Search Results (8,711)

This study evaluates the risk-adjusted performance of Hospitality REITs using multi-factor asset pricing models and downside risk measures with the aim of assessing their diversification potential and crisis sensitivity. Unlike prior studies that examine REITs in aggregate, this study isolates Hospitality REITs to explore their unique cyclical and macroeconomic sensitivities. This study looks at the risk-adjusted performance of Hospitality Real Estate Investment Trusts (REITs) in relation to more general REIT indexes and the S&P 500 Index. The study reveals that monthly returns of Hospitality REITs increasingly move in tandem with the stock markets during financial crises, which reduces their historical function as portfolio diversifiers. Investing in Hospitality REITs exposes one to the hospitality sector; however, these investments carry notable risks and provide little protection, particularly during economic upheavals. Furthermore, the study reveals that Hospitality REITs underperform on a risk-adjusted basis relative to benchmark indexes. The monthly returns of REITs show significant volatility during the post-COVID-19 era, which causes return-to-risk ratios to be below those of benchmark indexes. Estimates from multi-factor models indicate negative alpha values across conditional models, indicating that macroeconomic variables cause unremunerated risks. This industry shows great sensitivity to market beta and size and value determinants. Hospitality REITs’ susceptibility comes from their showing the most possibility for exceptional losses across asset classes under Value at Risk (VaR) and Conditional Value at Risk (CvaR) downside risk assessments. The findings have implications for investors and portfolio managers, suggesting that Hospitality REITs may not offer consistent diversification benefits during downturns but can serve a tactical role in procyclical investment strategies. Full article

Preserving historical porous materials requires careful monitoring of surface humidity to mitigate deterioration processes like salt crystallization, mold growth, and material decay. While microclimate monitoring is a recognized preventive conservation tool, its role in detecting surface-specific moisture risks remains underexplored. This study evaluates the relationship between indoor microclimate fluctuations and surface moisture dynamics across 13 historical sites in Northern Italy (Lake Como, Valtellina, Valposchiavo), encompassing diverse masonry typologies and environmental conditions. High-resolution sensors recorded temperature and relative humidity for a minimum of 13 months, and eight indicators—including dew point depression, critical temperature–humidity zones, and damp effect indices—were analyzed to assess the moisture risks. The results demonstrate that multivariate microclimate data could effectively predict humidity accumulation. The key findings reveal the impact of seasonal ventilation, thermal inertia, and localized air stagnation on moisture distribution, with unheated alpine sites showing the highest condensation risk. The study highlights the need for integrated monitoring approaches, combining dew point analysis, mixing ratio stability, and buffering performance, to enable early risk detection and targeted conservation strategies. These insights bridge the gap between environmental monitoring and surface moisture diagnostics in porous heritage materials. Full article

This study presents a simulation-based damage modeling and fatigue risk assessment of a reusable ceramic matrix composite thruster designed for short-duration, green bipropellant propulsion systems. The thruster is constructed from a fiber-reinforced ultra-high temperature ceramic matrix composite composed of zirconium diboride, silicon carbide, and carbon fibers. Time-resolved thermal and structural simulations are conducted on a validated thruster geometry to characterize the severity of early-stage thermal shock, stress buildup, and potential degradation pathways. Unlike traditional fatigue studies that rely on empirical fatigue constants or Paris-law-based crack-growth models, this work introduces a simulation-derived stress-margin envelope methodology that incorporates ±20% variability in temperature-dependent material strength, offering a physically grounded yet conservative risk estimate. From this, a normalized risk index is derived to evaluate the likelihood of damage initiation in critical regions over the 0–10 s firing window. The results indicate that the convergent throat region experiences a peak thermal gradient rate of approximately 380 K/s, with the normalized thermal shock index exceeding 43. Stress margins in this region collapse by 2.3 s, while margin loss in the flange curvature appears near 8 s. These findings are mapped into green, yellow, and red risk bands to classify operational safety zones. All the results assume no active cooling, representing conservative operating limits. If regenerative or ablative cooling is implemented, these margins would improve significantly. The framework established here enables a transparent, reproducible methodology for evaluating lifetime safety in ceramic propulsion nozzles and serves as a foundational tool for fatigue-resilient component design in green space engines. Full article

