Routine Clinical Practice Research Articles

Trabecular Attenuation of L1 in Adult Patients with Multiple Myeloma: An Observational Study on Low-Dose CT Images.

The aim of this study was to evaluate the impact of trabecular attenuation of the L1 vertebral body in low-dose CT in adult patients with multiple myeloma (MM), smoldering multiple myeloma (SMM), and monoclonal gammopathy of undetermined significance (MGUS). The study population consisted of 22 patients with MGUS and 51 consecutive patients with newly diagnosed MM (SMM, n = 21; symptomatic MM, n = 36). CT scans were conducted using a 128-slice CT scanner (Somatom go.Top, Siemens, Munich, Germany). Low-dose whole-body CT scans were performed at a single time point for each patient. Trabecular bone density values were obtained by defining regions of interest on non-contrast images at the level of L1 vertebra. A threshold of p = 0.05 was applied to determine statistical significance. The median Hounsfield unit (HU) value in patients with MGUS, SMM, and MM was 148 HU (range 81-190), 130 HU (range 93-193), and 92 HU (range 26-190), respectively, with a statistically significant difference between the groups (p = 0.0015). Patients with HU values ≤ 92 had lower progression-free survival with statistically significant differences compared to the group with HU values > 92 (p < 0.0499). This is the earliest evidence of the importance of evaluating L1 attenuation values in low-dose CT images in patients with MGUS, SMM, and MM. Further prospective studies could contribute to reinforcing these results and exploring the clinical applicability and generalization of L1 attenuation values in low-dose whole-body CT scans in routine clinical practice.

Evaluation of caries risk assessment practices among dental practitioners in Guangzhou, China: a cross-sectional study.

This cross-sectional study aimed to investigate dental practitioners' knowledge and practices regarding Caries risk assessment (CRA) in routine clinical practice in Guangzhou, China. An online questionnaire was disseminated to dental practitioners to gather socio-demographic information, factors associated with CRA, the implementation of preventive treatment, and the level of awareness regarding personalized preventive treatment in relation to CRA. Statistical analyses included descriptive statistics, Chi-square tests, ANOVA, MANCOVA, linear regression, and scatter plots. Out of the 695 dental practitioners who were contacted, 206 dentists participated in the online survey. However, out of the total number of dentists, 198 were successfully recruited, while the remaining 8 dentists had incomplete data in their questionnaires. 92.4% of dentists provided in-office fluoride treatments, and 73.2% held a strong belief in the correlation between current oral hygiene and tooth cavities. 23.7% of dentists evaluated caries risk on an individual basis, and a significant 41.9% never utilized a particular type of CRA. 53.5% of dentists recommended non-prescription fluoride rinses, whereas 51% advocated prescription fluoride treatments. Significant statistical relationships were found between the use of in-office fluoride and the effectiveness of restorative treatment (P < 0.05). Additionally, a significant association was discovered between the use of a specific form for CRA and the kind of dental school (P < 0.05). The study suggests that a significant number of dental practitioners in Guangzhou, China, do not utilize dedicated assessment forms for CRA in their routine professional activities. These findings highlight the im-portance of encouraging dentists to utilize CRA systems to effectively identify patients who are at risk of acquiring dental caries.

Aortic Stenosis, Heart Failure, and Aortic Valve Replacement

Heart failure (HF) and aortic stenosis (AS) frequently coexist, presenting a complex clinical challenge due to their intertwined pathophysiology and associated high morbidity and mortality. Despite numerous advancements in transcatheter and surgical aortic valve replacement (AVR), HF decompensation remains the leading cause of cardiac rehospitalization and a major predictor of mortality in patients with AS, before or after AVR. This review aims to provide a comprehensive analysis of the interplay between AS and HF, delving into myocardial changes caused by stenotic insult, the impact of AVR on these changes, and the prevalence and contributing elements of HF before and after AVR. The prevalence of HF remains high before and after AVR, particularly among patients with left ventricular dysfunction. Increased afterload from AS causes cardiac remodeling, which is initially benign but over time these changes become maladaptive, contributing to HF and increased mortality. The progression of HF is influenced by the degree of reverse cardiac remodeling, which can be affected by comorbid conditions, the hemodynamic performance of the valve prosthesis, and vascular stiffness. Several blood and imaging biomarkers offer insights into underlying AS pathophysiology, serving as mortality predictors and predicting HF in this patient population. HF development in AS is multifactorial and its link to left ventricular dysfunction is a complex process. Delineating the determinants of HF admissions in AS is crucial for identifying individuals at high risk. Identifying the early signs of left ventricular decompensation by using surrogate markers may be the key, even before left ventricular function becomes impaired. Translating multimodality imaging techniques and biomarkers into routine clinical practice for evaluating cardiac damage and integrating these markers with patient and procedural factors that affect HF before and after AVR can facilitate timely intervention, minimizing the likelihood of HF progression and influencing future guidelines.

