Apical hypertrophic cardiomyopathy (ApHCM), also known as Yamaguchi syndrome, is an uncommon variant of hypertrophic cardiomyopathy that may mimic acute coronary syndromes because of its characteristic electrocardiographic abnormalities. We report the case of a 66-year-old man with hypertension, type 2 diabetes mellitus, and active tobacco use who presented with recurrent exertional chest pain and giant symmetric T-wave inversion in leads V2-V6, producing a Wellens-like electrocardiographic pattern that mimicked Wellens syndrome and initially raised suspicion for critical proximal left anterior descending (LAD) artery disease. Coronary angiography demonstrated no significant obstructive coronary artery disease. Transthoracic echocardiography subsequently revealed localized apical hypertrophy with a maximal wall thickness of 14 mm and the characteristic spade-shaped left ventricular cavity, establishing the diagnosis of ApHCM. Treatment with bisoprolol, telmisartan, and atorvastatin resulted in complete symptom resolution, and the patient remained asymptomatic during follow-up. This case highlights the importance of considering ApHCM in the differential diagnosis of patients presenting with giant T-wave inversion and suspected acute coronary syndrome, as recognition of its characteristic electrocardiographic and echocardiographic features can facilitate an accurate diagnosis and help avoid misinterpreting Wellens-like electrocardiographic patterns as true Wellens syndrome.

Background Surgical aortic valve replacement (SAVR) remains the standard treatment for many patients with severe aortic valve disease. Implantation of a small prosthetic valve may result in prosthesis-patient mismatch (PPM), which adversely affects postoperative valve hemodynamics and long-term outcomes. Aortic root enlargement (ARE) has been proposed as a technique to facilitate the implantation of larger prosthetic valves; however, evidence from Indian populations remains limited. Methodology This prospective, observational study was conducted at Nizam's Institute of Medical Sciences, Hyderabad, over one year (2024-2025). A total of 40 patients undergoing AVR were included, of whom 22 underwent aortic valve replacement (AVR) alone, and 18 underwent AVR with ARE. Data were collected retrospectively and prospectively. Inclusion criteria comprised patients with moderate/severe symptomatic aortic stenosis or chronic severe aortic regurgitation undergoing elective SAVR. Exclusion criteria included active infection, prior prosthetic valves, or significant surgical risks. Data on demographics, preoperative variables, intraoperative details, and postoperative outcomes were collected using structured formats. Effective orifice area index was calculated to grade PPM severity. Statistical analysis included t-tests, chi-square test, Mann-Whitney U test, Kaplan-Meier survival, and logistic regression, with significance set at p-values <0.05. Results The median age of study subjects (n = 40) was 65.1 years (interquartile range = 53.2-71.3), with a female predominance (55%). Common comorbidities were hypertension (22/40, 55%), dyslipidemia (19/40, 47.5%), and diabetes mellitus (9/40, 22.5%). Preoperatively, 26 (65%) patients were categorized as New York Heart Association class III. Aortic stenosis (13/40, 32.5%) and mixed lesions (24/40, 60%) were the main pathologies. The mean implanted valve size was smaller in the ARE group than in the AVR group (21.2 mm vs. 23.5 mm; t(38) = 2.05, p = 0.047). Cardiopulmonary bypass (CPB) and aortic cross-clamp times were significantly longer in the ARE group (CPB: U = 107, p < 0.05; cross-clamp: t(38) = -2.07, p < 0.05). Postoperative mortality was comparable between groups (2/40, 5%; χ²(1) = 0.021, p = 0.884). The ARE group had a longer postoperative length of stay (median = 13 vs. 8 days; U = 80, p < 0.001). PPM occurred less frequently after ARE (χ²(3) = 9.045, p = 0.028); 26 patients (65%) had no PPM, and severe PPM was observed only in the AVR group. Kaplan-Meier analysis showed no difference in survival between groups over six months. Acute kidney injury was strongly associated with mortality (χ²(1) = 25.97, p = 0.004). Logistic regression identified female gender and lower effective orifice area as significant predictors for undergoing ARE. Conclusions This study highlights that ARE during AVR appears to be a safe adjunct procedure with comparable operative mortality or major complications in short-term follow-up. It effectively reduces the risk of PPM and allows implantation of larger prosthetic valves, which is particularly relevant in populations with smaller annuli. Although associated with longer operative and recovery times, ARE provides hemodynamic benefits without compromising short-term survival. These findings support the selective use of ARE in patients at risk for PPM to optimize surgical outcomes.

