University of Jamestown

OBJECTIVE: To investigate the effectiveness of intervention strategies for primary and secondary prevention of knee osteoarthritis (OA). DESIGN: Intervention systematic review of randomized controlled trials (RCTs). DATA SOURCES: The Medline, EMBASE, CINAHL, PEDro, and The Cochrane Library databases were searched from inception to June 10, 2025. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: RCTs evaluating interventions for primary/secondary knee OA prevention. Eligible trials targeted populations at-risk of developing knee OA or population with knee OA, and the outcome of interest must not have been present at study entry. Primary outcomes were self-reported knee pain and associated disability. Secondary outcomes included imaging features of knee joint structure and the incidence of knee arthroplasty. Data were synthesized narratively and reported as relative risks (RRs) with 95% Confidence Intervals (CIs). RESULTS: Five published reports from three RCTs (1481 participants) were included. We found evidence that a self-management lifestyle program for community-based women with BMI ≥ 25 kg/m 2 may reduce the risk of developing pain associated with knee OA at 12-months, when compared to a single education session (RR: 0.27, 95%CI: 0.16-0.46). There was uncertain evidence from four reports to draw conclusions about the effects of diet & exercise, glucosamine supplements, diet & exercise plus glucosamine supplements, and intra-articular sprifermin interventions for preventing or reducing Knee OA progression or arthroplasty. CONCLUSION: A self-management lifestyle program may be effective for reducing the risk of developing pain associated with knee OA in women with a BMI ≥ 25 kg/m 2 . Evidence for other preventive interventions remains uncertain.

ABSTRACTBackground and AimsVarious anthropometric differences and co‐morbidities have been associated with disparities in postoperative outcomes following spinal surgery. Gender has been identified in previous studies as a potential factor influencing the prevalence of conditions like lumbar disc radiculopathy, degenerative disc disease, and cauda equina syndrome. Our study aimed to evaluate the effect of gender as a risk factor on the rate of perioperative and early postoperative complications after tubular microdiscectomy for lumbar disc prolapse.MethodsThis retrospective multicenter study, conducted in two specialized spine centers in Baghdad, Iraq, involved 302 patients with lumbar disc herniation (174 males and 128 females) from January 2016 to January 2022. Data collection included comprehensive assessments of clinical and surgical outcomes, utilizing the Core Outcome Measures Index (COMI) score at 2, 6, and 12 weeks.ResultsA total of 134 males (77%) and 104 females (81%) were below 40 years old, while 40 males (23% of males) and 24 females (18.8% of females) were 40 or older. There was a significant difference in mean operative times (p < 0.001). The most common specific complication was spondylodiscitis with six males (3.4% of males) and three females (2.3% of females), while the most common general complication was post‐op back spasm with six males (3.4% of males) and four females (3.1% of females). It's noteworthy to emphasize that our analysis showed a non‐significant association of gender with the presence of either specific or general complications (p > 0.05).ConclusionGender has a minimal impact on most perioperative and early postoperative complications. Longer operative times in females raise questions about gender‐specific differences across spine surgeries and specialties, necessitating further research. We also note a shift in the age profile for disc prolapse patients, emphasizing the need for additional research into contributing factors among younger populations.

