Systemic Risk Research Articles

External validation of the Systematic COronary Risk Evaluation 2 (SCORE2) model in cancer patients

Abstract Background Guidelines recommend cardiovascular disease (CVD) risk stratification before cancer treatment to better identify patients for intensified follow-up or cardioprotective treatment. Only a limited number of CVD risk stratification tools exists for cancer patients which at present is not widely used nor extensively validated. The ESC Guidelines on Cardio-oncology 2022 suggest using traditional CVD models like the SCORE2 (Systematic Coronary Risk Estimation 2). However, external validation in cancer populations is lacking. Purpose Our aim was to study the prevalence of CVD risk factors and incidence of cardiovascular events in a cancer cohort and externally validate the Systematic COronary Risk Evaluation 2 (SCORE2) model in this context. Methods We included 1058 patients from a large-scale populational study without diabetes or established CVD aged 40 to 69 years and diagnosed with cancer between 2006 and 2012. Participants were assessed for cardiovascular risk factors at baseline and followed until Sept 2023. The Norwegian Cancer Registry provided patient specific information about cancer characteristics and therapy. The primary outcome was the combination of myocardial infarction (MI), stroke or CVD mortality, which was retrieved from the local hospitals’ registries and the national causes of death registry. Performance was assessed using smooth calibration curves of predicted and observed risk and Harrel’s C-statistic for discrimination, both corrected for competing risks. SCORE2 was recalibrated by adapting the model with a single multiplicative constant based on the expected-to-observed ratio (E/O-ratio). Results The most common cancer types were gastrointestinal cancer (19%), male genital including prostate cancer (19%) and breast cancer (18%). Mean (SD) age was 58.6 (7.6) years, 54% were female. Prevalence of cardiovascular risk factors are shown in Table 1. In total, 121 (11%) individuals had a CVD event (MIs 53 (44%), strokes 46 (38%) and CVD deaths 22 (18%)) during a median (interquartile range) follow-up of 11.1 (3.4 to 13.1) years, and 360 (34%) died due to non-CVD causes. Calibration plots showed adequate agreement between estimated and observed 10-year prognosis after recalibration (C-statistics 0.685, 95% CI 0.643 to 0.728), Figure 1. E/O-ratio for men was 0.65 and for women 0.63, indicating underestimation of the observed CVD incidence. After recalibration, the median estimated 10-year risk was 8.1% (IQR 5 to 11), 36% had >10% 10-year risk and 9% had >15% 10-year risk. Conclusion SCORE2 underestimated CVD risk in a general cancer population but showed adequate agreement after recalibration and C-statistics aligned with the original external validation cohorts. SCORE2 is useful also in cardio-oncology setting (after recalibration) to identify individuals at higher risk of developing CVD.

Risk sharing framework and systemic tolerance in Indian banks: Double layer network approach

Interconnectedness spreads systemic risk and is critical in enhancing banks’ systemic tolerance through interbank liquidity and lines of credit. Literature on systemic risk has not considered the importance of interconnectedness in providing liquidity to improve banks’ systemic tolerance. As a bank’s resistivity towards systemic disruption depends on its tolerance, the current article develops a model to measure the systemic tolerance of individual banks in a two-layer interbank network using ΔCoVaR. It estimates systemic tolerance distance through a risk-sharing framework and analyzes the significance of macroeconomic and bank-specific factors in explaining systemic tolerance. The results support that systemic tolerance values are higher during the down-cycle than the up-cycle, signaling the importance of interconnectedness in protecting against systemic crises. The empirics further substantiate that risk-sharing distance is lower, and structure is complex with clusters during economic down-cycle. This highlights that banks couple with each other during stressful environments and empirically validate the importance of interbank and lines of credit in enhancing systemic tolerance and, therefore, possess the regulator to develop a robust interbank market through regulatory guidelines.

Impact of right ventricular - pulmonary arterial coupling on mortality after transcatheter aortic valve implantation in patients with aortic stenosis

