IRIS UniSR (’Università Vita-Salute San Raffaele)
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Connecting the dots: A narrative review of the relationship between heart failure and cognitive impairment
No full text: Large clinical data underscore that heart failure is independently associated to an increased risk of negative cognitive outcome and dementia. Emerging evidence suggests that cerebral hypoperfusion, stemming from reduced cardiac output and vascular pathology, may contribute to the largely overlapping vascular dementia and Alzheimer's disease. Despite these insights, cognitive outcomes remain largely overlooked in heart failure management. This narrative review outlines the prevalence and risk of cognitive impairment in heart failure patients, exploring potential shared pathophysiological mechanisms and examining the impact of heart failure therapy on cognitive deficits. Additionally, it discusses clinical implications and suggests future treatment approaches targeting therapeutic outcomes. Cognitive impairment is prevalent among individuals with heart failure, with reported rates varying widely depending on assessment methods. Shared pathological pathways and risk factors, including atrial fibrillation (AF), hypertension, obesity and type 2 diabetes mellitus, suggest a causal link. Mechanisms such as poor perfusion, microembolic events, ischaemic syndromes and cerebral inflammation contribute to this relationship. Moreover, heart failure itself may exacerbate cognitive dysfunction. This emerging understanding posits that vascular dementia and Alzheimer's disease may represent a pathophysiological continuum, driven by both the accumulation of misfolded proteins and cerebrovascular pathology due to cardiovascular dysfunction. Understanding these links is crucial for developing effective treatment strategies. The complex interplay between heart failure and cognitive impairment underscores the necessity for a holistic patient care approach. Both conditions share analogous disease processes, influencing self-management and independence in patients. Prioritizing brain health in heart failure management is essential to enhance patient prognosis and general well-being.Large clinical data underscore that heart failure is independently associated to an increased risk of negative cognitive outcome and dementia. Emerging evidence suggests that cerebral hypoperfusion, stemming from reduced cardiac output and vascular pathology, may contribute to the largely overlapping vascular dementia and Alzheimer's disease. Despite these insights, cognitive outcomes remain largely overlooked in heart failure management. This narrative review outlines the prevalence and risk of cognitive impairment in heart failure patients, exploring potential shared pathophysiological mechanisms and examining the impact of heart failure therapy on cognitive deficits. Additionally, it discusses clinical implications and suggests future treatment approaches targeting therapeutic outcomes. Cognitive impairment is prevalent among individuals with heart failure, with reported rates varying widely depending on assessment methods. Shared pathological pathways and risk factors, including atrial fibrillation (AF), hypertension, obesity and type 2 diabetes mellitus, suggest a causal link. Mechanisms such as poor perfusion, microembolic events, ischaemic syndromes and cerebral inflammation contribute to this relationship. Moreover, heart failure itself may exacerbate cognitive dysfunction. This emerging understanding posits that vascular dementia and Alzheimer's disease may represent a pathophysiological continuum, driven by both the accumulation of misfolded proteins and cerebrovascular pathology due to cardiovascular dysfunction. Understanding these links is crucial for developing effective treatment strategies. The complex interplay between heart failure and cognitive impairment underscores the necessity for a holistic patient care approach. Both conditions share analogous disease processes, influencing self-management and independence in patients. Prioritizing brain health in heart failure management is essential to enhance patient prognosis and general well-being
Antiplatelet Therapy in Low-Platelet-Count Patients After Percutaneous Coronary Intervention for Acute Coronary Syndromes
No full textThe risk of cardiovascular events increases considerably after an acute coronary syndrome (ACS), particularly in the first few months. Dual antiplatelet therapy represents the mainstay of secondary prevention during this period, but is associated with a not-negligible risk of bleeding which, among other factors, is influenced by the platelet count. Thrombocytopenic patients may experience an ACS, and several patients with ACSs develop thrombocytopenia during hospitalization: the management of antithrombotic therapy in this setting represents a challenge. Here, we review the available evidence on the use of antithrombotic therapy in patients with low platelet counts after an ACS