There is a synergistic and dysbiotic dental plaque microbial community with a keystone pathogen, Porphyromonas gingivalis, initiating the disruption of tissue homeostasis. The pathogenic organisms of periodontitis have been found to interact with other commensal species, such as fungi, of which Candida albicans has been found in the subgingival area, adding a new dimension to periodontal pathogenesis. Periodontitis and Candida infections are common complications seen in immunocompromised patients such as diabetics.

This study aimed to detect the presence and distribution of Candida from the dorsum of the tongue and subgingival area among healthy controls without periodontitis, patients with diabetes and chronic periodontitis with good or poor glycemic control, and patients without diabetes with chronic periodontitis, and to compare the presence of Candida in both sites. This study also aimed to establish an association between Candida albicans, probing depth, and glycemic control.

This was a cross-sectional observational study. It was conducted on 167 patients, and they were divided into four groups, which were as follows: Group A, healthy controls; Group B, individuals without diabetes and with chronic periodontitis; Group C, individuals with diabetes and chronic periodontitis with good glycemic control; and Group D, individuals with diabetes and chronic periodontitis with poor glycemic control. The sample was collected from the dorsum of the tongue with a sterile cotton swab, and subgingival samples were obtained using a Gracey curette in sterile capped containers with phosphate-buffered saline (PBS) and transported to the microbiology department for yeast identification using Sabouraud dextrose agar (SDA) and CHROMagar.

The prevalence of Candida albicans on the dorsum of the tongue was 93.1%, and it was statistically significant. (p=0.001), whereas in subgingival plaque it was found to be 62.1%, which was statistically non-significant (p=0.06). The most commonly found Candida was Candida albicans (53.2%). The other non-albicans species found were Candida glabrata (22.9%) and Candida tropicalis (23.9%). The highest percentage on the dorsum of the tongue and subgingival plaque was found in diabetic patients with chronic periodontitis with poor glycoregulation (88.1% and 76.2%, respectively). There was a statistically significant association between species abundance and probing depth (p=0.001). A greater number of medium and dense species were found in sites with probing depth > 6 mm. The mean HbA1c with respect to dense species was 9.6±0.7. There was a statistically significant correlation (p=0.002) found between high HbA1c levels and dense candidal species.

Out of the two sampling sites, Candida albicans was found more on the dorsum of the tongue. As this was a cross-sectional study, only an association could be established between Candida, probing depth, and glycemic control. More longitudinal studies are required to determine Candida as the causal organism for the progression of periodontitis and thereby provide antifungal-targeted approaches as a protocol in the future.