Background/Objectives: Melanoma is an aggressive type of skin cancer that poses serious health risks if not detected in its early stages. Although early diagnosis enables effective treatment, delays can result in life-threatening consequences. Traditional diagnostic processes predominantly rely on the subjective expertise of dermatologists, which can lead to variability and time inefficiencies. Consequently, there is an increasing demand for automated systems that can accurately classify melanoma lesions and retrieve visually similar cases to support clinical decision-making. Methods: This study proposes a transfer learning (TL)-based deep learning (DL) framework for the classification of melanoma images and the enhancement of content-based image retrieval (CBIR) systems. Pre-trained models including DenseNet121, InceptionV3, Vision Transformer (ViT), and Xception were employed to extract deep feature representations. These features were integrated using a weighted fusion strategy and classified through an Ensemble learning approach designed to capitalize on the complementary strengths of the individual models. The performance of the proposed system was evaluated using classification accuracy and mean Average Precision (mAP) metrics. Results: Experimental evaluations demonstrated that the proposed Ensemble model significantly outperformed each standalone model in both classification and retrieval tasks. The Ensemble approach achieved a classification accuracy of 95.25%. In the CBIR task, the system attained a mean Average Precision (mAP) score of 0.9538, indicating high retrieval effectiveness. The performance gains were attributed to the synergistic integration of features from diverse model architectures through the ensemble and fusion strategies. Conclusions: The findings underscore the effectiveness of TL-based DL models in automating melanoma image classification and enhancing CBIR systems. The integration of deep features from multiple pre-trained models using an Ensemble approach not only improved accuracy but also demonstrated robustness in feature generalization. This approach holds promise for integration into clinical workflows, offering improved diagnostic accuracy and efficiency in the early detection of melanoma. Full article

Introduction: Congestive heart failure (CHF), a complex clinical syndrome characterized by the heart’s inability to pump blood effectively due to structural or functional impairments, is a growing public health concern, with profound implications for patients’ physical and emotional well-being. In India, the burden of CHF is rising due to aging demographics and increasing prevalence of lifestyle-related risk factors. Among the subtypes of CHF, heart failure with preserved ejection fraction (HFpEF), i.e., heart failure with left ventricular ejection fraction of ≥50% with evidence of spontaneous or provokable increased left ventricular filling pressure, and heart failure with reduced ejection fraction (HFrEF), i.e., heart failure with left ventricular ejection fraction of 40% or less and is accompanied by progressive left ventricular dilatation and adverse cardiac remodeling, may present differing impacts on health-related quality of life (HRQoL), i.e., an individual’s or a group’s perceived physical and mental health over time, yet comparative data remains limited. This study assesses HRQoL among CHF patients using the Minnesota Living with Heart Failure Questionnaire (MLHFQ), one of the most widely used health-related quality of life questionnaires for patients with heart failure based on physical and emotional dimensions and identifies sociodemographic and clinical variables influencing these outcomes. Methods: A cross-sectional analytical study was conducted among 233 CHF patients receiving inpatient and outpatient care at the Department of Cardiology at a quaternary care teaching hospital in coastal Karnataka in India. Participants were enrolled using convenience sampling. HRQoL was evaluated through the MLHFQ, while sociodemographic and clinical characteristics were recorded via a structured proforma. Statistical analyses included descriptive measures, independent t-test, Spearman’s correlation and stepwise multivariable linear regression to identify associations and predictors. Results: The mean HRQoL score was 56.5 ± 6.05, reflecting a moderate to high symptom burden. Patients with HFpEF reported significantly worse HRQoL (mean score: 61.4 ± 3.94) than those with HFrEF (52.9 ± 4.64; p < 0.001, Cohen’s d = 1.95). A significant positive correlation was observed between HRQoL scores and age (r = 0.428; p < 0.001), indicating that older individuals experienced a higher burden of symptoms. HRQoL also varied significantly across NYHA functional classes (χ² = 69.9, p < 0.001, ε² = 0.301) and employment groups (χ² = 17.0, p < 0.001), with further differences noted by education level, gender and marital status (p < 0.05). Multivariable linear regression identified age (B = 0.311, p < 0.001) and gender (B = –4.591, p < 0.001) as significant predictors of poorer HRQoL. Discussion: The findings indicate that patients with HFpEF experience significantly poorer HRQoL than those with HFrEF. Older adults and female patients reported greater symptom burden, underscoring the importance of demographic-sensitive care approaches. These results highlight the need for routine integration of HRQoL assessment into clinical practice and the development of comprehensive, personalized interventions addressing both physical and emotional health dimensions, especially for vulnerable subgroups. Conclusions: CHF patients, especially those with HFpEF, face reduced HRQoL. Key factors include age, gender, education, employment, marital status, and NYHA class, underscoring the need for patient-centered care. Full article

