INTRODUCTION: The histopathological classification for antineutrophil cytoplasmic autoantibody (ANCA)-associated glomerulonephritis (ANCA-GN) is a well-established tool to reflect the variety of patterns and severity of lesions that can occur in kidney biopsies. It was demonstrated previously that deep learning (DL) approaches can aid in identifying histopathological classes of kidney diseases; for example, of diabetic kidney disease. These models can potentially be used as decision support tools for kidney pathologists. Although they reach high prediction accuracies, their "black box" structure makes them nontransparent. Explainable (X) artificial intelligence (AI) techniques can be used to make the AI model decisions accessible for human experts. We have developed a DL-based model, which detects and classifies the glomerular lesions according to the Berden classification. METHODS: Kidney biopsy slides of 80 patients with ANCA-GN from 3 European centers, who underwent a diagnostic kidney biopsy between 1991 and 2011, were included. We also investigated the explainability of our model using Gradient-weighted Class Activation Mapping (Grad-CAM) heatmaps. These maps were analyzed by pathologists to compare the decision-making criteria of humans and the DL model and assess the impact of different training settings. RESULTS: The DL model shows a prediction accuracy of 93% for classifying lesions. The heatmaps from our trained DL models showed that the most predictive areas in the image correlated well with the areas deemed to be important by the pathologist. CONCLUSION: We present the first DL-based computational pipeline for classifying ANCA-GN kidney biopsies as per the Berden classification. XAI techniques helped us to make the decision-making criteria of the DL accessible for renal pathologists, potentially improving clinical decision-making.

• Publication type
• Journal Article MeSH

Moderní medicína disponuje silnými nástroji k záchraně a udržení života. Přesto je každý lidský život konečný, a ne vždy je udržování života za každou cenu přijatelné ve smyslu zajištění jeho přijatelné kvality. Obecně uznávaným pravidlem ve společnosti je, že by žádný zdravotník neměl rozhodovat o životě a smrti pacienta. Navzdory tomu jsou ale zdravotníci často ve svém rozhodování postaveni do situací, kdy jejich postoj o životě rozhoduje, byť je to v kategorii zachránit, či nechat zemřít, nebo v aplikaci léků na tlumení bolesti či neklidu vysoko převyšující dávkovací limity uvedené v SPC, nebo dokonce při vysazování život udržující orgánové podpory. Jde o závažná rozhodnutí, pro něž zdravotníci potřebují pravidla a návody, které obecně zpracovává etika a v praxi jsou determinovány právními předpisy a morálními principy konkrétní společnosti. Jedním z pomáhajících etických pravidel je úcta k životu, jejímž praktickým vyjádřením v naší společnosti jsou i pravidla pro nezahajování kardiopulmonální resuscitace, omezování zdravotní péče v situaci nepomáhající léčby, přijetí paliativní péče, postoj k eutanazii a respektování dříve vyslovených přání pacienta. Z pohledu úcty k životu zaujímá článek přístup k těmto medicínským postupům s cílem povzbudit vzdělání a diskusi k etickým tématům, která mají stejný význam pro úroveň kvality zdravotnictví jako odborná úroveň aplikace nových vědeckých poznatků. Orientace v etických principech zdravotnictví se týká všech občanů společnosti, tedy nejen zdravotníků. Řada stížností v situacích zdravotní péče vyplývá z nedostatků v aplikaci morálních principů, a to na straně zdravotníků, pacientů a často též pacientovi blízkých osob. Stejně tak různé patologické psychické stavy u zdravotníků ve škále od přecitlivělého úzkostného jednání až po bezcitnost a cynismus mají původ v nezvládnutí etických principů. Odpovědnost za život je vztahována ke konkrétní osobě a společnosti, v náboženském prostředí též k nadpřirozené autoritě. Individuální život je vnímán v celistvosti vlastní i v začlenění do konkrétní společenské skupiny. Eutanazie, dystanazie a marná léčba jsou hodnoceny jako negativní jevy v chápání úcty k životu.

