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INTRODUCTION. Pharmacy compounding involves certain risks that are directly related to the process of extemporaneous preparation and the actions of its participants. However, the role of pharmacy cleaners, whose actions can influence the quality of compounded medicinal products, has not been studied yet.AIM. This study aimed to analyse the risks to the quality of compounded medicinal products associated with the functions of a pharmacy cleaner in pharmaceutical compounding of non-sterile dosage forms.MATERIALS AND METHODS. The study used failure modes and effects analysis (FMEA) in accordance with the relevant Russian State Standard, as well as open brainstorming discussion. The study examined the functions of a pharmacy cleaner in pharmaceutical compounding of non-sterile dosage forms. The results were assessed by statistically processing the study data and assigning each potential failure mode a certain category.RESULTS. The risk analysis identified 45 potential failure modes for the functions of a pharmacy cleaner. Of these, 12 failure modes (26.7%) had a high level of criticality, 14 failure modes (31.1%) had a medium level of criticality, and 19 failure modes (42.2%) had a low level of criticality. Not all potential failure modes had valid documented regulatory provisions for the risk assessment and the development of prevention-type controls.CONCLUSIONS. The analysis of the functions of a pharmacy cleaner highlighted the potential risks to the quality of extemporaneous medicinal products prepared by compounding pharmacies. The study identified a lack of valid regulatory documentation. The authors suggested using the study results to amend the regulatory documents and standard operating procedures (SOPs) guiding the work of a pharmacy cleaner, to develop illustrative educational materials, and to conduct on-the-job training for pharmacy staff.

Hazard and risk assessment of complex petroleum-derived substances has been in a state of continuous improvement since the 1970s, with the development of approaches that continue to be applied and refined. Alternative feeds are defined here as those coming into a refinery or chemical plant that are not hydrocarbons from oil and gas extraction such as biologically derived oils, pyrolysis oil from biomass or other, and recycled materials. These feeds are increasingly being used for production of liquid hydrocarbon streams, and hence, there is a need to assess these alternatives, subsequent manufacturing and refining processes and end products for potential risk to humans and the environment. Here we propose a tiered, problem formulation-driven framework for assessing the safety of hydrocarbon streams and products derived from alternative feedstocks in use. The scope of this work is only focused on petrochemical safety assessment, though the principles may be applicable to other chemistries. The framework integrates combinations of analytical chemistry, in silico and in vitro tools, and targeted testing together with conservative assumptions/approaches to leverage existing health, environmental, and exposure data, where applicable. The framework enables the identification of scenarios where de novo hazard and/or exposure assessments may be needed and incorporates tiered approaches to do so. It can be applied to enable decisions efficiently and transparently and can encompass a wide range of compositional space in both feedstocks and finished products, with the objective of ensuring safety in manufacturing and use. [ABSTRACT FROM AUTHOR]

The paper examines the issue of risk management in critical infrastructure facilities, highlighting the analysis of existing approaches and methods used to assess negative threats. Particular attention is paid to the importance of using information technologies for data collection and processing, as well as to the complexity of developing a systematic risk management methodology. Tracking activity in social networks, analyzing browser history and other data allows you to analyze and track a person’s psychological and physical state. Having access to information about interests and personal issues gives attackers the opportunity to develop various types of influence, including pressure, blackmail and manipulation. [ABSTRACT FROM AUTHOR]

Every work environment contains different types of risks and interactions between risks. Therefore, the method to be used when making a risk assessment is very important. When determining which risk assessment method (RAM) to use, there are many factors such as the types of risks in the work environment, the interactions of these risks with each other, and their distance from the employees. Although there are many RAMs available, there is no RAM that will suit all workplaces and which method to choose is the biggest question. There is no internationally accepted scale or trend on this subject. In the study, 26 sectors, 10 different RAMs and 10 criteria were determined. A hybrid approach has been designed to determine the most suitable RAMs for sectors by using k-means clustering and support vector machine (SVM) classification algorithms, which are machine learning (ML) algorithms. First, the data set was divided into subsets with the k-means algorithm. Then, the SVM algorithm was run on all subsets with different characteristics. Finally, the results of all subsets were combined to obtain the result of the entire dataset. Thus, instead of the threshold value determined for a single and large cluster affecting the entire cluster and being made mandatory for all of them, a flexible structure was created by determining separate threshold values for each sub-cluster according to their characteristics. In this way, machine support was provided by selecting the most suitable RAMs for the sectors and eliminating the administrative and software problems in the selection phase from the manpower. The first comparison result of the proposed method was found to be the hybrid method: 96.63%, k-means: 90.63 and SVM: 94.68%. In the second comparison made with five different ML algorithms, the results of the artificial neural networks (ANN): 87.44%, naive bayes (NB): 91.29%, decision trees (DT): 89.25%, random forest (RF): 81.23% and k-nearest neighbours (KNN): 85.43% were found. [ABSTRACT FROM AUTHOR]

Chemical industries are among the process industries and cause many risks. The present research aimed to analyze the health risks of a chemical warehouse of drilling rigs chemical Supply Company based on COSHH (Control of Substances Hazardous to Health), CHEM-SAM (Chemical Risk Management Self-Assessment Model), and SQRA (Subjective Quantified Risk Assessment) methods in 2021. The information was collected based on document review, MSDS of chemicals, processes, employees, and chemical exposure. Flammability, toxicity, allergy-causing, corrosivity, reactivity, LD50, and permissible thresholds of chemicals were also collected. The present research results showed that out of 59 main chemicals in the operational processes of the chemical warehouse of drilling rigs, 14 chemicals are flammable, 22 cause allergy responses, and three can cause death if inhaled. According to the results of the CHEM-SAM method, the employees and people outside the organization are at medium and low chemical risk based on the current management of the chemical warehouse, respectively. The results of the COSHH health assessment showed that chemicals had low, medium, high, and very high risk in 31, 13, 12, and 3 cases, respectively. The high-risk cases consisted of Ammonium Nitrate، Caustic Soda, and Poly.Aluminum.Chloride. Health risk assessment was also performed using the SQRA method, and results showed that chemicals have a very low, low, medium, high, and very high risk in 27, 12, 8, 9, and 3 cases, respectively. The results showed that the adverse health effects of chemical exposure in the drilling industry are alarming. Employees of different sectors of oil and gas industries are exposed to chemicals.

Every work environment contains different types of risks and interactions between risks. Therefore, the method to be used when making a risk assessment is very important. When determining which risk assessment method (RAM) to use, there are many factors such as the types of risks in the work environment, the interactions of these risks with each other, and their distance from the employees. Although there are many RAMs available, there is no RAM that will suit all workplaces and which method to choose is the biggest question. There is no internationally accepted scale or trend on this subject. In the study, 26 sectors, 10 different RAMs and 10 criteria were determined. A hybrid approach has been designed to determine the most suitable RAMs for sectors by using k-means clustering and support vector machine (SVM) classification algorithms, which are machine learning (ML) algorithms. First, the data set was divided into subsets with the k-means algorithm. Then, the SVM algorithm was run on all subsets with different characteristics. Finally, the results of all subsets were combined to obtain the result of the entire dataset. Thus, instead of the threshold value determined for a single and large cluster affecting the entire cluster and being made mandatory for all of them, a flexible structure was created by determining separate threshold values for each sub-cluster according to their characteristics. In this way, machine support was provided by selecting the most suitable RAMs for the sectors and eliminating the administrative and software problems in the selection phase from the manpower. The first comparison result of the proposed method was found to be the hybrid method: 96.63%, k-means: 90.63 and SVM: 94.68%. In the second comparison made with five different ML algorithms, the results of the artificial neural networks (ANN): 87.44%, naive bayes (NB): 91.29%, decision trees (DT): 89.25%, random forest (RF): 81.23% and k-nearest neighbours (KNN): 85.43% were found.