Type 1 diabetes (T1D) is a chronic metabolic disease mediated by autoimmunity. Its pathogenesis involves complex interactions between genetic susceptibility and environmental factors. Conventional T1D risk stratification primarily relies on genetic markers, islet autoantibodies, and glycemic indicators. Although these biomarkers remain indispensable in current clinical practice, they are often insufficient when used alone to accurately identify ultra-early high-risk individuals, predict disease progression rates, or support individualized preventive strategies. Consequently, more comprehensive molecular approaches are needed to improve precision risk stratification. In recent years, the rapid development of multi-omics technologies has provided new strategies for precise risk stratification of T1D. This narrative review critically evaluates how multi-omics integration strategies can improve precision risk stratification throughout the T1D disease continuum by integrating complementary molecular information from genomics, transcriptomics, proteomics, metabolomics, epigenomics, and the microbiome. Particular emphasis is placed on stage-specific biomarker discovery, multi-omics data integration frameworks, artificial intelligence-assisted prediction models, biomarker validation, and the opportunities and challenges associated with clinical translation. Current evidence suggests that integrated multi-omics approaches have the potential to improve risk prediction accuracy, distinguish heterogeneous disease trajectories, identify individuals at imminent risk of progression, and provide biologically informed targets for precision intervention. However, important challenges remain, including data harmonization, external validation, model interpretability, cost-effectiveness, and integration into routine clinical screening programs. Future research should prioritize prospective multicenter cohorts, standardized analytical pipelines, externally validated prediction models, and clinically interpretable multi-omics frameworks to facilitate the translation of precision risk stratification into routine T1D prevention and management.

Medication-related osteonecrosis of the jaw (MRONJ) is a debilitating condition characterized by a progressive necrosis of jaw bone in patients who have received anti-resorptive or anti-angiogenic medications. The purpose of this study was to analyze the scientometric characteristics and research trends of MRONJ.

All the papers on MRONJ were comprehensively retrieved from the Scopus database.

Among all the 2857 papers on MRONJ, 2251 (78.8 %) were published by stomatologists. The most common medications that cause MRONJ were diphosphonates, zoledronic acid, and denosumab. The MRONJ-related diseases were multiple myeloma, breast cancer, prostate cancer, bone metastasis, diabetes mellitus, and rheumatoid arthritis. Treatment strategies including debridement, antibiotic therapy, conservative treatment, hyperbaric oxygen therapy, low level laser therapy, and platelet-rich fibrin application. A good medical history with emphasis on the use of medication that cause MRONJ, detailed clinical and radiographic evaluations excluding jaw metastasis cancer and osteoradionecrosis, and attention to the patient's signs and symptoms are critical for the correct diagnosis and appropriate treatment. Herein, we also highlight the awareness of early recognition and timely diagnosis and improve the access to care for MRONJ.

This scientometric study elucidated the current scenario and research trends of MRONJ, and proposed that multidisciplinary comprehensive management should be conducted to achieve optimal outcomes.

Diabetes has become a major global public health challenge. Increasing pressure on healthcare systems and shorter hospital stays highlight the importance of effective discharge planning in enhancing post-discharge self-management and continuity of care for people with diabetes.

This scoping review aimed to map existing discharge planning practices that support continuity of care for people with diabetes and to inform the optimization of intervention programs in clinical practice.

The review was conducted according to the Joanna Briggs Institute (JBI) methodology and reported in accordance with the PRISMA-ScR guidelines. Eligible studies included randomized controlled trials and quasi-experimental studies investigating discharge planning services for adults with type 1 diabetes, type 2 diabetes, or gestational diabetes during the hospital-to-home transition. English and Chinese databases (PubMed, CINAHL, Embase, Web of Science, CNKI, Wanfang, VIP, and SinoMed) were systematically searched for studies published between January 2020 and June 2025. Study selection and data extraction were independently performed by two reviewers. The included studies were synthesized using descriptive and thematic analyses, and methodological quality was assessed using the Cochrane Risk of Bias 2 tool for randomized controlled trials and the JBI critical appraisal checklist for quasi-experimental studies.

A total of 20 studies met the inclusion criteria. Most studies involved adults with type 2 diabetes or mixed populations of adults with type 1 and type 2 diabetes. Technology-enabled components were incorporated into several interventions, whereas explicit theoretical or conceptual foundations were reported in only a subset of studies. Intervention timing varied across studies, with some interventions initiated during hospitalization and continued into the post-discharge period. Delivery approaches included in-person, digital, and hybrid formats. Core components included patient assessment, diabetes education, lifestyle guidance, medication and glucose management, complication prevention, and psychological support. Reported outcomes primarily included HbA1c, self-management-related outcomes, quality of life, and discharge readiness. Outcome assessments were commonly conducted at discharge, whereas post-discharge follow-up assessments were often performed approximately 3 months after discharge.

