Cardiac murmur grading and risk analysis of cardiac diseases based on adaptable heterogeneous-modality multi-task learning

Cardiovascular disease (CVDs) has become one of the leading causes of death, posing a significant threat to human life. The development of reliable Artificial Intelligence (AI) assisted diagnosis algorithms for cardiac sounds is of great significance for early detection and treatment of CVDs. However, there is scarce research in this field. Existing research mainly faces three major challenges: (1) They mainly limited to murmur classification and cannot achieve murmur grading, but attempting both classification and grading may lead to negative effects between different multi-tasks. (2) They mostly pay attention to unstructured cardiac sound modality and do not consider the structured demographic modality, as it is difficult to balance the influence of heterogeneous modalities. (3) Deep learning methods lack interpretability, which makes it challenging to apply them clinically. To tackle these challenges, we propose a method for cardiac murmur grading and cardiac risk analysis based on heterogeneous modality adaptive multi-task learning. Specifically, a Hierarchical Multi-Task learning-based cardiac murmur detection and grading method (HMT) is proposed to prevent negative interference between different tasks. In addition, a cardiac risk analysis method based on Heterogeneous Multi-modal feature impact Adaptation (HMA) is also proposed, which transforms unstructured modality into structured modality representation, and utilizes an adaptive mode weight learning mechanism to balance the impact between unstructured modality and structured modality, thus enhancing the performance of cardiac risk prediction. Finally, we propose a multi-task interpretability learning module that incorporates an important evaluation using random masks. This module utilizes SHAP graphs to visualize crucial murmur segments in cardiac sound and employs a multi-factor risk decoupling model based on nomograms. And then we gain insights into the cardiac disease risk in both pre-decoupled multi-modality and post-decoupled single-modality scenarios, thus providing a solid foundation for AI assisted cardiac murmur grading and risk analysis. Experimental results on a large real-world CirCor DigiScope PCG dataset demonstrate that the proposed method outperforms the state-of-the-art (SOTA) method in murmur detection, grading, and cardiac risk analysis, while also providing valuable diagnostic evidence.

PFAS assessment in fish - Samples from Illinois waters

Per- and Polyfluoroalkyl substances (PFAS) have been widely used in various industries, including pesticide production, electroplating, packaging, paper making, and the manufacturing of water-resistant clothes. This study investigates the levels of PFAS in fish tissues collected from four target waterways (15 sampling points) in the northwestern part of Illinois during 2021-2022. To assess accumulation, concentrations of 17 PFAS compounds were evaluated in nine fish species to potentially inform on exposure risks to local sport fishing population via fish consumption. At least four PFAS (PFHxA, PFHxS, PFOS, and PFBS) were detected at each sampling site. The highest concentrations of PFAS were consistently found in samples from the Rock River, particularly in areas near urban and industrial activities. PFHxA emerged as the most accumulated PFAS in the year 2022, while PFBS and PFOS dominated in 2021. Channel Catfish exhibited the highest PFAS content across different fish species, indicating its bioaccumulation potential across the food chain. Elevated levels of PFOS were observed in nearly all fish, indicating the need for careful consideration of fish consumption. Additional bioaccumulation data in the future years is needed to shed light on the sources and PFAS accumulation potential in aquatic wildlife in relation to exposures for potential health risk assessment.

Application of failure mode and effect analysis in ICU admission of potentially COVID-19 infected patients

BACKGROUND

To analyze the admission and treatment process of potentially COVID-19-infected patients in the intensive care unit under normalization, prevention, and control of the pandemic.

METHODS

A multidisciplinary team was assembled to develop a flowchart of potentially COVID-19-infected patients admitted to the intensive care unit and identify potential failure steps and modes throughout the process using the failure mode and effect analysis method. Through risk priority number (RPN) analysis of each failure mode, those with the highest impact on nosocomial infection were identified, and the priority of implementation was determined. Related corrective measures have been developed to continuously improve clinical practice and management.

RESULTS

Eighty potential failure modes were identified, and 8 potential failure modes were identified with RPNs greater than 100. These high RPNs of the failure modes were associated with careless inquiries of epidemiological histories by nurses, inadequate implementation of management standards by nursing assistants, and exposure of attending physicians to potentially risky environments. Finally, 18 general corrective measures are proposed.

CONCLUSIONS

Application of the failure mode and effect analysis method for quality improvement is a powerful tool for predicting potential failures in the process and can suggest corrective measures that could help avoid nosocomial infection during a pandemic.

Estimating the probability of occurrence of African dust outbreaks over regions of the western Mediterranean basin from thermodynamic atmospheric parameters

Desert dust is currently recognized as a health risk factor. Therefore, the World Health Organization (WHO) is actively promoting the establishment of early warning systems for sand and dust storms. This study introduces a methodology to estimate the probability of African dust outbreaks occurring in eight different regions of the Iberian Peninsula and the Balearic Islands. In each region, a multilinear regression model was developed to calculate daily probabilities of dust events using three thermodynamic variables (geopotential thickness in the 1000-500 hPa layer, mean potential temperature between 925 and 700 hPa, and temperature anomalies at 850 hPa) as assessment parameters. All days with African dust transport over each study region were identified in the period 2001-2021 using a proven procedure. This information was then utilized to establish a functional relationship between the values of the thermodynamic parameters and the probability of African dust outbreaks occurring. The validation of this methodology involved comparing the daily probabilities of dust events generated by the models in 2001-2021 with the daily African dust contributions to PM10 regional background levels in each region. On average, daily dust contributions increased proportionally with the increase in daily probabilities, reaching zero for days with low probabilities. Furthermore, a well-defined seasonal evolution of probability values was observed in all regions, with the highest values in the summer months and the lowest in the winter period, ensuring the physical relevance of the models' results. Finally, upward trends were observed in all regions for the three thermodynamic parameters over 1940-2021. Thus, the probability of dust events development also increased in this period. It demonstrates that the aggravation of warm conditions in southern Europe in the last decades, have modified the frequency of North-African dust outbreaks over the western Mediterranean basin.

The impact of indoor air pollution on children's health and well-being: the experts' consensus

BACKGROUND

Pollution of the indoor environment represents a concern for human health, mainly in case of prolonged exposure such as in the case of women, children, the elderly, and the chronically ill, who spend most of their time in closed environments.

MAIN BODY

The aim of the study is to organize a group of experts in order to evaluate the evidence and discuss the main risk factors concerning indoor air and the impact on human health as well as challenging factors regarding preventive strategies to reduce pollution. The experts highlighted the main risk factors concerning indoor air, including poor ventilation, climatic conditions, chemical substances, and socio-economic status. They discussed the impact on human health in terms of mortality and morbidity, as well as challenging factors regarding preventive strategies to reduce pollution.

CONCLUSION

The experts identified strategies that can be reinforced to reduce indoor pollution and prevent negative consequences on human health at national and local levels.

Measuring risk of renewable diesel production processes using a multi-criteria decision strategy

This study proposes measuring the risk of five alternative renewable diesel production technologies using a multi-criteria decision matrix strategy. Evaluated criteria include environmental, economic, technological, social, and process safety risks. The subjective Analytical Hierarchy Process (AHP) with stakeholder input provides criteria and sub-criteria weightings and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) ranks alternatives. Alternative renewable diesel options are Green Diesel from first, second, and third-generation feedstocks, Fischer-Tropsch Diesel from second-generation biomass, and the transesterification of vegetable oils (VO) to make biodiesel. This study is a response to an earlier work measuring the sustainability of the same renewable technologies. While the previous work indicated Fischer-Tropsch Diesel as the most sustainable, this current work indicated the process as the "most risky," suggesting that risk is a significant driver of decision making over sustainability, and newly developed decision tools should address both perspectives.

Development and application of a second-generation multilingual tool for invasion risk screening of non-native terrestrial plants

Under the increasing threat to native ecosystems posed by non-native species invasions, there is an urgent need for decision support tools that can more effectively identify non-native species likely to become invasive. As part of the screening (first step) component in non-native species risk analysis, decision support tools have been developed for aquatic and terrestrial organisms. Amongst these tools is the Weed Risk Assessment (WRA) for screening non-native plants. The WRA has provided the foundations for developing the first-generation WRA-type Invasiveness Screening Kit (ISK) tools applicable to a range of aquatic species, and more recently for the second-generation ISK tools applicable to all aquatic organisms (including plants) and terrestrial animals. Given the most extensive usage of the latter toolkits, this study describes the development and application of the Terrestrial Plant Species Invasiveness Screening Kit (TPS-ISK). As a second-generation ISK tool, the TPS-ISK is a multilingual turnkey application that provides several advantages relative to the WRA: (i) compliance with the minimum standards against which a protocol should be evaluated for invasion process and management approaches; (ii) enhanced questionnaire comprehensiveness including a climate change component; (iii) provision of a level of confidence; (iv) error-free computation of risk scores; (v) multilingual support; (vi) possibility for across-study comparisons of screening outcomes; (vii) a powerful graphical user interface; (viii) seamless software deployment and accessibility with improved data exchange. The TPS-ISK successfully risk-ranked five representative sample species for the main taxonomic groups supported by the tool and ten angiosperms previously screened with the WRA for Turkey. The almost 20-year continuous development and evolution of the ISK tools, as opposed to the WRA, closely meet the increasing demand by scientists and decision-makers for a reliable, comprehensive, updatable and easily deployable decision support tool. For terrestrial plant screening, these requirements are therefore met by the newly developed TPS-ISK.