Summary: The management of pregnant women with thrombophilia and a history of gestational vascular complications remains debatable. Treatment of the latter is often based on clinical outcome rather than disease mechanism. While the use of venous thromboembolism prophylaxis in pregnancy is recommended for those at increased risk, the ability of anticoagulant and/or antiplatelet agents to lower the risk of placenta‐mediated complications in this clinical setting remains controversial. The available guidelines are inconsistent in some situations, which reflects the limited evidence base. This review critically discusses risk assessment models (RAMs) and management strategies of women with thrombophilia and pregnancy complications, using clinical vignettes. RAMs, taking into account obstetric and thrombotic history as well as thrombophilia status, could drive a precision medicine approach, based on disease mechanism, and guide individual therapeutic interventions in high‐risk clinical settings. [ABSTRACT FROM AUTHOR]

Leading risk assessment standards such as the NIST SP 800-39 and ISO 27005 state that information security risk assessment (ISRA) is one of the crucial stages in the risk-management process. It pinpoints current weaknesses and potential risks, the likelihood of their materializing, and their potential impact on the functionality of critical information systems such as advanced metering infrastructure (AMI). If the current security controls are insufficient, risk assessment helps with applying countermeasures and choosing risk-mitigation strategies to decrease the risk to a controllable level. Although studies have been conducted on risk assessment for AMI and smart grids, the scientific foundations for selecting and using an appropriate method are lacking, negatively impacting the credibility of the results. The main contribution of this work is identifying an appropriate ISRA method for AMI by aligning the risk assessment criteria for AMI systems with the ISRA methodologies' characteristics. Consequently, this work makes three main contributions. First, it presents a comprehensive comparison of multiple ISRA methods, including OCTAVE Allegro (OA), CORAS, COBRA, and FAIR, based on a variety of input requirements, tool features, and the type of risk assessment method. Second, it explores the necessary conditions for carrying out a risk assessment for an AMI system. Third, these AMI risk assessment prerequisites are aligned with the capabilities of multiple ISRA approaches to identify the best ISRA method for AMI systems. The OA method is found to be the best-suited risk assessment method for AMI, and this outcome paves the way to standardizing this method for AMI risk assessment. [ABSTRACT FROM AUTHOR]

The purpose of this study is to examine the purpose of this study is to examine the features of managing financial institutions and risks under conditions of uncertainty. The current period of development of the financial sphere is characterized by availability of a significant number of approaches and methods of management through forecasting and assessing risks, their identifying and minimizing. Analysis of recent research and publications has shown that the use of innovative mathematical management methods can minimize risks and provide significant competitive advantages in the future. Methodology: general and special methods of system-structural analysis and synthesis, grouping and comparison were used in the research process. The risk management scheme proposed by the NBU for use by financial institutions has been analyzed and supplemented by taking into account reputational risks. The research findings show that the existing methods are based on the use of expert judgment and require a significant amount of information that is not always available. It has been proven that the construction, use, calibration and interpretation of results obtained during risk assessment should be handled by a risk committee, whose main task is to monitor, identify and manage risks that arise during the operation of the financial institution. It has been revealed that there is no single complete Bureau of Credit Histories in Ukraine, which is a significant barrier to the effective management of financial institutions. The prospect for further research is the formation of approaches that would allow managing several types of risks, in compliance with all regulations under current legislation. This will make it possible to fully satisfy customers, while the setup of a single bureau of credit histories will minimize risk manifestations.

As an important part of the urban environment, trees have certain risks while living in harmony with humans. For example, the failure of trees in extreme weather may cause casualties and damage to public and private; the decline and death of old and valuable trees can have an impact on the diversity and cultural value of trees. This paper outlines the theories related to tree risk and the development of tree risk assessment, evaluates the advantages and disadvantages of various tree risk assessment methods in existing studies, and explains some factors affecting the bearing capacity and related applications using knowledge of tree mechanics. Approaches in modern probing techniques are applied to study the response and loading of tree crowns and branches under wind loads, the application of different non-destructive testing techniques in visual assessment for detecting internal defects and root distribution of trees, and the role and impact of objective quantitative test results on tree risk assessment. Finally, the future development direction of tree risk assessment is predicted, which provides an important reference for research on tree risk assessment. [ABSTRACT FROM AUTHOR]

Hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) breast cancer is the most common subtype, representing over two-thirds of new diagnoses. Adjuvant therapy, which encompasses various medications and treatment durations, is the standard approach for managing early stage HR+ HER2- breast cancer. Optimizing treatment is essential to minimize unnecessary side effects while addressing the biological variability inherent in HR+/HER2- breast cancers. Incorporating biological biomarkers into treatment decisions, alongside traditional clinical factors, is vital. Gene expression assays can identify patients unlikely to benefit from adjuvant chemotherapy, thereby refining treatment strategies and improving risk assessment. This paper reviews evidence for several genomic tests, including Oncotype DX, MammaPrint, Breast Cancer Index, RucurIndex, and EndoPredict, which assist in tailoring adjuvant therapy. Additionally, we explore the role of liquid biopsies in personalizing treatment, emphasizing the importance of considering late relapse risks and potential benefits of extended systemic therapy for HR+/HER2- breast cancer patients.

Background: A neonatal mortality prediction score can assist clinicians in making timely clinical decisions to save neonates' lives by facilitating earlier admissions where needed. It can also help reduce unnecessary admissions., Objective: The study aimed to develop and validate a prognosis risk score for neonatal mortality within 28 days in public hospitals in the Amhara region, Ethiopia., Methods: The model was developed using a validated neonatal near miss assessment scale and a prospective cohort of 365 near-miss neonates in six hospitals between July 2021 and January 2022. The model's accuracy was assessed using the area under the receiver operating characteristics curve, calibration belt, and the optimism statistic. Internal validation was performed using a 500-repeat bootstrapping technique. Decision curve analysis was used to evaluate the model's clinical utility., Results: In total, 63 of the 365 neonates died, giving a neonatal mortality rate of 17.3% (95% CI: 13.7-21.5). Six potential predictors were identified and included in the model: anemia during pregnancy, pregnancy-induced hypertension, gestational age less than 37 weeks, birth asphyxia, 5 min Apgar score less than 7, and birth weight less than 2500 g. The model's AUC was 84.5% (95% CI: 78.8-90.2). The model's predictive ability while accounting for overfitting via internal validity was 82%. The decision curve analysis showed higher clinical utility performance., Conclusion: The neonatal mortality predictive score could aid in early detection, clinical decision-making, and, most importantly, timely interventions for high-risk neonates, ultimately saving lives in Ethiopia.

Background: Although there is increasing awareness of the health risks of air pollution as a global issue, few studies have focused on the methods for assessing individuals' perceptions of these risks. This scoping review aimed to identify previous research evaluating individuals' perceptions of air pollution and its health effects, and to explore the measurement of perceptions, as a key resource for health behaviour., Methods: The review followed the methodological framework proposed by Arksey and O'Malley. PubMed and Web of Science were searched. After initial and full-text screening, we further selected studies with standardised scales that had previously been tested for reliability and validity in assessing awareness and perceptions., Results: After full-text screening, 95 studies were identified. 'Perception/awareness of air quality' was often measured, as well as 'Perception of health risk.' Only nine studies (9.5%) used validated scaled questionnaires. There was considerable variation in the scales used to measure the multiple dimensions of risk perception for air pollution., Conclusion: Few studies used structured scales to quantify individuals' perceptions, limiting comparisons among studies. Standardised methods for measuring health risk perception are needed.

