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Aim: To conduct a systematic review with meta‐analysis to provide a comprehensive synthesis of randomized controlled trials (RCTs) and prospective cohort studies investigating the effects of currently available bolus advisors on glycaemic parameters in adults with diabetes. Materials and Methods: An electronic search of PubMed, Embase, CINAHL, Cochrane Library and ClinicalTrials.gov was conducted in December 2022. The risk of bias was assessed using the revised Cochrane Risk of Bias tool. (Standardized) mean difference (MD) was selected to determine the difference in continuous outcomes between the groups. A random‐effects model meta‐analysis and meta‐regression were performed. This systematic review was registered on PROSPERO (CRD42022374588). Results: A total of 18 RCTs involving 1645 adults (50% females) with a median glycated haemoglobin (HbA1c) concentration of 8.45% (7.95%–9.30%) were included. The majority of participants had type 1 diabetes (N = 1510, 92%) and were on multiple daily injections (N = 1173, 71%). Twelve of the 18 trials had low risk of bias. The meta‐analysis of 10 studies with available data on HbA1c showed that the use of a bolus advisor modestly reduced HbA1c compared to standard treatment (MD −011%, 95% confidence interval −0.22 to −0.01; I2 = 0%). This effect was accompanied by small improvements in low blood glucose index and treatment satisfaction, but not with reductions in hypoglycaemic events or changes in other secondary outcomes. Conclusion: Use of a bolus advisor is associated with slightly better glucose control and treatment satisfaction in people with diabetes on intensive insulin treatment. Future studies should investigate whether personalizing bolus advisors using artificial intelligence technology can enhance these effects. [ABSTRACT FROM AUTHOR]

Background: Proactive screening for cognitive dysfunction (CD) and peripheral neuropathy (PNP) in elderly patients with diabetes mellitus is essential for early intervention, yet clinical examination is time-consuming and prone to bias. Objective: We aimed to investigate PNP and CD in a diabetes cohort and explore the possibility of identifying key features linked with the respective conditions by machine learning algorithms applied to data sets obtained in playful games controlled by sensor-equipped insoles. Methods: In a cohort of patients diagnosed with diabetes (n=261) aged over 50 years PNP and CD were diagnosed based on complete physical examination (neuropathy symptom and disability scores, and Montreal Cognitive Assessment). In an observational and proof-of-concept study patients performed a 15 min lasting gaming session encompassing tutorials and four video games with 5,244 predefined features. The steering of video games was solely achieved by modulating plantar pressure values, which were measured by sensor-equipped insoles in real-time. Data sets were used to identify key features indicating game performance with correlation regarding CD and PNP findings. Thereby, machine learning models (e.g. gradient boosting and lasso and elastic-net regularized generalized linear models) were set up to distinguish patients in the different groups. Results: PNP was diagnosed in 59% (n=153), CD in 34% (n=89) of participants, and 23% (n=61) suffered from both conditions. Multivariable regression analyses suggested that PNP was positively associated with CD in patients with diabetes (adjusted odds ratio = 1.95; 95% confidence interval: 1.03-3.76; P=0.04). Predictive game features were identified that significantly correlated with CD (n=59), PNP (n=40), or both (n=59). These features allowed to set up classification models that were enriched by individual risk profiles (i.e. gender, age, weight, BMI, diabetes type, and diabetes duration). The obtained models yielded good predictive performance with the area under the receiveroperating-characteristic curves reaching 0.95 for CD without PNP, 0.83 for PNP without CD, and 0.84 for CD and PNP combined. Conclusions: The video game-based assessment was able to categorize patients with CD and/or PNP with high accuracy. Future studies with larger cohorts are needed to validate these results and potentially enhance the discriminative power of video games. [ABSTRACT FROM AUTHOR]

Aims: Inflammation and angiogenesis play an important role in the development of early diabetic kidney disease. We investigated the association of soluble Tumour Necrosis Factor Receptor 1 (sTNF‐R1), sTNF‐R2 and endostatin with new onset microalbuminuria in normoalbuminuric patients with diabetes mellitus type 2. Methods: We conducted a case control study to assess serum levels of sTNF‐R1, sTNF‐R2 and endostatin in 169 patients with new onset microalbuminuria and in 188 matched normoalbuminuric, diabetic controls. Baseline serum samples from participants of the ROADMAP (Randomized Olmesartan and Diabetes Microalbuminuria Prevention) and observational follow‐up (ROADMAP‐OFU) studies were used. Results: Endostatin and sTNF‐R1 but not sTNF‐R2 were increased at baseline in patients with future microalbuminuria. In the multivariate analysis, each log2 increment in endostatin levels was associated with an increase of only 6% in the risk of development of microalbuminuria (adjusted HR (95% CI) 1.006 (1.001–1011). sTNF‐R1 and sTNF‐R2 levels were conversely associated with microalbuminuria, but the results did not reach statistical significance. The respective adjusted HRs (95% CI) were 1.305 (0.928–1.774) and 0.874 (0.711–1.074). Conclusions: sTNF‐R1 and sTNF‐R2 failed to predict the occurrence of microalbuminuria in normoalbuminuric patients with type 2 diabetes. Likewise, the utility of endostatin in predicting new onset proteinuria is limited. [ABSTRACT FROM AUTHOR]

Summary: The prevalence of kidney disease is increasing rapidly worldwide, reflecting rising rates of obesity, diabetes, and associated metabolic syndrome (MetS). Chronic kidney disease and related comorbidities such as obesity, diabetes, and hypertension place a significant financial burden on healthcare systems. Despite the widespread use of RAAS inhibitors, intensive blood pressure and glycemic control, and newer therapeutic options consisting of sodium/glucose cotransporter‐2 (SGLT‐2) inhibitors or glucagon‐like peptide‐1 (GLP‐1) receptor agonists, a significant risk of progression to end‐stage renal disease remains in the high‐risk obese and diabetic population. The MetS is a cluster of cardiovascular risk factors that adversely affect the development and progression of chronic kidney failure. According to the criteria of the World Health Organization, it is defined by visceral adiposity, impaired glucose tolerance or insulin resistance, atherogenic dyslipidemia, raised blood pressure, and microalbuminuria with a albumin‐to‐creatinine ratio ≥30 mg/g. At molecular level MetS is marked by a proinflammatory state and increased oxidative stress leading to various pathophysiological changes causing endothelial dysfunction and a hypercoagulable state. Because the kidney is a highly vascularized organ, it is especially susceptible for those microvascular changes. Therefore, the MetS and its individual components are associated with the premature development, acceleration, and progression of chronic kidney disease. Therefore, it is becoming increasingly important to elucidate the underlying mechanisms of MetS‐associated chronic kidney disease in order to develop new strategies for preventing and slowing the progression of renal disease. In this review, we will elucidate (i) the renal structural, hemodynamic, and metabolic changes that occur in obesity and obesity‐related kidney injury; (ii) the clinicopathological characteristics of obesity‐related kidney injury, primarily focusing on obesity‐associated glomerulopathy; (iii) the potential additional factors or predisposing factors that may turn patients more susceptible to renal structural or functional compensatory failure and subsequent injury. [ABSTRACT FROM AUTHOR]