Type 2 diabetes mellitus (T2DM) is prevalent in Nepal, with many seeking primary care through Ayurveda, a widely practiced traditional system. However, concerns exist about suboptimal care and variability in clinical practice among Ayurvedic practitioners. No evidence-based clinical practice guideline (EB-CPG) is available for managing T2DM. Therefore, an EB-CPG was developed, and a feasibility study was conducted to inform a future cluster randomized controlled trial (RCT) assessing whether EB-CPG improves T2DM management compared with usual practice.

A two-arm feasibility cluster RCT was conducted in Ayurveda centers. Centers were randomized (1:1) by an independent statistician. Adults with newly diagnosed, treatment-naïve T2DM and glycated hemoglobin (HbA1c) of 6.5%-< 9% were recruited. Data collectors and the analyst were blinded to group allocation.

Fourteen Ayurveda centers were approached, all recruited (seven/group) and completed the study. One center withdrew and did not enroll participants. Of 151 potential participants, 121 (80%) were recruited (60 in intervention and 61 in control). Of those, 84% were followed up to 6 months (51/group). The median adherence score to EB-CPG among practitioners was 1-2 (partial to adequate adherence). The median (interquartile range) number of EB-CPG-recommended medicines not consumed by participants and days without consumption was 0 (0-10) and 0 (0-2.5), respectively. No serious adverse events occurred. Preliminary estimates suggest EB-CPG's beneficial effects on HbA1c, fasting plasma glucose, and health-related quality-of-life, though not statistically significant.

This feasibility trial demonstrated successful recruitment, follow-up, and intervention adherence. A definitive trial is feasible to evaluate the intervention's effectiveness in T2DM management.

ClinicalTrials.gov Identifier: NCT05259735; first posted on March 02, 2022.

Type 1 diabetes (T1D) is a lifelong condition typically diagnosed in childhood. Clinical practice guidelines recommend comprehensive multidisciplinary team (MDT)-based care led by paediatric endocrinologists. However, experiences and opinions of health professionals about the implementation of T1D MDTs in Australia are currently unknown.

To describe health service teams caring for children and youth with T1D in Australia and to identify opportunities for service improvements from providers' perspectives.

Mixed-methods study co-designed with clinicians and consumers, including a survey of clinic leaders and semi-structured interviews. Survey questions covered modes of care delivery, team composition and outreach. Interview transcripts were thematically analysed using a hybrid inductive/deductive approach.

Thirty-two T1D services leaders completed the survey; 16 were from major cities and 16 were from regional/rural areas across all Australian states and territories. The services provided care for ~51% of all <19-year-olds living with T1D. T1D services were multidisciplinary and commonly included dieticians (n = 29, 94%), nurse diabetes educators (n = 22, 71%) and general paediatricians (n = 21, 68%). Eight (29%) services had a dedicated psychologist. A quarter (25%) of regional/rural services had a paediatric endocrinologist compared with 100% of major city services (χ² = 18.355; p < 0.001). All services offered telehealth consultations. Interviews revealed that services placed high value on having established cohesive teams skilled in T1D. Service leaders had concerns regarding workforce capacity and shortages, limited access to psychologists, inequitable access to insulin pumps and limited links with general practitioners.

This mixed-methods study is the first Australia-wide exploration of T1D models of care that describes care provision from the clinicians' perspectives. A need exists to address current gaps to achieve the recommended MDT models of care for T1D. Understanding existing models of care will be essential to determine the future impacts of changes in policies, therapies and demands on paediatric T1D services.

Despite the popularity of complementary and alternative medicine among older persons, its use within this subpopulation is still not fully understood. This study aimed to explore the perceptions of older persons residing in communities in Ebonyi State as pertains the use of complementary and alternative medicine.

Qualitative data collection was by focus group discussions (FGDs), in four communities, two urban and two rural, in Ebonyi state, Nigeria. A total of 12 FGDs involving 96 participants, each consisting of 8 males or females respectively were conducted using a synthesized FGD guide. A thematic analysis of data was performed with the aid of NVivo software.

The Leventhal's self-regulatory model (SRM) was utilised as it provides a flexible framework for understanding the use of complementary and alternative medicine among older persons. Majority of the participants expressed belief in the inherent benefits of complementary and alternative medicine, which were categorized into medical and non-medical reasons. Febrile illness, including malaria, typhoid fever, and hepatitis; respiratory; haematological; and dermatological conditions were reported as the common health conditions for which participants used CAM. Additionally, participants mentioned using CAM for chronic conditions, such as diabetes mellitus, hypertension, and arthritis, as well as for general health promotion and wellbeing. Preference for CAM was influenced by belief in its effectiveness, perceived lower cost when compared to conventional treatments, delays in hospital diagnoses and treatments, and belief in the spiritual origins of diseases. Safety concerns regarding CAM use included a lack of information on dosing, directions for safe use, and potential side effects.

The findings indicate a strong belief among participants in the benefits of complementary and alternative medicine which they believe offer both medical and non-medical advantages. However, despite these perceived benefits, safety concerns were also raised by some participants. Efforts to promote education and awareness about CAM, improve access to reliable information, and ensure the safe and effective use of CAM therapies are crucial for supporting the health and well-being of older persons who choose to incorporate CAM into their healthcare practices.