Noncommunicable diseases (NCDs) like diabetes and cancer drive demand for therapeutic functional foods. This study developed freeze-dried fermented camel milk (FCM) with Ajwa date pulp (ADP), evaluating its physical and functional properties, probiotic survival, and potential benefits for diabetes and cancer. To achieve this target, six FCM formulations were prepared using ABT-5 starter culture (containing Lactobacillus acidophilus, Bifidobacterium bifidum, and Streptococcus thermophilus) with or without Lacticaseibacillus rhamnosus B-1937 and ADP (12% or 15%). The samples were freeze-dried, and their functional properties, such as water activity, dispersibility, water absorption capacity, water absorption index, water solubility index, insolubility index, and sedimentation, were assessed. Reconstitution properties such as density, flowability, air content, porosity, loose bulk density, packed bulk density, particle density, carrier index, Hausner ratio, porosity, and density were examined. In addition, color and probiotic survivability under simulated gastrointestinal conditions were analyzed. Also, antidiabetic potential was assessed via α-amylase and α-glucosidase inhibition assays, while cytotoxicity was evaluated using the MTT assay on Caco-2 cells. The results show that ADP supplementation significantly improved dispersibility (up to 72.73% in FCM15D+L). These improvements are attributed to changes in particle size distribution and increased carbohydrate and mineral content, which facilitate powder rehydration and reduce clumping. All FCM variants demonstrated low water activity (0.196–0.226), indicating good potential for shelf stability. The reconstitution properties revealed that FCM powders with ADP had higher bulk and packed densities but lower particle density and porosity than controls. Including ADP reduced interstitial air and increased occluded air within the powders, which may minimize oxidation risks and improve packaging efficiency. ADP incorporation resulted in a significant decrease in lightness (L*) and increases in redness (a*) and yellowness (b*), with greater pigment and phenolic content at higher ADP levels. These changes reflect the natural colorants and browning reactions associated with ADP, leading to a more intense and visually distinct product. Probiotic survivability was higher in ADP-fortified samples, with L. acidophilus and B. bifidum showing resilience in intestinal conditions. The FCM15D+L formulation exhibited potent antidiabetic effects, with IC₅₀ values of 111.43 μg mL⁻¹ for α-amylase and 77.21 μg mL⁻¹ for α-glucosidase activities, though lower than control FCM (8.37 and 10.74 μg mL⁻¹, respectively). Cytotoxicity against Caco-2 cells was most potent in non-ADP samples (IC₅₀: 82.22 μg mL⁻¹ for FCM), suggesting ADP and L. rhamnosus may reduce antiproliferative effects due to proteolytic activity. In conclusion, the study demonstrates that ADP-enriched FCM is a promising functional food with enhanced probiotic viability, antidiabetic potential, and desirable physical properties. This work highlights the potential of camel milk and date synergies in combating some NCDs in vitro, suggesting potential for functional food application. Full article

Existing risk assessment approaches for soft rock tunnels in fault-fractured zones typically employ single weighting schemes, inadequately integrate subjective and objective weights, and fail to define clear risk. This study proposes a risk-grading methodology that integrates an enhanced game theoretic weight-balancing algorithm with an optimized cloud entropy extension cloud model. Initially, a comprehensive indicator system encompassing geological (surrounding rock grade, groundwater conditions, fault thickness, dip, and strike), design (excavation cross-section shape, excavation span, and tunnel cross-sectional area), and support (initial support stiffness, support installation timing, and construction step length) parameters is established. Subjective weights obtained via the analytic hierarchy process (AHP) are combined with objective weights calculated using the entropy, coefficient of variation, and CRITIC methods and subsequently balanced through a game theoretic approach to mitigate bias and reconcile expert judgment with data objectivity. Subsequently, the optimized cloud entropy extension cloud algorithm quantifies the fuzzy relationships between indicators and risk levels, yielding a cloud association evaluation matrix for precise classification. A case study of a representative soft rock tunnel in a fault-fractured zone validates this method’s enhanced accuracy, stability, and rationality, offering a robust tool for risk management and design decision making in complex geological settings. Full article