Abstract Background Aortic stenosis (AS) leads to left ventricle (LV) pressure overload. In more advanced stages of the disease, this pressure, which is transmitted through the pulmonary vasculature, may result in right ventricle (RV) remodeling and eventual dilatation and disfunction. RV failure is associated with impair prognosis, even after relief of the obstruction. The interplay of pulmonary arterial (PA) pressure and RV function can be assess using RV-PA coupling index; in a compensate state RV function is coupled with pulmonary pressure, and this function has a proper response to an increase in pulmonary afterload; in contrast, when RV function uncouples with pulmonary pressure it means that RV function can no longer sustain PA afterload, leading to a decompensate state. RV-PA uncoupling has already been associated with poor prognosis in other heart conditions, such as heart failure or pulmonary hypertension; however, there is still not much evidence on how RV-PA uncoupling prior transcatheter aortic valve implantation (TAVI) impacts on mortality. Purpose Assess the impact of RV-PA uncoupling on all-cause mortality after TAVI in patients with aortic stenosis. Methods In a prospective TAVI registry, patients were included if they had an adequate echocardiographic evaluation prior TAVI. All-cause mortality after the procedure was analyzed in two subgroups, according to their RV-PA coupling status. RV-PA was assess using tricuspid annular plane systolic excursion (TAPSE) and pulmonary arterial systolic pressure (PASP). The cut-off value was 0.39, consistent with other studies. Hazard ratios (HR) are calculated by univariate and multivariate Cox proportional hazard model. Multivariate adjustment included baseline characteristics – including age, gender, hypertension, diabetes, dyslipidemia, atrial fibrillation, and serum albumin –, and Society of Thoracic Surgeons Predicted Risk of Mortality (STS-PROM) and European System for Cardiac Operative Risk Evaluation (EUROSCORE) II. Results A total of 1190 patients underwent TAVI from January 2011 to December 2023; 315 patients were eligible, with mean age 82,24 years (± 8,0), 52% being women, and a mean EUROSCORE II score of 4.0 (± 9,3). The RV-PA cut-off value of 0.39 stratified patients into groups of RV-PA coupling (n = 194/63,6 %) or uncoupling (n = 121/38,4 %). During follow-up time (35,94 months ±25,6), patients with unpaired coupling had a 64% more risk of all-cause mortality in univariate analysis and, after adjusting for the parameters above, a 58% increased risk in multivariate analysis. Table. Conclusions Patients with significant aortic stenosis who had an impair RV-PA coupling prior TAVI had a significant increased risk of all-cause mortality. This suggests the need to incorporate this parameter to our right-side hemodynamics evaluation prior the procedure. Broader experience to determine its application and cut-off value are still needed.

Implications of five different risk models in primary prevention guidelines

Abstract Background A lack of consensus exists across guidelines as to which risk model should be used for the primary prevention of cardiovascular disease (CVD). Purpose The objective of this study was to determine potential improvements in the number needed to treat (NNT) with statins using different risk models in patients eligible for risk stratification. Methods A retrospective observational cohort was assembled from primary care patients in Ontario, Canada between January 1st, 2010, to December 31st, 2014 and followed for up to 5 years. Risk estimation was undertaken in patients 40-75 years of age, without CVD, diabetes, or chronic kidney disease using the Framingham Risk Score (FRS), Pooled Cohort Equations (PCEs), a recalibrated FRS (R-FRS), Systematic Coronary Risk Evaluation 2 (SCORE2), and the low-risk region recalibrated SCORE2 (LR-SCORE2). Results The cohort consisted of 47,399 patients (59% women, mean age 54). The NNT at 5 years with statins was lowest for SCORE2 at 40, followed by LR-SCORE2 at 41, R-FRS at 43, PCEs at 55, and FRS at 65. Models that selected for individuals with a lower NNT recommended statins to fewer, but higher risk patients. For instance, SCORE2 recommended statins to 7.9% of patients (5-year CVD incidence 5.92%). The FRS, however, recommended statins to 34.6% of patients (5-year CVD incidence 4.01%; Figure). Conclusions Newer models such as SCORE2 may improve statin allocation to higher risk groups with a lower NNT.Figure

Redefining cardiovascular risk evaluation: employing the CaRi-Heart validated FAI-score in patients screened with SCORE2 and CAD-RADS 2.0 techniques

