Patient-reported outcomes in digital health solutions can offer patients with type 1 diabetes an opportunity to voice their needs in outpatient care, enabling clinicians to tailor support. Evidence on long-term health impact and routine integration of such digital solutions outside controlled settings is limited.

This study aimed to compare a flexible digital supplement to outpatient care for type 1 diabetes (DigiDiaS) with usual care over 1 year, with self-management as the primary outcome and glycemic control and well-being as secondary outcomes.

This longitudinal real-world observational pre-post study was conducted at the Endocrinology Department of Akershus University Hospital in Norway. Adults with type 1 diabetes were recruited consecutively from October 2022 to October 2023 and could choose either the digital mobile health (mHealth)-based outpatient care model-"DigiDiaS" care-or usual care. DigiDiaS care is delivered via a smartphone app and includes a messaging service; patient-reported outcome-based preconsultation questionnaires; video, telephone, and in-person consultations; and an individually tailored information section. Outcome data comprised self-reported measures, clinical data extracted from electronic medical records, the national diabetes registry, and the digital platform. Data were collected at baseline and at the 1-year follow-up. Change in self-management (Patient Activation Measure short version [PAM-13]; primary outcome) and the secondary outcomes well-being (Five Well-Being Index [WHO-5]) and glycemic control (glycated hemoglobin [HbA_1c]) were analyzed using a generalized linear model. Utilization of the digital solution and health care services was also explored.

We included 237 patients, with 185 (78%) opting for DigiDiaS care and 52 (22%) for usual care. At the follow-up, most participants (145/178, 81%) in the DigiDiaS care group used the digital solution. The messaging service was the most utilized feature with 592 messages sent collectively (median 1, min-max 0-57). There were no statistically significant between-group differences in change from baseline to follow-up in self-management (mean difference 1.18, 95% CI -5.2 to 7.6; P=.72), glycemic control (HbA_1c mean difference -2.1, 95% CI -6.6 to 2.4; P=.36), or well-being (mean difference 1.9, 95% CI -3.1 to 6.9; P=.46). Health care utilization did not differ between the groups, including participation in one or more individual consultations during the 1-year follow-up (DigiDiaS care: 159/178, 89%; usual care: 42/50, 84%; P=.30) or appointment cancellations (DigiDiaS care: 64/91, 70%; usual care: 13/18, 72%; P=.20).

This real-world pragmatic observational comparison under routine conditions demonstrates that reorganizing outpatient care for patients with type 1 diabetes into a flexible digital model, DigiDiaS care, did not result in statistically significant between-group differences in health outcomes, including self-management, glycemic control, and well-being, compared with usual care. Over 80% of participants in DigiDiaS care utilized the digital solution, with patient-initiated asynchronous messaging as the most frequently used feature.

RR2-10.2196/52766.

Metabolic disorders such as obesity, type 2 diabetes mellitus, and fatty liver disease are associated with a disruption in the coordinated regulation of nutrient sensing, energy metabolism, and cellular homoeostasis. Increasing evidence indicates that sirtuins, a family of NAD⁺-dependent enzymes, play a central role in integrating metabolic and stress-responsive pathways. By coupling the cellular redox state to transcriptional and post-translational regulation, sirtuins coordinate key processes such as glucose and lipid metabolism, mitochondrial function, and inflammatory signalling. Sirtuins are functionally specialised according to their subcellular localisation. Nuclear sirtuins (SIRT1, SIRT6, and SIRT7) regulate transcriptional programs controlling metabolism and inflammation, whereas mitochondrial sirtuins (SIRT3, SIRT4, and SIRT5) directly modulate metabolic enzyme activity and redox homoeostasis. SIRT2 links cytosolic metabolic signalling to cytoskeletal dynamics and cell cycle regulation. Importantly, the activity of all sirtuins is tightly dependent on NAD⁺ availability, positioning NAD⁺ metabolism as a central regulator of the sirtuin network. In this review, we provide a systems-level perspective on sirtuin biology, highlighting how NAD⁺ metabolism, subcellular compartmentalisation, and specific functions converge to form an integrated regulatory network governing metabolic homoeostasis. We further discuss how disruption of this network contributes to the pathogenesis of metabolic disorders through impaired metabolic flexibility, mitochondrial dysfunction, and chronic inflammation. Overall, this network-based framework provides a unified view of sirtuin function in metabolic regulation and helps to explain the complexity and tissue-specific heterogeneity of metabolic diseases.