Background: Taste changes are common during pregnancy and can have a significant impact on dietary habits. Objective: This study aimed to investigate the influence of the perception of sweet and fat taste on diet in pregnant diabetic women. Methods: This cross-sectional observational study included 66 pregnant women, 33 with gestational diabetes and 33 with pre-gestational type 2 diabetes. Taste perception tests were conducted to evaluate thresholds for detecting sweet and fatty tastes. Dietary surveys were used to assess daily nutrient intake, and various biochemical parameters, such as glycemia, HbA1c, and cholesterol, were analyzed. Results: The low-fat taster group (threshold > 0.75 mmol/L) included more patients with diabetes compared to those with gestational diabetes. All diabetic patients had low sucrose perception. Although pregnant women with gestational diabetes detected sweetness at high concentrations, pregnant women with diabetes detected it at lower concentrations (0.012 ± 0.023 mmol/L vs. 0.006 ± 0.005 mmol/L; p = 0.3). High-fat tasters exhibited elevated glycemia compared to low-fat tasters (6.04 ± 1.88 mmol/L vs. 7.47 ± 3.4 mmol/L; p = 0.03). They also had higher cholesterol (p = 0.04) and lower HDL-C levels (4.96 ± 1.04 mmol/L vs. 1.36 ± 0.29 mmol/L; p = 0.03). High-fat tasters showed more frequent daily consumption of oil, butter, cheese, and chocolate. The highly sweet tasters had higher cholesterol levels and lower LDL levels. Individuals who reported being highly sensitive to sweet taste consumed more daily oil, sweetened yogurt, or cream desserts, as well as white sugar. Conclusions: These findings indicate that altered sensitivity to fat and sweet tastes is associated with different dietary habits and metabolic profiles in pregnant women with diabetes. Specifically, reduced sensitivity to the taste of fat is associated with higher consumption of high-fat foods and poorer lipid profiles. In contrast, sensitivity to sweet taste correlates with an increased intake of sugary and fatty foods. Understanding these taste-related behaviors can help develop personalized nutritional strategies to improve metabolic control and maternal–fetal outcomes in this high-risk group. Full article

Background/Objectives: Affecting close to one-third of the global population, metabolic dysfunction-associated steatotic liver disease (MASLD) is a highly prevalent chronic liver disorder linked to metabolic risk factors such as obesity and insulin resistance. Liver fibrosis is a key determinant of prognosis, and its progression increases the risk of liver-related and overall mortality. This exploratory research evaluated the potential impact of a 3-month intervention involving dietary counseling and liraglutide therapy on liver fibrosis and related metabolic markers in patients with MASLD and obesity without diabetes. Methods: In this prospective, single-arm exploratory intervention, 28 adult patients with MASLD and obesity received structured dietary counseling and daily subcutaneous liraglutide for 12 weeks. Liver fibrosis was assessed using non-invasive indices (FIB-4, APRI, BARD, ELF) and transient elastography performed with the FibroScan^® device (Echosens, Paris, France). Results: After 3 months, a significant reduction in liver stiffness (−7.14%, p < 0.05) and ELF score (from 6.71 to 6.63; −1.2%, p < 0.05) was observed. APRI (p = 0.06) and FIB-4 (p = 0.09) showed trends toward improvement, while the BARD score and AST/ALT ratio remained unchanged. Conclusions: Short-term liraglutide therapy combined with lifestyle modification may improve early-stage liver fibrosis in patients with MASLD and obesity, as indicated by reductions in liver stiffness and ELF score. These preliminary findings highlight the potential of advanced non-invasive fibrosis markers in monitoring treatment response. However, as an exploratory study, results should be interpreted with caution, and larger, long-term trials are needed to confirm these observations and evaluate efficacy in patients with more advanced fibrosis stages. Full article