Artificial Intelligence and Advanced Technology in Glaucoma: A Review.

Glaucoma is a leading cause of irreversible blindness worldwide, necessitating precise management strategies tailored to individual patient characteristics. Artificial intelligence (AI) holds promise in revolutionizing the approach to glaucoma care by providing personalized interventions. This review explores the current landscape of AI applications in the personalized management of glaucoma patients, highlighting advancements, challenges, and future directions. A systematic search of electronic databases, including PubMed, Scopus, and Web of Science, was conducted to identify relevant studies published up to 2024. Studies exploring the use of AI techniques in personalized management strategies for glaucoma patients were included. The review identified diverse AI applications in glaucoma management, ranging from early detection and diagnosis to treatment optimization and prognosis prediction. Machine learning algorithms, particularly deep learning models, demonstrated high accuracy in diagnosing glaucoma from various imaging modalities such as optical coherence tomography (OCT) and visual field tests. AI-driven risk stratification tools facilitated personalized treatment decisions by integrating patient-specific data with predictive analytics, enhancing therapeutic outcomes while minimizing adverse effects. Moreover, AI-based teleophthalmology platforms enabled remote monitoring and timely intervention, improving patient access to specialized care. Integrating AI technologies in the personalized management of glaucoma patients holds immense potential for optimizing clinical decision-making, enhancing treatment efficacy, and mitigating disease progression. However, challenges such as data heterogeneity, model interpretability, and regulatory concerns warrant further investigation. Future research should focus on refining AI algorithms, validating their clinical utility through large-scale prospective studies, and ensuring seamless integration into routine clinical practice to realize the full benefits of personalized glaucoma care.

Preparing the Laboratory for Neoadjuvant Cancer Immunotherapy: Insights from a Pathology Learning Collaborative

Abstract Introduction/Objective Neoadjuvant immunotherapy (NIT) is an emerging strategy to treat multiple types of early- stage resectable cancers by inducing a systemic anti-tumor immune response and increasing the likelihood of complete pathological response (pCR). The evaluation of pathological response following NIT is challenging and requires specific expertise. Traditional response criteria may be difficult to apply since immunotherapy may lead to unique changes in the tumor bed. Moreover, many laboratories may not feel prepared to evaluate pathologic response following immunotherapy given their lack of experience and the time required to accurately assess specimens and report findings. Methods/Case Report To explore ways to help laboratories prepare for these challenges, the American Society for Clinical Pathology (ASCP) formed an immuno-oncology learning collaborative to engage pathologists from different institutions and subspecialties. The group met over six months to review and discuss the implications of relevant literature, guideline recommendations, and emerging trends such as tumor-specific recommendations (eg, IASLC Neoadjuvant Therapy Pathologic Response Initiative) to pan-tumor immune-related pathologic response criteria (irPRC). ASCP then developed a series of educational resources based on recommendations made by the group. Results (if a Case Study enter NA) Members of the ASCP learning collaborative identified and prioritized several topics to help laboratories prepare and equip their teams to perform pathologic assessment after neoadjuvant immunotherapy in routine clinical practice. These included: definition and classification of pathological response criteria, assessing unique changes in the tumor bed (ie, regression bed), interpreting data from clinical trials, reporting results in routine clinical practice, organizing educational resources, and staffing workload. The group also emphasized the importance of collaborating with oncologists and surgeons and promoting communication about these topics within each institution. Conclusion Based on promising results from neoadjuvant immunotherapy clinical trials, we can expect more FDA approvals for neoadjuvant indications and a growing number of patients receiving this treatment. Pathologists and laboratory professionals need to prepare their institutions for a future where the assessment of pathological response in routine clinical practice will impact treatment decisions following surgical resection.

