Development Of Risk Assessment Tool Research Articles

Applying Neural Networks to Analyse Inflammatory, Sociodemographic, and Psychological Factors in Non-Melanoma Skin Cancer and Colon Cancer: A Statistical and Artificial Intelligence Approach.

Background/Objectives: Chronic inflammation and psychosocial factors significantly influence cancer progression and patient behavior in seeking medical care. Understanding their interplay is essential for enhancing early detection and developing personalized treatment strategies. This study aims to develop a comprehensive patient profiling model by comparing non-melanoma skin cancer (NMSC) and colorectal cancer (CRC). The goal is to identify common and distinct patterns in inflammation and psychosocial factors that affect disease progression and clinical presentation. Methods: We conducted a comparative analysis of patients diagnosed with NMSC and CRC, integrating clinical data with sociodemographic and psychological assessments. Advanced neural network algorithms were employed to detect subtle patterns and interactions among these factors. Based on the analysis, a cancer risk assessment questionnaire was developed to stratify patients into low-, moderate-, and high-risk categories. Results: Patients with low systemic inflammation and adequate vagal tone, supported by a stable family environment, demonstrated heightened sensitivity to subclinical symptoms, enabling earlier diagnosis and timely intervention. Conversely, patients with high systemic inflammation and reduced vagal tone, often influenced by chronic stress and unstable family environments, presented at more advanced disease stages. The developed risk assessment tool effectively classified patients into distinct risk categories, facilitating targeted preventive measures and personalized therapeutic strategies. Neural network profiling revealed significant interactions between biological and psychosocial factors, enhancing our understanding of their combined impact on cancer progression. Conclusions: The integrated profiling approach and the newly developed risk assessment questionnaire have the potential to transform cancer management by improving early detection, personalizing treatment strategies, and addressing psychosocial factors. This model not only enhances clinical outcomes and patient quality of life but also offers a framework adaptable to other cancer types, promoting a holistic and patient-centered approach in oncology.

Meta-Analysis: Prevalence of Frailty and Associated Adverse Events in Inflammatory Bowel Diseases.

The number of adults aged over 60 years with inflammatory bowel disease (IBD) is increasing. Frailty, rather than chronological age, may be a better predictor of adverse health outcomes. To summarise current knowledge about frailty in adults with IBD including the prevalence and associations of frailty and IBD-related adverse outcomes. We performed an electronic search of MEDLINE, EMBASE and EMBASE Classic databases using search terms for IBD and frailty from inception to 14 February 2024. All studies involving adults aged ≥ 16 with a confirmed diagnosis of IBD that included a frailty assessment were eligible for inclusion. We included 23 observational studies involving 1,893,448 adults. Risk of bias was low for 18 studies and moderate for five. Twelve methods of frailty assessment were used, the most common being the Hospital Frailty Risk Score. Pooled prevalence of frailty in IBD patients was 18% (95% confidence interval (CI) 12.4%-25.6%). Meta-analysis of unadjusted events data demonstrated that frailty increased the risk of infection-related admissions following treatment in two studies (relative risk (RR) 1.9; 95% CI 1.2-3.0), post-operative morbidity in three (RR 2.0; 95% CI 1.4-2.7) and mortality in seven (RR 4.3; 95% CI 2.6-7.4). Frailty is common in patients with IBD and is associated with IBD-related adverse outcomes including infection-related admissions following treatment, post-operative morbidity and death. Future work should focus on developing risk assessment tools to better support decision making for older people with frailty and IBD.

Risk factors and characteristics of intraoperative pressure injuries caused by medical devices and adhesives: A case-control retrospective study.

Undesirable injuries during the intraoperative period, such as pressure injuries caused by improper positioning, medical devices, or adhesive tapes, can lead to patient harm and decreased satisfaction. This study aims to identify the risk factors of pressure injuries during the intraoperative period and the characteristics of these injuries. A retrospective case-control study was conducted at King Khaled University Hospital in Riyadh, Saudi Arabia. Data were collected from the hospital incident reporting system and electronic medical records for incidents reported from January 1, 2022 to December 31, 2022. Inclusion criteria consisted of all patients with a reported pressure injury, including pressure ulcers, medical adhesive-related skin injuries, or medical device-related pressure injuries, occurring at least once during surgery. Among the 113 patients, 57 (50.44%) had intraoperative pressure injuries (cases), while 56 (49.56%) did not (controls). The most common locations for pressure injuries were the lips (33.33%). Most of these injuries were classified as Medical Adhesive-Related Skin Injury (61.40%). Stage 1 injuries were observed in 47 cases (82.46%), while Stage 2 injuries were observed in 10 cases (17.54%). Duration of surgery and device tightness were identified as significant risk factors (P < 0.001). This case-control study identified the duration of surgery and device tightness as significant risk factors for intraoperative pressure injuries. The findings emphasize the importance of implementing evidence-based prevention strategies. Healthcare professionals should prioritize staff education and training, while future research should focus on conducting prospective, multicenter studies and developing risk assessment tools and innovative medical devices.

