) nor for all-cause mortality (ROR, 1.00; 95% CI, 0.97-1.04). For the primary outcomes, smaller trials published before the mega-trials had more favorable results than the mega-trials (ROR, 1.05; 95% CI, 1.01-1.10) and subsequent smaller trials published after the mega-trials (ROR, 1.10; 95% CI, 1.04-1.18). Conclusions and Relevance: In this meta-research analysis, meta-analyses of smaller studies showed overall comparable results with mega-trials, but smaller trials published before the mega-trials gave more favorable results than mega-trials. These findings suggest that mega-trials need to be performed more often given the relative low number of mega-trials found, their low significant rates, and the fact that smaller trials published prior to mega-trial report more beneficial results than mega-trials and subsequent smaller trials

"Chrononutrition as a therapeutical strategy and its impact on metabolic diseases"

reservedL’aumento globale delle malattie metaboliche, come l’obesità e il diabete mellito di tipo 2 (T2DM), rappresenta un grave problema di salute pubblica. Una nuova ricerca evidenzia l’importanza della crononutrizione, un potenziale paradigma terapeutico, nell’affrontare queste condizioni complesse. La crononutrizione si concentra sulle caratteristiche temporali dell'assunzione di cibo, allineando i modelli dietetici ai ritmi circadiani del corpo. I ritmi circadiani gestiscono delicatamente diversi processi metabolici durante la giornata, regolando il metabolismo del glucosio, la fluttuazione ormonale e la regolazione dei lipidi. Le interruzioni del ritmo circadiano sono state associate a malattie metaboliche, tra cui il diabete, l'obesità, la malattia del fegato grasso non alcolica (NAFLD) e la steatoepatite non alcolica (NASH). L'obesità, uno dei tratti distintivi della società moderna, è stata identificata come una "malattia cronobiologica". Comportamenti alimentari irregolari, soprattutto mangiare a tarda notte, interrompono il ritmo circadiano, causando aumento di peso e disregolazione metabolica. La TRF, una forma di crononutrizione, è emersa come una potenziale tecnica per riallineare i comportamenti dello stile di vita con i ritmi circadiani. Inoltre, la ricerca ha dimostrato che l’orario dei pasti influisce sul controllo glicemico nelle persone con T2DM. Spostare la maggior parte dell’apporto calorico giornaliero alle prime ore del mattino ha mostrato miglioramenti nella risposta glicemica postprandiale, nella reattività delle cellule beta e nella sensibilità all’insulina. Le strategie di crononutrizione, come l’adozione di una finestra alimentare dalla mattina al primo pomeriggio, hanno portato a un migliore controllo del glucosio e alla gestione del peso nei pazienti diabetici. L’impatto sull’idoneità metabolica e sul rischio di diabete è importante nel contesto del lavoro a turni e del jet lag, entrambi collegati all’interruzione circadiana. I lavoratori a turni hanno livelli di glucosio e insulina disregolati, il che contribuisce ad aumentare il rischio di T2DM. Il jet lag, d’altro canto, altera l’orologio circadiano interno, provocando temporanei disturbi metabolici. Questa revisione completa fornisce informazioni sulla complessa relazione tra crononutrizione e disordini metabolici. Sottolinea il potenziale della crononutrizione come approccio terapeutico per ridurre il peso globale dell’obesità e del T2DM. Questo studio fa luce su nuovi modi per la prevenzione e la gestione delle malattie rivelando la complicata interazione tra tempi dei pasti, ritmi circadiani e salute metabolica.The global rise in metabolic diseases, such as obesity and type 2 diabetes mellitus (T2DM), presents a major public health concern. New research highlights the importance of Chrononutrition, a potential therapeutic paradigm, in addressing these complex conditions. Chrononutrition focuses on the temporal characteristics of food intake, aligning dietary patterns with the body's circadian rhythms. Circadian rhythms delicately manage different metabolic processes throughout the day, regulating glucose metabolism, hormone fluctuation, and lipid regulation.Circadian rhythm disruptions have been associated with metabolic diseases, including diabetes, obesity, Non-alcoholic fatty liver disease (NAFLD) and Non-alcoholic steatohepatitis (NASH). Obesity, one of the hallmarks of modern society, has been identified as a "chronobiological disease." Irregular eating behaviors, especially late-night eating, disrupt the circadian rhythm, causing weight gain and metabolic dysregulation. TRF, a form of Chrononutrition, has emerged as a potential technique for realigning lifestyle behaviors with circadian rhythms. Moreover, research has shown that meal timing affects glycemic control in people with T2DM. Shifting the majority of daily caloric intake to earlier hours has shown improvements in postprandial glucose response, beta-cell responsiveness, and insulin sensitivity. Chrononutrition strategies, such as adopting an eating window from the morning to the early afternoon, have resulted in improved glucose control and weight management in diabetes patients. The impact on metabolic fitness and diabetes risk is important in the context of shift work and jet lag, both of which are linked with circadian disruption. Shift workers have dysregulated glucose and insulin levels, which contributes to an increased risk of T2DM. Jet lag, on the other hand, disrupts the internal circadian clock, resulting in temporary metabolic disturbances. This comprehensive review provides insight into the complex relationship between Chrononutrition and metabolic disorders. It emphasizes Chrononutrition's potential as a therapeutic approach for reducing the global burden of obesity and T2DM. This study sheds light on novel ways for disease prevention and management by revealing the complicated interplay between meal timing, circadian rhythms, and metabolic health