Perceptions and attitudes toward digital dentistry among dental professionals: a questionnaire survey study

In recent decades, digital technologies have become increasingly essential in dentistry, continuing the field's long-standing necessity of cutting-edge technology and innovation.The objective of the study was to determine the perception and attitude of dentists towards the use of digital technology.A Questionnaire study was conducted amongst 400 dental professionals. The questionnaire was sent electronically to all participants. The data from the filled forms was then compiled in a spreadsheet. The data was analyzed using IBM-SPSS (Statistical Package for Social Studies) Version 22. P value was taken as statistically significant (P-Value &amp;#60; 0.05). 58% dental professionals did not receive any training. 42% dental professionals have received formal training or education in digital dentistry during their professional career while 58% didn’t receive any training. 62% of professionals have noted changes in treatment outcomes or patient satisfaction since integrating digital dentistry technologies into their practice. 77% of participants expressed a willingness to adopt CAD/CAM systems in their practices. More than 75% were optimistic about bright future of digital technologies in dentistry in improving patient care and treatment outcomes.The majority of dental professionals were in the favor of incorporation of digital dentistry into clinical practice. Initial high cost of equipment’s and lack of formal training were the major barrier for incorporating digital technologies in routine clinical practice.

Recent Noteworthy Studies in Thoracic Oncology.

In this paper, we review recent prospective surgical studies on resectable esophageal and lung cancer. A narrative literature review was performed using the terms 'resectable esophageal cancer' and 'multimodal therapy' and 'resectable non-small cell lung cancer'. Prospective surgical trials performed from 2010 to 2023 were identified and analyzed. gov was queried for ongoing studies. The studies on esophageal cancer demonstrate the benefits of neoadjuvant chemoradiation, compared with surgery alone, and the emerging role of immunotherapy as part of induction and adjuvant treatment protocols. The selected studies on lung cancer demonstrate the evolving role of sublobar resection for patients with peripheral node-negative clinical stage IA1 disease and the developing role of neoadjuvant and adjuvant immunotherapy for patients with stage II-IIIA disease. The methods of treating patients with resectable esophageal or lung cancer are changing. Efforts to limit patient morbidity and optimize tumor treatment before surgery are increasingly being pursued and these approaches will likely continue to evolve as tumor biology and long-term pharmacologic mechanisms of action become clearer. Personalized medicine strategies that are based on tumor characteristics and the host genetic profile remain on the horizon, not yet ready for adoption in routine clinical practice.

Can the Systemic Inflammatory Index be a Prognostic Indicator in COVID-19 Patients Presenting to the Emergency Department?

Background: This study aimed to evaluate whether the systemic immune-inflammatory index (SII) can be used as a prognostic indicator in COVID-19 patients presenting to the emergency department. Given the high mortality and morbidity associated with COVID-19, identifying reliable prognostic markers is crucial for optimizing patient management. Methods: This retrospective observational study included 639 COVID-19 patients admitted to our emergency department between February 1, 2022, and February 1, 2023. Patients’ SII was calculated using complete blood count parameters (neutrophil, lymphocyte, and platelet counts). Data on patient outcomes, including intensive care unit (ICU) admission and in-hospital mortality, were analyzed using statistical methods such as receiver operating characteristic (ROC) curve analysis to assess the predictive power of SII, neutrophil-to-lymphocyte ratio (NLR), and neutrophil-to-platelet ratio (NPL). Results: Among the 639 patients, 136 died during hospitalization. Significant differences in SII, NLR, and NPL were observed between patients admitted to the ICU and those with less severe outcomes. The highest AUC (area under the curve) value was observed for NLR, with a cut-off value of &gt;4.87, predicting mortality with a sensitivity of 72.79% and specificity of 77.73%. SII also demonstrated significant prognostic value with a cut-off of &gt;806.03, predicting mortality with a sensitivity of 75.74% and specificity of 66%. Conclusion: SII, NLR, and NPL are effective prognostic indicators in COVID-19 patients, particularly in predicting the need for intensive care and mortality risk. These findings suggest incorporating these markers into routine clinical practice could improve risk stratification and patient outcomes. However, further large-scale studies are needed to validate these results and refine the use of these markers in clinical settings.