Modern medicine has powerful tools to save and sustain life. Nevertheless, every human life is finite, and maintaining life at any cost is not always acceptable in the sense of ensuring its acceptable quality. It is a generally accepted rule in society that no health care professional should decide the life and death of a patient. Despite this, however, in their decision-making, medical professionals are often put in situations where their attitude decides about life, even if it is in the category of saving or letting die, or in the application of drugs to reduce pain or restlessness that greatly exceed the dosage limits specified in the Summary of Product Characteristics, or even when withdrawing life-sustaining organ support. These are serious decisions for which health professionals need rules and instructions, which are generally processed by ethics and in practice are determined by legal regulations and moral principles of a particular society. One of the helping ethical rules is respect for life, the practical expression of which in our society are also the rules for not starting cardiopulmonary resuscitation, limiting health care in a situation of non-helpful treatment, accepting palliative care, the attitude towards euthanasia and respecting the previously expressed wishes of the patient. From the point of view of respect for life, the article takes an approach to these medical procedures with the aim of encouraging education and discussion on ethical topics that are as important to the level of quality of health care as the professional level of the application of new scientific knowledge. Orientation in the ethical principles of health care concerns all citizens of society, i.e. not only health professionals. Anumber of complaints in health care situations result from shortcomings in the application of moral principles, on the part of health professionals, patients and often also patients ́ relatives. In the same way, various psychological pathological conditions in health professionals ranging from oversensitive, anxious actions to callousness and cynicism have their origin in failure to master ethical principles. Responsibility for life is related to a specific person and society, in a religious environment also to a supernatural authority. Individual life is perceived both in its own integrity and in its integration into a specific social group. Euthanasia, distanasia and futile treatment are evaluated as negative phenomena in the understanding of respect for life.

With the incorporation of effective therapies for myelofibrosis (MF), accurately predicting outcomes after allogeneic hematopoietic cell transplantation (allo-HCT) is crucial for determining the optimal timing for this procedure. Using data from 5183 patients with MF who underwent first allo-HCT between 2005 and 2020 at European Society for Blood and Marrow Transplantation centers, we examined different machine learning (ML) models to predict overall survival after transplant. The cohort was divided into a training set (75%) and a test set (25%) for model validation. A random survival forests (RSF) model was developed based on 10 variables: patient age, comorbidity index, performance status, blood blasts, hemoglobin, leukocytes, platelets, donor type, conditioning intensity, and graft-versus-host disease prophylaxis. Its performance was compared with a 4-level Cox regression-based score and other ML-based models derived from the same data set, and with the Center for International Blood and Marrow Transplant Research score. The RSF outperformed all comparators, achieving better concordance indices across both primary and postessential thrombocythemia/polycythemia vera MF subgroups. The robustness and generalizability of the RSF model was confirmed by Akaike information criterion and time-dependent receiver operating characteristic area under the curve metrics in both sets. Although all models were prognostic for nonrelapse mortality, the RSF provided better curve separation, effectively identifying a high-risk group comprising 25% of patients. In conclusion, ML enhances risk stratification in patients with MF undergoing allo-HCT, paving the way for personalized medicine. A web application (https://gemfin.click/ebmt) based on the RSF model offers a practical tool to identify patients at high risk for poor transplantation outcomes, supporting informed treatment decisions and advancing individualized care.

• MeSH
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Survival Rate MeSH
• Primary Myelofibrosis * therapy   mortality   MeSH
• Prognosis MeSH
• Aged MeSH
• Machine Learning * MeSH
• Hematopoietic Stem Cell Transplantation * mortality   MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

INTRODUCTION: The provision of optimal care for older adults with complex chronic conditions (CCCs) poses significant challenges due to the interplay of multiple medical, pharmacological, functional and psychosocial factors. To address these challenges, the I-CARE4OLD project, funded by the EU-Horizon 2020 programme, developed an advanced clinical decision support tool-the iCARE tool-leveraging large longitudinal data from millions of home care and nursing home recipients across eight countries. The tool uses machine learning techniques applied to data from interRAI assessments, enriched with registry data, to predict health trajectories and evaluate pharmacological and non-pharmacological interventions. This study aims to pilot the iCARE tool and assess its feasibility, usability and impact on clinical decision-making among healthcare professionals. METHODS AND ANALYSIS: A minimum of 20 participants from each of the seven countries (Italy, Belgium, the Netherlands, Poland, Finland, Czechia and the USA) participated in the study. Participants were general practitioners, geriatricians and other medical specialists, nurses, physiotherapists and other healthcare providers involved in the care of older adults with CCC. The study design involved pre-surveys and post-surveys, tool testing with hypothetical patient cases and evaluations of predictions and treatment recommendations. Two pilot modalities-decision loop and non-decision loop-were implemented to assess the effect of the iCARE tool on clinical decisions. Descriptive statistics and bivariate and multivariate analysis will be conducted. All notes and text field data will be translated into English, and a thematic analysis will be performed. The pilot testing started in September 2024, and data collection ended in January 2025. At the time this protocol was submitted for publication, data collection was complete but data analysis had not yet begun. ETHICS AND DISSEMINATION: Ethical approvals were granted in each participating country before the start of the pilot. All participants gave informed consent to participate in the study. The results of the study will be published in peer-reviewed journals and disseminated during national and international scientific and professional conferences and meetings. Stakeholders will also be informed via the project website and social media, and through targeted methods such as webinars, factsheets and (feedback) workshops. The I-CARE4OLD consortium will strive to publish as much as possible open access, including analytical scripts. Databases will not become publicly available, but the data sets used and/or analysed as part of the project can be made available on reasonable request and with the permission of the I-CARE4OLD consortium.

