Diabetes-related distress (DRD) is exacerbated in people at risk of Diabetes-related Foot Disease (DFD); however, knowledge on this topic is still limited, especially in Primary Health Care (PHC), which focuses on prevention and monitoring. This study evaluated DRD and its associated factors in PHC individuals at risk of developing DFD, aiming to support management strategies to reduce complications.

Cross-sectional study with 1563 individuals with diabetes mellitus (DM) registered in PHC services in Brazil. Participants were stratified according to their risk of DFD, based on the criteria from the International Working Group on the Diabetic Foot. The DRD was measured using the Problem Areas in Diabetes (B-PAID) scale, considering a score ≥ 40 as indicative of high distress. Sociodemographic, clinical, and behavioral variables were collected and analyzed using Gamma regression on the software Statistical Package for the Social Sciences (SPSS 26.0).

Among 1563 people with DM, 39.8% were at risk for DFD. In the multiple regression model, there is notable increase in DRD associated with greater difficulty in caring for the feet (β = 1.129; 1.014-1.257), loss of protective sensation (β = 1.311; 1.110-1.549), and poor glycemic control (β = 0.850; 0.761-0.951).

Sociodemographic and clinical factors, particularly loss of protective sensation in the feet, difficulty in foot care, and inadequate control of glycated hemoglobin, are associated with greater DRD in people at risk for DFD. Primary health care stands out as a strategic space for integrating psychosocial support and clinical management, ensuring that preventive measures are implemented and resulting complications are avoided or detected early.

This study explored risk factors associated with depressive symptoms in older patients with obstructive sleep apnea (OSA) and assessed correlations of mean pulse oxygen saturation (MSpO₂) with depressive symptoms.

In total, 1,085 older patients diagnosed with OSA via polysomnography (PSG) were included. Based on scores from the 12-item Geriatric Depression Scale (GDS-12), participants were classified into two subgroups to identify depressive symptom-related risk factors. Logistic regression analysis, restricted cubic splines, and subgroup analyses were performed to evaluate correlations of MSpO₂ with depressive symptoms.

Depressive symptoms were observed in 139 patients (12.8% of the sample). Logistic regression analysis indicated that age (per 1-year increase, odds ratio [OR] = 1.11, 95% confidence interval [CI]: 1.08-1.14; P < 0.001), smoking (OR = 1.66, 95% CI: 1.02-2.69; P = 0.041), MSpO₂ (per 1% increase, OR = 0.90, 95% CI: 0.85-0.94; P < 0.001), diabetes mellitus (OR = 1.61, 95% CI: 1.03-2.51; P = 0.038), and renal dysfunction (OR = 2.26, 95% CI: 1.10-4.66; P = 0.027) were significantly associated with depressive symptoms. Additionally, sleep parameters including AHI, ODI, and LSpO₂ were independently associated with depressive symptoms. Restricted cubic splines suggested a linear correlation between MSpO₂ and depressive symptoms (nonlinear P = 0.38). Compared with patients in the highest category (MSpO₂ ≥ 95.0%), those in the lowest category (MSpO₂ ≤ 91.7%) showed increased depressive symptom risk (OR = 2.25, 95% CI: 1.34-3.78, P = 0.002). Subgroup analyses confirmed this linear relationship.

A linear correlation exists between MSpO₂ and depressive symptoms in older patients with OSA. Additionally, age, smoking, diabetes mellitus, and renal dysfunction are strongly associated with depressive symptoms in this population.

We aim to explore the support needs of individuals living with type 2 diabetes and disordered eating behaviours.

We conducted semistructured interviews with adult participants living with type 2 diabetes and self-identified disordered eating behaviours recruited from an Australian allied health service. Data were analysed through reflective thematic analysis.

Ten adults with type 2 diabetes (seven female, three male; mean age 66.3 ± 8.97, range: 52-80) were interviewed. Four themes are presented related to participants' support needs: (1) the need for increased information about the interactions between food, eating behaviours and diabetes and self-management; (2) a desire for increased time with knowledgeable health professionals who provide tailored person-centred diabetes care and support; (3) mental health services integrated into diabetes care are desired due to relationships between mental health, disordered eating behaviours and diabetes management; and (4) family, peers and community can offer invaluable support, but stigma can be a barrier to support seeking.

Individuals living with T2DM and disordered eating behaviours report diverse support needs including tailored informational support and emotional support from health professionals, family and peers. Although further research is required to develop and evaluate the implementation of specific interventions and care pathways, health professionals should endeavour to provide adequate time and resources for personalised education, and to promote and facilitate appropriate mental health and peer supports.

Sodium-glucose cotransporter inhibitors (SGLTi) as an adjunctive to insulin therapy may offer cardiometabolic and renal benefits in adults with type 1 diabetes (T1D). Their effective use depends on patient selection, education, and ketone monitoring to prevent diabetic ketoacidosis (DKA). Starting with the lowest effective dose, making appropriate insulin adjustments, and following structured protocols for ketone monitoring and DKA risk mitigation are essential for safe use of SGLTi in adults with T1D.