Since the first genetically engineered or modified crops or organisms (GMO) were approved for commercial production in 1995, no new GMO has been proven to be a hazard or cause harm to human consumers. These modifications have improved crop efficiency, reduced losses to insect pests, reduced losses to viral and microbial plant pathogens and improved drought tolerance. A few have focused on nutritional improvements producing beta carotene in Golden Rice. Regulators in the United States and countries signing the CODEX Alimentarius and Cartagena Biosafety agreements have evaluated human and animal food safety considering potential risks of allergenicity, toxicity, nutritional and anti-nutritional risks. They consider risks for non-target organisms and the environment. There are no cases where post-market surveillance has uncovered harm to consumers or the environment including potential transfer of DNA from the GMO to non-target organisms. In fact, many GMOs have helped improve production, yield and reduced risks from chemical insecticides or fungicides. Yet there are generic calls to label foods containing any genetic modification as a GMO and refusing to allow GM events to be labeled as organic. Many African countries have accepted the Cartagena Protocol as a tool to keep GM events out of their countries while facing food insecurity. The rationale for those restrictions are not rational. Other issues related to genetic diversity, seed production and environmental safety must be addressed. What can be done to increase acceptance of safe and nutritious foods as the population increases, land for cultivation is reduced and energy costs soar?

Pesticide applications in agriculture result in complex mixtures of Plant Protection Products (PPPs) in the environment. The ecotoxicological effects of these mixtures can occur at concentrations considered safe for individual chemicals, indicating potential risks underestimated by current regulatory assessments focused on individual active ingredients. To address this challenge, our study introduces a methodology for identifying priority PPPs for formulating mixtures, enabling further ecotoxicological testing in water and sediment compartments of edge-of-field surface water bodies, targeting pelagic and benthic organisms. This methodology was primarily based on the actual quantification of PPPs present in these compartments from selected case study sites (CSSs) in Europe and Argentina (11 and 4 for water and sediments, respectively). A conceptual framework was developed that discriminates and selects concerning PPPs based on their individual risk quotient and frequency of occurrence in each CSS, drawing upon two EU regulatory risk assessment approaches, i.e., the general approach under REACH for any environmental contaminant of concern - the European Chemicals Agency (ECHA) approach; and that specifically focusing on PPPs - the European Food Safety Authority (EFSA) approach. Irrespective of whether the focus is on water or sediments, the study revealed disparities in PPP rankings depending on the approach used to identify PPPs of concern, with the ECHA approach being more conservative than the EFSA approach. Despite this, the EFSA approach follows a more standardized assessment factor definition strategy, potentially allowing avoidance of risk overestimation, as well as resulting in a more balanced representation of different PPP classes for subsequent mixtures testing. Overall, the methodological development reported herein, along with the inconsistencies found when comparing different regulatory approaches to assess the risk of environmental contaminants, highlight the need for further discussion on the most appropriate directions towards the standardization of the regulatory risk assessment of PPP mixtures., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

To synthesize vast amounts of high-throughput biological information, omics-fields like epigenetics have applied risk scores to develop biomarkers for environmental exposures. Extending the risk score analytic tool to the metabolomic data would be highly beneficial. This research aimed to develop and evaluate metabolomic risk score (metRS) approaches reflecting the biological response to traffic-related air pollution (TRAP) exposure (fine particulate matter, black carbon, and nitrogen dioxide). A simulation study compared three metRS methodologies: elastic net regression, which uses penalized regression to select metabolites, and two variations of thresholding, where a p-value cutoff is used to select metabolites. The methods performance was compared to assess 1) ability to correctly select metabolites associated with daily TRAP and 2) ability of the risk score to predict daily TRAP exposure. Power calculations and false discovery rates (FDR) were calculated for each approach. This metRS was applied to two real cohorts, the Center for Health Discovery and Wellbeing (CHDWB, n = 180) and Environment and Reproductive Health (EARTH, n = 200). In simulations, elastic net regression consistently presented inflated FDR for both high and low effect sizes and across all three sample sizes (n = 200; 500; 1000). Power to detect correct metabolites exceeded 0.8 for all three sample sizes in all three methods. In the real data application assessing associations of metabolomics risk scores and TRAP, associations were largely null. While we did not identify strong associations between the risk scores and TRAP in the real data application, metabolites selected by the risk score approaches were enriched in pathways that are well-known for their association with TRAP. These results demonstrate that certain methodologies to construct metabolomics risk scores are statistically robust and valid; however, standardized metabolic profiling and large sample sizes are required., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Cardiovascular implantable electronic devices (CIEDs) monitor physiologic variables that could identify subacute heart failure (HF) decompensation and impending HF hospitalization. One such algorithm uses measurements from the previous 30 days of CIED remote monitoring data to predict low-, medium-, or high-probability of HF hospitalization in the next 30 days. We sought to understand how to prospectively implement the use of such algorithms in routine HF care. From January 18, 2024 to April 19, 2024, HF risk categories were predicted from scheduled remote transmissions every 30 days and from unscheduled transmissions for all patients at 2 distinct cardiology clinics. Clinicians contacted and assessed patients at high risk regarding symptoms and then provided an empiric 3-day diuretic intervention (initiation or dose augmentation), adjusted guideline-directed medical therapy, or performed other clinical action as appropriate. Among 358 patients with 1,140 remote transmissions, 72 (20%) had ≥1 transmission categorized as high-risk. The mean patient age was 72.8 years, 346 (97%) were male, and 221 (62%) had a pre-existing diagnosis of HF. Of these 72 patients, 67 (93%) were successfully contacted, 34 (51%) had no HF symptoms, 24 (36%) had mild to moderate symptoms, and 2 (3%) had severe symptoms. A total of 46 patients (69%) had clinical action taken, including 28 (42%) with a diuretic intervention and 12 (18%) with guideline-directed medical therapy augmented. In this implementation study, clinicians contacted and assessed nearly all patients at high risk for HF decompensation based on CIED remote monitoring data and intervened in more than 2/3s. A randomized clinical trial is needed to determine whether this algorithm and subsequent intervention improves clinical outcomes., Competing Interests: Declaration of competing interest The authors have no competing interests to declare., (Published by Elsevier Inc.)

