Search Results (976)

Semaglutide, a glucagon-like peptide-1 receptor agonist (GLP-1RA), has demonstrated substantial efficacy in managing type 2 diabetes mellitus (T2DM). It provides glycemic control, promotes weight loss, and offers cardiovascular protection. Evidence also supports its role in diabetic kidney disease (DKD), a leading global cause of end-stage renal disease. DKD arises from a multifactorial interaction involving hyperglycemia, hypertension, and inflammation, which leads to cumulative nephron loss. Beyond glycemic control, semaglutide’s mechanisms of action target metabolic and hemodynamic pathways that contribute to renal damage. This review evaluates the preclinical and clinical evidence of semaglutide’s role in preventing DKD, focusing on its renal effects and the mechanistic basis for renoprotection. We also position semaglutide within the broader DKD therapeutic landscape by reviewing clinical trial findings, translational studies, real-world evidence, and its effectiveness compared to other drug classes. The expanded actions of semaglutide make it a promising agent in patients with T2DM and DKD and encourage further mechanistic research and long-term evaluation. Full article

Background: Waste collection is a critical logistical challenge in urban management, and while Internet of Things (IoT) technologies are increasingly used to optimize collection routes, a systematic, quantitative synthesis of their impact is lacking. This study aims to bridge this gap by quantifying the effect of IoT-enabled routing optimization on waste collection distances. Methods: We conducted a systematic review and meta-analysis following the PRISMA protocol, searching the Scopus, IEEE Xplore, and ACM Digital Library databases. This process yielded 11 eligible studies, providing 21 distinct samples for quantitative synthesis. Results: The analysis reveals that IoT-enabled routing optimization reduces collection distance by a combined average of 21.51%. A significant disparity was found between study types, with simulation-based approaches reporting higher reductions (−39.79%) compared to real-world deployments (−12.37%). No statistically significant performance differences were observed across different routing algorithm categories or Vehicle Routing Problem (VRP) variants. Conclusions: These findings provide robust quantitative evidence of the significant efficiency gains from implementing IoT-based smart waste management systems. The gap between simulated and real-world results underscores the need for practitioners to set realistic expectations, while our analysis supports the adoption of these technologies for more sustainable urban logistics. Full article

There remains a persistent lack of patient-centered evidence on insurance reform and real-world experiences of patients with chronic disease. This study gathered insights around insurance design from chronic disease beneficiaries. This mixed-methods analysis comprised an online survey and virtual focus group sessions (August to December 2023) involving US residents with chronic disease and health insurance. Patients’ perspectives on insurance design were explored. Survey data were analyzed descriptively. Key themes were identified from focus group transcripts and direct observations. In total, 146 patients across 15 chronic diseases completed the survey; 29 then participated in focus groups. Although most beneficiaries were satisfied with their health plan, concerns centered on prescription medication affordability due to high deductibles and cost exposure, the disproportionate effects of cost exposure based on income, and the unpredictability of out-of-pocket costs. For some, the financial burden led to financial debt, therapy abandonment, mental health issues, and/or worsening of their condition. Overall, there was broad support for policy solutions to redesign insurance and adjust cost exposure for patients with chronic disease. This research offers valuable patient insights into health insurance design in the US to ensure patients’ needs are addressed. Full article

Background: Poor nutrition drives chronic disease, health disparities, and rising health care costs in the United States. Medically tailored meals (MTMs), designed by registered dietitians, are a Food-as-Medicine intervention with potential to improve outcomes and reduce costs. This review synthesizes evidence on the clinical, economic, and policy implications of MTMs. Methods: We conducted a narrative review of peer-reviewed studies, real-world program evaluations, and policy analyses. Sources included PubMed, Google Scholar, and grey literature from government, nonprofit, and industry organizations. Articles and reports were included if they examined MTMs in Medicare, Medicaid, or other high-risk populations. Results: Evidence demonstrates that MTMs improve health outcomes, reduce hospitalizations, and lower total cost of care. Case studies from Medicaid and Medicare Advantage plans, including those administered by Mom’s Meals^®, report reductions in emergency department visits, hospital readmissions, and total cost of care, alongside sustained high member satisfaction. Despite these findings, gaps in coverage and limited stakeholder awareness hinder broader access and adoption. Conclusions: Federal policy action can expand MTM availability and maximize utilization of existing benefits. Opportunities include establishing a Medicare Fee-for-Service demonstration, expanding and encouraging use in Medicare Advantage, and leveraging MTMs within Center for Medicare and Medicaid Innovation models. Broader implementation and utilization could reduce the nation’s chronic disease burden, advance health equity, and promote value-based care. Full article

