Prospective Risk Assessment Research Articles

Quantifying the Accuracy of Clinician Risk Assessment for Postpartum Hemorrhage

Abstract Objective To measure the accuracy of postpartum hemorrhage (PPH) risk assessment performed by unaided individual clinicians, to inform future comparison to alternative risk assessment methods. Methods Prospective PPH risk assessments were collected from obstetric care team clinicians at two quaternary medical centers in the United States (Vanderbilt University Medical Center, Brigham and Women’s Hospital) from January 2022 to January 2023, following written informed consent from the providers. The data included a cohort of both vaginal and cesarean deliveries (CD). For each assessment, the clinician quantified the patient’s predicted PPH risk on a scale from 0 to 100% and rated their confidence in these assessments using a 5-point Likert scale, ranging from ‘not at all confident’ to ‘completely confident’. Medical records were reviewed 24 hours postpartum to assess the dichotomous outcome of PPH, defined as blood loss ≥1000 mL. The accuracy of these predictions was evaluated using the area under the receiver operating characteristic curve (AUC). Results Of 271 patients, 32 (11.8%) experienced PPH, accounting for 11.4% (104/915) of assessments. The overall AUC was 0.64 (95% confidence interval (CI): 0.58–0.71). Prediction accuracy was higher for CD than for vaginal deliveries, with AUCs of 0.82 (95% CI: 0.72–0.91) and 0.56 (95% CI: 0.48–0.63), respectively. No significant differences in the accuracy of assessments were observed according to physician specialty, physician experience level, or confidence level of the assessment. Conclusion Overall unaided clinician performance in predicting PPH was moderate, with an AUC of 0.64. Predictions were more accurate for patients undergoing CD. Further study is needed to understand how clinician performance compares to other modalities of risk prediction.

Older Adult Fall Risk Prediction with Deep Learning and Timed Up and Go (TUG) Test Data.

Falls are a major health hazard for older adults; therefore, in the context of an aging population, predicting the risk of a patient suffering falls in the near future is of great impact for health care systems. Currently, the standard prospective fall risk assessment instrument relies on a set of clinical and functional mobility assessment tools, one of them being the Timed Up and Go (TUG) test. Recently, wearable inertial measurement units (IMUs) have been proposed to capture motion data that would allow for the building of estimates of fall risk. The hypothesis of this study is that the data gathered from IMU readings while the patient is performing the TUG test can be used to build a predictive model that would provide an estimate of the probability of suffering a fall in the near future, i.e., assessing prospective fall risk. This study applies deep learning convolutional neural networks (CNN) and recurrent neural networks (RNN) to build such predictive models based on features extracted from IMU data acquired during TUG test realizations. Data were obtained from a cohort of 106 older adults wearing wireless IMU sensors with sampling frequencies of 100 Hz while performing the TUG test. The dependent variable is a binary variable that is true if the patient suffered a fall in the six-month follow-up period. This variable was used as the output variable for the supervised training and validations of the deep learning architectures and competing machine learning approaches. A hold-out validation process using 75 subjects for training and 31 subjects for testing was repeated one hundred times to obtain robust estimations of model performances At each repetition, 5-fold cross-validation was carried out to select the best model over the training subset. Best results were achieved by a bidirectional long short-term memory (BLSTM), obtaining an accuracy of 0.83 and AUC of 0.73 with good sensitivity and specificity values.

Cohort profile: a nationwide study in Dutch CHEK2 c.1100delC families using the infrastructure of the HEreditary Breast and Ovarian cancer study Netherlands – Hebon-CHEK2

PurposeCHEK2 c.1100delC is associated with an increased breast cancer risk in women. While this variant is prevalent in the Netherlands (1% in the general population), knowledge of aetiology and prognosis...