Spatiotemporal variation in heatwaves and elderly population exposure across China

Heatwaves have been intensified worldwide due to climate change, posing great health risks, especially to elderly populations. However, in China, limited studies have employed the heat index to decipher the spatiotemporal trends of heatwaves and their impacts on the elderly population. By comparing the three heatwave definitions, this study aimed to evaluate the long-term spatiotemporal variations in heatwaves from 1964 to 2022 across China using the Excess Heat Factor (EHF). We took advantage of high-resolution reanalysis temperature data on the Google Earth Engine (GEE) platform to efficiently calculate the heatwaves. Our results revealed that the frequency and duration of heatwaves increased significantly in approximately 77 % of China's total area, with South China experiencing the most frequent and prolonged heatwaves. Conversely, in most areas, no significant trend was discerned in the growth of the maximum and average heatwave intensities. The total number of elderly people affected by heatwaves surged from approximately 11.96 million in 2001 to over 30.31 million in 2020, with an estimated additional 1.12 million older adults exposed to heatwaves annually across the nation (R2 = 0.60, p < 0.05). The population factor exhibited largest effect on the exposure of heatwaves, followed by climate effects and combined factors, with the corresponding explanatory power about 42.84 %, 34.85 % and 22.31 %, respectively. These individuals predominantly resided in the Northeast China, Southwest China, and South China. We also found geographical variations in heatwave exposure along elevations and land use types. These insights underscore the pressing necessity for formulating strategic interventions to mitigate the health threats presented by mounting heatwave exposure, especially for susceptible groups like the elderly in China.

Oil spill risk analysis for the NEOM shoreline

A risk analysis is conducted considering an array of release sources located around the NEOM shoreline. The sources are selected close to the coast and in neighboring regions of high marine traffic. The evolution of oil spills released by these sources is simulated using the MOHID model, driven by validated, high-resolution met-ocean fields of the Red Sea. For each source, simulations are conducted over a 4-week period, starting from first, tenth and twentieth days of each month, covering five consecutive years. A total of 180 simulations are thus conducted for each source location, adequately reflecting the variability of met-ocean conditions in the region. The risk associated with each source is described in terms of amount of oil beached, and by the time required for the spilled oil to reach the NEOM coast, extending from the Gulf of Aqaba in the North to Duba in the South. To further characterize the impact of individual sources, a finer analysis is performed by segmenting the NEOM shoreline, based on important coastal development and installation sites. For each subregion, source and release event considered, a histogram of the amount of volume beached is generated, also classifying individual events in terms of the corresponding arrival times. In addition, for each subregion considered, an inverse analysis is conducted to identify regions of dependence of the cumulative risk, estimated using the collection of all sources and events considered. The transport of oil around the NEOM shorelines is promoted by chaotic circulations and northwest winds in summer, and a dominant cyclonic eddy in winter. Hence, spills originating from release sources located close to the NEOM shorelines are characterized by large monthly variations in arrival times, ranging from less than a week to more than 2 weeks. Similarly, large variations in the volume fraction of beached oil, ranging from less then 50% to more than 80% are reported. The results of this study provide key information regarding the location of dominant oil spill risk sources, the severity of the potential release events, as well as the time frames within which mitigation actions may need to deployed.

Evaluation of the offset static rope evacuation procedure: insights from a safe job analysis

BACKGROUND

Recently, the Norwegian Helicopter Emergency Medical Service (HEMS) has developed a procedure for a special type of static rope rescue operation, referred to as the offset technique. In this technique, the helicopter is offset from the accident site, and the HEMS technical crew member uses an offset throw line to gain access to the scene. Today, there is little practical experience of such operations, and a need has been identified for more knowledge on the potential hazards encountered during this type of operation. Such knowledge is of importance for further development of the procedure for the offset technique.

OBJECTIVE

To identify potential hazards for helicopter rescue operations using the static rope offset technique and, thereby, to improve the procedure for such operations. This may lead to improved safety for patients and crew members during offset rescue operations.

METHOD

A Safe Job Analysis was used to identify the hazards of offset rescue operations. Such operations are divided into tasks and sub-tasks. For each sub-task, we identified potential hazards and suggested ways of preventing these.

RESULTS

Through the Safe Job Analysis, we suggest some changes in the existing procedure for the offset technique, to make it more robust against potential hazards.

CONCLUSION

We have demonstrated the value of Safe Job Analysis for improving the static rope offset evacuation procedure. Our analysis has led to some changes in the procedure for offset rescue operations. This is the importance of having two throw lines and focusing on "why" in the procedure.

Non-invasive tools for liver steatosis and steatohepatitis predict incidence of diabetes, cardiovascular disease and mortality 20 years later: The ATTICA cohort study (2002-2022)

BACKGROUND & AIMS

Non-alcoholic fatty liver disease (NAFLD) or, as recently renamed, metabolic dysfunction-associated steatotic liver disease (MASLD), has common metabolic pathways with diabetes and cardiovascular disease (CVD). Non-invasive tools (NITs) for liver steatosis and steatohepatitis (MASH) were studied as potential predictors of diabetes, cardiovascular disease (CVD) and mortality over a 20-year period.

METHODS

In 2001-02, 3042 individuals from the Attica region of Greece were recruited randomly, and were stratified by subgroups of sex, age and region to reflect the general urban population in Athens, Greece. Validated NITs for hepatic steatosis (Hepatic Steatosis Index (HIS), Fatty Liver Index (FLI), Lipid Accumulation Product (LAP), NAFLD liver fat score (NAFLD-LFS)) and steatohepatitis (Index of non-alcoholic steatohepatitis (ION), aminotransferase-creatinine-clearance non-alcoholic steatohepatitis (acNASH)) were calculated. Incidence of diabetes, CVD and mortality were recorded 5, 10 and 20 years later.

RESULTS

Within a 20-year observation period, the diabetes and CVD incidence was 26.3% and 36.1%, respectively. All hepatic steatosis and steatohepatitis NITs were independently associated with diabetes incidence. ION and acNASH presented independent association with CVD incidence [(Hazard Ratio (HR)per 1 standard deviation (SD) = 1.33, 95% Confidence Interval (95% CI) (1.07, 1.99)) and (HRper 1 SD = 1.77, 95% CI (1.05, 2.59)), respectively]. NAFLD-LFS which is a steatosis NIT indicating features of steatohepatitis, was linked with increased CVD mortality (HRper 1 SD = 1.35, 95% CI (1.00, 2.30)) and all-cause mortality (HRper 1 SD = 1.43, 95% CI (1.08, 2.01)). Overall, steatohepatitis NITs (i.e., ION and acNASH) presented stronger associations with the outcomes of interest compared with steatosis NITs. Clinically important trends were observed in relation to diabetes and CVD incidence progressively over time, i.e. 5, 10 and 20 years after baseline.

CONCLUSIONS

Easily applicable and low-cost NITs representing steatohepatitis may be early predictors of diabetes and CVD onset. More importantly, these NITs increased the attributable risk conveyed by conventional CVD risk factors by 10%. Thus, their potential inclusion in clinical practice and guidelines should be studied further.

Spatio-temporal analysis and risk modeling of foot-and-mouth disease outbreaks in China

FMD is an acute contagious disease that poses a significant threat to the health and safety of cloven-hoofed animals in Asia, Europe, and Africa. The impact of FMD exhibits geographical disparities within different regions of China. The present investigation undertook an exhaustive analysis of documented occurrences of bovine FMD in China, spanning the temporal range from 2011 to 2020. The overarching objective was to elucidate the temporal and spatial dynamics underpinning these outbreaks. Acknowledging the pivotal role of global factors in FMD outbreaks, advanced machine learning techniques were harnessed to formulate an optimal prediction model by integrating comprehensive meteorological data pertinent to global FMD. Random Forest algorithm was employed with top three contributing factors including Isothermality(bio3), Annual average temperature(bio1) and Minimum temperature in the coldest month(bio6), all relevant to temperature. By encompassing both local and global factors, our study provides a comprehensive framework for understanding and predicting FMD outbreaks. Furthermore, we conducted a phylogenetic analysis to trace the origin of Foot-and-mouth disease virus (FMDV), pinpointing India as the country posing the greatest potential hazard by leveraging the spatio-temporal attributes of the collected data. Based on this finding, a quantitative risk model was developed for the legal importation of live cattle from India to China. The model estimated an average probability of 0.002254% for FMDV-infected cattle imported from India to China. TA sensitivity analysis identified two critical nodes within the model: he possibility of false negative clinical examination in infected cattle at destination (P5) and he possibility of false negative clinical examination in infected cattle at source(P3). This comprehensive approach offers a thorough evaluation of FMD landscape within China, considering both domestic and global perspectives, thereby augmenting the efficacy of early warning mechanisms.