Abstract Background Cardiac computed tomography (CCT) has confirmed the fat attenuation index (FAI) as a trustworthy marker for coronary inflammation, notably in relation to plaque vulnerability and progression. The systematic coronary risk evaluation 2 (SCORE2) is a valuable instrument for forecasting the 10-year likelihood of initial cardiovascular disease (CVD) occurrence. This study aims to determine risk re-categorization using CaRi-Heart in comparison to SCORE2 and the coronary artery disease-reporting and data system (CAD-RADS 1.0/2.0). Methods We enrolled patients (INTEL-FAT study) undergoing CCT, who were aged 40-69 years and had no previous history of CVD or diabetes. SCORE2 classified very-high-risk regions as follows: low-moderate risk as <2.5% (<50 years) and <5% (50-69 years), high risk as 2.5 to <7.5% (<50 years) and 5 to <10% (50-69 years), and very-high risk as ≥7.5% (<50 years) and ≥10% (50-69 years). The CaRi-Heart risk assessment categorized low risk as FAI-score ≤75th percentile for the LAD or RCA and <95th percentile for the LCX; medium risk as falling between the 76th and 89th percentiles for LAD/RCA and ≥95th percentile for LCX; and high risk as ≥90th percentile for LAD/RCA. Results 203 patients were included, with a mean age of 58.7 ± 6.78; 143 (70.44%) were male. CaRi-Heart assessment redefined 71.13% (69/97) of individuals from high to low SCORE2 risk, and 40.0% (8/30) from low-moderate to high SCORE2 risk. The weighted Cohen's kappa analysis revealed minimal concordance between SCORE2 and CaRi-Heart (k=-0.043). 19.71% of patients categorized as CAD-RADS 1 in CCT were reassigned to high risk after CaRi-Heart evaluation, and 26.66% of those classified as CAD-RADS 4 were downgraded to low risk. Furthermore, of the CAD-RADS 1 P1/P2 group, 15.38% and of the P3/P4 group, 66.66% were upgraded to high risk. Conversely, 45.45% of CAD-RADS 4 P1/P2 and 15.78% of P3/P4 were reassigned to low CaRi-Heart risk. The Cohen's kappa analysis comparing CAD-RADS 1.0 and 2.0 with CaRi-Heart risk revealed a low concordance (k=0.067 and k=0.014). In comparing SCORE2 risk categories to CAD-RADS classifications, a significant association was found for low-moderate SCORE2 with CAD-RADS 2 (diagnostic odds ratio [DOR] of 11.26; 95% CI: 4.37-29.00; p<0.001), and for high SCORE2 with CAD-RADS 4 (DOR: 0.085; 95% CI: 0.036-0.20; p<0.001), indicating a strong predictive value of the SCORE2 system for certain CAD-RADS classifications. Conclusions The CaRi-Heart method significantly alters risk classifications in comparison to the SCORE2 risk assessment models or the anatomical CAD-RADS 1.0 and 2.0 diagnostic instruments. These results indicate the importance of integrating established scoring systems with additional markers, such as the FAI-score. This integration offers critical understanding into the severity and future course of CAD, assisting in risk stratification and informing therapeutic choices.SCORE2, CAD-RADS and CaRi-Heart risk.Interpretation of the CaRi-Heart® risk.

A direct comparison of non-invasive blood markers of liver fibrosis as associates of cardiovascular risk. The Athens cardiometabolic registry

Abstract Background Non-alcoholic fatty liver disease (NAFLD) is associated with increased risk of cardiovascular disease (CVD). This risk increases further with advanced liver fibrosis. To date, non-invasive tests (NIT) for liver fibrosis risk have not been established as diagnostic or prognostic biomarkers of CVD. Purpose The purpose of the study was to compare NIT of liver fibrosis with respect to their associations with vascular injury and cardiovascular (CV) events. Methods Individuals without clinically overt CVD and patients with CVD (total n=1,692), consecutively recruited in the Athens Cardiometabolic Registry, were analysed in this study. We retrospectively evaluated the association of NIT (i.e. Fibrosis-4 index (FIB-4), NAFLD Fibrosis score (NFS), BARD score) with indices of subclinical arterial injury (i.e. carotid wall thickness and atherosclerotic plaque for subclinical atherosclerosis, pulse wave velocity (PWV), for arterial stiffness) and the incidence of CV events. Patients were followed-up for CV events for a median time of 39 months. Results Elevated FIB-4 (>2.67) was associated with vascular damage [adjusted odds ratio (aOR)=2.97, 95% confidence intervals (CI)= 1.71-5.78 for maximal wall thickness (maxWT) and aOR=4.58, 95% CI=2.44-8.60 for PWV] across the entire study population, including those with or without clinically overt CVD. NFS> 0.675 showed similar associations but lacked significant correlation with arterial stiffness in coronary artery disease patients. FIB-4> 2.67 and BARD> 2 were associated with increased risk of the composite endpoint of CV death, acute myocardial infarction, or coronary revascularization [adjusted hazard ratio, (aHR)=2.00, 95% CI= 1.12-3.55 and aHR=3.36, 95% CI=1.03-11.0 for FIB-4 (n=842) and BARD (n=887) respectively]. FIB-4 and BARD as continuous variables confered incremental prognostic value compared to European Systematic Coronary Risk Evaluation 2 (SCORE2). Conclusion In a population with a wide range of cardiometabolic risk, FIB-4 was associated with both markers of atherosclerotic disease and arterial stiffness as well as with adverse CV events. These data support further investigation of FIB-4 as a biomarker of CV risk.