Predicting Antidepressant Treatment Response From Cortical Structure on MRI: A Mega-Analysis From the ENIGMA-MDD Working Group
No full textAccurately predicting individual antidepressant treatment response could expedite the lengthy trial-and-error process of finding an effective treatment for major depressive disorder (MDD). We tested and compared machine learning-based methods that predict individual-level pharmacotherapeutic treatment response using cortical morphometry from multisite longitudinal cohorts. We conducted an international analysis of pooled data from six sites of the ENIGMA-MDD consortium (n = 262 MDD patients; age = 36.5 ± 15.3 years; 154 (59%) female; mean response rate = 57%). Treatment response was defined as a ≥ 50% reduction in symptom severity score after 4–12 weeks post-initiation of antidepressant treatment. Structural MRI was acquired before, or < 14 days after, treatment initiation. The cortex was parcellated using FreeSurfer, from which cortical thickness and surface area were measured. We tested several machine learning pipeline configurations, which varied in (i) the way we presented the cortical data (i.e., average values per region of interest, as a vector containing voxel-wise cortical thickness and surface area measures, and as cortical thickness and surface area projections), (ii) whether we included clinical data, and the (iii) machine learning model (i.e., gradient boosting, support vector machine, and neural network classifiers) and (iv) cross-validation methods (i.e., k-fold and leave-one-site-out) we used. First, we tested if the overall predictive performance of the pipelines was better than chance, with a corrected 10-fold cross-validation permutation test. Second, we compared if some machine learning pipeline configurations outperformed others. In an exploratory analysis, we repeated our first analysis in three subpopulations, namely patients (i) from a single site, (ii) with comparable response rates, and (iii) showing the least (first quartile) and the most (fourth quartile) treatment response, which we call the extreme (non-)responders subpopulation. Finally, we explored the effect of including subcortical volumetric data on model performance. Overall, performance predicting antidepressant treatment response was not significantly better than chance (balanced accuracy = 50.5%; p = 0.66) and did not vary with alternative pipeline configurations. Exploratory analyses revealed that performance across models was only significantly better than chance in the extreme (non-)responders subpopulation (balanced accuracy = 63.9%, p = 0.001). Including subcortical data did not alter the observed model performance. Cortical structural MRI alone could not reliably predict individual pharmacotherapeutic treatment response in MDD. None of the used machine learning pipeline configurations outperformed the others. In exploratory analyses, we found that predicting response in the extreme (non-)responders subpopulation was feasible on both cortical data alone and combined with subcortical data, which suggests that specific MDD subpopulations may exhibit response-related patterns in structural data. Future work may use multimodal data to predict treatment response in MDD
Conventional and non-conventional antigen-binding sites promote the development and function of chronic lymphocytic leukemia stereotyped subset #4 clones
No full textImmunoglobulins (IGs) made by chronic lymphocytic leukemia (CLL) B cells are unique in that they bind themselves (homo-dimerize). This interaction leads to signal transduction with functional consequences that depend on the affinity of homo-dimerization. We have studied the antigen-binding properties of the IGs from a subset of patients with CLL (Subset #4) that homo-dimerize at high affinity. Previously, we had found that subset #4 IGs bound viable lymphocytes. Our new studies, probing an array of >8,000 antigens, indicate that these IGs also bind influenza virus. Because of the IGs high-affinity homo-dimerization, we asked if the defined foreign- and self-antigenic interactions were mediated by conventional B-cell receptor (BCR) domains or a non-conventional receptor created by homo-dimerization. The studies indicated the latter since abrogation of homo-dimerization eliminated binding to influenza virus and its hemagglutinin and to viable lymphocytes. Using these findings, we modeled a developmental path whereby a naive IgM+ B cell with subset #4 heavy and light chain variable domains used the conventional BCR to interact with auto- and foreign antigens and acquire homo-dimerization capacity to create the non-conventional antigen-receptor when transitioning to a leukemic cell. Future studies will determine if this process is an idiosyncratic occurrence or a physiologic principle