This article provides a stepwise guidance on the safe use of glucagon-like peptide-1 receptor agonists (GLP-1RAs) as adjunctive therapy in adults with type 1 diabetes (T1D). Here, we first identify the phenotypes within T1D most likely to benefit and then outline best practices for GLP-1RA initiation and titration. We dive into details on the components of patient education and counseling, best practices for monitoring, strategies to mitigate adverse effects and a practical framework for insulin dose adjustments to provide individualized care in adults with T1D. We additionally provide a one-page, provider-facing checklist to support safe, patient-centered implementation in clinical practice.

Phase 2 clinical trials using daily injectable glucagon-like peptide-1 receptor agonists as adjunct therapy in type 1 diabetes showed promising signals for efficacy on glycemic control and weight. These effects were confirmed in larger phase 3 trials but accompanied by safety issues including hypoglycemia and ketosis. Of note, these trials were conducted before the availability of widespread continuous glucose monitoring (CGM) and used simple one size fits all rules for insulin dose titration. Attention has moved on to weekly injectable agents at present, with more individualized insulin titration and guided by CGM.

Insulin resistance (IR) is an underrecognized feature of type 1 diabetes (T1D), present even in lean individuals. Rising obesity rates have further amplified this burden, creating a mixed metabolic phenotype that accelerates cardiorenal disease. Paradoxically, despite fewer traditional cardiovascular risk factors, individuals with T1D experience higher rates of cardiorenal complications than those with type 2 diabetes, a gap not fully explained by glycemic control. This article examines the epidemiologic, pathophysiologic, and mechanistic underpinnings of this hidden cardiorenal risk, including key drivers of end-organ damage. Broader therapeutic interventions targeting IR in T1D are essential to prevent future cardiorenal disease.

Peripheral artery disease (PAD) affects millions of individuals annually and can lead to severe morbidity and mortality. Risk factors for development of PAD include hypertension, obesity, diabetes mellitus, and smoking. Conventional methods to detect PAD include the Ankle-Brachial Index (ABI) with duplex ultrasound being the gold standard for diagnosis. Factors such as vessel compressibility, cuff placement, patient positioning, and sequence of measurements serve as limitations or sources of inaccuracy for ABI. BlueDop Vascular Expert (BVE) is an artificial intelligence (AI) powered device that offers a standardized, accurate, and reliable method to detect early PAD development regardless of comorbidities. The device is portable, user-friendly, easy to interpret and has the potential to expand early PAD detection.

Individuals at risk for PAD underwent both ABI and BVE testing. Full leg arterial duplex interpreted by an independent vascular surgeon served as the reference standard. Subgroup analysis compared BVE and ABI capabilities among those with underlying comorbidities such as diabetes mellitus, hypertension, tobacco use, and obesity. Data from two cohorts were used: this study and Tessendorf et al.

For all-comers overall accuracy was 91.2% and 80.6% for BVE and ABI respectively. Overall sensitivity for BVE was 82.5% and specificity was 93.9%. In contrast, ABI sensitivity was 58.3%, specificity was 87.4%. Increased accuracy, sensitivity, specificity, and κ constant was present in all analyzed subgroups when comparing BVE to ABI.

Across diverse patient populations, BVE provides more accurate and reliable PAD screening than ABI, including those with comorbidities that reduce ABI accuracy. BVE's portability, usability, and minimal reliance on specialized interpretation support it as a first-line screening tool, particularly in rural and underserved settings. Broader implementation of BVE could help reduce diagnostic disparities and improve outcomes for patients at risk of PAD.

Diabetic foot infections (DFIs) are a common complication of diabetes mellitus and a leading cause of hospitalization. Due to the polymicrobial nature of these infections and delays in aerobic and anaerobic culture results, patients are often started on broad-spectrum antibiotics, which may lead to unnecessary antimicrobial use. The purpose of this study was to assess the incidence of methicillin-resistant Staphylococcus aureus (MRSA), Pseudomonas aeruginosa, and anaerobic organisms in DFIs. Secondary endpoints evaluated the frequency of empiric antibiotic coverage for these organisms in both the emergency department (ED) and on initial hospital admission.

This single-center retrospective study reviewed medical records over a five-year period for patients admitted with an initial DFI. The incidence of positive cultures for MRSA, Pseudomonas, and anaerobic organisms was compared with the frequency of empiric antimicrobial coverage for each. The incidence of these organisms was also compared between patients with and without hospitalization within the prior 90 days.

Of the 184 patients in the study, 102 patients (55.43%) had cultures positive for one or more of the following: MRSA (17.0%), Pseudomonas (5.40%), and/or anaerobic organisms (45.10%). In the ED, 117 patients (63.59%) were treated empirically for MRSA, 111 patients (60.30%) were treated empirically for Pseudomonas, and 82 patients (44.60%) were treated empirically for anaerobes. On admission, 164 patients (89.10%) were treated empirically for MRSA, 140 patients (76.10%) were treated empirically for Pseudomonas, and 115 patients (62.50%) were treated empirically for anaerobes.

The study demonstrated rates of MRSA and Pseudomonas consistent with prior literature. However, rates of anaerobic organisms, which have historically been less studied in DFIs, were prominent. Despite this, empiric antimicrobial coverage for anaerobes was lowest among the organisms studied. This study may help guide clinicians in considering organism incidence and in selecting empiric parenteral antibiotic therapy.