Risk factor analysis for perioperative complications in impacted third molar surgery - a single center experience

BACKGROUND

The surgical removal of impacted third molars is usually carried out by an oral/maxillofacial surgeon. Two specific risks of surgical removal of impacted third molars are oroantral communication (OAC) when extracting ​​upper third molars and hypesthesia of the inferior alveolar nerve (IAN) ​​when extracting lower third molars. The aim of this study is to determine the distribution of complications in deeply impacted third molar surgery, to identify specific risk factors influencing the most common perioperative (OAC, IAN hypesthesia) and to compare these results with other studies.

MATERIALS AND METHODS

The clinical findings, digital panoramic radiographs, intra- and postoperative data of 80 patients with a total of 232 impacted third molars that had been subjected for tooth extraction, from December 2022 and August 2023, were collected and analyzed. Perioperative complications (IAN hypesthesia, OAC, hypesthesia lingual nerve, postoperative bleeding, postoperative infection) were identified. A risk analysis for OAC and IAN hypesthesia was performed regarding perioperative data.

RESULTS

Overall, the rate of OAC for the right upper third molar was 12.8% and for the left upper third molar 15.6%. The complication rates regarding transient hypesthesia were 8.1% for the left IAN and 7.3% for the right IAN. The distance to maxillary sinus, the depth score according to Pell and Gregory, the bone coverage score, the operation time, the tooth's angulation and the type of surgeon (oral surgeon, DMD) were identified as significant risk factors for the occurrence of OAC. The minimum distance to IAN, the bone coverage score, the total operation time and the operation by an oral surgeon (DMD) were identified as significant risk factors for hypesthesia of the IAN.

CONCLUSION

Next to the risk factors from above, the present study is one of the first showing that patients who were primarily operated on by an oral surgeon (DMD) and not a maxillofacial surgeon (MD, DMD) showed higher rates of OAC and IAN hypesthesia in impacted third molar extraction. The results of this study can serve as a baseline for further studies to investigate complication patterns in impacted third molar surgery.

Risk analysis of critical infrastructure with the MOSAR method

The smooth running of the electric energy system is crucial, especially given the current geopolitical environment. To achieve this goal, it is essential to establish a solid infrastructure that is both accessible and safe. We protect consumer reputation and trust, reduce financial losses, and lessen unfavourable effects on employees and business owners by maintaining continuous functioning. This study has discovered several important concerns using the Method Organised Systematic Analysis of Risk (MOSAR). These include the possibility of cyberattacks, the availability of information and technology systems, the loss of critical individuals, and network problems. To address these risks, it is necessary to deliver electrical energy on time and at a high standard, to be responsive to client requests, and to follow best practices, technical standards, and personal and environmental protection measures. The findings of this study make valuable contributions to risk assessment efforts, allowing us to identify potential threats to the security and reliability of national power systems. Overall, it is essential to maintain a robust and resilient energy infrastructure to ensure uninterrupted operation and mitigate risks effectively.

Towards quality management of artificial intelligence systems for medical applications

The use of artificial intelligence systems in clinical routine is still hampered by the necessity of a medical device certification and/or by the difficulty of implementing these systems in a clinic's quality management system. In this context, the key questions for a user are how to ensure robust model predictions and how to appraise the quality of a model's results on a regular basis. In this paper we discuss some conceptual foundation for a clinical implementation of a machine learning system and argue that both vendors and users should take certain responsibilities, as is already common practice for high-risk medical equipment. We propose the methodology from AAPM Task Group 100 report No. 283 as a conceptual framework for developing risk-driven a quality management program for a clinical process that encompasses a machine learning system. This is illustrated with an example of a clinical workflow. Our analysis shows how the risk evaluation in this framework can accommodate artificial intelligence based systems independently of their robustness evaluation or the user's in-house expertise. In particular, we highlight how the degree of interpretability of a machine learning system can be systematically accounted for within the risk evaluation and in the development of a quality management system.

[Reform of early access program in France: Impact on workload in a pharmacy and risk identification]

The reform of derogatory access authorisations (DAs) on 1st July 2021 has distorted the routine of the hospital pharmacists dealing with innovative medicines that are waiting for marketing authorization or approval. There are two distinct categories of DAs: Compassionate Access Authorisations (CAAs) are granted by the French National Agency for the Safety of Medicines (ANSM) while Early Access Authorisations (EAPs) are granted at the request of pharmaceutical companies by the French National Authority for Health (HAS). All AAPs and a majority of the AACs are supported by a Protocol for Therapeutic Use and Data Collection (PTU-DC). The aim of this study is to assess the impact of the reform on pharmacy process one year following its implementation, and to identify the risks related to the new circuits. The working group, composed of three pharmacists carried out an initial assessment of the effects first measured the impact of the reform on medicine processes in DAs. They performed a comparison of the changes in their management methods: 3 months prior to the reform (M0), and 3 (M3) and 12 months (M12) post-reform. Risks analysis was conducted using the Failure Modes, Effects and Criticality Analysis (FMEA) method. The analysis was limited to the process steps specific related to DAs drugs were analyzed. The critical severity of the risk situations identified was rated. A critical hierarchy matrix was used to establish priority actions. The priority actions to be taken were determined using the critical hierarchy matrix. Over the span of one year, the number of DAs in our establishment showed a 31.7% increase, from 41 at M0 to 54 at M12. At M0, the proportion of drugs needed inclusion via a drug-specific digital platform, specific to each drug, stood at 27% (11/41) of drugs at M0 while at M12, it rose to 52% (28/54). The percentage of PTU-DCs therefore increased by a factor of 1.7, rising from 29% (12/41) at M0 to 47% (21/45) at M3 and 60% (32/54) at M12. For orders, which are always nominative, approval depends on both the presence of the PTU-DC tracking sheet being present in 12% of PAAs, and the inclusion number in 26% of PAAs. The risk analysis shows 49 failure modes leading to risk situations. Among the failure modes, 36 have a consequence of acceptable or tolerable criticality under control, whilst 13 are deemed of unacceptable criticality. A suitable control method exists has been identifies for 5 of them. Finally, the ranking evaluation of criticalities has highlighted 4 situations which require immediate action as a priority: delivery times, obtaining completed tracking sheets and ordering procedures. The aim of the DAs reform is to simplify access to innovative medicines. However, the reform has significant and damaging repercussions on pharmaceutical activities. Corrective measures need to be taken in conjunction with all parties involved in the circuits including laboratories and service providers (CROs), authorities and healthcare professionals.

Identification of key potential infection processes and risk factors in the computed tomography examination process by FMEA method under COVID-19

PURPOSE

To identify the key infection processes and risk factors in Computed Tomography (CT) examination process within the standard prevention and control measures for the COVID-19 epidemic, aiming to mitigate cross-infection occurrences in the hospital.

METHOD

The case hospital has assembled a team of 30 experts specialized in CT examination. Based on the CT examination process, the potential failure modes were assessed from the perspective of severity (S), occurrence probability (O), and detectability (D); they were then combined with corresponding risk prevention measures. Finally, key infection processes and risk factors were identified according to the risk priority number (RPN) and expert analysis.

RESULTS

Through the application of RPN and further analysis, four key potential infection processes were identified, including "CT request form (A1)," "during the scan of CT patient (B2)," "CT room and objects disposal (C2)," and "medical waste (garbage) disposal (C3)". In addition, eight key risk factors were also identified, including "cleaning personnel does not wear masks normatively (C32)," "nurse does not select the vein well, resulting in extravasation of the peripheral vein for enhanced CT (B25)," "patient cannot find the CT room (A13)," "patient has obtained a CT request form but does not know the procedure (A12)," "patient is too unwell to continue with the CT scan (B24)," "auxiliary staff (or technician) does not have a good grasp of the sterilization and disinfection standards (C21)," "auxiliary staff (or technician) does not sterilize the CT machine thoroughly (C22)," and "cleaning personnel lacks of knowledge of COVID-19 prevention and control (C33)".

CONCLUSION

Hospitals can publicize the precautions regarding CT examination through various channels, reducing the incidence of CT examination failure. Hospitals' cleaning services are usually outsourced, and the educational background of the staff employed in these services is generally not high. Therefore, during training and communication, it is more necessary to provide a series of scope and training programs that are aligned with their understanding level. The model developed in this study effectively identifies the key infection prevention process and critical risk factors, enhancing the safety of medical staff and patients. This has significant research implications for the potential epidemic of major infectious diseases.