The role of coronary artery calcium score and european score2 in primary prevention of cardiovascular disease

Abstract Background There is limited evidence about the role of using coronary artery calcium (CAC) score in conjunction with the European SCORE2 (systematic coronary risk evaluation) for the identification of individuals at higher risk of cardiovascular disease. Purpose To evaluate the relationship between CAC score and the European SCORE2 for cardiovascular risk stratification in an asymptomatic population in primary prevention. Methods This is a preliminary analysis from a single-centre, prospective, randomised 1:1, controlled trial assessing the use of CAC score vs standard preventive strategies in asymptomatic individuals undergoing primary cardiovascular prevention. The 10-year risk of cardiovascular events was assessed with either SCORE2 (ages 45-69) or SCORE2-OP (ages 70-89). Subjects were classified as 1) low to moderate risk, 2) high risk, and 3) very high risk according to SCORE2/SCORE2-OP. CAC score was assessed by ECG gated low-dose computed tomography with no contrast administration. A CAC score of zero was considered to reclassify risk one level downward in high or very-high risk patients. CAC score ≥ 100 was used to reclassify risk one level upward in patients with low to moderate risk and a CAC score > 1000 to reclassify risk upward in subjects with high risk. Results A total of 1,252 participants: 627 in the CAC group and 625 in the control group, median age 55 yrs, 25th-75th 50-61 yrs, with availability of SCORE2 and SCORE2-OP were included in this analysis. SCORE2/SCORE 2-OP was similar in the CAC and control groups. Among the subjects in the CAC group, there was a highly significant difference in SCORE2/SCORE 2-OP between participants with CAC score = zero and those with CAC > zero (median 5.6, 25th-75th 3.6-8.55 vs 2.9, 1.8-4.6, p< 0.001) as well as between those with CAC ≥ 100 and those with CAC score < 100 [median 6.8, 25th-75th (10.3-4.5) vs 3.3 (2.0-5.3), p<0.001]. The prevalence of CAC score = zero was 75% in the low to moderate risk group, 47% in the high risk, and 20% in the very high risk, p<0.001. By contrast the prevalence of CAC score ≥ 100 was 7% in the low to moderate risk group, 24% in the high risk, and 45% in the very high risk, p< 0.001. The proportion of patients classified as low to moderate risk group was 72% with CAC score vs 59% without CAC score, high risk 23% with CAC score vs 35% without CAC score, very high risk 5% vs 6% respectively, p<0.001. Using CAC score risk reclassification occurred in 48% downward and 2% upward in originally classified high risk subjects, 7% upward in originally classified low to moderate risk, and 20% downward in originally classified very high risk subjects. Conclusions CAC score may lead to risk reclassification in a substantial proportion of individuals, in particular among those originally classified as high risk by the SCORE2/SCORE2-OP. The cardiovascular risk prediction accuracy of adding CAC score to SCORE2/SCORE2-OP awaits validation at long-term follow-up.

Identification of premature cardiovascular disease using a family-based strategy: a feasibility pilot study

Abstract Background Current guidelines fail to identify and effectively prevent cardiovascular disease (CVD) in young adults. Purpose To assess the feasibility of a systematic cardiovascular risk assessment in first-degree relatives of individuals with premature coronary artery disease (CAD). Method Index patients with obstructive CAD aged ≤ 45 years or ≤ 55 years without standard modifiable cardiovascular risk factor or ≤ 55 years with a 3-vessel coronary disease were prospectively identified among admissions. Pre-existing cases of CVD and prior cardiovascular check-ups were assessed among their first-degree relatives. Siblings and adult-children (≥25 years) without known CVD or active cardiology follow-up were eligible for a first cardiovascular evaluation. Index patients were encouraged to invite their eligible relatives to contact the Cardiology service for consultation. The primary endpoint was the relative’s eligibility for a cardiovascular prevention consultation. Result From September 2022 to June 2023, 137 patients with premature CAD, with 55.5% aged ≤ 45, were invited to initiate cardiovascular screening among their first-degree relatives. Of the 626 identified relatives, 153 (24.4%) had known atherosclerotic disease, primarily CAD (19.6%). Premature onset (before the age of 45) occurred in 5% of first-degree relatives. Among the 352 siblings and adult-children, 48 (13.6%) were already diagnosed with CVD, 68 (19.3%) were treated or followed for primary prevention, and 226 (64.2%) lacked active cardiovascular monitoring or treatment and were eligible for a first cardiovascular check-up (Figure 1). Within 10 months, 11.1% (25/226) of eligible relatives attended a first cardiovascular evaluation. Conclusion This family-based screening strategy for premature CVD demonstrated 1) a significant familial dimension, with 33% of siblings & adult-children already monitored for CVD prevention, and 2) an opportunity for cardiovascular prevention in two out of three young relatives.