Rotator cuff tears (RCTs) represent a significant clinical challenge with high post-operative re-tear rates, especially in diabetic patients. Through comprehensive bioinformatic analysis of a publicly available transcriptomic dataset (GSE236746), we identified the significant downregulation of the mechanosensitive hub gene PIEZO2 and the aberrant activation of oxidative stress/inflammatory pathways as primary pathological barriers in diabetic patients. This metabolic dysfunction triggers the advanced glycation end products (AGEs)/receptor for AGEs (RAGE) axis, creating a self-amplifying oxidative stress loop that traps macrophages in a persistent pro-inflammatory M1 phenotype and impairs the recruitment of bone/tendon progenitor cells. Addressing these interconnected metabolic and mechanical barriers, we engineered an energy-responsive, multi-catalytic nanocomposite (Au-Pd/BTO, termed APB) integrated into a thermosensitive Pluronic F127 hydrogel (APBF). The APBF platform functions as a "metabolic-electric" dual-regulator: the cascade enzyme mimetic activities (glucose oxidase [GOD]-, superoxide dismutase [SOD]-, and catalase [CAT]-like) of the Au-Pd alloy effectively attenuate the glucose-reactive oxygen species (ROS)-AGEs/RAGE cascade. Thereby resolving the inflammatory niche and promoting M2 macrophage polarization. Simultaneously, piezoelectric Barium Titanate (BTO) nanocrystals generate endogenous electrical signals under physiological mechanical loading to compensate for the intrinsic PIEZO2-mediated mechanosensing deficiency, thereby enhancing angiogenesis, osteogenesis, and chondrogenesis. Systematic in vivo evaluation, including micro-computed tomography (micro-CT) analysis analysis, biomechanical testing, and histological assessment, demonstrated that APBF successfully restores the structural integrity and mechanical strength of the tendon-bone interface (TBI). Based on transcriptomic evidence, this study designed of physiology-matched biomaterials for complex tissue regeneration.

Ischemic stroke remains a leading cause of death and disability worldwide. This single-center retrospective case-control study evaluated the independent and interactive effects of smoking, alcohol consumption, and traditional cardiovascular risk factors on first-ever ischemic stroke. Cases with radiologically confirmed first-ever ischemic stroke and controls were matched in a 1:2 ratio by age (±3 years) and sex between January 2018 and June 2025. Smoking status, pack-years, alcohol intake, hypertension, diabetes mellitus, and lipid variables were assessed. Conditional logistic regression with pre-specified covariates was applied, with interaction evaluated on both multiplicative and additive scales. Firth's penalization was used to address sparse data, and multiple imputation by chained equations was used to handle missing data. A total of 312 cases and 624 controls were included. Current smoking (odds ratio [OR] 2.34, 95% confidence interval [CI] 1.82-3.01), heavy alcohol consumption (>100 g/wk; OR 1.89, 95% CI 1.34-2.67), hypertension (OR 3.21, 95% CI 2.54-4.06), and diabetes mellitus (OR 2.12, 95% CI 1.56-2.88) were independently associated with ischemic stroke. Hypertension and current smoking demonstrated significant interaction on both multiplicative (interaction OR 1.58, 95% CI 1.12-2.24; P = 0.009) and additive scales (relative excess risk due to interaction 2.87, 95% CI 1.21-4.53; attributable proportion 0.32, 95% CI 0.15-0.49; synergy index 2.18, 95% CI 1.35-3.52). Model discrimination was good (area under the curve 0.82, 95% CI 0.79-0.85). These findings support integrated prevention strategies for individuals with coexisting hypertension and smoking exposure.

Sodium-glucose cotransporter 2 inhibitors reduce the risk of kidney disease progression in patients with diabetic kidney disease (DKD); however, evidence describing early clinical and biological changes following treatment initiation in routine clinical practice remains limited. This study used a dual-phase design to evaluate serum C1q/tumor necrosis factor-related protein 7 (CTRP7) and the effects of dapagliflozin in DKD. In the cross-sectional phase, 108 participants were categorized into healthy controls, type 2 diabetes without kidney disease, and DKD groups to assess serum CTRP7 expression. In the longitudinal phase, 48 patients with DKD received dapagliflozin therapy and were followed for 12 weeks to monitor clinical and biochemical changes. Serum CTRP7 levels increased progressively with disease severity. A nomogram integrating systolic blood pressure, glycated hemoglobin, body mass index, and serum CTRP7 demonstrated strong predictive performance for identifying DKD risk. After 12 weeks of dapagliflozin treatment, urinary albumin-to-creatinine ratio and blood pressure were reduced. Improvements were accompanied by decreased malondialdehyde levels and increased superoxide dismutase levels, suggesting attenuation of oxidative stress. These findings suggest that serum CTRP7 may serve as a potential biomarker of DKD and that dapagliflozin treatment is associated with improvements in renal and inflammatory profiles.