Cloud-Enabled Mobile-Based Approach for Enhancing Psychosis Cognitive Assessment.

The study aims to assess the feasibility of developing cognitive tools and integrating the cloud-enabled mobile-based technology into routine clinical practice for psychotic patients. Furthermore, it aims to investigate the correlation between the results obtained using developed tools and established clinical measures, offering valuable insights into tools for enhancing the accuracy, efficiency and ease of administration of cognitive evaluation. A total of 160 participants were recruited (83 outpatients with early course of schizophrenia (SZs) and 77 healthy controls [HCs]). The participants were subjected to cognitive assessments, and the data were collected by cognitive assessment digital smart tool (CADST) and PGI memory scale (PGIMS) to assess attention (ATT) and working memory (WM). Outcome measures of these parameters were digit span (score,time) for ATT and delayed recall (score,time) for WM. The total average score in HCs was significantly higher than in SZs for ATT and WM, and CADST was significantly correlated with PGIMS for evaluating ATT and WM. Furthermore, test completion times for ATT and WM were observed more in SZs although most of SZs had achieved scores as high as that of HCs. The potential of CADST as a valuable addition to the conventional cognitive assessment method is highlighted, showing promising feasibility and strong correlations with the established tool. The importance of integrating time parameters suggests broader implications for understanding cognitive function beyond conventional scoring metrics. It demonstrates the effective and accurate approach for large-scale screening of cognitive parameters in public service settings.

An integrated approach to the treatment of Rheumatic diseases: the role of psychological interventions.

Rheumatic diseases are chronic conditions that often result in significant physical and psychological challenges, reducing patients' quality of life and increasing the economic burden on healthcare systems. This study examines the vital role of psychological interventions in the comprehensive treatment of rheumatic diseases. The findings reveal a high prevalence of psycho-emotional disorders such as depression, anxiety, and stress among these patients, which can worsen disease progression and hinder treatment adherence. The review highlights the bidirectional relationship between the central nervous and immune systems, showing how psychological stress influences the pathophysiology of inflammatory diseases. Various psychological interventions are explored, including mind-body therapies, cognitive behavioral therapy, acceptance and commitment therapy, and mindfulness-based practices such as meditation, yoga, and tai chi. These approaches improve emotional well-being, help reduce pain, and enhance overall quality of life. The article emphasizes a holistic treatment model incorporating pharmacological care, physical rehabilitation, and psychological support. This integrated approach fosters more effective management of rheumatic diseases by addressing their complex nature and promoting better functional outcomes. The study advocates for the seamless incorporation of psychological support into routine clinical practice tailored to the biopsychosocial profile of each patient. Future research should focus on identifying the most effective psychological interventions for different patient groups to enhance the quality of life for individuals with rheumatic diseases.

Optimal electrode placements for localizing premature ventricular contractions using a single dipole cardiac source model

IntroductionThe inverse problem of electrocardiography describes non-invasively the electrical activity of the heart using potential recordings from tens to hundreds of torso electrodes. Regrettably, the use of numerous electrodes poses a challenge to its integration into routine clinical practice. MethodsOptimal electrode placements, ranging from 8 to 112 electrodes, were derived from the singular values of the transfer matrices computed for all feasible positions of a single dipole cardiac source across 12 patients with unique geometrical characteristics from the Bratislava dataset. The transfer matrices were computed using the boundary element method. Subsequently, these optimal electrode placements were used to compute the inverse solution for localizing the origin of premature ventricular contraction (PVC) with a single dipole cardiac source. The localization error (LE) was computed as the Euclidean distance between the true PVC origin, obtained through an invasive radiofrequency ablation, and the inverse solution. This enabled a direct comparison of LE computed for each optimal electrode placement with that from the full 128-electrode set. ResultsResults showed that subsets of electrodes, particularly 32 to 112, provided comparable localization accuracy (LE of 30.5 ± 15.0 mm and 26.8 ± 12.6 mm) to the full 128-electrode set (LE of 27.2 ± 11.5 mm). High errors were observed with 8 and 16-electrode placements (LE of 48.6 ± 21.3 mm and 41.0 ± 18.3 mm). ConclusionPrecise PVC localization can be achieved using strategically positioned subsets of electrodes, offering advantages in reduced preparation time, enhanced patient comfort, and improved cost-effectiveness of body surface potential mapping.