Discharge planning services for patients with diabetes during the hospital-to-home transition were commonly described as multicomponent interventions intended to support continuity of care. However, variations in delivery formats, outcome measures, follow-up periods, evaluation methods, and reporting quality highlight the need for further research with clearer intervention descriptions, consistent outcome measures, process evaluations, stakeholder perspectives, and longer-term outcome assessments. Future initiatives should prioritize continuous and adaptable discharge planning service models that are feasible, acceptable, and responsive to the needs of individuals with diabetes across different care contexts.

https://archive.org/details/osf-registrations-3bnyq-v1, identifier doi: 10.17605/OSF.IO/3BNYQ.

To explore the influencing factors of catheter blockage in patients with implantable venous access ports (IVAP) and to construct a risk prediction model.

A total of 563 patients who underwent IVAP implantation from January 2022 to March 2024 were retrospectively enrolled and randomly divided into a modeling group (n = 394) and a validation group (n = 169) at a 7∶3 ratio. Univariate analysis and multivariate logistic regression (bidirectional stepwise regression) were used to identify independent influencing factors for catheter blockage. A nomogram prediction model was then constructed and evaluated in terms of discrimination, calibration, and clinical utility.

The incidence of catheter blockage was 12.79% (72/563). Multivariate Logistic regression showed that body mass index (BMI) ≥ 24 kg/m² (OR = 3.535, 95%CI: 1.500-8.329), diabetes mellitus (OR = 3.723, 95%CI: 1.540-8.999), malignancy (OR = 3.161, 95%CI: 1.327-7.526), history of thrombosis (OR = 3.324, 95%CI: 1.425-7.755), elevated D-dimer (OR = 547.088, 95%CI: 46.093-649.462), and catheter retention time ≥ 6 months (OR = 2.633, 95%CI: 1.060-6.543) were independent risk factors, while regular maintenance (OR = 0.200, 95%CI: 0.080-0.499) was an independent protective factor (all P<0.05). The area under the receiver operating characteristic curve (AUC) of the nomogram model was 0.91 (95%CI: 0.87-0.96) in the modeling group and 0.94 (95%CI: 0.88-1.00) in the validation group. The Hosmer-Lemeshow test showed good calibration for both the modeling group (χ² = 10.782, P = 0.214) and the validation group (χ² = 3.744, P = 0.879). Decision curve analysis indicated a positive net clinical benefit.

The IVAP catheter blockage risk prediction model constructed in this study demonstrates good predictive performance and clinical utility. It can assist healthcare providers in early identification of high-risk patients and implementation of individualized preventive interventions, thereby reducing the incidence of catheter blockage.

Background Glycated hemoglobin (HbA1c) is widely used as a marker of glycemic control and has been associated with cardiovascular disease (CVD); however, whether HbA1c is independently associated with prevalent CVD after accounting for traditional cardiometabolic risk factors remains uncertain. Methodology We conducted a cross-sectional analysis of 30,804 U.S. adults aged ≥18 years from the National Health and Nutrition Examination Survey (NHANES). Cardiovascular outcomes (coronary artery disease (CAD), myocardial infarction, and stroke) were defined using self-reported physician diagnoses. Associations between HbA1c and cardiovascular outcomes were evaluated using sequential logistic regression models with adjustment for demographic, metabolic, socioeconomic, and diabetes-related variables. Results Higher HbA1c levels were associated with increased odds of cardiovascular outcomes in unadjusted analyses. These associations were attenuated after adjustment for age and sex and were no longer statistically significant in fully adjusted models. Diabetes duration demonstrated a strong age-dependent gradient and contributed to attenuation of HbA1c effects. In stratified analyses, HbA1c was not significantly associated with outcomes in either individuals with diabetes or those without diabetes. Interaction analyses showed no consistent effect modification, except for a potential interaction between HbA1c and diabetes status for CAD. Conclusions The observed associations between HbA1c and prevalent cardiovascular outcomes were attenuated after adjustment for demographic, metabolic, socioeconomic, and diabetes-related variables. Because some adjustment variables may lie on the causal pathway, these findings should be interpreted cautiously and as observational associations rather than evidence of causality.