ABSTRACTBackground and AimsTongue transplantation is emerging as a novel reconstructive option aimed at restoring critical functions—such as articulation, swallowing, and taste—in patients with extensive tongue defects due to squamous cell carcinoma or trauma. This systematic review and meta‐analysis synthesizes current clinical outcomes, challenges, and future directions in tongue transplantation.MethodsA comprehensive literature search was performed in PubMed, Google Scholar, Medline, Cochrane, Web of Science, and ScienceDirect from January 2000 to August 2020, using predefined Boolean combinations of keywords (e.g., “Tongue Transplant,” “Tongue Reconstructive Surgery”). Studies were screened and selected according to PRISMA guidelines. Six studies meeting strict inclusion criteria—providing detailed patient demographics, surgical techniques, and outcomes (totaling 51 patients)—were included. Data extraction and quality assessment were performed independently by three reviewers. Meta‐analysis was conducted using Review Manager 5.4 and Jamovi 2.4.1.0. Heterogeneity was assessed with the I² statistic; for I² values ≥ 50%, a random‐effects model was used. Statistical significance was defined as p < 0.05 (two‐sided tests), with effect sizes and 95% confidence intervals reported.ResultsAnalysis revealed substantial heterogeneity among studies (I² = 85%, p < 0.001). Overall, tongue transplantation was associated with improved functional outcomes—such as restoration of swallowing and partial recovery of taste sensation—with variable degrees of success. Detailed comparative analysis of surgical techniques, donor selection, and immunosuppressive protocols highlights both common benefits and notable challenges, including technical complexity and risks related to immunosuppression.ConclusionTongue transplantation shows promise in significantly improving quality of life in select patients; however, technical, immunological, and reinnervation challenges remain. Future research should focus on refining surgical protocols, exploring tissue engineering alternatives, and standardizing post‐transplant care to optimize long‐term outcomes.

ObjectiveHeart failure with preserved ejection fraction (HFpEF) is a growing clinical burden worldwide, yet diagnosis remains difficult due to phenotypic heterogeneity and the lack of a gold standard. Two algorithms—H2FPEF (Heavy, Hypertensive, Atrial Fibrillation, Pulmonary Hypertension, Elder, and Filling Pressure score) and the Heart Failure Association Pre-test Assessment, Echocardiography and Natriuretic Peptide, Functional Testing, Final Etiology (HFA-PEFF)—have been developed to aid diagnosis, but evidence indicates substantial discordance. Moreover, neither incorporates social determinants of health (SDoH), which may contribute to inequities.Materials and MethodsWe conducted a systematic review following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to identify studies comparing the H2FPEF and HFA-PEFF algorithms within the same patient cohorts. Searches were performed in PubMed, Embase, Scopus, and Web of Science. Eligible studies reported diagnostic discordance or comparative performance. Narrative synthesis was applied, and methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2).ResultsTen studies including 4,532 participants were reviewed. Discordance between algorithms ranged from 28% to 41%. H2FPEF demonstrated greater sensitivity, whereas HFA-PEFF showed higher specificity, but both achieved only moderate diagnostic accuracy. None of the studies incorporated SDoH variables, despite their established influence on heart failure diagnosis.ConclusionMarked diagnostic discordance exists between H2FPEF and HFA-PEFF, underscoring the limitations of current tools. Excluding SDoH risks perpetuating disparities in HFpEF recognition and care. Future diagnostic frameworks should integrate both clinical and social variables. Explainable artificial intelligence, particularly machine learning models trained on multimodal data that include SDoH, offers a promising avenue toward more equitable, data-driven diagnosis of HFpEF.

AimsUlotaront is an investigational trace amine‐associated receptor 1 (TAAR1) agonist demonstrated to slow gastric emptying in schizophrenia patients with metabolic syndrome (MetSyn) and prediabetes type 2. Here we evaluate the effects of ulotaront on glucose‐insulin dynamics in schizophrenia patients with MetSyn and prediabetes.Methods and MethodsNCT05463770 was a Phase 1b clinical trial, with an open‐label, multi‐dose design comparing ulotaront's metabolic effects to each participant's baseline of prior antipsychotic treatment. Oral glucose tolerance test (oGTT), a mixed meal tolerance test (MMTT) and a spirulina breath test (GEBT) were conducted at a baseline of prior antipsychotic medication and repeated after up to 3 weeks of twice‐a‐day dosing of ulotaront.ResultsIn oGTT and MMTT, mean changes from baseline AUCs for glucose, c‐peptide and insulin were −19.7 h×mg/dL, −269 h×pg/mL, −41.0 h×uIU/mL, and −10.8 h×mg/dL, −2860 h×pg/mL, −132 h×mg/dL, respectively. Insulin response during the MMTT reached nominal statistical significance (p = 0.021, effect size = −0.7). The mean change from baseline gastric emptying time was −0.60 min.ConclusionsDespite limited sample size, primary endpoints favoured ulotaront over prior antipsychotics with respect to a reduction trend in glucose, c‐peptide and insulin. The insulin response after a solid meal was nominally significant, suggesting that semi‐chronic twice‐a‐day dosing of ulotaront might improve insulin dynamics in schizophrenia patients at high diabetes risk.