A web-based microbiological hazard identification tool for infant foods

An integrated approach to identify and assess Microbiological Hazards (MHs) and mitigate risks in infant food chains is crucial to ensure safe foods for infants and young children. A systematic procedure was developed to identify MHs in specific infant foods. This includes five major steps: 1) relevant hazard-food pairing, 2) process inactivation efficiency, 3) recontamination possibility after processing, 4) MHs growth opportunity, and 5) MHs-food association level. These steps were integrated into an online tool called the Microbiological Hazards IDentification (MiID) decision support system (DSS), targeting food companies, governmental agencies and academia users, and is accessible at https://foodmicrobiologywur.shinyapps.io/Microbial_hazards_ID/. The MiID DSS was validated in four case studies, focussing on infant formula, fruit puree, cereal-based meals, and fresh fruits, each representing distinct products and processing characteristics. The results obtained through the application of the MiID DSS, compared with identification by food safety experts, consistently identified the top MHs in these food products. This process affirms its effectiveness in systematic hazard identification. The introduction of the MiID DSS helps to structure the first steps in HACCP (hazard analysis) and in risk assessment (hazard identification) to follow a structured and well-documented procedure, balancing the risk of overlooking relevant MHs or including too many irrelevant MHs. It is a valuable addition to risk analysis/assessment in infant food chains and has the potential for future extension. This includes the incorporation of newly acquired data related to infant foods via a semi-publicly hosted platform, or it can be adapted for hazard identification in general food products using a similar framework.

Safeguarding drinking water: A brief insight on characteristics, treatments and risk assessment of contamination

Water pollution stands as a critical worldwide concern, bearing extensive repercussions that extend to human health and the natural ecosystem. The sources of water pollution can be diverse, arising from natural processes and human activities and the pollutants may range from chemical and biological agents to physical and radiological contaminants. The contamination of water disrupts the natural functioning of the system, leading to both immediate and prolonged health problems. Various technologies and procedures, ranging from conventional to advanced, have been developed to eliminate water impurities, with the choice depending on the type and level of contamination. Assessing risks is a crucial element in guaranteeing the safety of drinking water. Till now, research is continuing the removal of contaminates for the sake of supplying safe drinking water. The study examined physical, inorganic, organic, biological and radiological contaminants in drinking water. It looked at where these contaminants come from, their characteristics, the impact they have and successful methods used in real-world situations to clean the contaminated water. Risk assessment methodologies associated with the use of unsafe drinking water as future directives are also taken into consideration in the present study for the benefit of public concern. The manuscript introduces a comprehensive study on water pollution, focusing on assessing and mitigating risks associated with physical, inorganic, organic, biological and radiological contaminants in drinking water, with a novel emphasis on future directives and sustainable solutions for public safety.

Effects of integrated nutrient management and urea deep placement on rice yield, nitrogen use efficiency, farm profits and greenhouse gas emissions in saline soils of Bangladesh

Soil salinity is one of the major yield-limiting factors in the coastal ecosystems of Bangladesh. An efficient fertilizer management practice and selection of appropriate crop cultivars could play a crucial role in improving yield and promoting low-carbon agriculture across saline soils. A two-year multi-location field experiment was conducted during the Boro (dry) season (December-April) to investigate the effects of fertilizer management and rice cultivar selection on rice yield, economic viability, and global warming potential (GWP) in coastal saline soils of Bangladesh. The study included seven fertilizer treatments with varying nitrogen rates and sources, as well as two rice cultivars (BRRI dhan67 and BRRI dhan88). The results showed that integrated nutrient management-2 (INM-2) significantly (p < 0.05) increased rice yield and nitrogen use efficiency compared to other treatments for both BRRI dhan67 and BRRI dhan88. Similarly, INM-2 gave a higher return on fertilizer investment and marginal benefit-cost ratio than other treatments in both locations and under both cultivars. BRRI dhan67 significantly (p < 0.05) increased rice yield relative to BRRI dhan88 by 21 % and 52 % at the BRRI farm and Kaliganj in Satkhira, respectively. The cost-dominant analysis excluded BRRI dhan88 and all fertilizer treatments, except urea deep placement (UDP) and INM-2, from consideration in both locations. Consequently, INM-2 and UDP proved to be economically viable in both locations, with INM showing a higher marginal rate of return than UDP in BRRI dhan67. In terms of environmental sustainability, UDP significantly (p < 0.05) reduced GWP and yield-scaled emissions of CH4 by 31 % and 38 % without causing yield loss compared to INM-2. Similarly, BRRI dhan67 significantly (p < 0.05) reduced GWP and yield-scaled emissions of CH4 by 5 and 22 % compared to BRRI dhan88. These findings suggest that selecting salt-tolerant rice cultivars and implementing appropriate fertilizer management practices can enhance economic profitability, ensure food security, and mitigate the adverse effects of climate change in coastal saline soils.

Distribution and impaction patterns of third molars in a sample of German population: Retrospective analysis in a high turnover maxillofacial department

BACKGROUND

The surgical removal of impacted third molars is considered a routine procedure for oral and maxillofacial surgeons. However, the distribution of impacted molars varies among different populations. A study into impaction patterns in the German population is currently not described. The aim of this retrospective study is to determine patterns of impacted third molars in a sample of German population, to identify gender and age specific differences as well as further risk factors for impacted molar extraction and to compare these results with other studies.

MATERIALS AND METHODS

The clinical findings and digital panoramic radiographs of 84 patients with a total of 243 impacted third molars that had been subjected for tooth extraction, from January to September 2023, were collected and analyzed. All third molars were analyzed according to Winter´s angulation, Pell and Gregory Score of depth and relationship to ramus. Furthermore, inferior alveolar nerve and maxillary sinus proximity were identified through a newly developed risk score and an analysis of patient´s gender and age regarding impaction patterns was performed.

RESULTS

No significant gender specific differences were found regarding the impaction patterns. Third molar angulations significantly differed regarding patient´s age (cut-off 26 years). In comparison, third molar depth, bone coverage, nerve approximity and angulation patterns differed from the results of other populations.

CONCLUSION

The results of this study can serve as a baseline for further studies of third molar impactions in the German population to minimize perioperative complications in impacted third molar surgery.

Pharmaceuticals, hazard and ecotoxicity in surface and wastewater in a tropical dairy production area in Latin America

Pharmaceuticals comprise a complex group of emerging pollutants. Despite the significant number of pharmaceuticals used in veterinary medicine, the input of these compounds into the environment due to livestock activities has been scarcely described. This work assays for the first time in Central America the occurrence of pharmaceuticals in farm wastewater in an area devoted to dairy production, and in the surrounding surface waters. Among 69 monitored pharmaceuticals, a total of eight compounds were detected in wastewater samples collected from seven dairy farms after three sampling campaigns. Six pharmaceuticals were considered either of high (albendazole, lovastatin and caffeine) or intermediate estimated hazard (ciprofloxacin, acetaminophen and ketoprofen) based on the HQ approach, while 26% of the samples were considered of high estimated hazard according to the cumulative ∑HQ approach. Similarly, when ecotoxicological tests were applied, all the samples showed some level of toxicity towards Daphnia magna, and most samples towards Vibrio fischeri and Lactuca sativa. Fourteen pharmaceuticals were detected in surface water samples collected in the surroundings of the dairy production farms, including rural and urban areas. Seven out of these compounds showed high estimated risk (risperidone, diphenhydramine, trimethoprim, fluoxetine, ofloxacin, caffeine and ibuprofen), while three (gemfibrozil, ciprofloxacin and cephalexin) exhibited intermediate estimated risk. In a similar worrisome way, 27% of these samples were estimated to pose high environmental risk according to the pharmaceutical content. Despite being nontoxic for D. magna or V. fischeri, frequent inhibition (>20%) of GI in L. sativa was determined in 34% of surface water samples; such findings raise concern on the apparent inceptive environmental pollution and risk within the area. According to the pharmaceutical content patterns in both kinds of studied matrices, no clear evidence of significant contamination in surface water due to livestock activities could be retrieved, suggesting a main role of urban influence.

Upscaling the remediation of acidic landscapes - the coastal floodplain prioritisation method

Over 24 million hectares of the world's coastal floodplains are underlain by acid sulfate soils (ASS). Drainage of these sediments has led to widespread environmental degradation, raising serious health concerns. To date, onsite rehabilitation has been complicated by differing stakeholder priorities, with resources often allocated to sites with more vocal proponents rather than those exposed to more significant environmental impacts. To address this issue, this paper introduces the Coastal Floodplain Prioritisation (CFP) Method; a novel, data driven and spatially explicit multi-criteria assessment that ranks floodplain catchment areas according to their risk of transferring acidic drainage waters to an estuary. Results can be used to prioritise where remediation actions are likely to have the greatest benefit. The method was applied across six different estuaries in south-east Australia, with major field campaigns undertaken at each site. Within each estuary, the largest acid fluxes and impacts are identified with relevant mitigation measures provided. On a catchment scale, the results reflect the broader hydrogeomorphic characteristics of each estuary, including the historic acid formation conditions and recent anthropogenic drainage activities. Low-lying backswamps were identified as the highest risk zones within each estuary. These areas are also the most vulnerable to sea level rise. Reinstatement of tidal inundation to these backswamps effectively remediates acid sulfate soil discharges and provides a nature-based solution for adaptation to sea level rise with a range of co-benefits to encourage further investment.