Background: Hydrosalpinx is a major cause of female infertility, but the long-term outcomes of Palmer-type neosalpingostomy remain insufficiently documented. Methods: We retrospectively analyzed 160 women with primary or secondary infertility and laparoscopically confirmed hydrosalpinx who underwent Palmer-type neosalpingostomy at a single specialized center in Romania (2018–2024). Patients were enrolled consecutively, and disease severity was classified intraoperatively using standardized criteria. The primary outcome was clinical pregnancy; secondary outcomes included live birth, miscarriage, ectopic pregnancy, recurrence, and time to conception. Results: The clinical pregnancy rate was 33.8%, intrauterine/live birth rate 25.6%, miscarriage rate 3.8%, and ectopic pregnancy rate 4.4%. Recurrence occurred in 21.2% of cases. Outcomes were strongly influenced by hydrosalpinx severity and pelvic adhesions: women with mild disease achieved the highest pregnancy rates, whereas those with severe adhesions had poor prognosis. Neither age, AMH, nor laterality were independent predictors. Median time to pregnancy was 9 months. Conclusions: Palmer-type neosalpingostomy can achieve satisfactory reproductive outcomes in selected women, particularly those with mild hydrosalpinx and no adhesions. This study provides long-term real-world evidence from Eastern Europe, complementing international literature and emphasizing the importance of individualized patient selection. Full article

The spectral coexistence of LPWAN technologies, such as IEEE 802.11ah and LoRaWAN, in the sub-GHz band presents significant challenges for the performance of dense IoT networks. This study analyzes the impact of LoRaWAN interference on IEEE 802.11ah using an NS-3-based simulation environment. To this end, both technologies were integrated within a unified simulation framework, enabling the configuration of PHY and MAC parameters, as well as operating frequency bands consistent with real-world deployments in the US902–928 MHz ISM band and aligned with official standards. The evaluation focuses on fundamental performance metrics—throughput, total packet loss percentage (PPP), and signal-to-interference-plus-noise ratio (SINR)—under varying node densities and payload configurations. Across our sweep, moving from the lowest to the highest LoRa load (from 10 to 8000 LoRa nodes within the specified deployment radius), IEEE 802.11ah throughput decreases by up to 31%, and the packet loss percentage (PPP) increases by up to 79%. Furthermore, an SINR threshold was established as the criterion for packet loss under interference. Overall, this work provides a reproducible methodology for assessing inter-protocol coexistence in unlicensed sub-GHz bands, contributing quantitative evidence to the analysis and design of multi-protocol IoT networks in dense environments. Full article

Indoor Air Quality (IAQ) in educational environments is a critical determinant of students’ health, well-being, and learning performance, with inadequate ventilation and pollutant accumulation consistently associated with respiratory symptoms, fatigue, and impaired cognitive outcomes. Conventional monitoring approaches—based on periodic inspections or subjective perception—provide only fragmented insights and often underestimate exposure risks. Artificial intelligence (AI) offers a transformative framework to overcome these limitations through sensor calibration, anomaly detection, pollutant forecasting, and the adaptive control of ventilation systems. This review critically synthesizes the state of AI applications for IAQ management in educational environments, drawing on twenty real-world case studies from North America, Europe, Asia, and Oceania. The evidence highlights methodological innovations ranging from decision tree models integrated into large-scale sensor networks in Boston to hybrid deep learning architectures in New Zealand, and regression-based calibration techniques applied in Greece. Collectively, these studies demonstrate that AI can substantially improve predictive accuracy, reduce pollutant exposure, and enable proactive, data-driven ventilation management. At the same time, cross-case comparisons reveal systemic challenges—including sensor reliability and calibration drift, high installation and maintenance costs, limited interoperability with legacy building management systems, and enduring concerns over privacy and trust. Addressing these barriers will be essential for moving beyond localized pilots. The review concludes that AI holds transformative potential to shift school IAQ management from reactive practices toward continuous, adaptive, and health-oriented strategies. Realizing this potential will require transparent, equitable, and cost-effective deployment, positioning AI not only as a technological solution but also as a public health and educational priority. Full article