Systemic inflammation and risk of death in patients with atherosclerotic cardiovascular disease and chronic kidney disease

Abstract Background Atherosclerotic cardiovascular disease (ASCVD) and chronic kidney disease stage 3 - 4 (CKD) affects 7% and 10% of the Danish population, respectively. Systemic inflammation (SI) contributes to destabilisation of atherosclerotic plaques and is characterized by elevated levels of C-reactive protein (CRP) in the blood. CKD is associated with SI and is independently associated with an increased risk of ASCVD. CRP levels ≥2 mg/L have been identified as a risk factor for mortality and major adverse cardiovascular events (MACE). Purpose To provide real-world evidence on the clinical burden of SI in patients diagnosed with ASCVD and CKD, using national health registers. Method Data from the Danish National Patient Registry from 1994-2022 was used to identify ASCVD patients by ICD-10 codes. CKD was identified by eGFR test results in the range [15 -59mL/min/1.73m2], in the Register of Laboratory Results for Research (RLRR). The latter diagnosis of ASCVD and CKD was set as index date. CRP-test results were extracted from RLRR and only individuals with at least two CRP tests were included. If two CRP-test results ≥2mg/L to < 20mg/L were observed less than six month apart, and within two years of index date, the individual was classified to have SI. The eGFR data from RLRR was available from 2011 onwards, with some regional differences in reporting. Individuals observed with CKD or ASCVD in the first year of eGFR availability were excluded to ensure a study of incident individuals. Individuals using select medications or diagnosed with selected chronic conditions thought to influence CRP levels were excluded. Additional population characteristics were extracted from corresponding national health and administrative registers. Hazard of all-cause mortality and MACE was analysed in a Cox proportional risk regression. Results From 2012 to 2022, a total of 19,162 individuals were eligible for the study population (SI: 13,039, No SI: 6,123). Median follow-up time was 4.1 and 8.2 years for individuals with or without SI, respectively. Median CRP two years before and after index date in the two groups was 7mg/L and 1mg/L. No clinically significant differences were found for demographic or socioeconomic characteristics. Patients with SI had more frequent history of hypertension, atrial fibrillation, COPD, heart failure and Type 2 diabetes before index, and higher risk of hypertension, atrial fibrillation, stroke, heart failure and type 2 diabetes after index. SI population had significantly increased hazard of mortality in a crude model (HR: 2.35, 95% CI: [2.22 – 2.50]), and in adjusted analysis HR: 2.06 ([1.92 - 2.21]). The corresponding hazard ratios for MACE were 1.9 ([1.81 – 2.01]) and 1.66 ([1.57 – 1.77]). The results were consistent across different model specifications and subgroups. Conclusion SI is associated with a significantly higher clinical burden of disease and a higher risk of all-cause mortality.Flowchart of inclusion/exclusionHazard ratio, overall and by subgroup

Impact of organisational injustice on health and wellbeing of female police: A meta-ethnography

Abstract Background Female police officers face more bias, discriminatory treatment, and insufficient support compared to male officers, resulting in poorer health outcomes. This meta-ethnographic review investigates beyond individual responsibilities to explore the dimensions of policing, and their effects on the health and well-being of female police officers. Methods The study reviewed qualitative and mixed-method studies (2000-2022) on the health and well-being of female police officers. Ten databases were searched using keywords related to health, well-being, women, police, and qualitative study. Twenty-one papers were synthesised, analysed, and interpreted using a seven-phase inductive and interpretative meta-ethnographic approach. Results The data analysis unveiled a distinct outcome, indicating a strong correlation and significant impact of organisational injustice on the health and well-being of women in law enforcement. Our research findings imply that organisational injustice, including procedural, relational, distributive, and gendered injustice, notably affects the health and well-being of female officers, with mental health being frequently cited, followed by effects on social, workplace, and physical health. Furthermore, the consequences of these four types of organisational injustice, alongside related cultural, systemic, and structural risk factors, reach beyond the immediate health and well-being of individual female officers. They also hinder various aspects of their professional lives, such as career advancement and maintaining a healthy work-life balance, potentially exacerbating long-term health and well-being issues. Conclusions This review emphasizes addressing organisational injustice and related cultural, systemic, and structural determinants in policing for healthier work environments for female officers. Policy makers must scrutinize gender-neutral policies affecting women, enabling transformative action for safer, supportive, and healthier workplaces. Key messages • Organisational injustice in various forms, significantly impact health and wellbeing of female police officers, necessitating policy reforms. • Addressing organisational injustice embedded in seemingly gender-neutral policies and practices, is vital for ensuring equitable treatment and health promotion of female police officers.

