Focal entrapment of the Common Peroneal (Fibular) nerve (CPN) is the most frequent lower-extremity nerve entrapment yet it can be difficult to diagnose clinically. The Phoenix Sign-an increase in extensor hallucis longus (EHL) motor strength following lidocaine injection-may assist diagnosis. Additional observed effects include improved arterial perfusion and Doppler waveforms.

In this double-blinded, randomized small pilot study, only four patients (N = 4) with diabetic peripheral neuropathy underwent bilateral peripheral nerve blocks with lidocaine or papaverine. The first leg to be tested was randomized; the contralateral leg received a different agent that was randomized initially. Pre- and post-block assessments included motor strength, Doppler velocity of dorsalis pedis and posterior tibial arteries, and near-infrared spectroscopy for microvascular perfusion.

All patients demonstrated increased EHL motor strength after injection with either agent. Doppler waveforms of the dorsalis pedis artery improved: lidocaine produced a 151.7% increase in blood flow velocity (p = 0.03), whereas papaverine produced a 16.8% increase (p = 0.19). Posterior tibial artery flow increased by 37.4% with lidocaine (p = 0.06) and 13.9% with papaverine (p = 0.33), but neither was statistically significant. No changes in oxygen saturation, oxyhemoglobin, deoxyhemoglobin, or total hemoglobin were observed using near-infrared spectroscopy. The consistency of motor responses across subjects supports the validity of the Phoenix Sign as a diagnostic tool.

Peripheral nerve blocks with lidocaine or papaverine improved motor strength and macrovascular function in patients with diabetic peripheral neuropathy, though microvascular changes were not detected. These preliminary findings are consistent with the Phoenix Sign phenomenon and support further study as a potential clinical indicator. While these preliminary findings indicate support as a diagnostic tool, they are preliminary and hypothesis-generating for evaluating the Phoenix Sign as a potential clinical indicator of CPN entrapment and highlight the need for larger studies to evaluate vascular responses.

NCT06919289 (retrospectively registered 8 April 2025).

Background: There is a positive relationship between mitochondrial damage in the cell and uptake in technetium Tc 99m monomer methoxy isobutyl isonitrile (^99mTc-MIBI) scintigraphy. Severe mitochondrial dysfunction with cell death occurs in patients with diabetic foot ulcers (DFUs). To decide on the level of amputation, ^99mTc-MIBI scintigraphy should be considered. Methods: Prospectively, 24 patients with DFUs were included in the study. Based on treatment that started with the hospitalization, patients were divided into two groups: those whose DFUs healed and did not need surgical intervention (healed group) and those whose DFUs did not regress despite surgical and medical treatment and who required further surgical intervention (reoperation group). Before surgery, ^99mTc-MIBI scintigraphy was performed. The ^99mTc-MIBI uptake rates of the injured foot relative to the healthy foot were recorded. Deep-tissue culture was taken at surgery. Erythrocyte sedimentation rate, white blood cell count, and C-reactive protein (CRP) and albumin levels were measured. Results: The ^99mTc-MIBI uptake rates of patients with poor prognosis were higher at all times than those of patients who did not require revision surgery. A significant difference was found between these values in the 10 and 30 s rates. The mean ± SD CRP level was 86.04 ± 21.87 mg/dL in the healed group and 144.43 ± 27.54 mg/dL in the reoperation group (p = 0.040). There was a positive correlation between ulcerated foot and healthy foot ^99mTc-MIBI involvement rates at 10 and 30 s and CRP values, and a negative correlation between albumin values. Conclusions: There was a significant relationship between ^99mTc-MIBI involvement rates and poor prognosis and reamputation. The correlation between CRP and albumin levels, which are among the predictive values, and ^99mTc-MIBI uptake confirmed this relationship in DFUs, which are difficult to manage and treat.

The Therapeutic Shoe Benefit (TSB) allows Medicare insurance beneficiaries to reduce their diabetic foot ulcer risk by providing offloading shoes. Anecdotal evidence suggests that the process is cumbersome and that not all providers are aware of this benefit. This study evaluated TSB awareness across multiple healthcare disciplines and documented barriers to utilization. An online study surveyed healthcare providers practicing in the United States to determine familiarity with TSB and barriers to prescribing therapeutic shoes. The project was IRB-reviewed and received exempt status. The survey was sent to a wide variety of healthcare practitioners including: podiatrists, primary care providers, physical therapists, orthotist/prosthetists, specialty providers, and diabetes educators. This was done through targeted emails from professional organizations, word-of-mouth messaging through private practice groups, and marketing on LinkedIn. The survey was administered via Qualtrics with embedded branching logic used to gather data from the TSB's three classifications of healthcare specialists: certifying physicians, prescribing practitioners, and suppliers. A total of 580 valid completions of the survey were analyzed. Irrespective of the TSB, podiatric physicians and medical professionals providing direct patient care recommend supportive shoes for patients with diabetes 98.2% (336/342) of the time. When asked about knowledge of the TSB, 522 or 90% of respondents indicated awareness of this Medicare benefit. Knowledge by specialty was hard to differentiate due to low responses by some specialties; however, prescribing podiatrists and prosthetic providers both responded with a familiarity rate above 92%. Common obstacles to providers prescribing shoes were: complexity of documentation (67.8%), challenges communicating with other providers (55.0%), and financial reasons/labor-to-reimbursement ratio (38.4%). TSB has the potential to reduce amputations and wound care costs. However, therapeutic shoes are underutilized with less than 20% of potential beneficiaries accessing this benefit. This research strengthens the argument that streamlining the process may increase access to therapeutic shoes.