Genetic Testing Among Breast Cancer Patients in the Eastern Region of Saudi Arabia: Single-Center Experience

BackgroundGenetic testing for persons with a heightened likelihood of harboring a germline mutation permits early identification and appropriate management. This study aimed to identify the proportion of breast cancer (BC) patients who were offered genetic testing and the prevalence of BRCA mutations among them. Additionally, we assessed the demographic and clinical features of BC patients in the Eastern Region of Saudi Arabia.Materials and MethodsData from 2535 patients with BC were retrieved from the registry between 2017 and 2021. The data were analyzed and presented using univariate and bivariate statistics. Odds ratios and 95% confidence intervals using logistic regression analysis were computed to identify the predictors of BRCA testing.ResultsPatients with BC ranged in age from 18 to 103 years, and the mean age was 49.60 ± 12.14 years. BC was detected in men in 29 (1.1%) cases. Among diagnosed patients with BC, a total of 96 (3.7%) patients underwent testing for BRCA gene mutations. Of them, 36 (37.5%) patients had a BRCA gene mutation. The likelihood of undergoing BRCA testing was higher for those who were diagnosed with the condition before the age of 50, patients who were referred from private institutions, and patients with a history of previously diagnosed cancer. The likelihood of conducting BRCA testing was significantly lower among those with distant metastases.ConclusionThe proportion of BRCA testing among BC patients was found to be relatively low. The development of a cost-effective, locally developed risk assessment tool that incorporates genetic counseling and testing for those with a familial predisposition to BC is imperative.

Assessing risk indicators of intimate partner femicide considering victim's coping strategies to violence: A dynamic multilevel linear mixed model based on genetic algorithms

Intimate partner femicide (IPF) is a grave social and health concern affecting women worldwide, with approximately 30,000 deaths annually at the hands of their current or former intimate partners. Previous studies have focused on identifying risk factors for IPF and developing risk assessment tools to identify high-risk cases. However, an important aspect that has been overlooked in these studies is victims' coping strategies in response to intimate partner violence. Understanding victims' coping strategies can provide valuable insights into how they deal with the abuse and can inform the development of effective interventions and prevention strategies. This study aims to address this gap by developing a multilevel linear mixed model (LMM) to analyze the impact of engagement and disengagement coping on the likelihood of IPF and identify common and specific IPF risk indicators for these coping strategies. A total of 491 Spanish cases of violence against women by current or former intimate partners were analyzed from penal sentences issued by Spanish provincial and supreme courts from 2019 to 2022. The LMM model obtained from the study has competitive performance in identifying IPF and non-IPF cases, including risk indicators of prior history of injuries, history of sexual aggression, frequency and escalation of violence, physical violence, place of crime, lonely place of crime, and community presence. Victims with engagement coping and disengagement coping share some risk indicators, while others belong to just one category. Overall, the results suggest that victims with disengagement coping are more predisposed to suffer IPF than victims with engagement coping. This evidenced-based knowledge emphasizes the significance of considering coping strategies in predicting and preventing IPF, with further implications discussed at the end of this paper.

Preoperative glycaemic control, number of pain locations, structural knee damage, self-reported central sensitisation, satisfactionand personal control are predictive of 1-year postoperative pain, and change in pain from pre- to 1-year posttotal knee arthroplasty.