Background/Objectives: Type 2 diabetes and obesity present escalating global health and economic challenges, highlighting the need for therapies that can effectively manage glycemic levels and reduce excess adiposity. Semaglutide, a glucagon-like peptide-1 receptor (GLP-1R) agonist available in subcutaneous or oral formulation, has quickly evolved from a theoretical concept to a crucial component of modern metabolic care. This review explores the comprehensive development journey of semaglutide, drawing on evidence from medicinal chemistry, animal studies, initial human trials, the pivotal SUSTAIN and STEP programs, and real-world post-marketing surveillance. Methods: We conducted a detailed analysis of preclinical data sets, Phase I–III clinical trials, regulatory documents, and pharmaco-epidemiological studies published between 2008 and 2025. Results: Through strategic molecular modifications, such as specific amino-acid substitutions and the addition of a C18 fatty-diacid side chain to enhance albumin binding, the half-life of the peptide was extended to approximately 160 h, allowing for weekly dosing. Studies in rodents and non-human primates showed that semaglutide effectively lowered blood glucose levels, reduced body weight, and preserved β-cells while maintaining a favorable safety profile. Phase I trials confirmed consistent pharmacokinetics and tolerability, while Phase II trials identified 0.5 mg and 1.0 mg once weekly as the most effective doses. The extensive SUSTAIN program validated significant reductions in HbA1c levels and weight loss compared to other treatments, as well as a 26% decrease in the relative risk of major adverse cardiovascular events (SUSTAIN-6). Subsequent STEP trials expanded the use of semaglutide to chronic weight management, revealing that nearly two-thirds of patients experienced a body weight reduction of at least 15%. Regulatory approvals from the FDA, EMA, and other regulatory agencies were obtained between 2017 and 2021, with ongoing research focusing on metabolic dysfunction-associated steatohepatitis, cardiovascular events, and chronic kidney disease. Conclusions: The trajectory of semaglutide exemplifies how intentional peptide design, iterative translational research, and outcome-driven clinical trial design can lead to groundbreaking therapies for complex metabolic disorders. Full article

Background: Randomized controlled trials (RCTs) are the foundation of evidence-based medicine. However, the rapid pace of technological innovation in cardiovascular surgery and interventional cardiology challenges the traditional RCT framework. Observational studies may hold renewed value in fields where device evolution outpaces the time required to validate clinical outcomes. Methods: This analysis evaluates 270 randomized and non-randomized studies in transcatheter aortic valve implantation (TAVI), one of the most rapidly evolving areas in cardiovascular medicine. The investigation follows two lines: first, mapping the timeline of major RCTs against the introduction of new prosthetic models; second, comparing the prevalence, duration, and role of randomized (R) versus non-randomized (NR) studies. Results: The timeline reveals a persistent misalignment between innovation and validation. New prosthetic models frequently enter the market while RCTs for prior generations are still ongoing. For example, the Sapien 3 valve was approved, while trials on Sapien XT were still enrolling. Similarly, newer Evolut and Acurate models were introduced during ongoing studies of earlier versions, often prompting new studies before existing ones concluded. This leapfrogging effect fragments the evidence base and delays definitive comparisons. In parallel, randomized trials have increased in number and tend to be shorter in duration, reflecting a maturing field. However, non-randomized studies remain crucial for early testing and post-market surveillance. Conclusions: In a field with rapid technological evolution a sort of Zeno’s paradox occurs: long-term validation cannot keep pace with fast innovation, resetting the evidence base with each new model. To overcome this paradox, a paradigm shift in evidence generation is desirable. Future strategies must augment adaptive trial designs, leverage real-world data and use higher-level, advanced analyses to incorporate subjective variables and phenotypic diversity, to reduce confounding factors and speed up data access. Higher-level, integrative evidence analytics could help Achilles walk alongside the tortoise. Full article

Introduction: This study evaluates the real-world application of anifrolumab in managing articular involvement in systemic lupus erythematosus (SLE), providing insights into its efficacy and safety in routine clinical practice. Additionally, a systematic review examines anifrolumab’s role specifically in joint manifestations of SLE, consolidating existing real-world data on its therapeutic impact in articular disease. Methods: This monocentric case series presents data from four patients with SLE-related arthritis treated with anifrolumab. Clinical outcomes, including joint symptoms, clinimetric indices (DAS28, SLEDAI-2K, and SLICC), and treatment tolerability, were assessed. Ultrasound evaluation did not represent an outcome since it was not performed regularly. A systematic review was conducted to explore anifrolumab’s real-world application in articular disease manifestations, offering a comparative perspective. Results: All patients achieved complete remission of arthritis and lupus disease activity within four months, with no serious adverse reactions and without treatment discontinuation. Additionally, two patients completely discontinued corticosteroid (GC) therapy within two months, while the remaining two significantly reduced their GC doses. Only three promising relevant articles emerged from the systematic review, underlining the need for further studies to better support the role of anifrolumab in the treatment of arthritis in SLE. Conclusions: These findings highlight anifrolumab’s practical utility in real-world settings, particularly for articular involvement, while the systematic review contextualizes its impact within SLE management. The results underscore anifrolumab’s potential as a valuable treatment option for joint manifestations of SLE, addressing an unmet clinical need in routine practice. This evidence may assist clinicians in selecting the most suitable therapeutic approach based on predominant clinical features, thus enhancing personalized treatment strategies in SLE. Full article