Clinical services for adults with early-onset type 2 diabetes (EOT2D) are in urgent need of improvement.

We evaluated a multi-disciplinary clinic for individuals with EOT2D at high risk (HbA1c >9%/triglyceride >20 mmol/L), providing 2-3 flexibly arranged consultations per individual between March 2024 and September 2025. Nurse-led case-finding in primary care supported identification and targeted referral of high-risk individuals. On 3 November 2025, electronic medical records were used to evaluate change in cardiometabolic outcomes at 6- and 12-months from baseline and evaluate service activity, including proportions with recorded health information and prescriptions. The paired t-test (continuous) and McNemar's test (proportions) were used to assess change in outcomes. Patient feedback was obtained using questionnaires.

In total, 159 individuals received an appointment (45% women; median age 34 years). At both 6- and 12-months post-baseline, HbA1c (at 12-months: -2.53% [95% CI: -3.13, -1.93]/-28 mmol/mol [-34, 21]), systolic (-5.89 mmHg [-9.88, -1.91]) and diastolic (-2.72 mmHg [-5.34, -0.10]) blood pressure, body mass index (BMI; -1.49 kg/m² [-2.31, -0.67]) and weight (-3.52 kg [-6.32, -0.72]) were significantly lower. Triglycerides were lower at 12-months only (-1.12 mmol/L [-1.89, -0.34]). The proportion with BMI or smoking status recorded, and with a glucagon-like peptide-1 receptor-based treatment, was higher at 12-months than at baseline, whereas creatinine and retinal screening measurements were less frequent. A limited amount of patient feedback was positive.

Case-finding and invitation to flexibly run multidisciplinary clinics were associated with improvements in cardiometabolic outcomes and positive patient feedback. Similar services are immediately required given the rising prevalence of EOT2D and associated complications.

To develop and temporally validate a nationwide prediction model for cesarean delivery following induction or augmentation of labor in Japan.

We conducted a retrospective cohort study using the Japan Society of Obstetrics and Gynecology Perinatal Database. Women with singleton pregnancies who underwent induction or augmentation of labor at ≥37 weeks of gestation between 2020 and 2022 were included. Cases from 2020 to 2021 (n = 113 572) formed the development cohort, and cases from 2022 (n = 59 045) served as the temporal validation cohort. Predictors were selected based on clinical relevance. Variable selection used least absolute shrinkage and selection operator logistic regression with the one standard error rule, followed by multivariable logistic regression. Model performance was assessed with the area under the receiver operating characteristic curve (AUROC) and calibration plots.

A total of 172 617 women were included in the study. Thirteen predictors were selected: maternal age, height, pre-pregnancy body mass index (BMI), gestational BMI gain, multiparity, gestational age, assisted reproductive technology pregnancy, mechanical cervical ripening, pregestational diabetes mellitus, hypertensive disorders of pregnancy, epidural analgesia, birthweight, and neonatal sex. Discrimination was good in the development cohort (AUROC 0.757, 95% confidence interval [CI] 0.754-0.761) and temporal validation cohort (AUROC 0.767, 95% CI 0.762-0.772). Multiparity and epidural analgesia were associated with lower risk, whereas all other predictors increased cesarean risk (all P < 0.001).

This nationwide prediction model demonstrated robust performance and might support individualized counseling, risk assessment, and perinatal care planning.

Achieving rapid glycemic stability with intensive insulin therapy in hospitalized type 2 diabetes patients remains unpredictable. We hypothesized that underlying insulin resistance is a key determinant of this response. This exploratory study aimed to test this hypothesis and develop a predictive nomogram.

We retrospectively analyzed 393 hospitalized patients initiating insulin pump therapy with continuous glucose monitoring. Stability was defined as Time in Range >70% for 24 consecutive hours. Collected data included body mass index, hemoglobin A1c (HbA1c), fasting glucose, fasting insulin, lipids, and calculated insulin resistance indices. Cox regression identified predictors of time to stability.

Analysis confirmed insulin resistance's significant role. Multivariate Cox regression identified older age, higher fasting insulin, elevated HbA1c, and a higher triglyceride-glucose (TyG) index as independent risk factors for prolonged time to stability (all P<0.05), with the TyG index interpreted as a marker of lipotoxic metabolic inflexibility rather than merely a surrogate of insulin resistance. A nomogram integrating these factors demonstrated good predictive accuracy, with a C-index of 0.801 (95% CI: 0.77-0.83). Calibration and decision curve analysis supported its clinical utility.

Insulin resistance significantly influences time to glycemic stabilization. The developed nomogram, incorporating the TyG index, fasting insulin, age, and HbA1c, provides a practical tool for early risk stratification, potentially guiding more personalized inpatient diabetes management.

Diabetic retinopathy (DR) can significantly impair vision and lead to blindness. Vitamin D (VD) has been shown to enhance the production of anti-inflammatory factors, alleviating the effects of hyperglycemia. However, downstream genes and molecular networks associated with VD signaling in DR remain unidentified. This study aimed to employ a systems biology approach to nominate high-priority candidate genes and cellular contexts as a hypothesis-generating effort to facilitate future functional studies on the role of VD in DR.