Background: Effective communication with patients is vital for improving health outcomes in chronic disease management. In this study, we investigated WoundScribeAI's Scribe AI, also known as Ambient Technology, and its patient education and engagement app, Pingoo.AI. It employed a multi-agent AI model that leveraged Large Language Models (LLMs) and NotebookLM to enhance patient communication in clinical settings. Methods: The system comprised specialized agents that transcribed healthcare provider-patient conversations through ambient dictation. This transcription generated medical notes that followed the Subjective, Objective, Assessment, and Plan (SOAP) format-a structured document used by healthcare providers to record and communicate information about patient encounters. Simultaneously, comprehensive visit summaries were also created. In the next step, these visit summaries were used to produce conversational and educational content by leveraging NotebookLM, an AI model introduced by Google that can generate podcast-style conversations from provided information. Integrating these agents allows clinicians to deliver engaging, empathetic, and actionable information to patients. Medical experts conducted a two-phase evaluation of the system's performance based on multiple criteria, with a particular focus on diabetes education and diabetic foot care. The first phase used pre-recorded training videos, while the second phase involved simulated consultations by clinicians using the system. To validate the AI-generated educational content, we used several established frameworks in health communication that closely align with our enhancement goals. Results: The results showed that the AI model generated accurate clinical documentation and met the criteria for accurate SOAP Notes, visit summaries, and engaging educational content for patients. Given that hallucination is a significant concern related to large language models, especially in critical fields like healthcare, we meticulously analyzed the generated outputs to identify any signs of hallucinated information. Three outcomes successfully passed the validation criteria, including accuracy, completeness, comprehensiveness, absence of potential harm, and no hallucination. Additionally, the Conversational Education content was confirmed against established patient education frameworks and met criteria such as the use of metaphors, empathetic tone, and appropriate language, providing additional detail to help manage the condition. Conclusions: By providing specific instructions and prompts to NotebookLM to transform visit summaries into educational conversations, we significantly enhanced the comprehensiveness and engagement of the content for patients. In contrast to a traditional summary of the clinical visit, the podcast-style conversation enriched the content with background information, encouraging language, an empathetic tone, and helpful metaphors. Our analysis confirmed that the system did not exhibit any hallucinations, highlighting the effectiveness of our approach in mitigating this risk. These findings support the use of multi-agent AI models, combined with ambient dictation and tools like NotebookLM, to improve patient communication that surpasses traditional paper-based brochures, which are often impersonal, minimal, and do not always adhere to recommended factors for health literacy.

Missing data is common in observational studies, and even more so in type 2 diabetes mellitus with mild cognitive impairment(T2DM-MCI), which limits the completion of assessments. We evaluated the extent, current reporting, and handling of missing data, as well as the prevailing research trends in observational studies related to T2DM-MCI.

A systematic search of PubMed, Embase, and Cochrane Library was conducted from January 2020 to April 2025 to identify observational studies related to T2DM-MCI. Bibliometrics was performed using VOSviewer and CiteSpace to evaluate publishing trends, authors, journals, and keywords. The reporting and handling of missing data were assessed according to the guidelines recommended by STROBE and Sterne et al., with a focus on the recording, causes, mechanisms, processing methods, and sensitivity analysis of missing data. Data analysis was conducted using SPSS 26, and visualization was performed using Origin Pro 2024.

Among the 4,471 screened records, 88 studies (78 in English and 10 in Chinese) were included in this analysis. Among the 78 English articles, the annual publication volume exhibited fluctuations, peaking in 2024. Chinese institutions and authors led in research output. Diabetes, Metabolic Syndrome, and Obesity had the highest publication volume (7, 8.97%). Keyword identified five clusters: 1) resting-state functional magnetic resonance imaging, 2) metabolic disorders, 3) clinical assessment tools, 4) molecular mechanisms, and 5) emerging fields such as the gut microbiome.