The aim of this study was to identify preoperative predictors for 1-year posttotal knee arthroplasty (TKA) pain and pre- to post-TKA pain difference in knee osteoarthritis (KOA) patients. From March 2018 to July 2023, this prospective longitudinal cohort study enrolled KOA patients awaiting TKA from four hospitals in Belgium and the Netherlands. Different biopsychosocial predictors were assessed preoperatively by questionnaires and physical examinations (input variables). The Knee injury and Osteoarthritis Outcome Score (KOOS) subscale pain was used to measure pain intensity. The absolute KOOS subscale pain score 1-year post-TKA and the difference score (ΔKOOS = 1-year postoperative - preoperative) were used as primary outcome measures (output variables). Two multivariable linear regression analyses were performed. Two hundred and twenty-threeparticipants were included after multiple imputation. Worse absolute KOOS subscale pain scores 1-year post-TKA and negative or closer to zero ΔKOOS subscale pain scores were predicted by self-reported central sensitisation, lower KOA grade and preoperative satisfaction,and higher glycated haemoglobin, number of pain locationsand personal control (adjusted R2 = 0.25). Additional predictors of negative or closer to zero ΔKOOS subscale pain scores were being self-employed, higher preoperative pain and function (adjusted R2 = 0.37). This study reports different biopsychosocial predictors for both outcomes that have filtered out other potential predictors and providevalue for future studies on developing risk assessment tools for the prediction of chronic TKA pain. The protocol is registered at clinicaltrials.gov (NCT05380648) on 13 May 2022. Level II.

Machine learning based peri-surgical risk calculator for abdominal related emergency general surgery: a multicenter retrospective study.

Currently, there is a lack of ideal risk prediction tools in the field of emergency general surgery (EGS). The American Association for the Surgery of Trauma recommends developing risk assessment tools specifically for EGS-related diseases. In this study, we sought to utilize machine learning (ML) algorithms to explore and develop a web-based calculator for predicting five perioperative risk events of eight common operations in EGS. This study focused on patients with EGS and utilized electronic medical record systems to obtain data retrospectively from five centers in China. Five ML algorithms, including Random Forest (RF), Support Vector Machine, Naive Bayes, XGBoost, and Logistic Regression, were employed to construct predictive models for postoperative mortality, pneumonia, surgical site infection, thrombosis, and mechanical ventilation >48 h. The optimal models for each outcome event were determined based on metrics, including the value of the Area Under the Curve, F1 score, and sensitivity. A comparative analysis was conducted between the optimal models and Emergency Surgery Score (ESS), Acute Physiology and Chronic Health Evaluation II (APACHE II) score, and American Society of Anesthesiologists (ASA) classification. A web-based calculator was developed to determine corresponding risk probabilities. Based on 10,993 patients with EGS, we determined the optimal RF model. The RF model also exhibited strong predictive performance compared with the ESS, APACHE II score, and ASA classification. Using this optimal model, we developed an online calculator with a questionnaire-guided interactive interface, catering to both the preoperative and postoperative application scenarios. We successfully developed an ML-based calculator for predicting the risk of postoperative adverse events in patients with EGS. This calculator accurately predicted the occurrence risk of five outcome events, providing quantified risk probabilities for clinical diagnosis and treatment.

The reality of occupational harm incurred by Japanese home health care nurses, the hazardous situations they face, and protective measures: a cross-sectional study

Objectives: To gain a comprehensive understanding of the occupational hazards encountered by home health care nurses in Japan and to elucidate the reality of harm they incur, the hazardous situations, and the protective measures taken Methods:A questionnaire survey of managers of home health care nursing agencies in Japan was conducted, and 355 valid responses were obtained. The survey questions concerned the occupational hazards experienced by home health care nursing staff. The occupational hazards were classified into 6 categories, and responses were obtained regarding harm, hazardous situations, and protective measures in each category Results: The types of harm that occurred at highest rates during the previous 3 years were emotional abuse by the patient or their family members, lower back pain resulting from improper posture while providing care, sexual harassment by the patients and their family members, automobile accidents while traveling to home care sites, and allergic reactions to the environment at home care sites. Some hazardous situations were caused by the unique environments of home care sites Conclusions: In order to prevent the occurrence of harm, the development of risk assessment tools, educational initiatives to increase awareness of occupational hazards, and consideration of the financial and technical support that will enable the use of assistive devices in the practice of nursing techniques were considered necessary. The development of effective guidelines and manuals specific to the occupational hazards encountered by home health care nurses is an important challenge

Premorbid intelligence quotient and school failure as risk markers for bipolar disorder and major depressive disorder