DeLoSo: Detecting Logic Synthesis Optimization Faults Based on Configuration Diversity

Logic synthesis tools are the core components of digital circuit design, which convert programs written in hardware description languages into gate-level netlists, and optimize the netlists. However, the netlist optimization is complex, with numerous optimization parameters to be configured. Any minor optimization faults in logic synthesis tools may cause circuit diagrams to significantly deviate from the original design, posing risks in target systems. We propose DeLoSo, the De tector of Lo gic S ynthesis o ptimization faults, the first method specifically designed to identify potential faults in the optimization processes of logic synthesis tools. DeLoSo relies on netlist differences and parameter variations to guide the generation of diverse Logic Synthesis Optimization Configuration (LSOC) combinations to thoroughly test the optimization process. DeLoSo consists of three components: LSOC generator, which generates diverse LSOC combinations through configuration recombination and mutation; LSOC diversity evaluator, which assesses the diversity of optimization configurations; and LSOC validator, which validates the generated LSOC combinations to discover optimization faults. DeLoSo identified 19 faults in two established logic synthesis tools (i.e., Vivado and Yosys); 15 of them have been fixed by vendors. Particularly, the community maintainers of Yosys have considered incorporating DeLoSo into Yosys’ existing test suite.

Data driven cost-sensitive boosted tree for interpretable banking systemic risk prediction

Systemic risk (SR) in the banking sector poses a significant threat to both the financial system and the real economy. Its inherent characteristics of nonlinearity, non-equilibrium, and interconnectedness make it challenging to analyze using conventional statistical methods. In this paper, a cost-sensitive gradient boosting tree algorithm, FLXGBoost, is proposed for predicting SR. FLXGBoost considers the boosted tree, XGBoost as the base framework, boosting trees as the fundamental framework, guaranteeing the robustness of SR prediction. Additionally, to tackle the challenge of extreme data imbalance prevalent in SR prediction tasks, a cost-aware loss function, focal loss, is embedded into the boosted tree to enable FLXGBoost a risk-aware fashion. Moreover, a tree-derived interpretable algorithm SHAP is incorporated into this cost-sensitive solution, making FLXGBoost an accurate and interpretable risk-aware model. Experimental results on a financial risk prediction dataset pertaining to banking SR evince the capacity of FLXGBoost to significantly reduce the misclassification rate of risk banks, thereby mitigating substantial losses attributed to erroneous predictions of risky scenarios. Moreover, compared with classical imbalanced machine learning-based SR prediction approaches, the diverse evaluation metrics of FLXGBoost show that it is a competitive solution for accurate SR prediction. Besides, the explanatory analysis further demonstrates that FLXGBoost is a promising solution to address the issue of biased predictions in imbalanced banking SR in the interpretation perspective.

ORGANIZATION OF COUNTERMEASURES AGAINST THE NEGATIVE IMPACT OF RISKS IN LOGISTICS TRANSPORT SYSTEMS

The article is devoted to the issue of effective management decision-making in the organization of counteracting the negative consequences of the impact of risks in logistics transport systems. The purpose of the article is to identify risks in the logistics transport system and provide adaptive information on risk management strategies and recommendations. Modernization of the management mechanism based on risk management tools is relevant to ensure the efficiency and reliability of the logistics transport system at all its levels. The study established the fundamental characteristics of the risk management process and developed a set of management measures to reduce transport risks for logistics transport systems. This set of measures significantly affects the reduction of the negative impact of risks on each of the components of the transport and logistics system at different levels of management and is the basis for the integration of management methods, models and tools into a single mechanism, which is a systematic approach to risk management of the logistics transport system. The results of this study create a comprehensive basis for risk management of the logistics transport system. The results of this study indicate that the proposed systematic approach to risk management of the logistics transport system can be defined as an integrated management of business processes related to the promotion of products and the corresponding flows from their source to the final consumer. The effectiveness of this approach has been demonstrated in achieving optimal efficiency of transport enterprises. In the light of the above considerations, the implementation of this systemic approach serves to create an appropriate organizational basis for the implementation of countermeasures against the negative consequences of the impact of risks in logistics transport systems. In essence, it is a risk management tool.