Atmospheric Micro- and nano-plastics (MNPs) can be easily inhaled and ingested by humans and have become a global health concern. With the development of instruments and techniques, an increasing number of sampling and analytical methods have been applied to study airborne MNPs. Active samplers and passive collectors are used to collect suspended aerosols and atmospheric depositions. Microscopes and scanning electron microscopy (SEM) have been used to physically identify the MNPs, while Fourier transform infrared (FTIR), Raman spectroscopy, and Pyrolysis gas chromatography-mass spectrometry (Py-GC/MS) are used to identify the polymer compositions of the MNPs. However, the diversity of methods and strategies has greatly limited our ability to compare results and assess exposure risks. In this review, we extracted data from PubMed, Embase, and Scopus from 2018 to 2024 that reported sampling methods, analytical techniques, and abundance/deposition of airborne MNPs. Through a systematic review of the included 140 articles, we emphasized the advantages and limitations of different methods for collecting and analyzing airborne MNPs. In addition, we provided an in-depth analysis of the performance of specific methods across different airborne environments. Furthermore, the current knowledge regarding the abundance, deposition, exposure risks of airborne MNPs, and exposure risk assessment models has been discussed. Finally, we provide concrete recommendations for standardization of methods. This review identified knowledge gaps and recommended future research directions for exposure assessment of airborne MNPs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Nonischemic dilated cardiomyopathy (NIDCM) is associated with an increased risk of atrial fibrillation (AF) and stroke, especially in patients with high CHA 2 DS 2 -VASc. We aimed to identify variables associated with incident AF or stroke using left atrial deformation analysis and its prognostic value added to CHA 2 DS 2 -VASc score. Patients with NIDCM and left ventricular ejection fraction <50% in sinus rhythm were included between January 2015 and December 2019. Left atrial volume index (LAVI) and atrial strain were used in combination with the CHA 2 DS 2 -VAS score to predict ischemic stroke or incident AF. Proportional hazards Cox regression was used to provide hazard ratios (HRs). There were 338 patients included. After a median follow-up of 3.6 years, the end point occurred in 41 patients (12.1%). LAVI outperformed other echocardiographic parameters, with a significant improvement in risk reclassification compared with CHA 2 DS 2 -VASc alone (net reclassification index 0.6, increase in Harrell's C from 0.63 to 0.73, p = 0.003), and remained significant after multivariate adjustment. LAVI was associated with both components of the end point separately. The best cutoff for LAVI was 44 ml/m 2 . LAVI ≥44 ml/m 2 increased the risk of the end point among those with CHA 2 DS 2 -VASc ≥3 (HR 6.0, 95% confidence interval 2.6 to 13.5) but not in those with CHA 2 DS 2 -VASc <3 (HR 1.2, 95% confidence interval 0.3 to 4.5). Competing risk analysis did not alter the results. In conclusion, LAVI might be used to assess the risk of incident AF or stroke in NIDCM. Patients with LAVI ≥44 ml/m 2 and CHA 2 DS 2 -VASc ≥3 could be at high risk of AF and stroke and may benefit from more intensive surveillance., Competing Interests: Declaration of competing interest The authors have no competing interests to declare., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Tools for precise prediction of bleeding risk in patients undergoing percutaneous coronary intervention (PCI) with cangrelor are lacking., Methods: Consecutive patients undergoing PCI and treated with cangrelor in 7 centers were retrospectively enrolled. The primary endpoint was Bleeding Academic Research Consortium (BARC) BARC 2, 3, or 5 bleeding 48 h after PCI. Predictors of BARC 2-5 bleeding were identified in a derivation cohort and combined into a numerical risk score. Discrimination and calibration were assessed in the derivation and validation cohorts. A threshold to define high bleeding risk (HBR) was identified and its diagnostic accuracy was compared with that of currently recommended bleeding risk scores., Results: 1071 patients undergoing PCI with cangrelor were included. Fifty-four patients (5 %) experienced a BARC 2-5 bleeding, of whom 24 (44 %) from the access site. Age ≥ 75 years (odds ratio [OR] 2.58, 95 % confidence interval [CI] 1.21-5.48, p = 0.01), acute coronary syndrome at presentation (OR 8.14, 95 % CI 2.28-52, p = 0.01), and femoral access (OR 6.21, 95 % CI 2.71-14, p < 0.001) independently predicted BARC 2-5 bleeding at 48 h after PCI. The three items were combined to form a new risk score, the ICARUS score, showing good discrimination in both the derivation (area under the curve [AUC] 0.78) and internal validation (AUC 0.77) cohorts, and excellent calibration. An ICARUS score > 9 points accurately identified patients at HBR, showing better discrimination than other risk scores., Conclusions: A risk score based on age, clinical presentation and access site, predicts the risk of periprocedural bleeding in patients receiving cangrelor (ClinicalTrials.gov ID: NCT05505591)., (Copyright © 2024. Published by Elsevier B.V.)

Background: Chagas cardiomyopathy (CCM) is increasingly prevalent in developed countries due to migration from endemic areas. Accurate risk stratification is crucial due to the variable clinical course of CCM., Objective: To analyze the association between Rassi score progression and electrophysiology study (EPS) changes in CCM patients., Methods: This prospective, observational cohort study involved CCM patients from two tertiary hospitals. Patients were classified as low, intermediate, or high risk based on the Rassi score. Data collected included demographics, clinical history, and diagnostic tests. EPS assessed AH, HH, and HV intervals, and inducibility of ventricular arrhythmias. Follow-ups were at 30 days and six-month intervals, with individualized discussions for cardiac implantable electric devices (CIED) based on EPS results., Results: Of 67 screened CCM patients, 59 underwent EPS. The mean Rassi score was 8.7 ± 4.5 points, with 33.8 % low, 38.9 % intermediate, and 27.1 % high risk. EPS abnormalities were found in 57.6 % of patients, mainly VT/VF (52.5 %). Most induced ventricular arrhythmias were monomorphic VT (80.7 %). A significant association was found between Rassi score risk classification and EPS changes (OR = 1.88 95 %CI: 1.15-3.06 p = 0.02). Higher Rassi scores correlated with VT presence on EPS (p = 0.0036). Syncope/pre-syncope had an OR 2.45 95 %CI:1.21-4.94; p = 0.012, independent of Rassi risk. Decreased ejection fraction was linked to EPS changes (p = 0.04)., Conclusion: EPS changes among CCM was associated with progression of the Rassi score, indicating its utility as a stratification tool. Factors such as the presence of syncope/pre-syncope, decreased LVEF and wall motion abnormalities emerged as independent predictors within Rassi scores for changes in EPS., Competing Interests: Declaration of competing interest The authors have declared that no competing interests exist related to this project., (Copyright © 2024. Published by Elsevier B.V.)

Introduction: The BE-ALIVE score is an additive scoring system for estimating 30-day mortality in patients presenting with an acute coronary syndrome (ACS) [1]. However, it had only previously been tested on an internal validation cohort. The aim was to assess the scoring system on an external validation cohort., Methods: The scoring system comprises six domains: (1) Base Excess (1 point for < -2 mmols/L), (2) Age (<65 years: 0 points, 65-74: 1 point, 75-84: 2 points, ≥ 85: 3 points), (3) Lactate (<2 mmols/L: 0 points, 2-4.9: 1 point, 5-9.9: 3 points, ≥ 10: 6 points), (4) Intubated & Ventilated (2 points), (5) Left Ventricular function (normal or mildly impaired: -1 point, moderately impaired: 1 point, severely impaired: 3 points) and (6) External / out of hospital cardiac arrest (1 point). We applied the BE-ALIVE score was applied to 205 consecutive patients at a different institution., Results: Calibration was strong, with an observed to expected ratio of 1.01, a calibration slope of 1.26 and calibration in the large of -0.03. The Spiegelhalter's Z-statistic was -0.95 (p = 0.34). The AUC was 0.95 (0.92-0.98) in the external validation cohort versus 0.90 (0.85-0.95) during internal validation. Overall performance was excellent with a Brier score of 0.07 versus 0.06 during internal validation. The negative predictive value for 30-day mortality of a BE-ALIVE score < 4 was 98 %, with a positive predicted value of a score ≥ 10 of 95 %., Conclusions: The BE-ALIVE score remains a robust predictor of 30-day mortality in an external validation cohort., Competing Interests: Declaration of competing interest None., (Copyright © 2024. Published by Elsevier B.V.)