BackgroundHeart failure is a complex clinical syndrome characterized by the molecular remodeling of myocardial tissue that significantly impacts global health outcomes. Transcriptomic analysis offers powerful tools to identify disease-specific gene expression signatures and potential therapeutic targets.MethodsWe analyzed publicly available gene expression data from the Gene Expression Omnibus (GEO) dataset GSE57345, comprising 313 left ventricular tissue samples (295 controls, 18 heart failure) profiled using Affymetrix Human Gene 1.1 ST Arrays (Thermo Fisher Scientific, Waltham, Massachusetts, United States). Differential expression analysis was performed using limma with Benjamini-Hochberg multiple testing correction.ResultsWe identified 401 significantly differentially expressed genes (adjusted p<0.05) between heart failure and control samples. The molecular signature showed balanced dysregulation with 198 genes upregulated and 203 genes downregulated in heart failure. Pathway analysis revealed significant enrichment in mitochondrial dysfunction, immune activation, and extracellular matrix remodeling pathways. Top dysregulated genes included AIDC1, SECA1, PVRL2, PLD1, and KTR3CL3, with high statistical significance (p<1×10⁻⁶) despite modest fold changes characteristic of complex disease pathophysiology. Cross-validation with established heart failure signatures showed significant overlap (31.7% concordance), confirming biological relevance.ConclusionsThis 401-gene transcriptomic signature provides insights into heart failure molecular mechanisms and represents a potential resource for biomarker development and therapeutic target identification. The balanced pattern of gene dysregulation reflects the comprehensive transcriptional remodeling underlying cardiac dysfunction and supports precision medicine approaches for heart failure diagnosis and treatment stratification.

BackgroundHeart failure (HF) is a leading cause of morbidity and hospitalization, encompassing distinct phenotypes: heart failure with preserved ejection fraction (HFpEF) and heart failure with reduced ejection fraction (HFrEF). Disparities in diagnostic imaging may contribute to underdiagnosis and unequal care. This study evaluates differences in combined diagnostic imaging utilization between HFpEF and HFrEF, focusing on social determinants of health (SDoH) and hospital region.MethodsWe conducted a retrospective cross-sectional study using the 2020 National Inpatient Sample (NIS). Adults (≥18 years) hospitalized with HF were identified using International Classification of Diseases, 10th revision (ICD-10) codes. The primary outcome was receipt of any diagnostic imaging (composite of echocardiography, cardiac magnetic resonance imaging (MRI), and cardiac catheterization). We examined associations between imaging and patient-level (race, income, education, insurance, employment) and hospital-level (region) factors using separate multivariable logistic regression models for HFpEF and HFrEF groups.ResultsAmong 6.47 million weighted HF admissions, 6.95% were HFpEF and 6.55% were HFrEF. Combined diagnostic imaging utilization was low overall (1.72%). After adjustment, Black patients had lower odds of HFpEF diagnosis (adjusted odds ratio (aOR) 0.83, 95% confidence interval (CI): 0.83-0.84) but higher odds for HFrEF (aOR 1.24, 95% CI: 1.23-1.25) than White patients. Cardiac catheterization was strongly associated with both phenotypes (HFpEF, aOR 3.68, 95% CI: 3.62-3.73; HFrEF, aOR 6.23; 95% CI: 6.14-6.32; all p<0.001). Income, education, employment, and hospital region were all significant predictors of imaging disparities.ConclusionMarked disparities in diagnostic imaging exist for both HF phenotypes, driven by race, socioeconomic status, and geography. Despite the clinical importance of imaging, underutilization persists, particularly among minoritized and disadvantaged populations, exacerbated by structural barriers. Implementing targeted interventions to address diagnostic access is essential for equitable HF care.