Randomized clinical trials are considered the gold standard for the evaluation of new interventions and therapies. The results from randomized clinical trials are highly influential in treatment decision-making and decisions about the implementation of new therapeutic options within the field of oncology. This article describes a narrative review of the literature to further explore the strengths and limitations of real-world evidence in comparison to randomized clinical trials and provides a commentary on opportunities for real-world evidence in thoracic malignancies. However, randomized trials often exclude oncology patients with poorer functional status or comorbidities which are routinely considered for treatment in real-world practice. Real-world data may complement existing data from randomized clinical trials and play an important role in evaluating patterns and outcomes of care, informing everyday oncology practice. While real-world data is increasingly reported in the medical literature, strengths and limitations exist which can also limit their applicability. More work is needed to standardize methodologies for real-world studies. Full article

Background and Objectives: Evidence on epilepsy surgery from Central Asia is limited, reflecting the real-world challenges of developing this service in low- and middle-income settings. We evaluated one-year seizure outcomes after resective surgery for drug-resistant focal epilepsy at a single center in Kazakhstan, and we assessed whether the use of advanced presurgical imaging was associated with seizure freedom. Materials and Methods: A retrospective cohort study was conducted, including consecutive adults who underwent curative-intent resective epilepsy surgery from 2017 to 2023. Outcomes at 12 months or more post-surgery were classified using the Engel criteria. Logistic regression was used to examine associations between the advanced presurgical diagnostic tool and achieving an Engel class I outcome. Crude and adjusted risk ratios (RRs) for not achieving Engel I were estimated using modified Poisson regression with robust SEs. Results: Among 112 patients (median age 31 years; median epilepsy duration 19 years), 76% underwent temporal lobe procedures and 71% had lobectomies. At one year, 74 patients were seizure-free (Engel II: 15.2%, III: 11.6%, IV: 7.1%). Year-to-year Engel I rates varied without a significant linear trend from 2018 to 2023. In bivariable analyses, MRI-defined atrophy (RR, 3.14) and mixed lesions (RR, 2.62) were associated with a higher risk of not achieving Engel I, whereas longer epilepsy duration was linked to a lower risk (RR, 0.97 per year). In adjusted models, predictors of not achieving Engel I included generalized tonic–clonic seizures (aRR, 1.96), atrophy (aRR, 2.98), mixed lesions (aRR, 2.45), and undergoing any advanced diagnostic test (aRR, 3.38). Longer epilepsy durations remained protective (aRR 0.95 per year). In modality-specific logistic models, fMRI use was associated with higher odds of Engel I (aOR 3.39), and MR spectroscopy was associated with lower odds (aOR 0.33). Conclusions: In this Central Asian single-center cohort, about two-thirds of adults achieved complete seizure freedom one year after resective surgery—comparable to international benchmarks. Advanced imaging modalities showed divergent associations with outcomes, likely reflecting confounding by indication. These findings support the feasibility of effective epilepsy surgery in a low-resource context and the value of targeted use of advanced imaging. Full article

Background/Objectives: The aging global population has led to a rising prevalence of type 2 diabetes mellitus (T2DM), in which biomedical outcomes alone fail to capture patients’ lived experiences. Patient-Reported Outcome Measures (PROMs) can provide insights into psychological, psychosocial, and quality-of-life (QoL) dimensions, yet their use—particularly among older adults—remains inconsistent. This AI-assisted rapid review aimed to map how PROMs are currently applied in adults with T2DM, with specific attention to studies involving older populations, focusing on their role in assessing well-being, distress, depression, and treatment satisfaction, as well as their implementation in clinical and organizational practice. Methods: A rapid review was conducted using Elicit, an AI tool designed to support systematic evidence synthesis. Studies published between 2015 and 2025 were identified from Semantic Scholar, complemented by manual searches for recent or unindexed papers. Eligibility criteria required inclusion of adults with T2DM and use of validated PROMs in real-world settings. Studies explicitly describing older or elderly subgroups were highlighted separately. After screening 504 records, 167 studies were included. Data extraction covered study design, instruments used, populations, outcomes, and implementation details. Results: The most frequently assessed outcomes were diabetes distress, depression, QoL, treatment satisfaction, and self-efficacy. Common instruments included PAID, DDS, PHQ-9, WHO-5, EQ-5D, SF-36, DTSQ, and GDS. Evidence showed PROMs effectively identified high-risk patients and informed tailored interventions, but integration into routine care remained limited. Barriers included workflow disruption, lack of provider training, heterogeneity of tools, and insufficient cultural validation. Facilitators included brief instruments, digital administration, and linkage with care planning. Conclusions: PROMs are valuable in capturing psychosocial and psychological burdens in adults with T2DM, including but not limited to older populations, but routine implementation is inconsistent. Broader adoption will require digital infrastructure, clinician training, and organizational integration, as well as the development of PROMs that capture experiences with emerging diabetes technologies. Methodologically, this study illustrates the feasibility of AI-assisted rapid reviews to generate timely, evidence-informed syntheses. Full article