Comprehensive factor analysis and risk quantification study of fall from height accidents

Working at heights poses frequent and significant risks, demanding scientific approaches for investigating fall-from-height (FFH) incidents and proposing preventive measures to enhance building safety. Nevertheless, ongoing research on analyzing the causal factors behind fall-from-height accidents lacks a comprehensive qualitative and quantitative assessment of the interplay between these factors. To bridge this gap, this study introduces an integrated risk analysis model. Utilizing incident reports and leveraging the multi-case rootedness theory, the model initially identifies influential elements. Subsequently, employing the Grey Decision Making Laboratory (Grey-DEMATEL) and Interpretive Structural Modeling (ISM) techniques, a hierarchical network is constructed, followed by the transformation of this hierarchical network model into a Bayesian Network (BN) model using GeNie2.0 software. Ultimately, the study was based on data from 420 accident cases and analyzed the causes and diagnosis of the accidents. The findings indicate that A5 (Low-security awareness) is the most significant factor contributing to falls from great heights and that the connection between the components is dynamic and non-linear rather than simply independent and linear. Furthermore, the study established a likelihood of occurrence of such incidents of up to 57 % and ranked the probability of occurrence of each contributing component in the case of a fall from height. This study presents a scientifically valid method for analyzing fall-from-height accidents. Experimental results confirm the model's applicability, empowering contractors to improve safety management by accessing precise risk information and prioritizing preventive measures against interrelated accidents. The model facilitates informed decision-making for contractors to effectively mitigate fall-from-height risks and establish a safer working environment.

Driving effect of multiplex factors on Mpox in global high-risk region, implication for Mpox based on one health concept

Mpox is an ongoing viral zoonotic disease epidemic worldwide. Being different from conventional animal-to-human transmission, the present outbreak is mainly caused by human-to-human transmission of Mpox virus, putting forward the risk of worldwide epidemic. The current spatial distribution characteristics and risk area prediction are urgently needed for preparedness for prevention and control of the disease based on the One Health strategy. In the present study, the global outbreak point of Mpox virus were collected and used to predict potential global risk of Mpox virus with ecological niche model constructed with a combination of eco-geographical, anthropoid, meteorological, and host variables. The results showed that human factors are the key to the risk and prevalence of Mpox. The risk map indicated that Mpox may affect extensive areas worldwide. Europe and North America have the highest risk of Mpox. Although most areas have never recorded Mpox before, there are some high-risk areas in Asia. Our findings highlight population density is the most important contributing factor for high-risk area. Many large cities with dense populations, developed transportation, and high migration rate in the world, are in high risks. At present, the spread of Mpox is highly valued in the world and strict prevention and control measures have been taken. However, under the influence of human factors, Mpox has the potential of a global pandemic. The risk area prediction and main risk factors provide key information for targeted preparedness for prevention and control of Mpox outbreak and avoiding potential global epidemic through the One Health approach.

EPIDEMIOLOGY OF TOXOPLASMA GONDII AND NEOSPORA CANINUM INFECTION IN GOATS FROM AGUASCALIENTES, MEXICO

The objective of this study was to describe the epidemiology of Toxoplasma gondii and Neospora caninum infection by estimating seroprevalence and its association with certain risk factors in goats from Aguascalientes, Mexico. A total of 150 blood samples was taken from 10 farms and serum samples were subjected to enzyme-linked immunosorbent assay indirect test to detect T. gondii and N. caninum antibodies; the association between seroprevalence and some potential risk factors was estimated through logistic regression analysis. The general seroprevalence for T. gondii was 12.6%, observed in the farms in a range of 6.6 to 60%, finding seropositive animals in 80% of them; for N. caninum the seroprevalence was 3.3% and in farms a range of 6.6 to 13.3% was identified and 30% of them had at least 1 seropositive animal. The coinfection was 0.66%. The risk analysis for T. gondii identified a history of abortions (odds ratio 9.25) as a factor associated with seroprevalence; for N. caninum, no risk factor was identified.

How do people perceive driving risks in small towns? A case study in Central Texas

The number of studies investigating the relationship between perceived and objective traffic risk from drivers' perspective is limited. This study aims to investigate this dynamic within an understudied transportation environment - small towns in Texas, USA, defined as incorporated places with a population of less than 50,000. A web-based survey was distributed to six small towns in central Texas to ascertain perceptual traffic risk factors and personal characteristics. A participatory GIS exercise was also conducted to collect where high-risk locations were perceived and to correlate them to high crash zones. This study spatially examined the relations between perceived and observed risk locations and statistically identified a set of contributing factors which could make crash-intensive areas more perceivable by road users. The results indicated that road users' perceived risk locations are not always associated with high crash rates. The match rate between perceived and observed risk locations varied significantly across studied sites. We found that some personal and built environment factors significantly impacted people's sensitivity to perceiving crash-intensive locations. The binary logistic regression model was accurate (74.13%) in highlighting whether a perceived risk location matches observed risk locations. The results emphasize the importance of considering perceived and objective risk simultaneously to gain a better understanding of traffic risk mitigation, especially in underserved small towns.

Performance of a gross pollutant trap-biofilter and sand filter treatment train for the removal of organic micropollutants from highway stormwater (field study)

This field study assessed the occurrence, event mean concentrations (EMCs), and removal of selected organic micro-pollutants (OMPs), namely, polycyclic aromatic hydrocarbons (PAHs), petroleum hydrocarbons (PHCs), nonylphenol (NP), 4-t-octylphenol (OP), and bisphenol A (BPA), in a gross pollutant trap (GPT)-biofilter/sand filter stormwater treatment train in Sundsvall, Sweden. The effects of design features of each treatment unit, including pre-sedimentation (GPT), sand filter medium, vegetation, and chalk amendment, were investigated by comparing the units' removal performances. Overall, the treatment train removed most OMPs from highway runoff effectively. The results showed that although the sand filter provided moderate (<50 % for phenolic substances) to high (50-80 % for PAHs and PHCs) removal of OMPs, adding a vegetated soil layer on top of the sand filter considerably improved the removal performance (by at least 30 %), especially for BPA, OP, and suspended solids. Moreover, GTP did not contribute to the treatment significantly. Uncertainties in the removal efficiencies of PAHs and PHCs by the filter cells increased substantially when the ratio of the influent concentration to the limit of quantification decreased. Thus, accounting for such uncertainties due to the low OMP concentrations should be considered when evaluating the removal performance of biofilters.

Unified risk analysis in radiation therapy

PURPOSE

The increasing complexity of new treatment methods as well as the Information Technology (IT) infrastructure within radiotherapy require new methods for risk analysis. This work presents a methodology on how to model the treatment process of radiotherapy in different levels. This subdivision makes it possible to perform workflow-specific risk analysis and to assess the impact of IT risks on the overall treatment workflow.

METHODS

A Unified Modeling Language (UML) activity diagram is used to model the workflows. The subdivision of the workflows into different levels is done with the help of swim lanes. The model created in this way is exported in an xml-compatible format and stored in a database with the help of a Python program.

RESULTS

Based on an existing risk analysis, the workflows CT Appointment, Glioblastoma Multiforme, and Deep Inspiration Breath Hold (DIBH) were modeled in detail. Part of the analysis are automatically generated workflow-specific risk matrices including risks of medical devices incorporated into a specific workflow. In addition, SQL queries allow to quickly retrieve e.g., the details of the medical device network installed in a department.

CONCLUSION

Activity diagrams of UML can be used to model workflows in radiotherapy. Through this, a connection between the different levels of the entire workflow can be established and workflow-specific risk analysis is possible.

Exploring safety capacity from a risk and safety information integration perspective: Connotation, dimension mining and dimensionality reduction

With the development of safety science, the concept of safety capacity (SC) has been proposed. SC has been applied in many fields. Concurrently, there has been an active and robust development of research pertaining to it. However, SC research mainly focuses on practical engineering problems, and SC research is only regarded as the establishment of a quantitative model for system safety. Hence, the theoretical study of SC is ignored. Indeed, the integrated theoretical system and connotation of SC are lacking. In this study, an attempt is made to enrich the theoretical connotation of SC. The following aspects of theoretical exploration are included: (a) The theoretical connotation of SC is redefined so that the lack of theory with respect to SC can be made up. Moreover, research directions of SC are indicated as dimension mining (DM) and dimensionality reduction (DR). (b) The application value of safety similarity theory in the DM of SC is expounded according to the principle of analogism. Core principles of DM are proposed and explained. (c) Common methods of DR are summarized, and the one-sided cognition of DR for the current SC research is corrected. A case study of an explosion accident caused by a boiler water shortage is employed for further discussion. For the investigation of the explosion accident using fault tree analysis (FTA), DR of SC is utilized to provide a more comprehensive explanation. Therefore, the proposed SC is proven to be practical for the analysis of system safety. The results obtained from this study have important implications for research and practice of SC.