• MeSH
• Chronic Disease therapy   MeSH
• Clinical Decision-Making * methods   MeSH
• Humans MeSH
• Pilot Projects MeSH
• Prognosis MeSH
• Aged MeSH
• Machine Learning * MeSH
• Decision Support Systems, Clinical * MeSH
• Check Tag
• Humans MeSH
• Aged MeSH
• Publication type
• Journal Article MeSH

Gout and hyperuricemia increase cardiovascular disease risk, highlighting the need for improved risk stratification. In this pilot study, we evaluated the Coronary Event Risk Test (CERT) in 94 hyperuricemic and 196 gout patients, and 53 controls. Plasma ceramides were determined by liquid chromatography-mass spectrometry. Elevated CERT scores (≥7) occurred in 11.7 % (2-fold increase) of hyperuricemic and 31.12 % (5.5-fold increase) of gout patients compared to controls. Additionally, both hyperuricemic and gout patients with increased CERT also exhibited higher levels of inflammation and atherogenic index of plasma, both of which were significantly associated with CERT. Incorporating CERT into routine care may enhance risk stratification and guide targeted interventions in this patient population.

• MeSH
• Biomarkers blood   MeSH
• Ceramides * blood   MeSH
• Chromatography, Liquid MeSH
• Gout * blood   diagnosis   complications   MeSH
• Adult MeSH
• Risk Assessment MeSH
• Hyperuricemia * blood   diagnosis   complications   MeSH
• Cardiovascular Diseases * diagnosis   blood   etiology   epidemiology   MeSH
• Uric Acid * blood   MeSH
• Middle Aged MeSH
• Humans MeSH
• Decision Support Techniques * MeSH
• Pilot Projects MeSH
• Predictive Value of Tests MeSH
• Prognosis MeSH
• Heart Disease Risk Factors MeSH
• Aged MeSH
• Case-Control Studies MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

AIMS: Despite increasing prevalence, the general population lacks knowledge regarding diagnosis, implications, and management of cardiac arrhythmias (CA). This study aims to assess public perception of CA and identify knowledge gaps. METHODS AND RESULTS: The 36-item PULSE survey was disseminated via social media to the general population and conducted under the auspices of the European Heart Rhythm Association Scientific Initiatives Committee (EHRA SIC) with EHRA patient committee support. Among 3924 participants (2177 healthy, 1747 with previously diagnosed CA; 59% female, 90% European), 81% reported fear of CA. Females were more likely to be 'very' or 'moderately afraid' than males [odds ratio (OR) 1.159 (1.005, 1.337), P = 0.046]. While most recognized complications of CA-heart failure (82%), stroke (80%), and death (75%)-43% were unaware that CA can be asymptomatic. Those with cardiopulmonary resuscitation (CPR) training in the past 5 years were 2.6 times and 4.7 times more confident identifying sudden cardiac death and initiating CPR (P < 0.001). Confidence was lower in retired participants [OR 0.574 (0.499, 0.660), P < 0.001] and Southern Europeans [OR 0.703 (0.600, 0.824), P < 0.001]. Without CPR training, only 15% felt confident initiating CPR. Among CA participants, 28% reported severe to disabling daily symptoms. Males were more often asymptomatic (20% vs. 9%, P < 0.001). Treatment rates were comparable between sex categories (81% vs. 79%, P = 0.413). Interdisciplinary shared decision-making processes were reported by 4%. Notably, 1 in 10 CA cases was self-diagnosed using a wearable device, and 30% of CA participants used smartwatches for self-monitoring. CONCLUSION: Significant knowledge gaps regarding CA exist in the general population. Targeted educational initiatives could be a viable tool to enhance public knowledge, confidence in detecting and managing arrhythmias, particularly for women, who experience greater fear and symptom severity despite similar treatment rates.