Introduction: Breast density is a well-recognized factor in breast cancer risk assessment, with higher density linked to increased malignancy risk and reduced sensitivity of conventional mammography. Background parenchymal enhancement (BPE), observed in contrast-enhanced imaging, reflects physiological contrast uptake in non-pathologic breast tissue. While extensively characterized in breast MRI, the role of BPE in contrast-enhanced mammography (CEM) remains uncertain due to inconsistent findings regarding its correlation with breast density and cancer risk. Unlike breast density—standardized through the ACR BI-RADS lexicon—BPE lacks a uniform classification system in CEM, leading to variability in clinical interpretation and research outcomes. To address this gap, we introduce the BPE-CEM Standard Scale (BCSS), a structured four-tiered classification system specifically tailored to the two-dimensional characteristics of CEM, aiming to improve consistency and diagnostic alignment in BPE evaluation. Materials and Methods: In this retrospective single-center study, 213 patients who underwent mammography (MG), ultrasound (US), and contrast-enhanced mammography (CEM) between May 2022 and June 2023 at the “A. Perrino” Hospital in Brindisi were included. Breast density was classified according to ACR BI-RADS (categories A–D). BPE was categorized into four levels: Minimal (< 10% enhancement), Light (10–25%), Moderate (25–50%), and Marked (> 50%). Three radiologists independently assessed BPE in a subset of 50 randomly selected cases to evaluate inter-observer agreement using Cohen’s kappa. Correlations between BPE, breast density, and age were examined through regression analysis. Results: BPE was Minimal in 57% of patients, Light in 31%, Moderate in 10%, and Marked in 2%. A significant positive association was found between higher breast density (BI-RADS C–D) and increased BPE (p < 0.05), whereas lower-density breasts (A–B) were predominantly associated with minimal or light BPE. Regression analysis confirmed a modest but statistically significant association between breast density and BPE (R² = 0.144), while age showed no significant effect. Inter-observer agreement for BPE categorization using the BCSS was excellent (κ = 0.85; 95% CI: 0.78–0.92), supporting its reproducibility. Conclusions: Our findings indicate that breast density is a key determinant of BPE in CEM. The proposed BCSS offers a reproducible, four-level framework for standardized BPE assessment tailored to the imaging characteristics of CEM. By reducing variability in interpretation, the BCSS has the potential to improve diagnostic consistency and facilitate integration of BPE into personalized breast cancer risk models. Further prospective multicenter studies are needed to validate this classification and assess its clinical impact. Full article

Background and Objectives: Heart failure (HF) and chronic kidney disease (CKD) frequently coexist and are closely interrelated, significantly affecting clinical outcomes. Among CKD-related markers, albuminuria and estimated glomerular filtration rate (eGFR) have emerged as key prognostic indicators in HF. However, their specific predictive value across different HF phenotypes—namely HF with preserved ejection fraction (HFpEF) and HF with reduced ejection fraction (HFrEF)—remains incompletely understood. This systematic review aims to evaluate the prognostic significance of albuminuria and eGFR in patients with HF and to compare their predictive roles in HFpEF versus HFrEF populations. Materials and Methods: We conducted a systematic search of major databases to identify clinical studies evaluating the association between albuminuria, eGFR, and adverse outcomes in HF patients. Inclusion criteria encompassed studies reporting on cardiovascular events, all-cause mortality, or HF-related hospitalizations, with subgroup analyses based on ejection fraction. Data extraction and quality assessment were performed independently by two reviewers. Results: Twenty-one studies met the inclusion criteria, including diverse HF populations and various biomarker assessment methods. Both albuminuria and reduced eGFR were consistently associated with increased risk of mortality and hospitalization. In HFrEF populations, reduced eGFR demonstrated stronger prognostic associations, whereas albuminuria was predictive across both HF phenotypes. Heterogeneity in study design and outcome definitions limited comparability. Conclusions: Albuminuria and eGFR are valuable prognostic biomarkers in HF and may enhance risk stratification and clinical decision-making, particularly when integrated into clinical assessment models. Differential prognostic implications in HFpEF versus HFrEF highlight the need for phenotype-specific approaches. Further research is warranted to validate these findings and clarify their role in guiding personalized therapeutic strategies in HF populations. Limitations: The current evidence base consists primarily of observational studies with variable methodological quality and inconsistent reporting of effect estimates. Full article