Mock Assessment: Acute prospective cumulative risk assessment

Abstract This Mock assessment is a part of the Framework Partnership Agreement between ANSES and EFSA with the help of RIVM to investigate the feasibility of a tiered approach proposed by EFSA for prospective acute cumulative risk assessment (CRA). Three tiers address successively a need for prospective CRA (Tier 0), the safety of the MRL (Tier I) and the safety of the intended GAP (Tier II). ANSES tested this approach with an application for change of MRL for the active substance tefluthrin (with acute effects on functional alterations of the motor division) on carrot based on a new intended use. For each tier, the Margin of Exposure (MOE) was calculated for 9 populations with MCRA software using input data provided by EFSA. At P99.9 of exposure, all the adjusted MOET at Tier I and Tier II of all populations were below the threshold of 100. Different settings were tested (IESTI equation, consumption data, adjustment for uncertainties, cycle of monitoring data…). With respect to Tier I, the trigger value of 1000 for the MOETier 0 is pragmatic. In the vast majority of cases, when the MOETier 0 is above 1000, the MOETTier I would be above 100. With respect to Tier II, a MOETier 0 higher than 1000 ensures a MOETTier II above 100. Tier I could be considered a good first estimate for a prospective CRA with conservative parameters for the foreground. Two routes were tested to account for uncertainties. One was not possible. The second resulted in a new median multiplicative factor (MF)exposure*toxicology of 2.82 that differs significantly from the value of 5.13 found in the retrospective assessment. Despite the simplifications envisaged, the uncertainty analysis seems difficult to be implemented on a routine basis and it might be useful to define criteria to identify cases where an uncertainty analysis is really needed.

Mock assessment: Chronic prospective cumulative risk assessment

Abstract This Mock assessment is a part of the Framework Partnership Agreement between ANSES and EFSA with the help of RIVM to investigate the feasibility of a tiered approach proposed by EFSA for prospective chronic cumulative risk assessment (CRA). Three tiers address successively (i) a need for prospective CRA (Tier 0) using a deterministic approach to estimate the foreground exposure based on IEDI equation, (ii) a first estimation of prospective CRA (Tier I) using a probabilistic approach to estimate the background exposure at P99.9 and a deterministic approach to estimate the foreground exposure at mean or P97.5 consumption and (iii) a second estimation of prospective CRA (Tier II) using a probabilistic approach to estimate the background and foreground exposure at P99.9. ANSES tested this approach with an MRL application for the active substance fenamidone (with chronic effects on the thyroid) on lettuce, based on a new intended use currently under assessment at national level. For each Tier, the Margin of Exposure (MOE) was calculated for 9 populations with MCRA software using input data provided by EFSA and settings according to EFSA protocol. Different combinations of settings were tested as part of sensitivity analyses (consumption data, adjustment for additional uncertainties, cycle of monitoring data, etc.) and were used as the basis for discussion of different open points (trigger value in Tier 0, use frequency for the focal combination in tier II, ad hoc uncertainty analysis to account for additional uncertainties, etc.) to be addressed before prospective CRA could be implemented as a routine exercise. Finally, based on these discussions, recommendations were made to consolidate the approach for chronic prospective CRA.

A conceptual framework for landscape-based environmental risk assessment (ERA) of pesticides

While pesticide use is subject to strict regulatory oversight worldwide, it remains a main concern for environmental protection, including biodiversity conservation. This is partly due to the current regulatory approach that relies on separate assessments for each single pesticide, crop use, and non-target organism group at local scales. Such assessments tend to overlook the combined effects of overall pesticide usage at larger spatial scales. Integrative landscape-based approaches are emerging, enabling the consideration of agricultural management, the environmental characteristics, and the combined effects of pesticides applied in a same or in different crops within an area. These developments offer the opportunity to deliver informative risk predictions relevant for different decision contexts including their connection to larger spatial scales and to combine environmental risks of pesticides, with those from other environmental stressors. We discuss the needs, challenges, opportunities and available tools for implementing landscape-based approaches for prospective and retrospective pesticide Environmental Risk Assessments (ERA). A set of “building blocks” that emerged from the discussions have been integrated into a conceptual framework. The framework includes elements to facilitate its implementation, in particular: flexibility to address the needs of relevant users and stakeholders; means to address the inherent complexity of environmental systems; connections to make use of and integrate data derived from monitoring programs; and options for validation and approaches to facilitate future use in a regulatory context. The conceptual model can be applied to existing ERA methodologies, facilitating its comparability, and highlighting interoperability drivers at landscape level. The benefits of landscape-based pesticide ERA extend beyond regulation. Linking and validating risk predictions with relevant environmental impacts under a solid science-based approach will support the setting of protection goals and the formulation of sustainable agricultural strategies. Moreover, landscape ERA offers a communication tool on realistic pesticide impacts in a multistressors environment for stakeholders and citizens.

Beat-to-beat blood pressure variability, hippocampal atrophy, and memory impairment in older adults.