Mood disorders significantly impact global health, with MDD ranking as the second leading cause of disability in the United States and BD ranking 18th. Despite their prevalence and impact, the relationship between premorbid intelligence and the subsequent development of BD and MDD remains inconclusive.This study investigates the potential of premorbid Intelligence Quotient (IQ) and school failure frequency as risk factors for Bipolar Disorder (BD) and Major Depressive Disorder (MDD) in a birth cohort setting. We analyze data from the Pelotas population-based birth cohort study, comprising 3580 participants aged 22, who had no prior mood disorder diagnoses. Utilizing regression models and accounting for potential confounders, we assess the impact of IQ and school failure, measured at age 18, on the emergence of BD and MDD diagnoses at age 22, using individuals without mood disorders as comparators. Results reveal that lower IQ (below 70) at 18 is associated with an increased risk of BD (Adjusted Odds Ratio [AOR] 1.75, 95%CI: 1.00–3.09, p < 0.05), while higher IQ (above 120) is linked to MDD (AOR 2.16, 95%CI: 1.24–3.75, p < 0.001). Moreover, an elevated number of school failures is associated with increased BD risk (AOR 1.23, 95%CI: 1.11–1.41, p < 0.001), particularly for BD type 1 (AOR 1.36, 95% CI: 1.17–1.58, p < 0.001). These findings offer insights into the distinct premorbid intellectual characteristics of BD and MDD and contribute to a deeper understanding of their developmental trajectories, potentially informing the development of risk assessment tools for mood disorders.

Identifying older adults at increased risk of medication-related readmission to hospital within 30 days of discharge: development and validation of a risk assessment tool

ObjectiveDeveloping and validating a risk assessment tool aiming to identify older adults (≥65 years) at increased risk of possibly medication-related readmission to hospital within 30 days of discharge.DesignRetrospective cohort study.SettingThe...

Above the Ravines: Flood Vulnerability Assessment of Earthen Architectural Heritage in Quito (Ecuador)

Floods represent one of the most threatening risks for earthen architectural heritage. Developing risk assessment tools is considered crucial to mitigate the risk and to protect heritage buildings. Due to its hygroscopic nature, earthen architecture is generally considered to be vulnerable to water, requiring a specific analysis. This paper proposes a vulnerability assessment method for earthen buildings in flood-prone areas. Based on the evaluation of the susceptibility of the building’s components and characteristics, the method allows for quantifying the vulnerability of the assets, in non-monetary terms. An application of the methodology is carried out assessing a selection of earthen construction in Quito Historic Centre (Ecuador). The results show the influence of each component in the global vulnerability of the earthen buildings. The response of different construction techniques and the importance of the maintenance of heritage buildings is exposed. Vulnerability assessment methods at the meso-small scale constitute the foundation for risk assessment. Thus, this study aims to provide a significant assessment tool that can be used for further analysis and future lines of research, aiming to protect cultural heritage that is at risk.

Risk Factors of Infections Due to Multidrug-Resistant Gram-Negative Bacteria in a Community Hospital in Rural Thailand.

Antimicrobial resistance is a major public health concern globally. The most serious antimicrobial resistance problem among pathogenic bacteria is multidrug resistance (MDR). The objectives of this study were to investigate the risk factors of MDR infections and to develop a risk assessment tool for MDR Gram-negative bacteria (MDR-GNB) infections at a community hospital in rural Thailand. The study revealed 30.77% MDR-GNB among GNB strains. The most common MDR-GNB strains were 63.02% for Escherichia coli and 11.46% for Klebsiella pneumoniae. A case-control study was applied to collect clinical data between January 2016 and December 2020. Univariate logistic regression and multivariate logistic regression were used to analyze the risk factors for MDR-GNB and a risk assessment score for each factor was determined based on its regression coefficient. The risk factors for MDR-GNB infections were as follows: the presence of Enterobacteriaceae that produce extended-spectrum beta-lactamase (ESBL) (ORAdj. 23.53, 95% CI 7.00-79.09), infections occurring within the urinary tract (ORAdj. 2.25, 95% CI 1.44-3.53), and patients with a history of steroid usage (ORAdj. 1.91, 95% CI 1.15-3.19). Based on the assigned risk scores for each associated factor, the newly developed risk assessment tool for MDR-GNB infections achieved 64.54% prediction accuracy (AUC-ROC 0.65, 95% CI 0.61-0.68), demonstrating that the tool could be used to assess bacterial infection cases in community hospitals. Its use should provide practical guidance on MDR evaluation and prevention. This study was part of an antibiotic stewardship program; the study surveyed antibiotic-resistant situations in a hospital and implemented an effective risk assessment tool using key risk factors of MDR-GNB infections.