CNS relapse in high-grade B-cell lymphoma with MYC and BCL2 rearrangements and dark-zone signature–expressing DLBCL

AbstractHigh-grade B-cell lymphoma with MYC and BCL2 rearrangements (HGBCL-DH-BCL2), or “double-hit lymphoma,” has been associated with a high risk of central nervous system (CNS) relapse. However, historic estimates are impacted by selection bias. We report CNS relapse rates associated with HGBCL-DH-BCL2 from a population-based cohort with complete fluorescence in situ hybridization testing, as well as diffuse large B-cell lymphoma morphology (DLBCL) tumors expressing the dark-zone gene expression signature (DZsig), which was originally derived from HGBCL-DH-BCL2. The 2-year CNS relapse risk in HGBCL-DH-BCL2 was 6.8%. CNS relapses were early, predominantly leptomeningeal (73%), and co-occurred with systemic relapse (64%). High-risk CNS International Prognostic Index (CNS-IPI) and concordant bone marrow involvement were associated with an elevated CNS relapse risk in HGBCL-DH-BCL2. The “refined cell-of-origin” classification assigned 20% of DLBCL morphology tumors with germinal center B-cell–like phenotype (GCB-DLBCL) into a distinct subgroup based on DZsig expression (DZsig+). CNS relapse risk in DZsig+ (2 year: 6.4%) was independent of HGBCL-DH-BCL2 status and was further stratified by the CNS-IPI. CNS relapse in DZsig-negative GCB-DLBCL was rare (2-year risk, 1.4%; P = .04 vs DZsig+) and exclusively parenchymal. Altogether, the CNS relapse risk in HGBCL-DH-BCL2 is lower than previously reported, and DZsig refines risk stratification in GCB-DLBCL.

Evaluation of antibiotics resistance and transmission risk of Escherichia coli in rice-frog coculture system

In order to assess the antibiotic resistance of Escherichia coli and its transmission risk in a rice-frog coculture system in Zhejiang Province, this study collected E. coli from isolated soil, field water, and frog feces from the rice-frog coculture systems in four different areas of Zhejiang Province. The collected isolates were identified by 16S rRNA sequencing, while their antibiotic-resistant phenotypes were determined by Kirby-Bauer (K-B) method. PCR was used to identify the antibiotic-resistant genotypes and integrons, while conjugative transfer experiments were used to assess resistance transmission characteristics. The results showed a high prevalence of antibiotic resistance in the 82 strains of E. coli tested, primarily against tetracycline, sulfisoxazole, amoxicillin, and erythromycin. Most of these strains exhibited multidrug resistance, with the Fuyang area demonstrating the highest resistance rate compared to the other three areas. Further PCR analysis identified the sul1 gene as the most frequently detected resistance gene (63.41%), followed by blaTEM, tetA, and tetB. Among the 16 antibiotic resistance genes (ARGs) detected, the Fuyang isolates consistencly exhibited higher detection rate of 9 ARGs in comparison to the other regions. Additionally, the integrase gene intI1 displayed the highest detection rate, with 14 strains (34.15%) of integrase-positive bacteria carrying gene cassettes. Four different gene cassette compositions were observed, with dfrA1-aadA1 and dfrA17-aadA5 being the most common combinations. Conjugative transfer experiments demonstrated successful transfer of gene cassettes in 4 out of 14 donor bacteria, with conjugation transfer frequencies ranging from 4.32×10-5 to 7.13×10-4. These findings revealed the severity of resistance in the Fuyang area among the four regions. Integrons play a significant role in mediating the resistance to multiple antibiotics in E. coli, facilitating the potential spread of resistance gene cassettes between different bacteria. Overall, this study provides valuable insights into the resistance status and transmission characteristics of E. coli in the rice-frog coculture system in Zhejiang Province, providing a theoretical basis for ensuring the food safety of rice crops.