Clonal hematopoiesis of intermediate potential (CHIP) is the presence of a clonally expanded hematopoietic stem cell because of a mutation in individuals without evidence of hematologic malignancy, dysplasia, or cytopenia. Interestingly, CHIP is associated with a two-fold increase in cardiovascular risk, independently of traditional risk factors. Recent studies using deep-targeted sequencing have revealed that CHIP mutations, primarily TET2 and DNMT3A, present a higher incidence in patients with AF compared to healthy controls. Moreover, the presence of the aforementioned mutations is positively correlated with the progression and the severity of the AF clinical course. Regarding the predisposition of AF, it has been proven that TET2 and ASXL1 mutations, and not DNMT3A mutation, are associated with higher interleukin-6 (IL-6) levels. IL-6 levels, being indices of cardiac remodeling, predispose to an elevated risk for AF in healthy subjects. Currently conducted research has focused on elaborating the mechanisms driving the association between AF and CHIP and on the evaluation of potential interventions to reduce the risk of AF development. The aims of our review are (i) to summarize published evidence regarding the presence of CHIP mutations as a contributor to AF severity and predisposition, and (ii) to highlight the potential benefits of investigating the correlations between CHIP and AF for AF-diagnosed patients. Full article

Transformers are critical assets for power system reliability, as they connect different voltage levels across generation, transmission, and distribution. Their failure can lead to significant impacts on multiple aspects. Given the aging transformer fleet, supply chain challenges, and constrained investment capacity, the adoption of risk-based strategies is essential to support long-term maintenance planning and investment. This paper proposes a multicriteria framework to assess the probability and impact of transformer failure, enabling a more comprehensive and data-driven risk evaluation. The method was applied to a sample fleet, enabling the identification and prioritization of the most critical units through a risk plot. The framework enhances asset management by identifying critical units within a transformer fleet, promoting efficiency, reliability, and long-term planning based on objective risk indicators. Full article

Housing sustainability is a cornerstone element of sustainable economic and social development. This is particularly true for China, where high-rise residential buildings are the primary form of housing. In recent years, China has experienced frequent housing-related accidents, resulting in a significant loss of life and property damage. This study aims to identify the key factors influencing housing sustainability and provide a basis for the prevention and control of housing-related safety risks. This study has developed a housing sustainability evaluation indicator system comprising three primary indicators and 16 secondary indicators. This system is based on an analysis of the causes of over 500 typical housing accidents that occurred in China over the past 10 years, employing research methods such as literature reviews and expert consultations, and drawing on the analytical frameworks of risk management theory and system safety theory. Subsequently, the NK-SNA model, which significantly outperforms traditional models in terms of adaptive learning and optimization, as well as the explicit modeling of complex nonlinear relationships, was used to identify the key risk factors affecting housing sustainability. The empirical results indicate that the risk coupling value is correlated with the number of risk coupling factors; the greater the number of risk coupling factors, the larger the coupling value. Human misconduct is prone to forming two-factor risk coupling with housing, and the physical risk factors are prone to coupling with other factors. The environmental factors easily trigger ‘physical–environmental’ two-factor risk coupling. The key factors influencing housing sustainability are poor supervision, building facilities, the main structure, the housing height, foundation settlement, and natural disasters. On this basis, recommendations are made to make full use of modern information technologies such as the Internet of Things, big data, and artificial intelligence to strengthen the supervision of housing safety and avoid multi-factor coupling, and to improve upon early warnings of natural disasters and the design of emergency response programs to control the coupling between physical and environmental factors. Full article

Gingival recession is a common problem, particularly affecting oral health and esthetics, and its treatment involves surgical root coverage procedures. The aim of this narrative review is to evaluate the role of systemic antibiotic therapy in mucogingival surgery for recession treatment. The available literature does not support routine antibiotic use in systemically healthy patients undergoing recession coverage surgery. Indications for prophylactic antibiotics are restricted to individuals at high risk of infective endocarditis and immunocompromised patients with elevated susceptibility to surgical site infections. Although mucogingival surgeries are performed in a non-sterile environment, the risk of infection remains low when proper aseptic techniques and good preoperative tissue preparation are applied. The review emphasizes the importance of making clinical decisions that consider the patient’s health status and are aligned with current recommendations. It also emphasizes the necessity for prospective studies to evaluate antibiotics’ effect on recession coverage procedures outcome. To bridge the gap between contemporary evidence and clinical practice and to foster responsible use of antibiotics in periodontal plastic surgery, the authors of this review integrate current evidence and clinical guidelines into a practical tool designed to assist clinicians in making reasoned, evidence-based decisions. Full article