• MeSH
• Adult MeSH
• Cardiopulmonary Resuscitation MeSH
• Middle Aged MeSH
• Humans MeSH
• Adolescent MeSH
• Young Adult MeSH
• Perception MeSH
• Surveys and Questionnaires MeSH
• Aged MeSH
• Arrhythmias, Cardiac * therapy   diagnosis   psychology   MeSH
• Fear MeSH
• Health Knowledge, Attitudes, Practice * MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Adolescent MeSH
• Young Adult MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Geographicals
• Europe MeSH

BACKGROUND: Identification of real-time adverse drug reactions [ADRs] (as opposed to the risk of ADRs) in older poly-medicated people in primary care is a challenging task, often undertaken without an explicit strategy. This systematic review aims to evaluate replicable instruments and methods for identifying and addressing ADRs. METHODS: A systematic search was conducted in Medline, CINAHL, Scopus, Web of Science and Cochrane library, using controlled vocabulary (MeSH) and free-text terms. Randomised controlled trials (RCTs) implementing strategies to identify or resolve ADRs experienced by patients in primary care were included. Two reviewers independently screened studies, extracted data, and assessed the risk of bias using the Cochrane Risk of Bias tool. Discrepancies were resolved by discussion. RESULTS: From 2,182 unique records, 49 studies were identified for full review. Eight papers reporting results from 6 RCTs were included. All six trials utilised a list of medicine-related unwanted symptoms to identify ADRs. Two of three studies using adverse drug reaction questionnaires reported statistically significant increased rates of ADR reporting. Two of three studies that combined symptom questionnaires with prescriber consultations reported reductions in the number of health problems. Overall, results suggest that the three studies that described multidisciplinary collaborations using lists of ADRs plus prescriber reviews enhanced patient safety. However, the RCTs were unblinded and reported suboptimal retention. When considered as a whole, findings are equivocal and the data are too heterogenous to warrant any firm conclusions, beyond the need for more research to optimise strategies to safeguard patient wellbeing. IMPLICATIONS: Adaptable and scalable instruments with decision support are needed in primary care to identify and mitigate medicine-related harm in older poly-medicated people. The effectiveness of adverse drug reaction identification instruments, the value of comprehensive instruments, and the optimum method of delivery should be explored in multicentre trials.

• MeSH
• Humans MeSH
• Drug-Related Side Effects and Adverse Reactions * MeSH
• Primary Health Care * MeSH
• Randomized Controlled Trials as Topic MeSH
• Adverse Drug Reaction Reporting Systems MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Systematic Review MeSH

Tento článek se zaměřuje na aktuální a komplexní přehled o stroke mimics (SM), jež představují výzvu pro diferenciální diagnostiku vzhledem k širokému spektru jejich příznaků podobných CMP. Uvádíme stručná epidemiologická data, klinický obraz a čtyři prediktivní škály vyvinuté pro diagnostiku SM, které byly identifikovány na základě literární rešerše: TeleStroke Mimic Score (TSM), FABS, simplified FABS (sFABS) a Khan score. Tyto validované nástroje mohou podpořit rychlé a efektivní rozhodování o léčbě v prostředí urgentního příjmu s cílem minimalizovat zpoždění v poskytování adekvátní péče pacientům s CMP. Rádi bychom upozornili na význam správného rozpoznání SM s ohledem na časovou citlivost rekanalizační léčby, důrazem na optimalizaci léčby a management pacientů s akutně vzniklými neurologickými příznaky.

The article presents a current and comprehensive review of stroke mimics (SM), which represent a challenge for differential diagnosis due to their wide range of similar symptoms with strokes. It delves into the brief epidemiology, clinical features, and four predictive scales for SM diagnosis, which were identified on the basis of a literature search: TeleStroke Mimic Score (TSM), FABS, simplified FABS (sFABS), and Khan score. These validated tools might support rapid and efficient decision-making regarding treatment in an emergency department setting with the goal of minimizing delays in providing adequate care to patients with stroke. We would like to highlight the importance of correct identification of SM given the time sensitivity of revascularization treatment, with a focus on optimizing treatment and management of patients with acute onset of neurological symptoms.