Elizabethkingia meningoseptica (E. meningoseptica) is an emerging multidrug-resistant nosocomial pathogen that primarily affects debilitated and immunocompromised individuals. We report a rare case of E. meningoseptica-associated sepsis arising from chronic bilateral gluteal pressure ulcers in a 64-year-old bedridden male patient with diabetes mellitus, hypertension, and recurrent cerebrovascular accidents, highlighting the importance of considering uncommon pathogens in non-healing wounds. An initial wound culture yielded Proteus mirabilis, and the patient was started on intravenous meropenem. Despite therapy, there was no clinical improvement, with persistent wound discharge and progressive tissue necrosis. Repeat wound and blood cultures subsequently grew E. meningoseptica, which was identified using the VITEK 2 automated system (bioMérieux, Marcy-l'Étoile, France). Antimicrobial susceptibility testing performed using the VITEK 2 system demonstrated susceptibility to piperacillin-tazobactam, cefoperazone-sulbactam, ciprofloxacin, and cotrimoxazole, with resistance to carbapenems and aminoglycosides. Meropenem was discontinued, and targeted therapy with piperacillin-tazobactam was initiated. Significant clinical improvement was observed within five to seven days, with marked reduction in wound discharge and local inflammatory signs and progressive wound granulation by day 14. This case highlights the importance of repeat cultures, accurate microbiological identification, and close laboratory-clinician communication in patients with non-healing chronic wounds who fail to respond to empirical therapy.

Research on coronary microcirculatory function in type 2 diabetes mellitus (T2DM) patients with ST-segment elevation myocardial infarction (STEMI) remains limited.

Patients diagnosed with new-onset STEMI between January 2022 and December 2023 were enrolled. All underwent culprit vessel revascularization, with simultaneous blood sampling and angiography-derived microvascular resistance (AMR) assessment in the reperfused vessel. The primary endpoint was the incidence of major adverse cardiovascular and cerebrovascular events (MACCEs).

A total of 545 patients were divided into four groups based on HbA1c and AMR levels. After adjustment for covariates using a multivariable Cox proportional hazards model, HbA1c (HR = 1.403, 95% CI: 1.131-1.740), AMR (HR = 1.213, 95% CI: 1.105-1.520), and NT-proBNP (HR = 1.244, 95% CI: 1.1053-2.868) remained independently associated with MACCEs. Patients with HbA1c ≥6.5% and AMR ≥250.5 mmHg·s/m exhibited the highest risk of MACCEs (HR = 6.903, 95% CI:3.260-14.618, P < 0.001). Restricted cubic spline analysis revealed nonlinear relationships between MACCEs and both HbA1c and AMR levels. RCS analysis indicated nonlinear relationships between MACCEs incidence and both HbA1c and AMR levels.

This study demonstrates that an elevated AMR following PCI independently predicts MACCEs in patients with STEMI and T2DM. Combined evaluation of AMR and HbA1c enhances risk stratification for MACCEs. Assessment of coronary microcirculatory function and sustained optimization of glycemic control may contribute to improved long-term clinical outcomes in this population.

To develop and internally validate a clinical prediction model for identifying asymptomatic type 2 diabetes (T2DM) patients at risk of incident heart failure (HF) or progression of subclinical cardiac dysfunction.

This single-center retrospective study included 326 asymptomatic T2DM patients with preserved LVEF, all with ≥3 echocardiographic assessments over 24 months. The primary outcome was a composite of incident clinical HF (classified as HFpEF or HFrEF based on symptoms, hospitalization, natriuretic peptides, and follow-up echo) and imaging-defined progression of subclinical dysfunction. Candidate predictors (clinical variables, GLS, LASr, E/e', LAVI, LVMI, NT-proBNP, galectin-3) were pre-specified. Missing data were handled by multiple imputation. A risk score was derived using multivariable Cox regression with Fine-Gray competing risk analysis, and optimism was assessed via bootstrap, 5-fold cross-validation, and internal split-sample validation.

Over 24 months, LV GLS modestly declined (17.4 ± 2.0% to 16.9 ± 2.1%), while LASr deteriorated more (38.5 ± 7.2% to 34.0 ± 6.5%). Independent predictors of the composite outcome were LASr ≤24% (HR 3.58), NT-proBNP ≥120 pg/mL (HR 2.48), galectin-3 ≥15 ng/mL (HR 1.79), age ≥70 years, diabetes duration ≥12 years, BMI ≥30 kg/m², and UACR ≥60 mg/g; SGLT2i/GLP-1 RA use was associated with lower observed risk. During follow-up, 40 patients reached the composite outcome (18 clinical HF: 14 HFpEF, 4 HFrEF; 22 imaging-only progression). The scoring system stratified patients into low- (≤3 points), intermediate- (4-6), and high-risk (≥7) groups, with 24-month cumulative incidences of 4.2%, 11.7%, and 27.5% (Gray's test P<0.001). The full model had a C-statistic of 0.835 (bootstrap-corrected 0.828) and good calibration (Brier score 0.068). Adding LASr and galectin-3 improved discrimination (ΔC=0.058 and 0.012, both P<0.05).

