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Background Preeclampsia (PE) and type 1 diabetes (T1D) are significant risk factors for cardiovascular disease (CVD), but their combined effect on atherosclerosis progression has not been fully explored. This study aimed to evaluate the impact of T1D and PE on the progression of atherosclerosis. Methods Prospective cohort study of 112 women divided into four groups: T1D + /PE + (n = 28), T1D + /PE− (n = 28), T1D−/PE + (n = 28), and T1D−/PE− (n = 28). Participants underwent an initial assessment and a follow-up visit five years later, which included anthropometric evaluation, blood tests, and carotid ultrasound. Atherosclerosis progression was defined as an increase in carotid plaque number or the occurrence of a cardiovascular event (CVE) during follow-up (fatal or non-fatal ischemic heart disease, fatal or non-fatal stroke, and/or heart failure). Results A total of 104 women (92.9%) completed the follow-up (54 with T1D, mean age at inclusion 45.2 ± 7.6 years, mean follow-up 5.3 ± 1.2 years). An increase in carotid plaques was identified in 34 women (32.7%), and 3 CVEs (2.9%) occurred. In women with T1D, a history of PE was associated with a twofold increase in atherosclerosis progression (57.7% vs 25.0%, p = 0.015). In multivariate models adjusted for age, T1D and cardiovascular risk factors, PE [OR 4.97 (1.61–15.29), p = 0.005] and PE + T1D [OR 7.69 (1.25–47.29), p = 0.028] were independently associated with atherosclerosis progression. Conclusions PE was a strong independent predictor of atherosclerosis progression over a 5-year follow-up period, with an additive effect in T1D. These findings highlight preeclampsia as a significant CVD risk enhancer in young women with T1D. Graphical abstract Research insights What is currently known about this topic? Women with type 1 diabetes (T1D) experience twice the excess risk of cardiovascular events compared to men, relative to individuals without T1D. Women with T1D have a higher prevalence of preeclampsia, an independent sex-specific cardiovascular risk factor. In a previous study, a history of preeclampsia was associated with preclinical atherosclerosis in women with T1D, but its independent relationship with atherosclerosis progression remains unexplored. What is the key research question? Does previous preeclampsia independently predict atherosclerosis progression in women with T1D over a 5-year follow-up period? What is new? Preeclampsia is a strong independent predictor of atherosclerosis progression in women with T1D.Women with both T1D and preeclampsia have twice the rate of atherosclerosis progression compared to those with T1D alone.Preeclampsia and T1D have an additive effect on atherosclerosis progression, even after adjusting for main cardiovascular risk factors. How might this study influence clinical practice? This study suggests that a history of preeclampsia should be considered a risk-enhancing factor in cardiovascular risk assessments for women with T1D, potentially leading to more intensive prevention strategies.

Background Since the arrival of continuous glucose monitoring (CGM), the relationship between the glucose management indicator (GMI) and HbA1c has been a topic of considerable interest in diabetes research. This study aims to explore the association between the GMI/HbA1c ratio and the presence of preclinical carotid atherosclerosis in type 1 diabetes (T1D). Methods Individuals with T1D and no prior history of cardiovascular disease were recruited from two centers. Carotid ultrasonography was performed using a standardized protocol and carotid plaques were defined as intima-media thickness ≥ 1.5 mm. CGM-derived data were collected from a 14-day report. A GMI/HbA1c ratio < 0.90 was selected to identify “fast-glycator” phenotype. Results A total of 584 participants were included (319 women, 54.6%), with a mean age of 48.8 ± 10.7 years and a mean diabetes duration of 27.5 ± 11.4 years. Carotid plaques were present in 231 subjects (39.6%). Approximately 43.7% and 13.4% of participants showed absolute differences of ≥ 0.5 and ≥ 1.0 between 14-day GMI and HbA1c, respectively. Among patients ≥ 48 years, the fast-glycator phenotype was independently associated with presence of plaques (OR 2.27, 95%CI: 1.06–4.87), even after adjusting for non-specific and T1D-specific risk factors and statin treatment. No significant association was observed in younger subjects (p for interaction < 0.05). Conclusions Fast-glycator phenotype is independently associated with atherosclerosis in T1D individuals aged ≥ 48 years, suggesting an age-related increase in the glycation risk. These findings highlight the potential of the GMI/HbA1c ratio for cardiovascular risk stratification in this population. Graphical abstract