Testing Similarity of Parametric Competing Risks Models for Identifying Potentially Similar Pathways in Healthcare.

The identification of similar patient pathways is a crucial task in healthcare analytics. A flexible tool to address this issue are parametric competing risks models, where transition intensities may be specified by a variety of parametric distributions, thus in particular being possibly time-dependent. We assess the similarity between two such models by examining the transitions between different health states. This research introduces a method to measure the maximum differences in transition intensities over time, leading to the development of a test procedure for assessing similarity. We propose a parametric bootstrap approach for this purpose and provide a proof to confirm the validity of this procedure. The performance of our proposed method is evaluated through a simulation study, considering a range of sample sizes, differing amounts of censoring, and various thresholds for similarity. Finally, we demonstrate the practical application of our approach with a case study from urological clinical routine practice, which inspired this research.

Individual placement and support (IPS): duration of employment support and equity of access and outcome in routine clinical practice.

To explore the duration of support, reach, effectiveness and equity in access to and outcome of individual placement and support (IPS) in routine clinical practice. A retrospective analysis of routine cross-sectional administrative data was performed for people using the IPS service (N = 539). A total of 46.2% gained or retained employment, or were supported in education. The median time to gaining employment was 132 days (4.3 months). Further, 84.7% did not require time-unlimited in-work support, and received in-work support for a median of 146 days (4.8 months). There was a significant overrepresentation of people from Black and minority ethnic communities accessing IPS, but no significant differences in outcomes by diagnosis, ethnicity, age or gender. Most people using IPS services do not appear to need time-unlimited in-work support. Community teams with integrated IPS employment specialists can be optimistic when addressing people's recovery goals of gaining and retaining employment.

Foundation models for cardiovascular disease detection via biosignals from digital stethoscopes

Auscultation of the heart and the electrocardiogram (ECG) are two central components of the cardiac exam. Recent innovations of the stethoscope have enabled the simultaneous acquisition of a high-quality digital acoustic signal and ECG. We present foundation models trained on phonocardiogram (PCG) and ECG data collected from digital stethoscopes during routine clinical practice. We show that these foundation models that are pre-trained on large unlabeled datasets in a self-supervised manner can be fine-tuned for a variety of cardiovascular disease detection tasks. This is the first study that builds foundation models specifically for synchronously captured PCG and ECG data. Our approach is based on the recently developed masked autoencoder framework which we extend to handle multiple signals that are synchronously captured. This paradigm makes it possible to use large capacity models leading to superior performance even though the size of datasets with medical label annotations may be limited.

The Potential Use of Targeted Proteomics and Metabolomics for the Identification and Monitoring of Diabetic Kidney Disease.

Diabetic kidney disease (DKD) is a prevalent microvascular complication of diabetes mellitus and is associated with a significantly worse prognosis compared to diabetic patients without kidney involvement, other microvascular complications, or non-diabetic chronic kidney disease, due to its higher risk of cardiovascular events, faster progression to end-stage kidney disease, and increased mortality. In clinical practice, diagnosis is based on estimated glomerular filtration rate (eGFR) and albuminuria. However, given the limitations of these diagnostic markers, novel biomarkers must be identified. Omics is a new field of study involving the comprehensive analysis of various types of biological data at the molecular level. In different fields, they have shown promising results in (early) detection of diseases, personalized medicine, therapeutic monitoring, and understanding pathogenesis. DKD is primarily utilized in scientific research and has not yet been implemented in routine clinical practice. The aim of this review is to provide an overview of currently available data on targeted omics. After an extensive literature search, 25 different (panels of) omics were withheld and analyzed. Both serum/plasma and urine proteomics and metabolomics have been described with varying degrees of evidence. For all omics, there is still a relative paucity of data from large, prospective, longitudinal cohorts, presumably because of the heterogeneity of DKD and the lack of patient selection in studies, the complexity of omics technologies, and various practical and ethical considerations (e.g., limited accessibility, cost, and privacy concerns).