Research on the Feasibility of Machine Learning Methods in Stock Price Prediction

Abstract: Stock price prediction has always been an important topic in financial research. Accurate price prediction can not only help investors make informed investment decisions but also enhance market stability and reduce systemic risk. In recent years, with advancements in computing technology and data science, machine learning methods have been increasingly applied in the financial field. Compared to traditional methods, machine learning methods can better handle high-dimensional, nonlinear, and large datasets, thus demonstrating higher prediction accuracy and applicability in stock price prediction.This paper reviews relevant literature and selects five models for empirical research: Support Vector Machine (SVM), Long Short-Term Memory network (LSTM), LightGBM, a combination of LSTM and LightGBM, and Convolutional Neural Network (CNN). The effectiveness of these models in predicting the stock price of Meituan-W (3690) was analyzed and compared in detail. The experimental results show that the LightGBM model performs best in terms of Mean Squared Error (MSE), Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE), proving its significant advantages in handling large-scale, high-dimensional, and nonlinear data. By comparing the prediction results of different models, this paper explores the strengths and weaknesses of each model and their feasibility and effectiveness in practical applications. Machine learning methods have significant potential in stock price prediction, model selection needs to comprehensively consider data characteristics, computational resources, and practical application scenarios.

The Life Cycle of Systemic Risk and Crises

The Life Cycle of Systemic Risk and Crises

Distribution and associated factors of choroidal thickness in highly myopic eyes-a real-world study based on a Chinese population.

To measure the subfoveal choroidal thickness (SFCT) in highly myopic eyes at different locations using enhanced depth imaging spectral-domain optical coherence tomography (EDI SD-OCT). To identify the ocular and systemic risk factors associated with choroidal thinning in high myopia. Based on the Beijing Eye Study, a detailed ophthalmic examination was performed including EDI SD-OCT for the measurement of SFCT. OCT images were obtained from 103 highly myopic eyes (≥ -6.00 dioptres) and 227 normal eyes randomly selected from the baseline population, matched for age and sex. The mean SFCT was 110.6 ± 85.2 μm in highly myopic eyes (range, 3-395 μm). Mean regional choroidal thickness was lowest on the nasal and inferior sides of the macula, and slightly higher on the temporal and superior sides than at the fovea. On multivariate analysis, SFCT was associated with age (b = -0.48; P < 0.001), axial length (b = -0.44; P < 0.001), gender (b = -0.31; P < 0.05) and staphyloma (b = -0.26; P = 0.05). In highly myopic eyes, SFCT decreased by 5.1 μm/year of age, by 9.2 µm/D of myopia, and by 22.6 µm/mm of axial length. The SFCT decreases with age and increased axial length in highly myopic eyes. The formation of a posterior staphyloma has been identified as a major contributor to choroidal thinning and is therefore a reliable indicator for risk management. The involvement of choroidal abnormalities may be a significant factor in the development of myopic degeneration.

Market-Consistent Valuation and Capital Assessment for Demographic Risk in Life Insurance: A Cohort Approach

We explore the quantification of demographic risk in accordance with the market-consistent actuarial valuation principles. Our contribution includes closed formulas for assessing the inflows and outflows of an insurance policy portfolio using a cohort approach. To maintain versatility, we address both traditional and equity-linked policies, providing a market-consistent valuation of liabilities. Subsequently, we compute the capital requirement for idiosyncratic risk (linked to accidental mortality) and systematic risk (trend risk), presenting an approach that allows consideration of the risks at cohort level. Specifically, we evaluate the minimum capital using an annual time horizon, a 99.5 % confidence level, and the Value at Risk as the risk measure, developing a framework aligned with the European Solvency II regulation for insurance and reinsurance companies. Moreover, the model can be easily adapted to accommodate other regulatory frameworks, incorporating specific rules and accounting principles relevant to diverse jurisdictions worldwide. The numerical analysis and the sensitivities reveal that the accidental volatility of policyholders’ deaths is influenced by the inherent characteristics of the cohort’s policies, the age of policyholders, and the variability of sums insured. Furthermore, trend risk is contingent on both accidental volatility and the longevity forecasting model employed.

Price-mediated contagion with endogenous market liquidity

AbstractPrice-mediated contagion occurs when a positive feedback loop develops following a drop in asset prices which forces banks and other financial institutions to sell their holdings. Prior studies of such events fix the level of market liquidity without regards to the level of stress applied to the system. This paper introduces a framework to understand price-mediated contagion in a system where the capacity of the market to absorb liquidated assets is determined endogenously. In doing so, we construct a joint clearing system in interbank payments, asset prices, and market liquidity. We establish mild assumptions which guarantee the existence of greatest and least clearing solutions. We conclude with detailed numerical case studies which demonstrate the, potentially severe, repercussions of endogenizing the market liquidity on system risk.