Only 22.7% (n = 20) of the studies quantified the missing data, with an average of 9.1%. Among studies with missing data (n = 23), 52.2% (n = 12) provided reasons for missing data, primarily citing poor quality of data collection (41.7%) and loss to follow-up (41.7%). Complete case analysis was the predominant method for addressing missing data (93.3%). No study articulated the hypothesized mechanisms underlying the missing data, and only 4.4% (n = 1) performed a sensitivity analysis.

In the domain of T2DM-MCI, research outcomes post-COVID-19 pandemic indicate a rebound, with China maintaining a leading position in scientific research output. However, the reporting of missing data remains ambiguous, and the methods employed to handle such data are insufficient, which may potentially introduce bias.

https://doi.org/10.17605/OSF.IO/EZDXM.

Recent studies have identified ATRX/DAXX and PDX1/ARX as biomarkers defining novel pancreatic neuroendocrine tumor (PanNET) subtypes, while the clinical significance of somatostatin receptors (SSTRs) remains incompletely understood.

We retrospectively analyzed 58 surgically resected primary PanNET samples and performed immunohistochemical evaluation of ATRX, DAXX, ARX/PDX1, and SSTR2a/5. The primary goal was to assess associations between biomarker expression and clinicopathological parameters. Secondary analyses explored relationships with recurrence-free survival (RFS), cancer-specific survival (CSS), and overall survival (OS). Quantitative expression scores were calculated, receiver operating characteristic (ROC) curve analysis was performed, and survival outcomes were assessed using Kaplan-Meier analysis.

The loss of DAXX or ATRX expression (86.3%) was more commonly observed in nonfunctional PanNETs cases compared to the functional PanNET group (13.7%) (p = 0.02). SSTR5 positive tumors were associated with longer median OS (73 vs. 7 months, p < 0.001) and RFS (36 vs. 6 months, p = 0.005). However, the difference in OS was not confirmed by Kaplan-Meier analysis (log-rank p = 0.078). In PanNETs ≥ 2 cm, a tumor size cutoff of 2.45 cm predicted ATRX/DAXX mutations with 96.9% sensitivity and 75% specificity (AUC 0.922, p = 0.007), in a cohort of 36 patients.

ATRX/DAXX loss was more prevalent in nonfunctional PanNETs (p = 0.02). Although SSTR5-positive tumors were associated with longer median OS, this difference was not confirmed by Kaplan-Meier analysis. Furthermore, tumor size demonstrates predictive value for ATRX/DAXX loss in PanNETs ≥2 cm, highlighting the relationship between tumor morphology and molecular alterations, however, this finding remains hypothesis-generating and requires further validation.

The roles of insulin resistance (IR) and β-cell dysfunction in diabetic retinopathy (DR) remain controversial, and whether age at type 2 diabetes mellitus (T2DM) onset modifies these associations is unclear. This study aimed to evaluate the associations of HOMA-IR and HOMA-β with DR risk, stratified by age at diagnosis.

In this real-world cross-sectional study, we analyzed data from 6,996 patients with T2DM from Lishui People's Hospital, China. Participants were categorized by age at onset (<65 vs. ≥65 years) and HOMA indices (HOMA-β <66 vs. ≥66; HOMA-IR <5 vs. ≥5). Multivariable logistic regression was used to assess adjusted odds ratios (aORs) for DR.

A total of 1,360 DR cases were identified in 6996 participants. Low HOMA-β was significantly associated with higher DR odds, especially in the younger-onset group (aOR = 2.97, 95% CI: 2.24-3.99). High HOMA-IR was associated with increased DR odds in younger-onset participants (aOR = 3.14, 95% CI: 2.31-4.33). Notably, among participants with high HOMA-β or low HOMA-IR, age at T2DM onset did not significantly modify the association with DR. Subgroup analyses showed strong associations in those with renal dysfunction or not using lipid-lowering agents.

Both β-cell dysfunction and insulin resistance were independently associated with increased odds of diabetic retinopathy in younger-onset type 2 diabetes. Age at onset significantly modified these associations, supporting age-stratified screening and tailored management strategies.

Complications of type 2 diabetes are a primary cause of public health challenges in the field of diabetes. The emergence of metabolomics and proteomics provides a direct perspective for revealing the mechanisms of metabolic diseases. Our research aims to explore the relationship between omics components and complications, as well as their clinical predictive performance.