DR-related datasets were obtained from public databases to identify differentially expressed genes (DEGs). Seven canonical VD metabolism-related genes (VDRGs) were subjected to weighted gene co-expression network analysis (WGCNA) to identify VD signaling-associated model genes. Candidate genes were selected based on the intersection of DEGs and model genes. "Boruta" and support vector machine-recursive feature elimination (SVM-RFE), along with expression validation, were used to screen for biomarkers. Further analyses included immune infiltration, gene set enrichment analysis (GSEA), regulatory network construction, and drug prediction. Single-cell RNA sequencing (scRNA-seq) was utilized to assess cellular heterogeneity, identifying distinct cell clusters and key cells based on gene expression profiles. Cell-cell communication within immune cells was also examined. Biomarker expression levels in clinical samples were validated through real-time reverse transcription polymerase chain reaction (RT-qPCR).

The biomarkers SLC36A1 and RAB23 were identified as VD signaling-associated downstream candidates and validated. GSEA revealed their primary association with glucose metabolism. B cells and CD4 T cells were identified as differentially expressed immune cells. Both biomarkers were regulated by a competing endogenous RNA (ceRNA) network, and the drug "methyl methanesulfonate" targeted both biomarkers simultaneously. Single-cell analysis identified 11 distinct cell types, including classical monocytes, B cells, and T cells. B cells and classical monocytes were identified as key cells due to the differential expression of biomarkers. The cell-cell communication network highlighted interactions, particularly between classical monocytes, B cells, and T cells. The differentiation of key cells and the stage of biomarker expression were also uncovered. RT-qPCR analysis revealed a significant upregulation of SLC36A1 and RAB23 in the DR group compared to controls (F = 5.184 p = 0.027 < 0.05; F = 4.147 p = 0.047 < 0.05).

SLC36A1 and RAB23 were identified as VD signaling-associated downstream biomarkers in DR, providing a framework for exploring the potential link between VD signaling and DR pathogenesis through these candidate genes.

Adrenal insufficiency is a life-threatening condition that often presents with non-specific symptoms, complicating diagnosis in elderly patients.

We report a case of a 77-year-old man with diabetes mellitus, hypertension and a history of cerebrovascular accident who presented with nausea, vomiting, weight loss and persistent giddiness. Laboratory tests revealed hyponatraemia and low serum osmolality. Further endocrine evaluation showed low morning cortisol, a suboptimal response to the short Synacthen test and suppressed adrenocorticotropic hormone levels confirming secondary adrenal insufficiency. The patient later disclosed recent use of a traditional Chinese medicine suggesting possible hidden glucocorticoid exposure and suppression of the hypothalamic-pituitary-adrenal axis. He improved after initiation of hydrocortisone replacement and discontinuation of the suspected products.

This case emphasises the need for greater awareness of the potential adulteration of traditional Chinese medicines with glucocorticoids. It also highlights the critical role of laboratory testing in diagnosing adrenal insufficiency, detecting hidden adulterants and recognising the limitations of immunoassays in interpreting adrenal function tests.

To evaluate the effects of multidisciplinary management in the Diabetes Reversal Clinic on the remission of type 2 diabetes mellitus (T2DM), and explore the predictive factors for remission of diabetes.

This was a real-world, single-arm observational study. Patients with T2DM who received remission-oriented treatment at the Diabetes Reversal Clinic and followed up regularly for more than 24 weeks were included. The primary outcome was the remission rate of T2DM, and the secondary outcomes were changes in fasting blood glucose (FBG), 2-hour postprandial blood glucose, HbA1c, blood lipids, and body composition. Differences in clinical characteristics between the remission and non-remission groups were analyzed. The multivariate logistic regression analysis was performed to screen predictive factors.

The remission rate was 29.24% (50/171) after multidisciplinary management in the Diabetes Reversal Clinic. The remission group was younger, had a shorter duration of diabetes, used fewer types of medications at baseline, had a lower FBG and HbA1c, a higher β-cell function index HOMA-β, and a lower triglyceride level. The multivariate logistic regression analysis revealed that age (OR = 0.93, 95% CI: 0.89-0.97, P = 0.002), type of medications at baseline (OR = 0.45, 95% CI: 0.26-0.77, P = 0.004), baseline FBG (OR = 0.64, 95% CI: 0.46-0.89, P = 0.008), and weight loss magnitude (OR = 1.15, 95% CI: 1.01-1.31, P = 0.038) were independent predictors of T2DM remission.

In this real-world study, the remission rate of T2DM patients who visited the Diabetes Reversal Clinic for more than 24 weeks was 29.24% (50/171). Younger age, shorter disease duration, fewer baseline medications, lower FBG and HbA1c, higher HOMA-β, lower triglycerides, and greater weight loss were associated with remission of T2DM. Among them, age, baseline medication type, baseline FBG, and weight loss were identified as factors independently associated with remission. However, due to the single-arm observational design, causality cannot be established, and further prospective controlled trials are required to confirm these findings.