• Keywords
• stroke mimics,
• MeSH
• Stroke diagnosis   pathology   MeSH
• Diagnosis, Differential MeSH
• Humans MeSH
• Nervous System Diseases * diagnosis   epidemiology   classification   pathology   MeSH
• Neurologic Manifestations MeSH
• Neurologic Examination classification   MeSH
• Predictive Value of Tests * MeSH
• Check Tag
• Humans MeSH
• Publication type
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH

BACKGROUND: Surgical-related incidents are a common cause of in-hospital adverse events. Surgical patient safety would benefit from evidence-based practices, but a comprehensive collection of patient safety recommendations is still lacking. This study aimed to compile and assess the perioperative patient safety recommendations for adults. METHOD: A systematic review of clinical practice guidelines was conducted using Medline, Embase, Cochrane, Virtual Health Library Regional Portal, and Trip Database from 2012 to 2022. Eligibility criteria followed a PICAR strategy for patient safety recommendations in the perioperative care continuum. Guidelines were appraised for quality, particularly focusing on the 'rigour of development' domain of the AGREE-II tool for those containing strong recommendations. Descriptive analyses were conducted, emphasizing guideline quality, recommendation strength, and the supporting level of evidence. RESULTS: From the 267 guidelines, 4666 perioperative patient safety recommendations were extracted, of which 44.9% (2095) were strongly recommended. Of these, 322 had the highest level of evidence, but only 18 guidelines met high standards in the AGREE-II 'rigour of development' domain. A subset of 78 recommendations ranked the highest in the strength of recommendation, level of evidence, and rigour of development of their guidelines. A gap was found within pre-admission and post-discharge care recommendations. DISCUSSION: This review highlights the noteworthy variability in the methodological quality of the guidelines, and a discordance between strength of recommendation and evidence level of the available perioperative patient safety recommendations. These findings provide valuable information for advising policy decisions and promoting best practices to enhance global surgical safety. REGISTRATION: PROSPERO (CRD42022347449).

• MeSH
• Patient Safety * standards   MeSH
• Humans MeSH
• Perioperative Care * standards   methods   MeSH
• Practice Guidelines as Topic * MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Systematic Review MeSH

AIMS: The 2021 European Society of Cardiology prevention guidelines recommend the use of (lifetime) risk prediction models to aid decisions regarding initiation of prevention. We aimed to update and systematically recalibrate the LIFEtime-perspective CardioVascular Disease (LIFE-CVD) model to four European risk regions for the estimation of lifetime CVD risk for apparently healthy individuals. METHODS AND RESULTS: The updated LIFE-CVD (i.e. LIFE-CVD2) models were derived using individual participant data from 44 cohorts in 13 countries (687 135 individuals without established CVD, 30 939 CVD events in median 10.7 years of follow-up). LIFE-CVD2 uses sex-specific functions to estimate the lifetime risk of fatal and non-fatal CVD events with adjustment for the competing risk of non-CVD death and is systematically recalibrated to four distinct European risk regions. The updated models showed good discrimination in external validation among 1 657 707 individuals (61 311 CVD events) from eight additional European cohorts in seven countries, with a pooled C-index of 0.795 (95% confidence interval 0.767-0.822). Predicted and observed CVD event risks were well calibrated in population-wide electronic health records data in the UK (Clinical Practice Research Datalink) and the Netherlands (Extramural LUMC Academic Network). When using LIFE-CVD2 to estimate potential gain in CVD-free life expectancy from preventive therapy, projections varied by risk region reflecting important regional differences in absolute lifetime risk. For example, a 50-year-old smoking woman with a systolic blood pressure (SBP) of 140 mmHg was estimated to gain 0.9 years in the low-risk region vs. 1.6 years in the very high-risk region from lifelong 10 mmHg SBP reduction. The benefit of smoking cessation for this individual ranged from 3.6 years in the low-risk region to 4.8 years in the very high-risk region. CONCLUSION: By taking into account geographical differences in CVD incidence using contemporary representative data sources, the recalibrated LIFE-CVD2 model provides a more accurate tool for the prediction of lifetime risk and CVD-free life expectancy for individuals without previous CVD, facilitating shared decision-making for cardiovascular prevention as recommended by 2021 European guidelines.

• MeSH
• Time Factors MeSH
• Adult MeSH
• Risk Assessment MeSH
• Cardiovascular Diseases * prevention & control   epidemiology   MeSH
• Middle Aged MeSH
• Humans MeSH
• Decision Support Techniques MeSH
• Prognosis MeSH
• Heart Disease Risk Factors * MeSH
• Risk Factors MeSH
• Aged MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Multicenter Study MeSH
• Geographicals
• Europe MeSH