Machine Learning Algorithm to Predict Obstructive Coronary Artery Disease: Insights from the CorLipid Trial.

Developing risk assessment tools for CAD prediction remains challenging nowadays. We developed an ML predictive algorithm based on metabolic and clinical data for determining the severity of CAD, as assessed via the SYNTAX score. Analytical methods were developed to determine serum blood levels of specific ceramides, acyl-carnitines, fatty acids, and proteins such as galectin-3, adiponectin, and APOB/APOA1 ratio. Patients were grouped into: obstructive CAD (SS > 0) and non-obstructive CAD (SS = 0). A risk prediction algorithm (boosted ensemble algorithm XGBoost) was developed by combining clinical characteristics with established and novel biomarkers to identify patients at high risk for complex CAD. The study population comprised 958 patients (CorLipid trial (NCT04580173)), with no prior CAD, who underwent coronary angiography. Of them, 533 (55.6%) suffered ACS, 170 (17.7%) presented with NSTEMI, 222 (23.2%) with STEMI, and 141 (14.7%) with unstable angina. Of the total sample, 681 (71%) had obstructive CAD. The algorithm dataset was 73 biochemical parameters and metabolic biomarkers as well as anthropometric and medical history variables. The performance of the XGBoost algorithm had an AUC value of 0.725 (95% CI: 0.691–0.759). Thus, a ML model incorporating clinical features in addition to certain metabolic features can estimate the pre-test likelihood of obstructive CAD.

Proteomic Analysis of Prostate Cancer FFPE Samples Reveals Markers of Disease Progression and Aggressiveness.

Simple SummaryProstate cancer (PCa) is the second most frequently diagnosed type of cancer in men. The lack of tools for accurate risk assessment is causing over-treatment of men with indolent PCa but also delayed detection of metastatic disease and thus high mortality. The aim of our study was to identify proteins related to the progression and aggressiveness of PCa that could serve as potential biomarkers for better risk stratification. To this end, we performed proteomic analysis of Formalin Fixed Paraffin Embedded (FFPE) prostate tissue specimens (n = 86) and compared them based on grade groups and biochemical recurrence status. Based on the valuable data generated by these comparisons, we have selected seven proteins (NMP1, UQCRH, HSPA9, MRPL3, VCAN, SERBP1, HSPE1) as common denominators of PCa aggressiveness and persistence that could potentially be used for the development of risk assessment tools. Notably, our observations are largely validated by transcriptomics data and literature.Prostate cancer (PCa) is the second most common cancer in men. Diagnosis and risk assessment are widely based on serum Prostate Specific Antigen (PSA) and biopsy, which might not represent the exact degree of PCa risk. Towards the discovery of biomarkers for better patient stratification, we performed proteomic analysis of Formalin Fixed Paraffin Embedded (FFPE) prostate tissue specimens using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Comparative analysis of 86 PCa samples among grade groups 1–5 identified 301 significantly altered proteins. Additional analysis based on biochemical recurrence (BCR; BCR+ n = 14, BCR- n = 51) revealed 197 significantly altered proteins that indicate disease persistence. Filtering the overlapping proteins of these analyses, seven proteins (NPM1, UQCRH, HSPA9, MRPL3, VCAN, SERBP1, HSPE1) had increased expression in advanced grades and in BCR+/BCR- and may play a critical role in PCa aggressiveness. Notably, all seven proteins were significantly associated with progression in Prostate Cancer Transcriptome Atles (PCTA) and NPM1NPM1, UQCRH, and VCAN were further validated in The Cancer Genome Atlas (TCGA), where they were upregulated in BCR+/BCR-. UQCRH levels were also associated with poorer 5-year survival. Our study provides valuable insights into the key regulators of PCa progression and aggressiveness. The seven selected proteins could be used for the development of risk assessment tools.

Evaluation of existing guidelines for their adequacy for the food and feed risk assessment of microorganisms obtained through synthetic biology.