Is Contrast-Enhanced Ultrasonography a New, Reliable Tool for Early-Graft-versus-Host Disease Diagnosis?

Acute gastrointestinal graft-versus-host disease (GI aGVHD) is a significant and life-threatening complication in patients undergoing allogeneic stem cell transplantation (allo-SCT). Early diagnosis of GI aGVHD is crucial for improving patient outcomes, but it remains a challenge due to the condition's nonspecific symptoms and the reliance on invasive diagnostic methods, such as biopsies and endoscopic procedures. In recent years, interest in non-invasive diagnostic techniques for graft-versus-host disease has increased, with contrast-enhanced ultrasound (CEUS) being one of them. For this reason, we aimed to examine the potential of ultrasound as a non-invasive, safe, and cost-effective alternative for the early detection and monitoring of GI aGVHD in this review. Our narrative review aims to describe the use of multimodal US that includes conventional US (B-mode and Doppler US) and advanced ultrasound techniques such as CEUS and CRTE for the non-invasive diagnosis of GI GVHD. We browsed several databases, including PubMed, Scopus, Web of Science, and Google Scholar. The search spanned 2000 to the present, focusing on articles written in English that reviewed the use of these imaging techniques in the context of GI GVHD. Following our research, we noticed that CEUS offers several advantages, including the real-time visualization of the gastrointestinal wall, assessment of blood flow, and detailed microvascular analysis-all achieved without the use of ionizing radiation. This feature makes CEUS an appealing option for repeated assessments, which are often necessary in monitoring the progression of GI aGVHD. When used in conjunction with conventional gastrointestinal ultrasound (GIUS), CEUS provides a more comprehensive view of the structural and functional changes occurring in the GI tract, potentially enhancing diagnostic accuracy and allowing for earlier intervention. In comparison to traditional diagnostic methods like tissue biopsy or CT scans, CEUS is less invasive, quicker to perform, and better tolerated by patients, especially those in fragile health following allo-SCT. Its non-invasive nature and ability to provide immediate imaging results make it a valuable tool for clinicians, particularly in settings where minimizing patient discomfort and risk is paramount. However, despite these advantages, there are still gaps in the literature regarding CEUS's full diagnostic accuracy for GI aGVHD. Further research, including larger clinical trials and comparative studies, is needed to validate CEUS's role in routine clinical practice and to establish standardized protocols for its use. Nonetheless, CEUS shows considerable potential to transform the diagnostic approach to GI aGVHD by improving early detection, reducing the need for invasive procedures, and ultimately enhancing treatment outcomes for affected patients.

Recommendations for implementing digital alcohol interventions in primary care: lessons learned from a Norwegian feasibility study.

Excessive alcohol consumption is a leading global risk factor for ill-health and premature death. Digital alcohol interventions can be effective at reducing alcohol consumption, but their widespread adoption is lagging behind. This study aimed to identify factors promoting or inhibiting the implementation of a digital alcohol intervention in Norwegian primary care, by using Normalization Process Theory (NPT). A mixed methods feasibility study combining quantitative and qualitative methods. A digital alcohol intervention called "Endre" was implemented across four GP practices in Stavanger and Oslo. Usage of the intervention was logged on the digital platform. General practitioners (GPs) reported their perceived uptake of the intervention via a web-based survey. The Normalization MeAsure Development (NoMAD) survey was used to measure support staff's perceived normalization of the intervention. Qualitative data were analyzed using the NPT framework, with quantitative data analyzed descriptively and using χ 2 and Wilcoxon signed-rank test for differences in current and future normalization. Thirty-seven GPs worked in the clinics and could recruit patients for the digital intervention. Thirty-six patients registered for the intervention. Nine patients dropped out early and 25 completed the intervention as intended. Low normalization scores at follow-up (n = 27) indicated that Endre did not become fully embedded in and across practices. Nonetheless, staff felt somewhat confident about their use of Endre and thought it may become a more integral part of their work in the future. Findings from six semi-structured group interviews suggested that limited implementation success may have been due to a lack of tailored implementation support, staff's lack of involvement, their diminished trust in Endre, and a lack of feedback on intervention usage. The outbreak of the Covid-19 pandemic further limited opportunities for GPs to use Endre. This study investigated the real-world challenges of implementing a digital alcohol intervention in routine clinical practice. Future research should involve support staff in both the development and implementation of digital solutions to maximize compatibility with professional workflows and needs. Integration of digital solutions may further be improved by including features such as dashboards that enable clinicians to access and monitor patient progress and self-reported outcomes.