Background: It is uncertain which lipid-related parameter is most suitable for predicting the risk of cardiometabolic disease (CMD) in individuals with hypertension., Aims: To explore which lipid-related parameter is most suitable for predicting the risk of CMD., Methods and Results: We studied 30,378 patients with hypertension who completed the 2006-2007 Kailuan health examination and followed up until December 31, 2021. In the constructed model, the utilities of lipid-related parameters for the prediction of CMD were compared using the C-index, NRI, and IDI. The best predictor (remnant cholesterol, RC) was identified and the participants were grouped according to RC quartile. Cox proportional hazard analysis was then used to evaluate the relationship between RC and the risk of CMD. During a median follow-up period of 14.7 years (IQR 5.3-15.1), 9502 (31.27 %) participants with hypertension developed CMD. The C-index, NRI, and IDI values for RC were higher than those for the other lipid parameters. After adjustment for multiple potential confounding factors, compared with the quartile (Q)1 RC group, the adjusted hazard ratios for CMD of the Q2-Q4 groups were 1.09 (1.03-1.16), 1.17 (1.11-1.24), and 1.25 (1.18-1.33) (P < 0.0001). Restrictive cubic spline analysis revealed dose-dependent relationships of lipid parameters with the risk of CMD., Conclusions: RC is superior to other lipid parameters for the prediction of the risk of CMD in individuals with hypertension. As the concentration of RC increases, the risk of CMD in such individuals also increases., Competing Interests: Declaration of competing interest The authors declare that they have no competing interests., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: CHA2DS2-VASc score is used to assess thromboembolic risk in patients with atrial fibrillation (AF)/atrial flutter (AFL), however its utilization to predict outcomes and readmission at following discharge in patients undergoing coronary artery bypass grafting (CABG) regardless of AF/AFL presence is understudied. We sought to assess its utility in predicting outcomes, length of hospital stay (LOS), and healthcare-associated costs (HAC) in these patients., Method: The National Readmission Database (NRD) was queried from 2010 to 2017 for patients with/without AF/AFL undergoing CABG using the International Classification of Diseases, Ninth and Tenth editions (ICD-9-&-10). Multiple regression analysis and multivariate analysis using Cox-Hazard analysis were used to evaluate outcomes up to 90-day readmission from discharge, LOS, and HAC against CHA 2 DS 2 -VASc score (cut-off-score:6) were abstracted from the database., Results: Of the 420,458 patients that underwent CABG, 76,859 (18.3 %) were re-admitted to hospital within 90-days from discharge. Statistically significant increase in 90-day all-cause readmissions were demonstrated with increasing CHA 2 DS 2 -VASc score [No AF/AFL vs AF/AFL: score-0 (2.4 % vs1.4 %), score-6 (3.1 % vs 4.5 %, p-value<0.0001]. Similar trends were seen in re-admissions for TIA/Stroke and heart failure. The survival rate for all events were lower with incremental increase in CHA 2 DS 2 -VASc score (score-0 = 100 %; score-6 = 73 %, p-value<0.0001). Greater LOS and HAC was associated with increasing higher CHA 2 DS 2 -VASc score (standardized-beta[β]; no AF/AFL vs AF/AFL: LOS = score-1: 0.08 vs 0.06, score-6: 0.12 vs 0.13. HAC = score-1: 0.02 vs 0.009, score-6: 0.02 vs 0.01, p-value <0.001)., Conclusion: CHA 2 DS 2 -VASc score is an easy-to-use tool that predicts poorer outcomes, higher readmission, longer LOS, higher HAC, not just in patients with AF/AFL undergoing CABG, but also in those without AF/AFL., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Dr. C. Anwar A. Chahal reports a relationship with American Heart Association that includes: funding grants. Dr. C. Anwar A. Chahal reports a relationship with National Institutes of Health that includes: funding grants. Dr. C. Anwar A. Chahal reports a relationship with Mayo Foundation for Medical Education and Research that includes: funding grants. Dr. C. Anwar A. Chahal reports a relationship with Paul and Ruby Tsai Foundation that includes: funding grants. Dr. Virend K. Somers reports a relationship with ResMed that includes: consulting or advisory. Dr. Virend K. Somers reports a relationship with Respicardia that includes: consulting or advisory. Dr. Virend K. Somers reports a relationship with Lilly and Jazz Pharmaceuticals that includes: consulting or advisory. Dr. Virend K. Somers reports a relationship with Sleep Number Scientific Advisory Board that includes: board membership. Other authors have no conflicts if interest to declare., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Current prediction models for mainland Europe do not include ethnicity, despite ethnic disparities in cardiovascular disease (CVD) risk. SCORE2 performance was evaluated across the largest ethnic groups in the Netherlands and ethnic backgrounds were added to the model., Methods: 11,614 participants, aged between 40 and 70 years without CVD, from the population-based multi-ethnic HELIUS study were included. Fine and Gray models were used to calculate sub-distribution hazard ratios (SHR) for South-Asian Surinamese, African Surinamese, Ghanaian, Turkish and Moroccan origin groups, representing their CVD risk relative to the Dutch group, on top of individual SCORE2 risk predictions. Model performance was evaluated by discrimination, calibration and net reclassification index (NRI)., Results: Overall, 274 fatal and non-fatal CVD events, and 146 non-cardiovascular deaths were observed during a median of 7.8 years follow-up (IQR 6.8-8.8). SHRs for CVD events were 1.86 (95 % CI 1.31-2.65) for the South-Asian Surinamese, 1.09 (95 % CI 0.76-1.56) for the African-Surinamese, 1.48 (95 % CI 0.94-2.31) for the Ghanaian, 1.63 (95 % CI 1.09-2.44) for the Turkish, and 0.67 (95 % CI 0.39-1.18) for the Moroccan origin groups. Adding ethnicity to SCORE2 yielded comparable calibration and discrimination [0.764 (95 % CI 0.735-0.792) vs. 0.769 (95 % CI 0.740-0.797)]. The NRI for adding ethnicity to SCORE2 was 0.24 (95 % CI 0.18-0.31) for events and - 0.12 (95 % CI -0.13-0.12) for non-events., Conclusions: Adding ethnicity to the SCORE2 risk prediction model in a middle-aged, multi-ethnic Dutch population did not improve overall discrimination but improved risk classification, potentially helping to address CVD disparities through timely treatment., Competing Interests: Declaration of competing interest All authors declare no conflicting interest., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

The European guidelines advocate a goal-oriented treatment approach in pulmonary arterial hypertension (PAH), based on a comprehensive risk assessment instrument, which has been validated in several PAH subgroups. We investigated its discriminatory ability and explored tricuspid annular plane systolic excursion and revised thresholds to improve its predictability within the adult congenital heart disease (CHD) population. In total, 223 adults (42 ± 16 years, 66% women, 68% Eisenmenger) were enrolled from 5 European PAH-CHD expert centers. Patients were classified as low, intermediate, or high risk at the baseline visit and at follow-up within 4 to 18 months. By the general PAH guidelines instrument, survival did not differ between the risk groups (p-value not significant), mostly because of the skewed group distribution. Reclassifying patients using revised thresholds for N-terminal pro-brain natriuretic peptide and 6-minute walk distance (i.e., low, intermediate, and high as <500, 500 to 1,400, >1,400 ng/L and >400, and 165 to 400 and <165 m, respectively) and use of tricuspid annular plane systolic excursion (low, intermediate, and high as >20, 16 to 20, and <16 mm, respectively) significantly improved the discrimination between the risk groups at baseline and follow-up (p = 0.001, receiver operating characteristic increase from 0.648 to 0.701), reclassifying 64 patients (29%). Irrespective of follow-up risk group, survival was better for patients with higher proportions of low-risk variables. Improvement to a low-risk profile at a median of 9 months of follow-up provided improved survival compared with the survival of patients who remained in the low-risk group. In conclusion, the external validity of general risk instrument for PAH appeared to be of limited discriminatory value in patients with PAH-CHD. We propose a refined risk instrument with improved discrimination for PAH-CHD., Competing Interests: Declaration of competing interest Dr. Bouma reports financial support was provided by Janssen-Cilag. The remaining authors have no competing interests to declare., (Copyright © 2024. Published by Elsevier Inc.)

Background: The prognosis among non-valvular atrial fibrillation (NVAF) patients with different CHA 2 DS 2 -VASc scores in the contemporary Asian population remains unclear. Additionally, there is a lack of research examining the disparities in management patterns, healthcare resource utilization (HCRU), and cost among these patients., Methods and Results: This retrospective cohort study assessed patients diagnosed with NVAF between January 2018 and July 2022. Patients were stratified into 3 cohorts by CHA 2 DS 2 -VASc scores: low-risk, intermediate-risk, and high-risk. One-year incidence rates and cumulative incidence of clinical outcomes (including ischemic stroke [IS], transient ischemic attack [TIA], arterial embolism [AE], and major bleeding [MB]) were calculated. Management patterns, HCRU, and cost were analyzed descriptively. Among 419,490 NVAF patients (mean age: 75.2 years, 45.1 % female), 16,541 (3.9 %) were classified as low-risk, 38,494 (9.2 %) as intermediate-risk, and 364,455 (86.9 %) as high-risk. The one-year incidence rates for IS, TIA, AE, and MB were 12.4 (95 % CI, 12.3-12.5), 1.1 (95 % CI, 1.0-1.1), 0.5 (95 % CI, 0.5-0.5), and 3.1 per 100 person-years (95 % CI, 3.1-3.2), with an increasing trend from the low-risk to the high-risk group, respectively. During follow-up, 16.4 % and 11.1 % of patients in the low-risk and high-risk cohorts received oral anticoagulants (OACs), respectively. In addition, significant differences in HCRU and cost were observed in these three cohorts., Conclusion: This study demonstrates that contemporary Asian NVAF patients with higher CHA 2 DS 2 -VASc scores experience higher incidence of adverse outcomes and increased hospital resource consumption. Additionally, suboptimal management was present across all CHA2DS2-VASc score groups., Competing Interests: Declaration of competing interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

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., (© 2024 The Author(s). Statistics in Medicine published by John Wiley & Sons Ltd.)