EFSA was asked by the European Commission to evaluate synthetic biology (SynBio) developments for agri‐food use in the near future and to determine whether or not they are expected to constitute potential new hazards/risks. Moreover, EFSA was requested to evaluate the adequacy of existing guidelines for risk assessment of SynBio and if updated guidance is needed. The scope of this Opinion covers food and feed risk assessment, the variety of microorganisms that can be used in the food/feed chain and the whole spectrum of techniques used in SynBio. This Opinion complements a previously adopted Opinion with the evaluation of existing guidelines for the microbial characterisation and environmental risk assessment of microorganisms obtained through SynBio. The present Opinion confirms that microbial SynBio applications for food and feed use, with the exception of xenobionts, could be ready in the European Union in the next decade. New hazards were identified related to the use or production of unusual and/or new‐to‐nature components. Fifteen cases were selected for evaluating the adequacy of existing guidelines. These were generally adequate for assessing the product, the production process, nutritional and toxicological safety, allergenicity, exposure and post‐market monitoring. The comparative approach and a safety assessment per se could be applied depending on the degree of familiarity of the SynBio organism/product with the non‐genetically modified counterparts. Updated guidance is recommended for: (i) bacteriophages, protists/microalgae, (ii) exposure to plant protection products and biostimulants, (iii) xenobionts and (iv) feed additives for insects as target species. Development of risk assessment tools is recommended for assessing nutritional value of biomasses, influence of microorganisms on the gut microbiome and the gut function, allergenic potential of new‐to‐nature proteins, impact of horizontal gene transfer and potential risks of living cell intake. A further development towards a strain‐driven risk assessment approach is recommended.

Post-separation abuse: A concept analysis.

To report an analysis of the concept of post-separation abuse and its impact on the health of children and adult survivors. Concept analysis. A literature search was conducted via PubMed, Cochrane and Embase and identified articles published from 1987 to 2021. Walker and Avant's (2019) eight stage methodology was used for this concept analysis, including identifying the concept, determining the purpose of analysis, identifying uses of the concept, defining attributes, identifying a model case and contrary case, antecedents and consequences and defining empirical referents. Post-separation abuse can be defined as the ongoing, willful pattern of intimidation of a former intimate partner including legal abuse, economic abuse, threats and endangerment to children, isolation and discrediting and harassment and stalking. An analysis of literature identified essential attributes including fear and intimidation; domination, power and control; intrusion and entrapment; omnipresence; and manipulation of systems. Antecedents to post-separation abuse include patriarchal norms, physical separation, children, spatiality and availability, pre-separation IPV and coercive control and perpetrator characteristics. Consequences include lethality, adverse health consequences, institutional violence and betrayal, such as loss of child custody and economic deprivation. This concept analysis provides a significant contribution to the literature because it advances the science for understanding the phenomenon of post-separation abuse. It will aid in developing risk assessment tools and interventions to improve standards of care for adult and children survivors following separation from an abusive partner. This concept analysis of post-separation abuse provides a comprehensive insight into the phenomenon and a theoretical foundation to inform instrument development, future research and intervention. Post-separation abuse is a complex, multi-faceted phenomenon that requires differential social, legal and healthcare systems responses to support the health and well-being of survivors and their children.

Development of Risk Assessment Tools for Enterprises

Th e purpose of this article is to develop tools for assessing the risks of enterprises, used both to assess the current activities of enterprises and during the implementation of investment proj-ects. It is supposed to be used both as the main risk assessment tool, for example, for small and medium-sized enterprises, and as an additional tool, mainly for large enterprises, for making a preliminary decision on the feasibility of the project. Th e developed tools include a comprehen-sive risk assessment system, which provides a fundamental basis for calculations, and a soft ware product that signifi cantly optimizes the calculations of a complex integral risk indicator. Th e risk assessment system represents individual risks, grouped by 51 risk groups. Making calculations using the developed risk assessment tools involves assigning to each risk the characteristics of assessing the level of infl uence by selecting the characteristic most appropriate to the current level of risk. A standard version of indicators is proposed for each risk and characteristics cor-responding to "high", "elevated", "medium", "moderate" and "low" risk levels. Based on the results of the analysis, a complex integral risk indicator is formed, which is a quantitative risk assessment, which allows you to classify an enterprise into one of three groups: "eff ective enterprise / project", "enterprise / project requiring improvements", "ineffi cient enterprise". To optimize the calcula-tions, the authors have developed a soft ware product that allows for analysis with a signifi cant reduction in the time spent on its implementation. In general, the use of the developed risk as-sessment system and tools makes it possible to signifi cantly optimize the risk assessment process and reduce the costs of analisys.