Characteristics, Prognosis and ESC/ERS Risk Stratification in Obese Patients with Pulmonary Arterial Hypertension (PAH)
No full textBackground: The impact of obesity on pulmonary arterial hypertension (PAH) remains largely underexplored, with excess weight potentially masking symptoms and affecting the reliability of current risk stratification tools. Research question: What are the clinical characteristics and prognosis of obese patients with PAH, and how well do current risk stratification tools perform in this population? Study design and methods: We retrospectively included patients with incident PAH diagnosis enrolled at ten European tertiary care centers for PAH management and compared patients with and without obesity, defined by a BMI ≥30 kg/m2. Uni- and multivariable Cox regression models were fitted to assess the association between obesity and 5-years all-cause mortality. Accuracy of the ESC/ERS risk stratification tool for the prediction of annual mortality at baseline and follow up in patients with and without obesity was assessed by ROC curve analysis. Results: Among 581 patients included (median age 58 years, IQR 41-75; 61% females), 139 (24%) were obese. Obese patients had more comorbidities and worse symptoms/functional capacity. 5-years crude and adjusted all-cause mortality risk was similar in obese and non-obese. Both the three- (AUC 0.71, 95% CI 0.62-0.81 vs 0.64, 95%CI 0.48-0.80) and the four-strata (AUC 0.79 95% CI 0.69-0.89 vs 0.64 95% CI 0.40-0.88) ESC/ERS risk stratification tool demonstrated lower accuracy for prediction of annual mortality in obese vs non-obese patients, although not statistically significant. However, most components of the risk stratification tool lack a significant prognostic association in obese patients. Interpretation: Despite the higher burden of comorbidity and the worse functional class, prognosis is similar in obese compared with non-obese patients with PAH. Currently recommended risk stratification strategies might not be sufficient in patients with obesity claiming for focused research to improve risk stratification across subgroups of patients with PAH
How do I manage a patient with Stenotrophomonas maltophilia infection?
No full textBackground: Stenotrophomonas maltophilia is a Gram-negative bacillus that may cause a range of infections, most frequently bloodstream and respiratory infections. S. maltophilia exhibits intrinsic resistance to several antibiotics including carbapenems. Clinical assessment and treatment of a patient with positive S. maltophilia cultures are challenging. Objectives: We aimed to provide a resource for clinicians to help diagnose and treat S. maltophilia infections. Sources: A comprehensive literature search on S. maltophilia infections was conducted using PubMed, with no restrictions on publication date. Content: The review uses a hypothetical clinical vignette as a context to explore the epidemiology, risk factors, clinical presentation, mortality, diagnostic management, antibiotic resistance mechanisms, and antibiotic management of S. maltophilia infections. Implications: The assessment and treatment of S. maltophilia infections remain challenging. Standardized indications to distinguish colonization from infection and to guide the start of targeted therapy are lacking. The optimal treatment approach has similarly not been established in randomized controlled trials
Repeated Transcatheter Valve Interventions After Surgical Mitral Valve Replacement: A 20-Year Journey Avoiding Surgical Redo
Get PDFLaparoscopic versus open liver resection for large (≥ 5 cm) hepatocellular carcinoma in elderly patients: a multicenter propensity score-matched study
No full textThe outcomes of laparoscopic liver resection (LLR) for large (≥ 5 cm) hepatocellular carcinoma (HCC) in elderly (≥ 70 years old) patients have not been deeply investigated so far. The aim of the study was to compare short- and long-term results of LLR vs. open liver resection (OLR) in this setting. Data regarding all patients undergoing liver resection for large HCC were retrospectively collected from referral European and Asian HPB centers. The cases were propensity score matched for age, BMI, center, underlying liver cirrhosis, comorbidities, extent of the resection, tumor size, and numbers. After matching 363 patients with large HCC aged ≥ 70 years old, two cohorts of 90 patients were compared. The laparoscopic group showed a shorter median length of hospital stay (7 vs 9 days, p = 0.01), with a lower rate of R1 resections (4.4% vs 13.3%, p = 0.03). No statistically significant differences were found in the median operative time (p = 0.34), intraoperative blood transfusions (p = 1.00), severe postoperative complications (p = 0.29), postoperative hemorrhage (p = 0.30), post-hepatectomy liver failure (p = 0.47), or in-hospital mortality (p = 0.31). After a median follow-up of 35 months (95% CI 27.6–42.3), there were no statistically significant differences in both overall survival (p = 0.28) and disease-free survival (p = 0.42). LLR was safe and effective in selected cases of large HCC in elderly patients and was proven to shorten median hospital stay and to reduce the R1 rates, without affecting both short- and long-term survival outcomes