Continuous glucose monitoring (CGM) plays an important role in treatment decisions for patients with type 1 diabetes under conventional or closed-loop therapy. Physical activity represents a great challenge for diabetes management as well as for CGM systems. In this work, the accuracy of CGM in the context of exercise is addressed. Six adults performed aerobic and anaerobic exercise sessions and used two Medtronic Paradigm Enlite-2 sensors under closed-loop therapy. CGM readings were compared with plasma glucose during different periods: one hour before exercise, during exercise, and four hours after the end of exercise. In aerobic sessions, the median absolute relative difference (MARD) increased from 9.5% before the beginning of exercise to 16.5% during exercise (p < 0.001), and then decreased to 9.3% in the first hour after the end of exercise (p < 0.001). For the anaerobic sessions, the MARD before exercise was 15.5% and increased without statistical significance to 16.8% during exercise realisation (p = 0.993), and then decreased to 12.7% in the first hour after the cessation of anaerobic activities (p = 0.095). Results indicate that CGM might present lower accuracy during aerobic exercise, but return to regular operation a few hours after exercise cessation. No significant impact for anaerobic exercise was found.

Background/Objectives: Obesity is associated with cognitive decline, and metabolic bariatric surgery (MBS) can improve both physical and cognitive outcomes. However, cognitive improvements post-surgery are variable. This study explores the role of skeletal muscle health, specifically muscle strength and mass, in cognitive performance after MBS, aiming to identify factors that influence cognitive recovery. Methods: In this prospective study, 55 patients scheduled for MBS were assessed 1 month before and 12 months after surgery. Body composition, including appendicular lean mass (ALM) and fat mass, was measured using dual-energy X-ray absorptiometry (DXA). Handgrip strength (HGS) was assessed via dynamometry, and neurocognitive performance was evaluated using a standardized test battery. Results: Significant improvements in cognitive performance were observed at 12 months post-surgery in attention, memory, language, executive functions and overall cognitive performance. Regarding body composition, significant reductions were observed in fat mass and body mass index (BMI). A decrease in ALM and no changes in HGS were observed; however, when adjusted for body size, both showed an increase. Regression analysis identified baseline HGS, but not muscle mass, as a significant predictor of cognitive performance at 12 months post-surgery. Conclusions: MBS leads to significant improvements in cognitive function. Our results suggest that baseline HGS may play a role in predicting cognitive outcomes post-surgery, highlighting the need for comprehensive assessments of both physical and cognitive health in patients undergoing MBS. Further longitudinal studies are needed to explore causal relationships and the potential reversibility of cognitive deficits post-surgery.

Background: Sarcopenia and diabetes contribute to the development of frailty. Therefore, accessible methods, such as muscle ultrasounds (MUSs), to screen for sarcopenia should be implemented in clinical practice. Methods: We conducted a cross-sectional pilot study including 47 patients with diabetes (mean age: 77.72 ± 5.08 years, mean weight: 75.8 kg ± 15.89 kg, and body mass index: 31.19 ± 6.65 kg/m2) categorized as frail by the FRAIL Scale or Clinical Frailty Scale and confirmed by Fried’s Frailty Phenotype or Rockwood’s 36-item Frailty Index. We used the SARC-F questionnaire to identify sarcopenia. The Short Physical Performance Battery (SPPB) and the Timed Up and Go (TUG) tests were used to assess physical performance and the risk of falls, respectively. In addition, other variables were measured: fat-free mass (FFM) and Sarcopenia Risk Index (SRI) with the bioimpedance analysis (BIA); thigh muscle thickness (TMT) of the quadriceps with MUS; and hand-grip strength with dynamometry. Results: We observed correlations between the SARC-F and FFM (R = −0.4; p < 0.002) and hand-grip strength (R = −0.5; p < 0.0002), as well as between the TMT and FFM of the right leg (R = 0.4; p < 0.02) and the SRI (R = 0.6; p < 0.0001). We could predict sarcopenia using a logistic regression model with a ROC curve (AUC = 0.78) including FFM, handgrip strength, and TMT. The optimal cut-off point for maximum efficiency was 1.58 cm for TMT (sensitivity = 71.4% and specificity = 51.5%). However, we did not observe differences in the TMT among groups of greater/less frailty based on the SARC-F, SPPB, and TUG (p > 0.05). Conclusions: MUSs, which correlated with the BIA (R = 0.4; p < 0.02), complemented the diagnosis, identifying regional sarcopenia of the quadriceps in frail patients with diabetes and improving the ROC curve to AUC = 0.78. In addition, a TMT cut-off point for the diagnosis of sarcopenia of 1.58 cm was obtained. Larger studies to validate the MUS technique as a screening strategy are warranted.