Integrating LASr, galectin-3, and clinical risk factors may help identify asymptomatic T2DM patients at higher risk of incident HF or subclinical progression. This internally validated model may support preliminary risk stratification for suspected early diabetic cardiomyopathy, but external validation and clinical utility assessment are needed before routine use.

Sarcopenia is common among older adults with type 2 diabetes mellitus (T2DM). Although chronic hyperglycemia is known to contribute to muscle loss, it remains unclear whether glucose fluctuations-independent of average glucose levels-also play a role. This study aimed to investigate the association between glucose fluctuation and pectoralis muscle mass in elderly patients with T2DM.

This retrospective cross-sectional study included 303 elderly patients with T2DM who underwent continuous glucose monitoring and chest CT between October 2022 and December 2025. Glycemic variability was assessed using several metrics: coefficient of variation (CV), standard deviation (SD), mean amplitude of glycemic excursions (MAGE), mean of daily differences, time in range, time above range, time below range (TBR), and mean blood glucose. Pectoralis muscle index (PMI) was measured from CT images at the T4 vertebra level. Multivariable linear regression, subgroup analyses, and sensitivity analyses were performed.

Four glycemic variability indicators-CV, SD, MAGE, and TBR-were independently associated with lower PMI after adjusting for confounders (all P < 0.05). Among these, CV explained the largest proportion of PMI variance (adjusted R² = 0.22), followed by TBR (0.21), SD (0.20), and MAGE (0.19). A linear dose-response relationship was observed between CV and PMI (P for trend < 0.001). The inverse association was stronger in patients with diabetes duration ≥ 10 years (β = -0.18, P < 0.001) and those with BMI < 24 kg/m² (β = -0.18, P < 0.001), with significant interactions for both subgroups (P = 0.022 and 0.027, respectively). Sensitivity analyses confirmed the robustness of these findings.

Greater glycemic variability is independently associated with lower pectoralis muscle mass in elderly patients with T2DM, especially among those with longer disease duration or normal body weight. Stabilizing glucose fluctuations may be an important consideration for preserving muscle mass in this population.

Cognitive impairment is increasingly recognized as an important central nervous system complication of type 2 diabetes mellitus (T2DM). Thyroid hormones (THs) and insulin resistance are both implicated in brain metabolism; however, the associations of free triiodothyronine (FT3) and the triglyceride-glucose (TyG) index with cognitive impairment in euthyroid patients with T2DM remain incompletely understood.

This retrospective cross-sectional study enrolled 525 euthyroid hospitalized patients with T2DM between September 2023 and March 2025. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA), and mild cognitive impairment (MCI) was defined as a MoCA score of 19-25. Logistic regression analyses were used to evaluate the associations of FT3 and the TyG index with MCI. Restricted cubic spline (RCS) models were applied to explore dose-response relationships and potential nonlinearity. Receiver operating characteristic (ROC) curve analyses were performed to assess the discriminative ability of FT3, the TyG index, and their combined model. The DeLong test was used to compare differences in AUCs between models. Calibration analysis and decision curve analysis (DCA) were further conducted to evaluate the predictive agreement and potential clinical utility of the combined FT3 - TyG model.

Lower FT3 levels were independently associated with a higher odds of MCI, even within the euthyroid range, exhibiting a significant linear negative dose-response relationship. The TyG index showed a nonlinear, asymmetric inverted J-shaped association with the odds of prevalent MCI, with a clear inflection point at TyG = 9.24, above which the estimated odds increased more rapidly. ROC analysis demonstrated good discriminative performance for FT3 alone (AUC = 0.761, 95% CI: 0.721-0.802), whereas the TyG index alone showed limited discriminative value (AUC = 0.571, 95% CI: 0.520-0.622). The combined FT3-TyG model yielded an AUC of 0.766 (95% CI: 0.726-0.807), which was not significantly higher than that of FT3 alone. However, within individuals with higher TyG levels, FT3 provided additional granularity for distinguishing those with a higher likelihood of MCI, supporting its role in risk stratification across heterogeneous metabolic profiles.

In euthyroid patients with T2DM, physiological variation in FT3 remains independently associated with cognitive status, while the TyG index is nonlinearly associated with cognitive impairment, with an identifiable metabolic threshold. The combined FT3-TyG model demonstrated good discriminative ability, suggesting that these readily accessible, noninvasive metabolic indicators may be useful for identifying individuals with a higher likelihood of MCI and for cognitive risk stratification in T2DM.