Identification of areas of high disease risk has been one of the top goals for infectious disease public health surveillance. Accurate prediction of these regions leads to effective resource allocation and faster intervention. This paper proposes a novel prediction surveillance metric based on a Bayesian spatio-temporal model for infectious disease outbreaks. Exceedance probability, which has been commonly used for cluster detection in statistical epidemiology, was extended to predict areas of high risk. The proposed metric consists of three components: the area's risk profile, temporal risk trend, and spatial neighborhood influence. We also introduce a weighting scheme to balance these three components, which accommodates the characteristics of the infectious disease outbreak, spatial properties, and disease trends. Thorough simulation studies were conducted to identify the optimal weighting scheme and evaluate the performance of the proposed prediction surveillance metric. Results indicate that the area's own risk and the neighborhood influence play an important role in making a highly sensitive metric, and the risk trend term is important for the specificity and accuracy of prediction. The proposed prediction metric was applied to the COVID-19 case data of South Carolina from March 12, 2020, and the subsequent 30 weeks of data., (© 2024 The Author(s). Statistics in Medicine published by John Wiley & Sons Ltd.)

International pet travel and commercial operations have increased animal disease importation risks, including for Leishmania infantum, a deadly parasite of humans and domestic dogs. Collaborating as an interdisciplinary working group, we developed an operational tool for veterinary and public health practitioners to assess and manage L. infantum risk in dogs imported to the United States. Overall risk varies by dog, human, and geographic factors but could be high without proper controls. We determined dog risk management strategies should include application of sand fly insecticides and repellents, sterilization, and treatment. US public health authorities can use a One Health approach to manage L. infantum importation risks via infected dogs.

Background: Despite the favorable prognosis of AJCC stage I/II melanoma patients, up to 20%-30% will develop metastases. Our objective is to predict long-term risk (probability) of recurrence in early-stage melanoma patients., Methods: A Risk Score to predict long-term recurrence was developed using Cox regression based on 2668 patients. Five clinicopathological risk factors were included. The association of the Risk Score with the risk of recurrence was evaluated using parametric models (exponential, Weibull, and Gompertz models) and compared to the Cox model using the Akaike information criterion. The discrimination of the model was measured by time-dependent ROC analyses. A calibration curve was used to evaluate the agreement between predicted and observed recurrence probabilities., Results: The bootstrap adjusted C-index was 0.76 (95% CI, 0.74-0.79) overall and 0.87 (0.83-0.90) and 0.82 (0.78-0.85) at one and two years, respectively, and then remained above 0.70 up to 20 years. The Gompertz model for prediction of survival from the Risk Score showed the best performance and displayed good agreement with the Kaplan-Meier curves. The calibration curve of the Gompertz model showed a good agreement between predicted and observed 2-, 5-, and 10-year risk of recurrence. Population-level analysis demonstrated a significant association of Risk Score with risk of recurrence, with 10-year risks of recurrence of 4.5%, 13.0%, and 33.7% in the first, second, and third tertiles, respectively., Conclusion: We developed a Risk Score to predict long-term risk of recurrence for early-stage melanoma patients. A Gompertz survival model fit to the Risk Score allows for individualized prediction of time-dependent recurrence risk., (© 2024 The Author(s). Cancer Medicine published by John Wiley & Sons Ltd.)

Background: Rejection remains an important cause of morbidity and mortality after pediatric heart transplantation (HT). Endomyocardial biopsy (EMB) is the gold standard for rejection diagnosis, but it comes with procedural risk. The frequency of EMB varies significantly across centers. Since April 2018, our center's surveillance EMB schedule is based on a rejection risk prediction score employing age, pre-HT diagnosis, and panel reactive antibodies (PRA). We aimed to evaluate outcomes in the 1st year post-HT before and after risk score implementation., Methods: Patients who underwent HT at our center at ≤ 18 years of age from January 2015 to December 2020 were reviewed. The primary endpoint was rejection-free survival at 1 year-post- HT. Clinical characteristics were compared for patients transplanted in Era 1 (January 2015-April 2018) and Era 2 (April 2018-December 2020). Cumulative 1-year survival free from rejection and from rejection with hemodynamic compromise (RHC) was compared between eras using Kaplan-Meier survival analysis., Results: 115 patients underwent HT during our study period (52 in Era 1 and 63 in Era 2). There was an increase in VAD utilization between eras (19% in Era 1 vs. 40% in Era 2, p = 0.025), but otherwise no significant difference in demographic or clinical variables between the two eras. No statistically significant difference in freedom from rejection or freedom from RHC was identified between the two eras. There was a 60% reduction in the median number of EMB per patient in the first year post-HT after employing the score (5 in Era 1 vs. 2 in Era 2, p < 0.001)., Conclusions: After employing a rejection risk prediction score, our center decreased the frequency of EMB without worsening early post-HT outcomes, thus establishing the clinical applicability of this tool., (© 2024 The Author(s). Pediatric Transplantation published by Wiley Periodicals LLC.)

Background: Neonatal illness severity scores are not extensively studied for their ability to predict mortality or morbidity in preterm infants. The aim of this study was to compare the Neonatal Sequential Organ Failure Assessment (nSOFA), Clinical Risk Index for Babies-II (CRIB-II), and Score for Neonatal Acute Physiology with Perinatal extension-II (SNAPPE-II) for predicting mortality and short-term morbidities in preterm infants ≤32 weeks., Methods: In this retrospective study, infants born in 2017-2018 with gestational age (GA) ≤32 weeks were evaluated. nSOFA, CRIB-II, and SNAPPE-II scores were calculated for each patient, and the ability of these scores to predict mortality and morbidities was compared. The morbidities were categorized as mod/sev bronchopulmonary dysplasia (BPD), necrotizing enterocolitis (NEC) requiring surgery, early-onset sepsis (EOS), late-onset sepsis (LOS), retinopathy of prematurity (ROP) requiring treatment, and severe intraventricular hemorrhage (IVH). Calculating the area under the curve (AUC) on receiver operating characteristic curves (ROC) analysis to predict and compare scoring systems' accuracy., Results: A total of 759 preterm infants were enrolled, of whom 88 deceased. The median nSOFA, CRIB-II, and SNAPPE-II scores were 2 (0, 3), 6 (4, 8), and 13 (5, 26), respectively. Compared with infants who survived, these three scores were significantly higher in those who deceased ( p  < 0.05). For predicting mortality, the AUC of the nSOFA, SNAPPE-II, and CRIB-II were 0.90, 0.82, and 0.79, respectively. The nSOFA scoring system had significantly higher AUC than CRIB-II and SNAPPE-II ( p  < 0.05). However, short-term morbidities were not strongly correlated with these three scoring systems., Conclusion: In infants ≤32 weeks gestation, nSOFA scoring system is more valuable in predicting mortality than SNAPPE-II and CRIB-II. However, further studies are required to assess the predictive power of neonatal illness severity scores for morbidity.