This prospective study utilized data from the UK Biobank, including over 1,400 proteins and more than 280 metabolites, to analyze outcomes such as type 2 diabetes, microvascular complications, macrovascular complications, neurological complications, kidney complications, retinal complications, cardiovascular complications, peripheral vascular complications, metabolic disorder complications, and all-cause mortality. A total of 50,021 participants without type 2 diabetes were included in the analysis. The baseline time frame spanned from 2006 to 2010, with an average follow-up duration of 12.0 to 12.03 years. Researchers used LASSO Cox and LightGBM to search for new markers of complications, and employed SHAP methods to explain the contributions of these markers within the machine learning models. Subsequently, a comprehensive prediction model was established to reveal the potential of new markers for the early diagnosis of complications under nonlinear patterns, utilizing nine specific machine learning methods (CatBoost, LightGBM, Random Forest, XGBoost, logistic regression, multi-layer perceptron, single-layer neural network, Naive Bayes, and support vector machine).

GDF15 alone is more accurate than blood glucose and HbA1c in reflecting future kidney complications, especially in differentiating those who develop the disease within the next five years (GDF15 AUC=0.94, blood glucose AUC=0.68, HbA1c AUC=0.85). Within the framework of the comprehensive prediction model, the GDF15 model improved the accuracy of early screening for kidney complications compared with models constructed using traditional indicators (5-year Max AUC=0.92, 10-year Max AUC=0.88). In conclusion, both machine learning and statistical methods support the correlation between GDF15 and kidney complications, reflecting its robustness.

The results highlight the association of GDF15 during the early asymptomatic stage of various complications, especially kidney complications, revealing the potential role of GDF15 at the molecular pathological level during disease progression. In distinguishing participants who developed complications after the baseline period, the comprehensive GDF15 model provides a method for the early warning of various complications, particularly kidney complications.

Type 2 diabetes mellitus (T2DM) with comorbid hypertension increases risks of vascular complications, necessitating optimized therapies. This study evaluated whether dapagliflozin combined with linagliptin improves time in range (TIR) and hepatorenal function compared to monotherapy in this population.

In this prospective observational cohort study at Danzhou People's Hospital (June 2021-September 2024), 136 patients aged 40-70 years with T2DM (HbA1c 7.5-11.0%) and hypertension were allocated to four groups (n=34 each): standard care (control), dapagliflozin (10 mg/day), linagliptin (5 mg/day), or combination therapy. Outcomes after 12 weeks included TIR via continuous glucose monitoring, blood pressure, lipids, hepatic (ALT, AST, liver-to-spleen ratio via CT), and renal parameters (UACR, eGFR). Data were analyzed using ANOVA, correlations, and regression.

Combination therapy achieved superior TIR (94.86 ± 3.65% vs. ~80% in monotherapies and 81.44% in control; P<0.001), with greater reductions in HbA1c (to 5.52%), fasting glucose, blood pressure (systolic to 124 mmHg), lipids (triglycerides to 0.72 mmol/L), liver enzymes (ALT to 9.74 U/L), and UACR (to 7.36 mg/g), plus higher eGFR (to 122.41 mL/min/1.73m²; all P<0.05 vs. others). TIR correlated with improved hepatorenal markers; combination therapy predicted greatest TIR change (β=7.896, P<0.001).

Dapagliflozin-linagliptin combination offers superior glycemic stability and organ protection, supporting its use for managing T2DM with hypertension.

Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are associated with increased heart rate (HR) and reduced heart rate variability (HRV) in patients with type 2 diabetes mellitus (T2DM). While sodium-glucose co-transporter 2 inhibitors (SGLT2i) may exert beneficial effects on cardiac autonomic function, it remains uncertain whether baseline SGLT2i use is associated with attenuation of GLP-1 RA-related HRV decline in T2DM.

In this prospective observational study, 45 patients with T2DM were divided into two groups according to pre-study dapagliflozin use: a dapagliflozin-naïve group (Control group, n=22) and a dapagliflozin-exposed group (DAPA group, n=23). All participants subsequently received GLP-1 RA therapy for 12 weeks. Changes in HRV parameters were assessed by 24-hour ambulatory electrocardiography before and after treatment. Between-group differences were further evaluated using analysis of covariance (ANCOVA), inverse probability of treatment weighting (IPTW), and multivariable linear regression models.

After 12 weeks of GLP-1 RA therapy, the Control group showed significant reductions in SDNN, SDANN, RMSSD, pNN50, and lnHF, together with increases in lnLF and the lnLF/lnHF ratio, whereas no significant within-group changes in HRV indices were observed in the DAPA group. In unadjusted between-group analyses, several HRV parameters differed significantly between groups. After covariate adjustment, significant between-group differences remained for SDNN, SDANN, lnHF, and the lnLF/lnHF ratio. IPTW-weighted sensitivity analyses yielded consistent findings. In multivariable regression, baseline dapagliflozin use was most clearly associated with a more favorable change in SDNN.

In patients with T2DM, dapagliflozin use was associated with a decline in HRV during GLP-1 RA therapy; these findings are hypothesis-generating and require confirmation in larger prospective studies.