Background: Parkinson’s Disease (PD) is characterized by motor and non-motor symptoms that can overlap with other movement disorders, complicating accurate diagnosis and monitoring. Wearable technologies, such as smartwatches, offer continuous and objective assessment of motor function, but their clinical utility in multiclass classification and symptom prediction remains underexplored. This study aimed to determine whether smartwatch-derived motor features can distinguish idiopathic PD from other movement disorders and whether motor variability is associated with non-motor symptom burden in PD. Methods: We analyzed data from the Parkinson’s Disease Smartwatch (PADS) dataset ( N = 469), which includes accelerometer and gyroscope signals recorded during 20 standardized motor tasks. For each participant, mean and standard deviation values for each axis were averaged across tasks. Diagnostic group classification was assessed using multinomial logistic regression. Among individuals with idiopathic PD ( n = 276), linear regression evaluated associations between motor variability and total non-motor symptom scores from a 30-item questionnaire. Results: Motor variability features, particularly accelerometer Y-axis and gyroscope X-axis standard deviations, significantly differentiated diagnostic groups (pseudo R 2 = 0.068). Age, sex, and handedness also contributed. In the PD subgroup, higher accelerometer X and gyroscope X variability were associated with greater non-motor symptom burden, while greater stability in the mediolateral (Y) axis was linked to fewer symptoms (adjusted R 2 = 0.0081, p &lt; 0.001). Conclusion: Smartwatch-derived motor variability features can modestly differentiate movement disorder diagnoses and are associated with non-motor symptom severity in PD. Our findings support the complementary use of wearable sensors in clinical assessment and remote monitoring. Our findings also lay the foundation for future integration of wearable-derived data into telemedicine workflows.

6032 Background: Advanced head and neck squamous cell carcinoma (HNSCC) exhibits variable responses to immunotherapy, highlighting the need to understand its complex molecular landscape. While immune checkpoint inhibitors show promise, optimizing treatment and predicting outcomes requires deeper molecular insights. Here, we leverage the cBioPortal for Cancer Genomics, analyzing ~800 HNSCC genomic and transcriptomic profiles, to investigate the molecular landscape influencing immunotherapy response in advanced disease. Methods: In this retrospective study, we analyzed publicly available data from 825 HNSCC patients treated with immunotherapy, enrolled in participating institutions between 2017 and 2022, sourced from the cBioPortal for Cancer Genomics. We investigated the frequency of most common mutations, copy number alterations, and mRNA expression levels, along with clinicopathological factors and overall survival (OS). Results: Genomic analysis of 809 HNSCC samples revealed TP53 as the most frequently mutated gene (63.5%, 514/809), followed by TTN (37.4%), FRG1BP (20.7%), FAT1 (19.3%), and CDKN2A (19.0%). Other genes were mutated at frequencies between 18.7% and 15.2%. Copy number alterations analysis (n=673) showed frequent homozygous deletions in 9p21.3, affecting CDKN2A-AS1 (30.3%, 158/673) and CDKN2A (26.0%, 175/673), and amplifications in 11q13.3, including PPFIA1 (25.7%), FADD (25.3%), CTTN (25.1%), and ANO1 (25.1%). Notably, TP53 mutations and CDKN2A-AS1 deletions were associated with inferior OS (log-rank P &lt; 0.001; mOS mutated vs wild-type 45.93 vs 156.37 months and P = 0.006; mOS altered vs non-altered 35.45 vs 65.77 months, respectively). Transcriptomic and GSEA profiling linked these alterations to dysregulation of oncogenic pathways, including DNA replication stress, p21 activation, apoptosis, and immune evasion. Conclusions: This study of immunotherapy-treated advanced HNSCC provides a valuable resource for understanding the complex genomic landscape of this disease. We identified frequent mutations and copy number alterations which were associated with inferior OS and linked to dysregulation of key oncogenic pathways. These findings underscore the potential of this to facilitate biomarker discovery and the development of personalized medicine approaches to improve outcomes in advanced HNSCC.