Improving regulatory confidence and acceptance of in silico toxicology methods for chemical risk assessment requires assessment of associated uncertainties. Therefore, there is a need to identify and systematically categorize sources of uncertainty relevant to the methods and their predictions. In the present study, we analyzed studies that have characterized sources of uncertainty across commonly applied in silico toxicology methods. Our study reveals variations in the kind and number of uncertainty sources these studies cover. Additionally, the studies use different terminologies to describe similar sources of uncertainty; consequently, a majority of the sources considerably overlap. Building on an existing framework, we developed a new uncertainty categorization framework that systematically consolidates and categorizes the different uncertainty sources described in the analyzed studies. We then illustrate the importance of the developed framework through a case study involving QSAR prediction of the toxicity of five compounds, as well as compare it with the QSAR Assessment Framework (QAF). The framework can provide a structured (and potentially more transparent) understanding of where the uncertainties reside within in silico toxicology models and model predictions, thus promoting critical reflection on appropriate strategies to address the uncertainties., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Clinical/methodical Issue: Risk assessment and accurate plaque characterization are key to individual prognosis in coronary artery disease (CAD)., Standard Radiological Methods: The standard of care is cardiac computed tomography (CT), including calcium scoring and coronary CT angiography (CCTA). Diagnosis is based on the CAD-RADS (Coronary Artery Disease-Reporting and Data System) classification., Methodological Innovations: New developments include CT-based fractional flow reserve (CT-FFR) and plaque quantification ("virtual histology")., Performance: A calcium score of 0 indicates an event risk of less than 1% over 10 years [7, 17]. CAD-RADS classes 1 to 5 allow risk assessment compared to patients without coronary plaques [2]. CT-FFR has high accuracy (area under the curve [AUC] 0.90; 95% confidence interval 0.87-0.94) in assessing the hemodynamic significance of stenoses compared with invasive coronary angiography [25]. Plaque quantification has shown that a necrotic core greater than 4% is associated with an almost fivefold increase in 5‑year event risk [29]., Achievements: The presence of obstructive CAD (stenosis > 50%) is a strong prognostic factor. The evaluation of the hemodynamic relevance of 40-90% stenoses by CT-FFR or other functional tests is already guideline-compliant in the USA, but not yet in Germany. Quantitative approaches to measure plaque volume and composition are gaining importance in research and are expected to become relevant in clinical practice., Practical Recommendations: The CAD-RADS 2.0 classification, which also provides therapy recommendations, should be used to assess the extent of CAD., Competing Interests: Einhaltung ethischer Richtlinien. Interessenkonflikt: J. M. Brendel, K. Nikolaou und B. Foldyna geben an, dass kein Interessenkonflikt besteht. Für diesen Beitrag wurden von den Autor/-innen keine Studien an Menschen oder Tieren durchgeführt. Für die aufgeführten Studien gelten die jeweils dort angegebenen ethischen Richtlinien., (© 2024. The Author(s).)

Aim: Arterial stiffness, a significant cardiovascular risk marker, is particularly important in patients with diabetes mellitus (DM). Pulse wave velocity (PWV), a non-invasive measure of arterial stiffness, has emerged as an independent predictor of cardiovascular morbidity and mortality. However, its precise prognostic value in DM patients for cardiovascular risk stratification remains unclear. To address this, a systematic review was conducted., Method: A thorough search of Ovid and Scopus databases was performed for cohort studies on PWV measurements for cardiovascular risk stratification in DM patients. Nine studies were included, examining the relationship between PWV and cardiovascular events or composite endpoints in DM patients asymptomatic of cardiovascular diseases (CVD)., Results: The review revealed that optimal PWV cutoffs to predict composite cardiovascular events ranged from 10 to 12.16 m/s (aortic PWV) and 14 to 16.72 m/s (brachial-ankle PWV). In addition, meta-analysis yielded a HR of 1.15 (95 % CI 1.07-1.24, p < 0.001, I 2  = 70 %) for aortic PWV in predicting cardiovascular events., Conclusion: The assessment of arterial stiffness via PWV shows promise as an early diagnostic marker for CVD in DM patients, aiding in improved disease management. This underscores the potential of PWV in enhancing cardiovascular risk assessment and guiding clinical decisions in this high-risk population, without invasive procedures or radiation exposure., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Minimal change disease (MCD) is a common pathological type of nephrotic syndrome. Relapses of MCD present a significant challenge for patients. This study aims to develop a predictive model for evaluating the probability of relapse in patients with MCD., Methods: This study enrolled 152 patients with biopsy-confirmed MCD, all of whom received exclusive glucocorticoid treatment at the First Affiliated Hospital of Zhejiang University in Hangzhou, China, between October 2012 and April 2021. The Cox regression analysis was utilized to identify the risk factors associated with the relapse in MCD, and a nomogram was constructed to predict the probability of relapse., Results: The results demonstrated that serum immunoglobulin E (IgE) levels > 936 IU/mL, age ≤ 30 years old, estimated glomerular filtration rate (eGFR) < 90 mL/(min × 1.73 m 2 ), serum total cholesterol (TCh) levels > 12.3 mmol/L, and time to remission were independent risk factors associated with relapses in patients with MCD. A nomogram was established and achieved a concordance index of 0.726 (95% CI = 0.659-0.793). The receiver operating characteristic curves demonstrated areas under the curve of 0.771, 0.853, and 0.811 for the prediction of relapse at 1-, 2-, and 3-year intervals after achieving remission in MCD patients respectively. These findings along with the calibration curves indicated the good discrimination and calibration performance of the nomogram in this cohort., The established nomogram provides a valuable tool for the identification of patients with MCD who are at risk of relapse, which may facilitate prompt treatment for these patients.

Background: Cancer-specific survival in older patients with gastric cancer is competitively affected by death from other causes. This study aimed to investigate cancer-specific survival and associated risk factors by competing-risk analysis in older patients with gastric cancer., Methods: The data of this study are from the SEER database, using univariable and multivariable analysis of competitive risk model to weaken the impact of competitive events, explore the risk factors of cancer-specific survival, and developed a nomogram model. Then, the performance of the model is verified by C-index, ROC curve, calibration curve and DCA, and the new model is compared with the traditional TNM stage by NRI and IDI., Results: Our study encompassed a total of 8183 patients, with 5731 in the training cohort and 2452 in the validation cohort. Univariable and multivariable analysis showed that age, years of diagnosis, race, site, SEER stage, TNM stage, surgery, radiation or chemotherapy, LNE, tumor grade and size are independent risk factors for cancer-specific survival in older patients with gastric cancer. Based on the risk factors, we developed a diagram model to predict cancer-specific survival. C-index, ROC curve, calibration curve and DCA also show good results. We compared the new model with the traditional TNM stage model, and the NRI and IDI showed the new model has been significantly improved., Conclusion: This study developed a nomogram to predict the cancer-specific survival of older patients with gastric cancer, which can accurately predict the prognosis and contribute to clinical treatment decision-making., Competing Interests: Declaration of Competing Interest The authors declare no competing interests., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Risk prediction scores are used to guide clinical decision-making. Our primary objective was to externally validate two patient-specific risk scores for 30-day in-hospital mortality using the Multicenter Perioperative Outcomes Group (MPOG) registry: the Pediatric Risk Assessment (PRAm) score and the intrinsic surgical risk score. The secondary objective was to recalibrate these scores., Methods: Data from 56 US and Dutch hospitals with paediatric caseloads were included. The primary outcome was 30-day mortality. To assess model discrimination, the area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve (AUC-PR) were calculated. Model calibration was assessed by plotting the observed and predicted probabilities. Decision analytic curves were fit., Results: The 30-day mortality was 0.14% (822/606 488). The AUROC for the PRAm upon external validation was 0.856 (95% confidence interval 0.844-0.869), and the AUC-PR was 0.008. Upon recalibration, the AUROC was 0.873 (0.861-0.886), and the AUC-PR was 0.031. The AUROC for the external validation of the intrinsic surgical risk score was 0.925 (0.914-0.936) and AUC-PR was 0.085. Upon recalibration, the AUROC was 0.925 (0.915-0.936), and the AUC-PR was 0.094. Calibration metrics for both scores were favourable because of the large cluster of cases with low probabilities of mortality. Decision curve analyses showed limited benefit to using either score., Conclusions: The intrinsic surgical risk score performed better than the PRAm, but both resulted in large numbers of false positives. Both scores exhibited decreased performance compared with the original studies. ASA physical status scores in sicker patients drove the superior performance of the intrinsic surgical risk score, suggesting the use of a risk score does not improve prediction., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Purpose of Review: This review is timely due to the increasing prevalence of obstructive sleep apnea (OSA) among patients undergoing ambulatory surgery, necessitating updated perioperative management strategies to improve outcomes and reduce complications., Recent Findings: Recent studies emphasize the importance of risk stratification using tools like STOP-Bang, highlighting the association between high-risk OSA and increased perioperative complications. Intraoperative management strategies, including the preference for regional anesthesia and careful monitoring of neuromuscular blockade, have been shown to mitigate risks. Postoperative protocols, particularly continuous monitoring, are crucial in preventing opioid-induced respiratory depression., Summary: Effective management of OSA in ambulatory surgery requires a multidisciplinary approach, encompassing preoperative screening, tailored intraoperative techniques, and vigilant postoperative monitoring. Implementing guidelines and protocols can significantly enhance patient safety and outcomes., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