Evaluation of the results of magnetic resonance imaging of the brain for cognitive impairment in patients with heart failure: A review

Cognitive impairment is a very common comorbidity in patients with heart failure (HF). Patients with HF show signs of memory decline, difficulty concentrating, and attention deficits. Cognitive dysfunction in HF is associated with a poor prognosis. However, the diagnosis of cognitive impairment in heart failure has received insufficient attention in routine clinical practice. Neuropsychological screening tests are available to screen for cognitive impairment, but they are used infrequently. Therefore, it is of practical interest to search for magnetic resonance equivalents of cognitive disorders. The use of magnetic resonance imaging as a tool for identifying and quantifying neural correlates of cognitive functions is discussed.

Glucagon-like peptide-1 receptor agonists improve outcomes in individuals with type 2 diabetes with and without heart failure

BackgroundThe effectiveness of glucagon-like peptide-1 receptor agonists (GLP1Ras) for prevention of heart failure (HF) in patients with type 2 diabetes (T2DM) without HF and for risk of death in patients with T2DM with HF has not been fully elucidated in routine clinical practice. MethodsUsing the real-world global electronic medical record TriNetX database, individuals with T2DM and with or without HF who initiated either GLP1Ras or sitagliptin from 2017 to 2020 were retrospectively analyzed. In individuals with T2DM without HF, the primary outcome was a composite of all-cause mortality and a new diagnosis of HF within three years. In individuals with T2DM with HF, the primary outcome was all-cause mortality within three years. Propensity-score (PS) matching was used to adjust for over 100 baseline characteristics. ResultsA total of 65,598 individuals with T2DM without HF starting a GLP1Ras were PS matched with 65,598 starting sitagliptin. GLP1Ras were associated with a lower incidence of the composite endpoint (10.5 % versus 11.8 %, hazard ratio [HR] 0.82, [0.80–0.85], p < 0.001), mortality (HR 0.66 [0.63–0.69]) and new diagnosis of HF (HR 0.92 [0.88–0.96]). There were 6002 individuals in each group matched for T2DM and HF. Mortality was lower in the GLP1Ras group (17.6 % versus 22.8 %, HR 0.70 [0.65–0.76], p < 0.001). Results were consistent across subgroups. ConclusionsIn this global real-world data analysis, GLP1Ra use was associated with a lower risk of death and HF in individuals with T2DM without HF, and lower risk of death in those with HF.

Insights, recommendations, and research priorities for central sleep apnea: report from an expert panel.

Central sleep apnea (CSA) is commonly encountered among patients with sleep-disordered breathing, however its clinical consequences are less well-characterized. We therefore convened an expert panel to discuss the common presentations of CSA, as well as challenges and knowledge gaps in the diagnosis and management of CSA. The panel identified several key research priorities essential for advancing our understanding of the disorder. Within the diagnostic realm, panel members discussed the utility of multi-night assessments, and importance of the development and validation of novel metrics and automated assessments for differentiating central versus obstructive hypopneas, such that their impact on clinical outcomes and management may be better evaluated. The panel also discussed the current therapeutic landscape for the management of CSA and agreed that therapies should primarily aim to alleviate sleep-related symptoms, after optimizing treatment to address the underlying cause. Most importantly, the panel concluded that there is a need to further investigate the clinical consequences of CSA, as well as the implications of therapy on clinical outcomes, particularly among those who are asymptomatic. Future research should focus on endo-phenotyping central events for a better mechanistic understanding of the disease, validating novel diagnostic methods for implementation in routine clinical practice, as well as the use of combination therapy and comparative effectiveness trials in elucidating the most efficacious interventions for managing CSA.