Human health risk model for microplastic exposure in the Arctic region

Microplastics enriched with carcinogens like heavy metals, polycyclic aromatic hydrocarbons (PAHs), and their derivatives are ubiquitous in Arctic waters. They contaminate the local land and sea-based food sources, which is a significant health hazard. It is thus imperative to assess the risk posed by them to the nearby communities, which primarily rely on locally available food sources to meet their energy requirements. This paper proposes a novel ecotoxicity model to assess the human health risk posed by microplastics. The region's geophysical and environmental conditions affecting human microplastic intake, along with the human physiological parameters influencing biotransformation, are incorporated into the developed causation model. It investigates the carcinogenic risk associated with microplastic intake in humans via ingestion in terms of incremental excess lifetime cancer risk (IELCR). The model first evaluates microplastic intake and then uses reactive metabolites produced due to the interaction of microplastics with xenobiotic metabolizing enzymes to assess cellular mutations that result in cancer. All these conditions are mapped in an Object-Oriented Bayesian Network (OOBN) framework to evaluate IELCR. The study will provide a vital tool for formulating better risk management strategies and policies in the Arctic region, especially concerning Arctic Indigenous peoples.

Occurrence and risk assessment of pharmaceuticals in hospital wastewater in Costa Rica

This work aims to determine the occurrence, hazard and prioritization of pharmaceuticals from hospital wastewater in Costa Rica through the monitoring of 70 compounds and assessing their environmental risk through a hazard quotient approach (HQ). Moreover, the quantification of selected antibiotic resistance genes (ARGs) was conducted for the first time in this matrix in this geographical location. Thirty-four pharmaceuticals were detected, being caffeine, 1,7-dimethylxanthine, acetaminophen, ibuprofen, naproxen, ciprofloxacin and ketoprofen the most frequent (>50% of the samples). Eighteen pharmaceuticals exhibited high hazard (HQ ≥ 1), while five more showed medium hazard (1 > HQ ≥ 0.1). Prioritization, which also included frequency parameters, revealed caffeine, lovastatin, diphenhydramine, acetaminophen, ibuprofen, ciprofloxacin, and sildenafil as the compounds of major concern. Similarly, cumulative hazard per sample (ΣHQ) estimated high hazard towards aquatic organisms in every sample. All selected ARGs, except mcr-1 (polymyxin resistance), were detected. Among genes conferring resistance to beta-lactams, blaCTX-M and blaKPC were the most abundant, related to resistance to cephalosporins and carbapenems. Ecotoxicological evaluation showed mostly low toxicity towards Daphnia magna and Vibrio fischeri, contrary to the marked effect observed towards Lactuca sativa. These findings provide relevant and novel information on the risk posed by hospital wastewater and their pharmaceutical content in the Latin American environmental context.

[Resilience of the critical infrastructure in hospitals : Categorization and quantification as a basis for optimization]

BACKGROUND

Critical infrastructure (CRITIS) in hospitals has become the focus of resilience research due to the impact of the COVID-19 pandemic and also the events in Ukraine. This foundational research examines overall contexts, categorizing and quantifying them. Previous research examined limited scale damage situations with little CRITIS involvement: Worst case studies are missing. The vulnerabilities of the CRITIS of one or more countries will likewise be a prime target for attack in current and future conflicts or criminal extortion, this is especially true in the healthcare sector. Therefore, detailed research with a black swan scenario is necessary in this field.

OBJECTIVE

The aim of the study was to create and validate a categorized and weighted model for the self-assessment of the resilience of critical infrastructure in German hospitals at different levels of care before the exemplary scenario of a prolonged supraregional power blackout.

MATERIAL AND METHODS

Using an explorative design, experts from 8 hospitals of different care levels performed an expert-based qualitative system analysis to develop, weight and test the model. The resilience index was then calculated using adapted interdependence analyses in a Vester influence matrix.

RESULTS

A total of 7 categories and 24 subcategories of hospital CRITIS were identified. There are several key elements: rank 1 of active elements is the emergency power system (E1), and for passive elements, it is the nursing staff (P2). This means that the emergency power system has the greatest impact on all other areas and the nursing staff are most dependent on all others for their work. The most critical elements, because they are most intertwined in the overall system, are the situation center/command staff (Z1) and technical staff (P3), on which the entire system depends. From the weighted individual elements of CRITIS, an overall resilience for a hospital can be calculated (resilience index). The developed model can be used by hospital crisis experts as part of a self-assessment to provide a basis for risk management, financial planning, technical planning, personnel planning or crisis and disaster management.

CONCLUSION

The categorization and quantification of critical infrastructure (CRITIS) in hospitals with the aim of resilience documentation and optimization is possible. The model that has been developed allows rapid adaptation to changing initial situations and increases in resilience that can be realized in the short and medium term. Emergency and crisis preparedness is a dynamic process, which has been combined here with the further development of critical infrastructure. Consequently, there can be no final state to be achieved but only a certain best possible framework within which the hospital as a business enterprise can operate. The classification of the categories in the model must also be constantly further developed and adapted to the current status. Once the explorative and qualitative basic research has been completed, it is necessary in a further step to subject the model, which has been validated by experts, to a broader review. Ideally, this will be done using quantitative methods and a significantly larger sample.

Development and clinical implementation of a digital system for risk assessments for radiation therapy

Before introducing new treatment techniques, an investigation of hazards due to unintentional radiation exposures is a reasonable activity for proactively increasing patient safety. As dedicated software is scarce, we developed a tool for risk assessment to design a quality management program based on best practice methods, i.e., process mapping, failure modes and effects analysis and fault tree analysis. Implemented as a web database application, a single dataset was used to describe the treatment process and its failure modes. The design of the system and dataset allowed failure modes to be represented both visually as fault trees and in a tabular form. Following the commissioning of the software for our department, previously conducted risk assessments were migrated to the new system after being fully re-assessed which revealed a shift in risk priorities. Furthermore, a weighting factor was investigated to bring risk levels of the migrated assessments into perspective. The compensation did not affect high priorities but did re-prioritize in the midrange of the ranking. We conclude that the tool is suitable to conduct multiple risk assessments and concomitantly keep track of the overall quality management activities.

Molecular and serological survey of bovine viral diarrhea virus infection in cattle in Kazakhstan

The aim of this study was to estimate the occurrence of bovine viral diarrhea virus (BVDV) infection and to assess the population immunity in cattle vaccinated against BVDV in different regions of Kazakhstan. Cattle samples were collected in 12 oblasts (43 districts) of Kazakhstan. A total of 2477 cattle from 114 herds and 21 Bukhara deer (Cervus elaphus bactrianus) were examined by ELISA and conventional RT-PCR. Univariate and multivariate logistic regression analysis was performed to identify risk factors associated with BVDV infection in the country. In total, antibodies against BVDV were found in 79.3% (1965/2477) of all the animals and 92.1% (105/114) of all the herds examined. Seroprevalence in unvaccinated and vaccinated animals was 48.6% (447/920) and 98.7% (1391/1410), respectively. Seroprevalence in deer was 19.1% (4/21). The BVDV RNA was detected in six unvaccinated cattle (0.2%). Sequence analysis of the 5'-untranslated region demonstrated that four of the detected strains belonged to BVDV-1 and two strains to BVDV-2. Regression analysis revealed that age, production type, housing method, farm size, and geographic location were risk factors for BVDV infection in cattle in Kazakhstan. The present data confirm circulation of BVDV-1 and BVDV-2 in Kazakhstan and highlight the need to improve strategies for prevention and control of BVDV infection in the country.

Quantitative assessment of microplastic contamination in muddy shores of Gulf of Khambhat, India

Microplastics (MPs) have become a global concern due to their widespread distribution in marine ecosystems. The present study was aimed to assess MPs contamination in 21 muddy shores sites situated in the Gulf of Khambhat. From each site, five samples (1 kg each) were collected. In the laboratory, the replicates were homogenated, out of which a 100 g sample was used for analysis. The total number of MPs, shape, colour, size and polymer composition of MPs were assessed. The MPs abundance ranged from 0.32 ± 0.18 particles/g (Jampore) to 2.81 ± 0.50 particles/g (Uncha Kotda) among different study sites. Moreover, threads were recorded maximum followed by films, foams and fragments. In case of MPs colour, black and blue coloured MPs occurred dominantly, with sizes ranging from 1 mm to 5 mm. FTIR analysis identified seven different types of plastic polymers, out of which polypropylene was the dominant plastic polymer (32.46 %) followed by polyurethane (32.16 %), acrylonitrile butadiene styrene (14.93 %), polystyrene (9.62 %), polyethylene terephthalate (4.61 %), polyethylene (3.71 %) and polyvinyl chloride (2.51 %). Based on the results of the Contamination factor (CF) value, Alang, Mahua, Ghogha and Uncha Kotda were identified as very high contaminated sites (CF ≥ 6). Pollution Load Index (PLI) value of entire study area revealed the Gulf of Khambhat as a polluted area with MPs contamination (PLI > 1). While value of Hazardous Index (H) identified 12 study sites as class-V risk category (H value > 10,000). Moreover, Pollution Risk Index (PRI) value revealed fifteen sites as very high contaminated sites (PRI > 1200). Pollution indices can be useful in predicting the level of MPs contamination at the study site. Overall, the present study provides the information on MPs contamination in the coastal region of the Gulf of Khambhat that can be used as a baseline data for future studies on the ecotoxicity of MPs on marine biota.