In this study, we aimed to develop and validate a nomogram to predicting the risk of sepsis-associated acute kidney injury (SA-AKI) in patients admitted to emergency departments (EDs). We randomly divided a retrospective dataset of 391 patients with sepsis into a 294-person training cohort and a 97-person validation cohort, and developed three predictive models using multivariate logistic regression analysis and clinical insight. No difference was observed between the three models using the DeLong test and Model 3 was selected as the risk prediction model based on the principle of least inclusion indicators. The use of vasopressor drugs, patient age, platelet count, procalcitonin, and D-dimer levels were included. The training and validation cohorts had a consistency index of 0.832 and 0.866, respectively, indicating high accuracy and stability in predicting SA-AKI risk. The area under the receiver operating characteristic curve was 0.832, showing excellent discrimination. The calibration curves for the training and validation cohorts showed excellent calibration. The decision curve and clinical impact curve analyses showed that the net clinical benefit of using the nomogram was greatest over a probability threshold of 0.05-0.90. In addition, the model showed moderate validity in predicting the 30-day survival and the incidence of major adverse renal events within 30 days. The nomogram developed for SA-AKI risk assessment in patients in EDs showed good discriminability and clinical utility. It can provide a theoretical basis for emergency physicians to prevent SA-AKI.

Aim: To systematically search, evaluate and synthesise the most robust evidence regarding pressure injury prevention in orthopaedic patients admitted to general wards., Design: The present study provides an evidence-based summary of the most robust findings, adhering to the evidence guidelines established by the Center for Evidence-Based Nursing of Fudan University., Method: According to the "6S" model, a systematic search was conducted for literature on pressure injury prevention among orthopaedic patients in general wards. The types of literature included guidelines, clinical decisions, expert Consensus, evidence summaries, etc. The search period covered the time from the beginning of the database up to December 2023., Data Sources: The following databases and resources were systematically searched: Up To Date, JBI, NICE, WOCN, NZWCS, etc. RESULTS: Fifteen literature sources were included, comprising one clinical decision, eight guidelines, one systematic review, and one expert Consensus. In these sources, a comprehensive collection of 34 pieces of best evidence was formed across six key topics: risk assessment, position management, skin care, device used for device-related pressure injury, nutritional assessment, and support, as well as health education and training. Among the evidence gathered, a strong recommendation was made for 18 pieces, while the remaining 16 received a weak recommendation., Conclusion: This study provides a comprehensive synthesis of the most robust evidence on pressure injury prevention in orthopaedic patients, encompassing 34 pieces of evidence that can serve as valuable references for clinical practice. Before implementing this evidence, it is crucial to evaluate the specific contextual factors within different countries and medical institutions, as well as the facilitators and barriers influencing its application by healthcare professionals and patient's preferences. Furthermore, targeted evidence selection should be conducted through careful screening and subsequent adjustments in implementation, thereby offering a more scientifically grounded basis for clinical nursing practice. Future research endeavours should prioritise investigating strategies for effective evidence utilisation., Implications for the Profession and Patient Care: The prevention of pressure injuries poses a significant challenge for orthopaedic patients. This study presents a synthesis of 34 pieces of best evidence to provide guidance on preventive measures for pressure injuries in orthopaedic patients. Adhering to and implementing these 34 pieces of evidence can effectively aid in preventing pressure injuries in clinical practice. This evidence encompasses risk assessment, position management, skin care, device usage for device-related pressure injuries, nutritional support and evaluation, and health education and training, establishing a comprehensive and systematic implementation process. Assessing the risk of pressure injuries during interventions serves as an essential prerequisite for developing effective strategies to prevent such injuries among orthopaedic patients. Ultimately, this study will offer valuable guidance to healthcare professionals worldwide regarding preventing pressure injuries in orthopaedic patients., Impact: Upon admission to the hospital, it is essential to conduct a risk assessment and implement evidence-based, individualised prevention measures for pressure ulcers in patients to prevent their occurrence. This study will provide valuable insights into preventing pressure injuries in orthopaedic patients admitted to orthopaedic wards for healthcare workers worldwide., State: The PRIMA manifest is utilised during the text preparation process., Trail Registration: ES20245365., (© 2024 John Wiley & Sons Ltd.)

Background and Objective: Prosthetic heart valve interventions such as TAVR have surged over the past decade, but the associated complication of long-term, life-threatening thrombotic events continues to undermine patient outcomes. Thus, improving thrombogenic risk analysis of TAVR devices is crucial. In vitro studies for thrombogenicity are typically difficult to perform. However, revised ISO testing standards include computational testing for thrombogenic risk assessment of cardiovascular implants. We present a fluid-structure interaction (FSI) approach for assessing thrombogenic risk of transcatheter aortic valves., Methods: An FSI framework was implemented via the incompressible computational fluid dynamics multi-physics solver of the ANSYS LS-DYNA software. The numerical modeling approach for flow analysis was validated by comparing the derived flow rate of the 29 mm CoreValve device from benchtop testing and orifice areas of commercial TAVR valves in the literature to in silico results. Thrombogenic risk was analyzed by computing stress accumulation (SA) on virtual platelets seeded in the flow fields via ANSYS EnSight. The integrated FSI-thrombogenicity methodology was subsequently employed to examine hemodynamics and thrombogenic risk of TAVR devices with two approaches: 1) engineering optimization and 2) clinical assessment., Results: Simulated effective orifice areas for commercial valves were in reported ranges. In silico cardiac output and flow rate during the positive pressure differential period matched experimental results by approximately 93 %. The approach was used to analyze the effect of various TAVR leaflet designs on hemodynamics, where platelets experienced instantaneous stresses reaching around 10 Pa. Post-TAVR deployment hemodynamics in patient-specific bicuspid aortic valve anatomies revealed varying degrees of thrombogenic risk with the highest median SA around 70 dyn·s/cm 2 - nearly double the activation threshold - despite those being clinically classified as "mild" paravalvular leaks., Conclusions: Our methodology can be used to improve the thromboresistance of prosthetic valves from the initial design stage to the clinic. It allows for unparalleled optimization of devices, uncovering key TAVR leaflet design parameters that can be used to mitigate thrombogenic risk, in addition to patient-specific modeling to evaluate device performance. This work demonstrates the utility of advanced in silico analysis of TAVR devices that can be utilized for thrombogenic risk assessment of other blood recirculating devices., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Danny Bluestein reports financial support was provided by National Institutes of Health. Author Kyle Baylous is a consultant for PolyNova Cardiovascular Inc. Authors Danny Bluestein and Marvin Slepian have an equity interest in PolyNova Cardiovascular Inc. Authors Rodrigo Paz and Marc Horner are employees of ANSYS, Inc., which develops the software for computational modeling and simulation used in the study., (Copyright © 2024 Elsevier B.V. All rights reserved.)