Risk Factors of Fluoropyrimidine Induced Cardiotoxicity among Cancer Patients: A Systematic Review and Meta-analysis.

Cancer patients experienced an increased risk of cardiotoxicity during fluoropyrimidine-based chemotherapy (5-fluorouracil or capecitabine). We searched PubMed, PsycINFO, IPA, CINAHL, Web of Science, and ClinicalTrials.gov for studies published between January 1, 1990 and December 31, 2019, in English, examining risk factors for cardiotoxicity induced by fluoropyrimidine. Included study-level data were converted to risk ratios (RRs) and pooled RRs were calculated for meta-analyses using a random-effects method. Among 690 publications identified for abstract and title screening, 22 unique studies were included in the review, and 20 had sufficient data for meta-analyses. Results indicated that patients undergoing capecitabine-based combination therapy had a higher risk than those with monotherapy (pooled RR = 1.61). Patients with pre-existing cardiac disease (pooled RR = 3.26), hypertension (pooled RR = 1.52) or smoking (pooled RR = 2.22) also had higher risks than their counterparts. Developing risk assessment tools to mitigate the risk could be a viable strategy to improve outcomes for cancer patients undergoing fluoropyrimidine-based treatments.

Development of risk assessment tool using damaging energy and argumentation theory for evaluating construction occupational safety and health risks

PurposeThe purpose of this paper is to describe the development of a risk assessment model to assess the occupational safety and health (OSH) risks presented by different construction approaches, namely traditional and industrialised building system (IBS). The development process applies the concept of argumentation theory, which helps construction designers integrate the management of OSH risk into the design process. In addition, an energy damage model is used as an underpinning framework for developing the model.Design/methodology/approachDevelopment of the model was achieved through two phases. Phase I involved collection of data on the activities involved in the construction process and their associated OSH risks, derived from five different case studies, field observation and interviews. Knowledge of design aspects that have the potential to impact on OSH was obtained from document analysis. Using the knowledge obtained in phase I, a model was developed in the form of argument trees (Phase II), which represent a reasoning template with regard to options available to designers when they make judgements about aspects of their designs. Inferences from these aspects eventually determined the magnitude of the damaging energies for every activity involved. Finally, the model was validated by panels of experts, and revisions and amendments were made to the model accordingly.FindingsThe risk assessment model development revealed that the concept of argumentation theory and energy damage model is suitable to represent design safety risk knowledge and effectively address the designer's role in making decisions in their designs and further illuminate the level of OSH risk their designs pose.Practical implicationsThe developed model provides best-practice reasoning support for construction designers, which help them to understand the impact of their designs decisions on worker's safety and health, and thereby assist them to further mitigate the risk to an acceptable level.Originality/valueThis study departs from the existing tool in that the model was developed based upon the combination of argumentation theory and energy damage model. The significance of the model is discussed.

Perspectives on Global Mycotoxin Issues and Management From the MycoKey Maize Working Group

During the last decade, there have been many advances in research and technology that have greatly contributed to expanded capabilities and knowledge in detection and measurement, characterization, biosynthesis, and management of mycotoxins in maize. MycoKey, an EU-funded Horizon 2020 project, was established to advance knowledge and technology transfer around the globe to address mycotoxin impacts in key food and feed chains. MycoKey included several working groups comprising international experts in different fields of mycotoxicology. The MycoKey Maize Working Group recently convened to gather information and strategize for the development and implementation of solutions to the maize mycotoxin problem in light of current and emerging technologies. This feature summarizes the Maize WG discussion and recommendations for addressing mycotoxin problems in maize. Discussions focused on aflatoxins, deoxynivalenol, fumonisins, and zearalenone, which are the most widespread and persistently important mycotoxins in maize. Although regional differences were recognized, there was consensus about many of the priorities for research and effective management strategies. For preharvest management, genetic resistance and selecting adapted maize genotypes, along with insect management, were among the most fruitful strategies identified across the mycotoxin groups. For postharvest management, the most important practices included timely harvest, rapid grain drying, grain cleaning, and carefully managed storage conditions. Remediation practices such as optical sorting, density separation, milling, and chemical detoxification were also suggested. Future research and communication priorities included advanced breeding technologies, development of risk assessment tools, and the development and dissemination of regionally relevant management guidelines.