Institutional Changes to Embed Citizen Science in RPOs: The Case of UniSR as an Implementer Partner of the European Project TIME4CS
No full textWhat is new? Institutional barriers and lack of engagement in research-performing organisations (RPOs) may limit the development and impact of Citizen Science (CS) initiatives. In the present case study, we detail the transformative and multidisciplinary approach of Vita-Salute San Raffaele University (UniSR) through the European project TIME4CS, showcasing how tailored roadmaps and mutual learning with other RPOs with established support structures and expertise for CS were able to overcome these challenges. What was the approach? The approach involved several key steps: 1) creation of a de novo research organization area dedicated to Research Development; 2) formation of a multidisciplinary core team to implement TIME4CS activities; 3) mapping the initial and final levels of awareness of CS among UniSR researchers through surveys; 4) developing and implementing a detailed communication plan, including seminars, newsletters, articles, and a repository of CS resources; 5) involvement of UniSR students, professors, researchers but also research support officers in the initiatives; 6) establishment of a contact point for stakeholders interested in CS and in active participation in European Citizen Science Association (ECSA) groups; 7) support to the development of pilot initiatives and projects of CS. What is the academic impact? The academic impact includes increased awareness and engagement in CS initiatives among UniSR researchers. The actions triggered by the TIME4CS project have led to the emergence of several new CS research projects, enhancing UniSR's research excellence and contributing to its strategic goals of internationalization and competitiveness. This case study provides a model for overcoming institutional barriers in the promotion of CS and enhancing research excellence. What is the wider impact? The wider impact of the initiatives includes fostering a more collaborative and inclusive research environment at UniSR. By involving researchers, students, professors, research support officers, and external stakeholders, the project promoted a culture of Open Science and Responsible Research and Innovation (RRI). The activities also contribute to the broader scientific community by participating in ECSA groups and sharing resources and best practices, potentially influencing other institutions to adopt similar approaches
Common data elements for observational studies in ocular toxoplasmosis: a Delphi consensus
No full textPurpose: Ocular toxoplasmosis (OT) is the most common cause of posterior uveitis globally, with a significant risk of visual impairment. However, the lack of standardized data collection hinders meaningful comparisons across studies. This study aimed to develop a consensus-based set of Common Data Elements (CDEs) for observational studies in OT using a Delphi approach. Design: A set of CDEs was developed through a combination of a comprehensive literature review, a hybrid workshop, and a Delphi consensus process. This effort was led by an international panel of experts in OT to define a standardized CDE set for research and clinical purposes. Methods: A multidisciplinary steering committee identified an initial list of candidate CDEs through a targeted literature review. A panel of 30 international experts participated in a structured, one-round Delphi process to evaluate and refine these CDEs. Consensus was determined based on predefined thresholds for inclusion, exclusion, and modification. Results: A total of 139 CDEs were categorized across nine domains: Demographic and Background Information, Medical and Ocular History, Clinical Presentation, Clinical Findings, Lesion Characteristics, Diagnostics, Imaging Findings, Treatment and Interventions, and Outcomes. All 139 CDEs met the inclusion criteria, with 79.8% rated as “very important”. The consensus underscores the importance of a comprehensive, standardized dataset for OT research. Conclusions: This study establishes the first expert-derived standardized dataset requested for reporting OT outcomes, providing a framework to standardize data collection for future observational studies. Adopting these CDEs will enhance data comparability, improve meta-analyses, and strengthen the evidence base for clinical decision-making in OT. Future work will focus on real-world validation and refinement of this dataset