Switching to a new glucose sensor: real-world benefits for people with type 1 diabetes using the tandem control-IQ system People with type 1 diabetes need to carefully monitor their blood sugar levels to stay healthy. Many use advanced technologies like insulin pumps and continuous glucose monitors (CGMs). This study looked at what happens when people already using an automated insulin delivery system (Tandem Control-IQ with Dexcom G6) switch to a newer sensor model, the Dexcom G7. Over three months, 92 adults with type 1 diabetes in Spain were followed after switching to the G7 sensor. Researchers checked their blood sugar control and asked them how they felt about the new system using questionnaires. The results showed that overall blood sugar levels stayed stable. But for those who started with less optimal control, blood sugar levels improved significantly after the switch. These participants also had lower average glucose and HbA1c levels. In addition to better glucose control, people reported feeling less stressed about managing their diabetes and noted improvements in quality of life—especially women and those who initially had poorer control. Most people were satisfied with the new sensor, and very few stopped using it. Some people mentioned mild skin irritation or connection issues, but these did not interfere with the treatment. This study suggests that moving to the Dexcom G7 sensor can be safe and beneficial for people already using advanced diabetes technology, especially for those who need help improving their glucose levels and emotional well-being.

Objective Diabetes Self-Management Education and Support (DSMES) is a critical component of diabetes care. This study aims to examine the effect of online-based educational interventions on diabetes management compared to face-to-face interventions. Methods A systematic review was conducted by searching three databases for studies in English or Spanish between December 2023 and March 2024. The inclusion criteria were studies that compared face-to-face DSMES with online interventions. Results The follow-up duration of the trials ranged from 1 to 12 months. Multidisciplinary teams delivered online DSMES through various means, including Short Message Service (SMS), telephone calls, video calls, websites, and applications. Online DSMES was found to be comparable to face-to-face interventions in terms of glycated hemoglobin (HbA1c) levels in people with type 1 diabetes (T1D). In contrast, online interventions that focus on weight management in people with type 2 diabetes (T2D) have shown a significant reduction in HbA1c compared to face-to-face interventions. Online DSMES was found to be superior in terms of quality of life and cost-effectiveness in both T1D and T2D. None of the analyzed studies explored the differences between individual and group methodologies. Conclusions The current evidence indicates that online DSMES services provide at least comparable biomedical benefits to face-to-face interventions, suggesting that online interventions could be incorporated into clinical practice as a complement or reinforcement. However, further research is needed to explore the potential benefits and effectiveness of online group sessions in DSMES.

Objectives: With the increasing prevalence of diabetes and frailty among older adults, there is an urgent need for precision medicine that incorporates comprehensive geriatric assessments, including frailty detection. This scoping review aims to map and synthesize the available evidence on validated tools for detecting pre-frailty and frailty in community-dwelling elderly individuals with diabetes and outpatient diabetes patients. Specifically, it addresses: (1) What validated tools are available for detecting pre-frailty and frailty in this population? (2) How are these tools associated with outcomes such as glycemic control, hypoglycemia, and metabolic phenotypes? (3) What gaps exist in the literature regarding these tools? Methods: The review followed PRISMA-ScR guidelines, conducting a systematic search across PubMed, Cochrane Library, and Web of Science. The inclusion criteria focused on studies involving individuals aged 70 years and older with diabetes, emphasizing tools with predictive capacity for disability and mortality. Results: Eight instruments met the inclusion criteria, including the Frailty Index, Physical Frailty Phenotype, and Clinical Frailty Scale. These tools varied in domains such as physical, psychological, and social aspects of frailty and their association with glycemic control, hypoglycemia, and metabolic phenotypes. The review identified significant gaps in predicting diabetes-related complications and their clinical application. Conclusions: Routine management of older adults with diabetes should incorporate frailty detection, as it is crucial for their overall health. Although widely used, the reviewed tools require refinement to address the unique characteristics of this population. Developing tailored instruments will enhance precision medicine, leading to more effective, individualized interventions for elderly individuals with diabetes.