Background/Objectives: Evidence on the use of biologics in severe eosinophilic asthma (SEA) associated with persistent airflow obstruction (PAO) status and smoking habits is scarce. As these factors could potentially impact real-world benralizumab clinical effects, this study was conceived to provide a deeper understanding of these specific patient subgroups. Methods: This observational, retrospective ORBE II study (NCT04648839) involved 204 adults with uncontrolled SEA treated with benralizumab in Spain. In this analysis, patients were categorized by baseline PAO status (PAO− or PAO+) and smoking habit (SMK− or SMK+) to assess baseline characteristics and clinical outcomes after one year of follow-up. The impact of smoking on PAO+ patients was also analyzed. Results: This analysis showed that 75.6% of patients had PAO and 36.9% were former/current smokers. After benralizumab, both PAO subgroups showed substantial improvement, with higher proportions of PAO+ patients achieving prespecified clinical objectives. Benralizumab benefited patients regardless of their smoking habit, though patients who had never smoked exhibited slightly fewer exacerbations, greater improvements in ACT scores, and a higher proportion achieved a ≥100 mL increase in pre-BD FEV₁. An analysis of the impact of smoking on the PAO+ subgroup showed that while a similar proportion of patients were able to eliminate exacerbations and discontinue OCS use, higher percentages of PAO+SMK− patients achieved an ACT score ≥ 20 and a ≥100 mL increase in pre-BD FEV₁. Conclusions: PAO is common among patients included in ORBE II, and a considerable proportion are former/current smokers. This study showed that clinical outcomes improved after benralizumab initiation regardless of these factors, highlighting its potential as a valuable therapeutic option for managing SEA. These findings also emphasize the need for further real-world evidence to optimize treatment strategies for diverse patient subgroups. Full article

Background: Artificial intelligence technologies are increasingly integrated into dental practice, offering potential improvements in diagnostic accuracy, treatment planning, and patient outcomes. However, the extent and quality of evidence supporting these applications remain unclear. Methodology: We conducted a systematic literature search using PubMed, Cochrane Library, Embase, and IEEE Xplore databases from January 2015 to December 2024. Search terms included combinations of “artificial intelligence,” “machine learning,” “deep learning,” “dentistry,” “diagnosis,” and “treatment planning.” Studies evaluating AI systems in clinical or laboratory settings with measurable outcomes were included. Data extraction followed PRISMA guidelines, and methodological quality was assessed using the QUADAS-2 tool. Results: Twenty-three studies met the inclusion criteria. Most focused on diagnostic accuracy (n = 21), with few addressing treatment planning (n = 1) or outcome prediction (n = 1). Reported accuracies ranged from 82–94% for caries detection, 85–92% for periodontal disease assessment, and 88–96% for oral lesion identification. Orthodontic applications achieved 95–98% accuracy in cephalometric landmark identification, while implant planning studies demonstrated up to 96% agreement with expert strategies. Despite promising technical performance, 79% of studies were retrospective and conducted in controlled research settings, with limited external or prospective clinical validation. Risk of bias was highest in patient selection due to frequent use of case–control designs and archived imaging datasets. Conclusions: AI shows significant promise for enhancing dental diagnostics and treatment planning. However, most applications require further clinical validation before routine implementation. The disconnect between laboratory performance and real-world clinical validation represents a critical gap that must be addressed. Current AI systems should be viewed as diagnostic aids rather than replacements for clinical judgment. Practitioners considering AI adoption should understand current limitations and evidence quality, particularly the lack of prospective clinical validation in diverse populations. Full article