To evaluate the association between an individualized exercise management program based on shared decision-making (SDM) and short-term glycemic control, self-care behaviors, and quality of life in patients with type 2 diabetes mellitus (T2DM).

This retrospective cohort study used data from electronic medical records and a diabetes management platform (January 2019 - December 2023). After propensity score matching (1:1 nearest-neighbor, caliper = 0.02 SD), 178 patients were included (89 in SDM-based intervention group, 89 in routine care control group). The intervention group received an SDM-driven personalized exercise program plus routine care, while controls received routine care alone. Outcomes included HbA1c, fasting plasma glucose (FPG), 2 h postprandial glucose (2hPG), time in range (TIR), mean amplitude of glycemic excursions (MAGE), 6-meter walking speed, medication adherence, Summary of Diabetes Self-Care Activities (SDSCA) score, and Diabetes-Specific Quality of Life (DSQL) score. Assessments were performed at baseline, 1 month, and 2 months.

At 1 and 2 months, the intervention group showed significantly greater reductions in HbA1c, FPG, 2hPG, and MAGE, and a significantly greater increase in TIR compared to controls (all p < 0.05). At 2 months, TIR was higher (67.72 ± 15.52% vs. 61.65 ± 23.12%, p = 0.004) and MAGE lower (5.35 ± 2.02 vs. 6.22 ± 1.86, p = 0.027) in the intervention group. The 6-meter walking speed also improved more in the intervention group (1.05 ± 0.11 vs. 0.98 ± 0.12 m/s, p = 0.003). Medication adherence across five domains (medication, diet, glucose monitoring, aerobic exercise, daily routine) was significantly better in the intervention group (all p < 0.05). The intervention group had significantly higher SDSCA scores and lower DSQL scores at 2 months (both p < 0.001), indicating enhanced self-management and improved quality of life.

An individualized exercise management program based on the SDM model was associated with improved short-term glycemic control, treatment adherence, self-management behaviors, and quality of life in T2DM patients. Future prospective randomized studies with longer follow-up are needed to establish causality and determine the sustainability of these improvements.

To systematically evaluate frailty risk prediction models for older patients with diabetes in China, providing a reference for healthcare professionals in selecting or developing appropriate frailty risk prediction models for older patients with diabetes and offering evidence for the formulation of intervention strategies.

A systematic search was conducted in PubMed, the Cochrane Library, Medline, Embase, Web of Science, China Biomedical Literature Database, China National Knowledge Infrastructure (CNKI), VIP Database, and Wanfang Database for studies related to frailty risk prediction models for older patients with diabetes. The search period covered from database inception to November 15, 2025. Data extraction and quality assessment were independently performed by two researchers using the Prediction Model Risk of Bias Assessment Tool (PROBAST) and a data extraction form.

A total of 14 studies involving 25 models were included, with outcome event incidence rates ranging from 10.1% to 51.2%. The area under the receiver operating characteristic curve (AUC) of the models ranged from 0.703 to 0.975. All 14 studies showed good overall applicability but exhibited a high risk of bias. High-frequency predictors included age, polypharmacy, nutritional status, glycated hemoglobin, and ADL score.

Frailty risk prediction models for older patients with diabetes in China demonstrate good discriminative ability and applicability, but have significant methodological flaws and a high risk of bias. Future studies should strictly follow reporting guidelines for risk prediction models to develop and evaluate frailty risk prediction models for older patients with diabetes in China, and validate their feasibility in clinical practice to provide high-quality evidence for clinical decision-making.