Introduction To describe and compare the routine use of continuous subcutaneous insulin infusion (CSII) in type 1 diabetes (T1D) patients with and without continuous glucose monitoring (CGM) in routine clinical practice and its relationship with glycemic outcomes. Methods Retrospective observational case–control study collecting routine use of CSII and CGM in T1D patients between January 2016 and December 2016. Patients with T1D using sensor augmented pump (SAP) were matched by sex and disease duration in a 1:3 ratio with those treated only with CSII. Patients used a Paradigm Veo or 640G Medtronic-Minimed ® insulin pump with or without a glucose sensor (Enlite, Medtronic-Minimed ® ) for at least 12 months. Results A total of 160 subjects with T1D were included, 40 using SAP and 120 on CSII (age 47 ± 12 years, 88 women, diabetes duration 29 ± 9.0 years, 10 ± 4.7 years on CSII, HbA 1C 7.6 ± 0.8%). Those in SAP therapy used the sensor 63% of time, performed less self-monitored blood glucose (SMBG)/day (3.3 ± 1.9 vs. 4.5 ± 2.0; p  < 0.01), more bolus/day (6.2 ± 3.6 vs. 4.8 ± 1.6; p  < 0.05), more basal insulin segment/day (6.5 ± 2.1 vs. 5.9 ± 1.5; p  < 0.05), and more suspension time of the pump (97 ± 93 vs. 9.6 ± 20 min/day; p  < 0.0001). Regarding metabolic control, SAP therapy patients had lower HbA 1c (7.4 ± 0.7 vs. 7.7 ± 0.9%; p  = 0.068), lower average SMBG value (151 ± 32 vs. 163 ± 30 mg/dL; p  < 0.05), a lower percentage of SMBG values greater than 180 mg/dL (30 ± 19 vs. 37 ± 16%; p  < 0.05) with no differences in SMBG values less than 70 mg/dL (12 ± 8.0 vs. 9.8 ± 9.8%; p  = 0.33) compared with patients on CSII. There were no differences in bolus wizard targets or in insulin/carbohydrate ratios per day. Conclusion In a real-world setting, SAP therapy is associated with more self-adjustments of insulin therapy when compared to CSII alone. This could result in an improvement in glucose control.

Background: Bariatric surgery (BS) has a significant impact on body composition (BC) and consequently may affect established sarcopenic obesity (SO) in candidate patients. The aim of this study was to assess the utility of muscle ultrasound (MUS) of rectus femoris thickness (RFT) for the evaluation of BC and skeletal muscle function in patients undergoing BS compared to bioimpedance analysis (BIA), dual-energy X-ray absorptiometry (DEXA) and dynamometry. On the other hand, we aimed to demonstrate how MUS of RFT correlates with quality of life (QoL) in this population, likely due to its ability to detect regional quadriceps muscle sarcopenia compared to the other mentioned methods. Methods: This was a prospective pilot study that included 77 participants (64.9% female, mean age: 53.2 ± 8.67 years) who underwent BS. Handgrip strength was measured using a dynamometer, fat-free mass index (iFFM) was assessed by BIA, appendicular muscle index (AMI) was calculated using DEXA, and RFT was measured by MUS. Moreover, homeostasis model assessment of insulin resistance (HOMA-IR) was calculated. All these measurements were conducted 1 month prior to BS and at the 12-month follow-up. QoL was assessed using the Moorehead–Ardelt questionnaire. Results: The mean BMI decreased by 12.95 ± 3.56 kg/m2 (p = 0.001). Firstly, we observed a positive correlation pre-surgery between HOMA and RFT (r = 0.27, p = 0.02), iFFM (r = 0.36, p = 0.001), AMI (r = 0.31, p = 0.01) and dynamometer readings (r = 0.26, p = 0.02). In addition, we found a correlation between RFT and iFFM (pre-surgery: r = 0.31, p = 0.01; post-surgery: r = 0.25, p = 0.05) and between RFT and lower-extremity AMI post-surgery (r = 0.27, p = 0.04). Secondly, we observed significant reductions in iFFM, AMI and RFT (p = 0.001), but not in dynamometer readings (p = 0.94). Finally, a tendency to a positive correlation between QoL questionnaire and RFT post-surgery results (r = 0.23, p = 0.079) was observed. Conclusions: Our results suggest that RFT measured by MUS is useful for evaluating SO and for the follow-up of these patients after BS. Moreover, RFT can provide relevant information about regional sarcopenia and probably has an accurate correlation with QoL in comparison with the other methods.