Release of live baitfish by recreational anglers drives fish pathogen introduction risk

Emerging diseases of wildlife are an existential threat to biodiversity, and human-mediated movements of live animals are a primary vector of their spread. Wildlife disease risk analyses offer an appealing alternative to precautionary approaches because they allow for explicit quantification of uncertainties and consideration of tradeoffs. Such considerations become particularly important in high-frequency invasion pathways with hundreds of thousands of individual vectors, where even low pathogen prevalence can lead to substantial risk. The purpose of this study was to examine the landscape-level dynamics of human behavior-mediated pathogen introduction risk in the context of a high-frequency invasion pathway. One such pathway is the use and release of live fish used as bait by recreational anglers. We used a stochastic risk assessment model parameterized by angler survey data from Minnesota, USA, to simulate one year of fishing in Minnesota and estimate the total number of risky trips for each of three pathogens: viral hemorrhagic septicemia virus, the microsporidian parasite Ovipleistophora ovariae, and the Asian fish tapeworm Schizocotyle acheilognathi. We assessed the number of introductions under four scenarios: current/baseline conditions, outbreak conditions (increased pathogen prevalence), source-focused control measures (decreased pathogen prevalence), and angler-focused control measures (decreased rates of release). We found that hundreds of thousands of introduction events can occur per year, even for regulated pathogens at low pathogen prevalence. Reducing the rate of illegal baitfish release had significant impact on risky trips in scenarios where a high number of anglers were involved, but was less impactful in circumstances with limited outbreaks and fewer affected anglers. In contrast, reducing pathogen prevalence in the source populations of baitfish had relatively little impact. In order to make meaningful changes in pathogen introduction risk, managers should focus efforts on containing local outbreaks and reducing illegal baitfish release to reduce pathogen introduction risk. Our study also demonstrates the risk associated with high-frequency invasion pathways and the importance of incorporating human behaviors into wildlife disease models and risk assessments.

[Care of the severely injured in mass casualty incidents : What is the difference compared to emergency room management?]

The management of a severely injured patient according to the standards and principles of individualized trauma care is a well-established procedure in many hospitals. The process is structured and standardized by the content of several course formats. In contrast, a mass casualty incident (MCI, MANV) is a rare and exceptional situation. In this case the treatment priorities and approaches are changed. The main aim in this situation is to ensure the best possible chance of survival for every casualty by organizational measures to mobilize rooms, personnel and material and to temporarily abandon the standards of individualized trauma care. To be prepared for a MCl situation it is necessary to know the realistic scenarios, to update the hospital emergency plan and to adapt all treatment procedures to the transient lack of resources. This article gives an overview of this process and summarizes the current clinical concepts to cope with a MCl situation and the current principles for the care of the severely injured involving many casualties.

A review of the effects of environmental hazards on humans, their remediation for sustainable development, and risk assessment

In the race for economic development and prosperity, our earth is becoming more polluted with each passing day. Technological advances in agriculture and rapid industrialization have drastically polluted the two pillars of natural resources, land and water. Toxic chemicals and microbial contaminants/agents created by natural and anthropogenic activities are rapidly becoming environmental hazards (EH) with increased potential to affect the natural environment and human health. This review has attempted to describe the various agents (chemical, biological, and physical) responsible for environmental contamination, remediation methods, and risk assessment techniques (RA). The main focus is on finding ways to mitigate the harmful effects of EHs through the simultaneous application of remediation methods and RA for sustainable development. It is recommended to apply the combination of different remediation methods using RA techniques to promote recycling and reuse of different resources for sustainable development. The report advocates for the development of site-specific, farmer-driven, sequential, and plant-based remediation strategies along with policy support for effective decontamination. This review also focuses on the fact that the lack of knowledge about environmental health is directly related to public health risks and, therefore, focuses on promoting awareness of effective ways to reduce anthropological burden and pollution and on providing valuable data that can be used in environmental monitoring assessments and lead to sustainable development.

Risk factors for SARS-CoV-2 seropositivity in a health care worker population during the early pandemic

BACKGROUND

While others have reported severe acute respiratory syndrome-related coronavirus 2(SARS-CoV-2) seroprevalence studies in health care workers (HCWs), we leverage the use of a highly sensitive coronavirus antigen microarray to identify a group of seropositive health care workers who were missed by daily symptom screening that was instituted prior to any epidemiologically significant local outbreak. Given that most health care facilities rely on daily symptom screening as the primary method to identify SARS-CoV-2 among health care workers, here, we aim to determine how demographic, occupational, and clinical variables influence SARS-CoV-2 seropositivity among health care workers.

METHODS

We designed a cross-sectional survey of HCWs for SARS-CoV-2 seropositivity conducted from May 15th to June 30th 2020 at a 418-bed academic hospital in Orange County, California. From an eligible population of 5,349 HCWs, study participants were recruited in two ways: an open cohort, and a targeted cohort. The open cohort was open to anyone, whereas the targeted cohort that recruited HCWs previously screened for COVID-19 or work in high-risk units. A total of 1,557 HCWs completed the survey and provided specimens, including 1,044 in the open cohort and 513 in the targeted cohort. Demographic, occupational, and clinical variables were surveyed electronically. SARS-CoV-2 seropositivity was assessed using a coronavirus antigen microarray (CoVAM), which measures antibodies against eleven viral antigens to identify prior infection with 98% specificity and 93% sensitivity.

RESULTS

Among tested HCWs (n = 1,557), SARS-CoV-2 seropositivity was 10.8%, and risk factors included male gender (OR 1.48, 95% CI 1.05-2.06), exposure to COVID-19 outside of work (2.29, 1.14-4.29), working in food or environmental services (4.85, 1.51-14.85), and working in COVID-19 units (ICU: 2.28, 1.29-3.96; ward: 1.59, 1.01-2.48). Amongst 1,103 HCWs not previously screened, seropositivity was 8.0%, and additional risk factors included younger age (1.57, 1.00-2.45) and working in administration (2.69, 1.10-7.10).

CONCLUSION

SARS-CoV-2 seropositivity is significantly higher than reported case counts even among HCWs who are meticulously screened. Seropositive HCWs missed by screening were more likely to be younger, work outside direct patient care, or have exposure outside of work.

The World Animal Health Information System as a tool to support decision-making and research in animal health

The World Animal Health Information System (WAHIS) collects and publishes a wealth of information gathered by individual countries' Veterinary Services, including detailed country-specific information on outbreaks of diseases listed by the World Organisation for Animal Health (WOAH, founded as OIE), including emerging diseases, in domestic animals and wildlife, and non-listed diseases in wildlife. The data set is one of the most comprehensive in the world, with 182 Members obliged to report this information to WOAH in a timely manner. As such, the data provide invaluable input for Veterinary Services, animal health researchers and stakeholders to gain insight into risk from infectious diseases, for example through the development of predictive models and risk assessments to address the risk from trade of animal products, globalisation, or movement of wildlife or vectors across country borders. This paper reviews previous analyses that have been conducted using WAHIS data and outlines ways in which these data can be used for preparedness and risk assessment.

Carcinogenic and human health risk assessment of children's and adults' exposure to toxic metal(oid)s from air PM10 in critical sites of the Republic of Serbia

With global urbanization and industrialization, air pollution has become an inevitable problem. Among air pollutants, toxic metals bound to particulate matter (PM) have a high hazardous potential, contributing to the development of several diseases, including various types of cancer. Due to PM pollution, Serbia is considered to be among the most polluted countries in Europe. Therefore, the objective of the study was to assess and characterize the non-carcinogenic and carcinogenic risks of children's and adults' exposure to metal(oid)s (Pb, Cd, Ni, and As) bound to PM₁₀ in five of the most polluted areas in the Republic of Serbia (Subotica, Smederevo, Bor, Valjevo, and Kraljevo). Non-carcinogenic (HQ and HI) and carcinogenic risk (CR) were calculated using USEPA methodology. Our results show that PM₁₀ concentrations exceeded the annual limit of 40 μg/m³ at four out of five monitoring sites (ranging from 44.33 to 63.25 μg/m³). Results obtained from Bor monitoring station show that safe limits were exceeded for both children and adults, indicating an unacceptable risk (> 1) obtained for inhalation exposure to the As (HQ = 6.14) and Cd (HQ = 1.17), while total HI was 7.43, which characterized the risk as unacceptable. For the same station, the CR value was 1.44E^-04 (> 1 × 10^-4). In other sites, the risks were acceptable. The characterized risk from exposure to the toxic elements via PM₁₀ in critical locations in Serbia contributes to improving air quality by requiring regulatory organs to take new actions and adopt new measures to reduce air pollution.

Risk management patterns in radiation oncology-results of a national survey within the framework of the Patient Safety in German Radiation Oncology (PaSaGeRO) project

PURPOSE

Risk management (RM) is a key component of patient safety in radiation oncology (RO). We investigated current approaches on RM in German RO within the framework of the Patient Safety in German Radiation Oncology (PaSaGeRO) project. Aim was not only to evaluate a status quo of RM purposes but furthermore to discover challenges for sustainable RM that should be addressed in future research and recommendations.

METHODS

An online survey was conducted from June to August 2021, consisting of 18 items on prospective and reactive RM, protagonists of RM, and self-assessment concerning RM. The survey was designed using LimeSurvey and invitations were sent by e‑mail. Answers were requested once per institution.

RESULTS

In all, 48 completed questionnaires from university hospitals, general and non-academic hospitals, and private practices were received and considered for evaluation. Prospective and reactive RM was commonly conducted within interprofessional teams; 88% of all institutions performed prospective risk analyses. Most institutions (71%) reported incidents or near-events using multiple reporting systems. Results were presented to the team in 71% for prospective analyses and 85% for analyses of incidents. Risk conferences take place in 46% of institutions. 42% nominated a manager/committee for RM. Knowledge concerning RM was mostly rated "satisfying" (44%). However, 65% of all institutions require more information about RM by professional societies.

CONCLUSION

Our results revealed heterogeneous patterns of RM in RO departments, although most departments adhered to common recommendations. Identified mismatches between recommendations and implementation of RM provide baseline data for future research and support definition of teaching content.

Quantitative microbial spoilage risk assessment of plant-based milk alternatives by Geobacillus stearothermophilus in Europe

Geobacillus stearothermophilus is one of the predominant spoilers of UHT-treated food products, due to its extremely heat-resistant spores. However, the surviving spores should be exposed to temperature higher than their minimum growth temperature for a certain time to germinate and grow to spoilage levels. Considering the projected temperature increase due to climate change, the events of non-sterility during distribution and transportation are expected to escalate. Hence, the aim of this study was to build a quantitative microbial spoilage risk assessment (QMRSA) model to quantify the risk of spoilage of plant-based milk alternatives within Europe. The model consists of four main steps: 1. Initial contamination of raw materials 2. Heat inactivation of spores during UHT treatment 3. Partitioning 4. Germination and outgrowth of spores during distribution and storage. The risk of spoilage was defined as the probability of G. stearothermophilus to reach its maximum concentration (N_max = 10^7.5 CFU/mL) at the time of consumption. The assessment was performed for North (Poland) and South (Greece) Europe, and the risk of spoilage was estimated for the current climatic conditions and a climate change scenario. Based on the results, the risk of spoilage was negligible for the North European region, while the risk of spoilage in South Europe was 6.2 × 10^-3 95% CI (2.3 × 10^-3;1.1 × 10^-2) under the current climatic conditions. The risk of spoilage was increased for both tested countries under climate change scenario; from zero to 1.0 × 10^-4 in North Europe, risk multiplied 2 or 3 in South Europe depending on air conditioning implementation at consumer's place. Therefore, the heat treatment intensity and the use of insulated trucks during distribution were investigated as mitigation strategies and led to significant reduction of the risk. Overall, the QMRSA model developed in this study can support risk management decisions of these products by quantify the potential risk under current climatic conditions and climate change scenarios.

Over Expression of Cancer Stem Cell Marker CD44 and Its Clinical Significance in Patients with Oral Squamous Cell Carcinoma

Cancer stem cell marker CD44 is a cell-surface glycoprotein which is involved in various cellular functions such as cell-cell interactions, cell adhesion, haematopoiesis and tumour metastasis. The CD44 gene transcription is partly activated by beta-catenin and Wnt signalling pathway, the later pathway being linked to tumour development. However, the role of CD44 in oral squamous cell carcinoma (OSCC) is not well understood. We investigated the expression of CD44 in peripheral circulation, tumour tissues of oral cancer patients and oral squamous cell carcinoma cell lines by ELISA and quantitative (q)-RTPCR. Relative CD44s mRNA expression was significantly higher in peripheral circulation (p = 0.04), tumour tissues (p = 0.049) and in oral cancer cell lines (SCC4, SCC25 p = 0.02, SCC9 p = 0.03). Circulating CD44total protein levels were also significantly (p < 0.001) higher in OSCC patients that positively correlated with increasing tumour load and loco-regional spread of the tumour. The circulating tumour stem cell marker CD44 appears to be a potent indicator of tumour progression and may be useful for developing suitable therapeutics strategies for patients with oral squamous cell carcinoma.

Probabilistic risk analysis of unit trains versus manifest trains for transporting hazardous materials

When transporting hazardous materials by rail, train types (unit train or manifest train) can influence derailment and release risks in several ways. Unit trains only experience risks on mainlines and when arriving at or departing from terminals, while manifest trains experience additional switching risks in yards. A comprehensive risk assessment methodology is needed to quantitively compare shipments with unit trains and manifest trains, considering both mainline and yard operations. To fulfill this research gap, this paper constructs event chains for line-haul risks, arrival/departure risks, and yard switching risks using various probabilistic models and finally determines expected casualties as the consequences of a potential train derailment and release incident. Five illustrative scenarios are designed to analyze the best and worst cases and compare the transportation risk differences between service options using unit trains and manifest trains. The comparison results indicate that placing all tank cars at the positions with the lowest probability of derailing and switching tank cars alone in classification yards could provide the lowest risk estimate given the same transportation demand.

Machine learning-based model for predicting the esophagogastric variceal bleeding risk in liver cirrhosis patients

BACKGROUND

Liver cirrhosis patients are at risk for esophagogastric variceal bleeding (EGVB). Herein, we aimed to estimate the EGVB risk in patients with liver cirrhosis using an artificial neural network (ANN).

METHODS

We included 999 liver cirrhosis patients hospitalized at the Beijing Ditan Hospital, Capital Medical University in the training cohort and 101 patients from Shuguang Hospital in the validation cohort. The factors independently affecting EGVB occurrence were determined via univariate analysis and used to develop an ANN model.

RESULTS

The 1-year cumulative EGVB incidence rates were 11.9 and 11.9% in the training and validation groups, respectively. A total of 12 independent risk factors, including gender, drinking and smoking history, decompensation, ascites, location and size of varices, alanine aminotransferase (ALT), γ-glutamyl transferase (GGT), hematocrit (HCT) and neutrophil-lymphocyte ratio (NLR) levels as well as red blood cell (RBC) count were evaluated and used to establish the ANN model, which estimated the 1-year EGVB risk. The ANN model had an area under the curve (AUC) of 0.959, which was significantly higher than the AUC for the North Italian Endoscopic Club (NIEC) (0.669) and revised North Italian Endoscopic Club (Rev-NIEC) indices (0.725) (all P <  0.001). Decision curve analyses revealed improved net benefits of the ANN compared to the NIEC and Rev-NIEC indices.

CONCLUSIONS

The ANN model accurately predicted the 1-year risk for EGVB in liver cirrhosis patients and might be used as a basis for risk-based EGVB surveillance strategies.

Increased human risk caused by cascading hazards - A framework

Cascading hazards occur frequently. Unexpected casualties and losses of properties, or even impacts on the society and the environment may ensue from failure to anticipate the amplified risks induced by cascading hazards. Current risk assessment methods pay relatively less attention to quantifying the increased human risk related to "cascading" events. An improved framework for quantifying the human risk caused by cascading hazards is proposed in this paper. The framework considers the interactions among the cascading hazards and among the vulnerabilities of elements to these hazards. Its kernel is to scientifically anticipate and gear up for any new intensified hazards, which may otherwise lead to serious social aftermath. The framework is illustrated with a multi-hazard example close to the epicenter of the Wenchuan earthquake, which involved a chain of hazards including slope failures, a large debris flow, river damming, and flooding.

Prospective risk analysis of the online-adaptive artificial intelligence-driven workflow using the Ethos treatment system

PURPOSE

The recently introduced Varian Ethos system allows adjusting radiotherapy treatment plans to anatomical changes on a daily basis. The system uses artificial intelligence to speed up the process of creating adapted plans, comes with its own software solutions and requires a substantially different workflow. A detailed analysis of possible risks of the associated workflow is presented.

METHODS

A prospective risk analysis of the adaptive workflow with the Ethos system was performed using Failure Modes and Effects Analysis (FMEA). An interprofessional team collected possible adverse events and evaluated their severity as well as their chance of occurrence and detectability. Measures to reduce the risks were discussed.

RESULTS

A total of 122 events were identified, and scored. Within the 20 events with the highest-ranked risks, the following were identified: Challenges due to the stand-alone software solution with very limited connectivity to the existing record and verify software and digital patient file, unfamiliarity with the new software and its limitations and the adaption process relying on results obtained by artificial intelligence. The risk analysis led to the implementation of additional quality assurance measures in the workflow.

CONCLUSIONS

The thorough analysis of the risks associated with the new treatment technique was the basis for designing details of the workflow. The analysis also revealed challenges to be addressed by both, the vendor and customers. On the vendor side, this includes improving communication between their different software solutions. On the customer side, this especially includes establishing validation strategies to monitor the results of the black box adaption process making use of artificial intelligence.