Visit-to-visit blood pressure variability (BPV) predicts age-related hippocampal atrophy, neurodegeneration, and memory decline in older adults. Beat-to-beat BPV may represent a more reliable and efficient tool for prospective risk assessment, but it is unknown whether beat-to-beat BPV is similarly associated with hippocampal neurodegeneration, or with plasma markers of neuroaxonal/neuroglial injury. Independently living older adults without a history of dementia, stroke, or other major neurological disorders were recruited from the community (N = 104; age = 69.5 ± 6.7 (range 55-89); 63% female). Participants underwent continuous blood pressure monitoring, brain MRI, venipuncture, and cognitive testing over two visits. Hippocampal volumes, plasma neurofilament light, and glial fibrillary acidic protein levels were assessed. Beat-to-beat BPV was quantified as systolic blood pressure average real variability during 7-min of supine continuous blood pressure monitoring. The cross-sectional relationship between beat-to-beat BPV and hippocampal volumes, cognitive domain measures, and plasma biomarkers was assessed using multiple linear regression with adjustment for demographic covariates, vascular risk factors, and average systolic blood pressure. Elevated beat-to-beat BPV was associated with decreased left hippocampal volume (P = .008), increased plasma concentration of glial fibrillary acidic protein (P = .006), and decreased memory composite score (P = .02), independent of age, sex, average systolic blood pressure, total intracranial volume, and vascular risk factor burden. In summary,beat-to-beat BPV is independently associated with decreased left hippocampal volume, increased neuroglial injury, and worse memory ability. Findings are consistent with prior studies examining visit-to-visit BPV and suggest beat-to-beat BPV may be a useful marker of hemodynamic brain injury in older adults.

Failure Mode and Effects Analysis Application in External Beam Radiotherapy

Background: Radiotherapy is a medical procedure with potential high risk to harm patients. In order to reduce that risk and create a workflow safe for patients, prospective analysis tools are used. Failure modes and effect analysis (FMEA) is one such tool, used to evaluate potential risks. As FMEA originated from industry, there is a constant effort to adjust FMEA methodology for use in radiotherapy. This has caused a variety of approaches and inhomogeneous practices. Purpose: To investigate the current practice of FMEA in external beam radiotherapy and to propose a more standardised approach. Materials and Methods: The search was performed in PubMed, Ovid and Embase databases, resulting in 312 articles retrieved. Using PRISMA methodology the number of unique articles meeting inclusion and exclusion criteria was reduced to a total of 35, containing 38 analyses. The data on FMEA methodology implemented, scope of analysis, expert team composition, number of failure modes (FM) detected, relative priority number (RPN) threshold, number of FM exceeding the threshold, minimum, maximum and mean RPN, RPN calculation method and risk mitigation strategies were selected as important properties of FMEA. Results: Data retrieved showed large variation in how FMEA is conducted. There is a considerable underreporting of minimum and mean RPN values. Large variations in RPN threshold value selection were also observed. Two different approaches to RPN calculation procedure were reported, and it is unclear what the best practice is. Expert teams were assembled according to the guidelines, but the optimal number of members is unclear. The vast majority of risk mitigation measures were applied directly, without the use of systematic tools. Conclusion: FMEA is a well-established and widely used tool for prospective risk assessment in radiotherapy. As a result of this analysis, recommendations for more standardized approaches were proposed. Possible additional research goals were proposed in order to provide evidence for best practice in some areas of FMEA.

The ConSoil project: An integrated framework for monitoring plant protection product residues in agricultural soil

AbstractPlant Protection Products (PPPs) are widely used to maintain high productivity and protect crops, but can have unintended toxic effects on beneficial non‐target soil organisms. To avoid unacceptable adverse effects of PPPs on soil organisms, a prospective risk assessment is carried out, which focuses on individual substances and their effects on a few individual species or groups. However, the reality of agricultural soils consists of complex networks of organisms exposed to mixtures of several PPP active substances. It is therefore essential to monitor PPP residues in soils. This paper describes the ConSoil project and its proposed framework for monitoring PPP residues in Swiss Agricultural soils which includes and integrates (1) risk‐based reference values for PPP residues in soil and (2) indicators of their effects on long‐term soil fertility. For risk‐based reference values, a proposal has been developed to derive Soil Guideline Values (SGVs) for PPP residues and a mixture risk assessment concept is being developed. Regarding indicators, a toolbox of ecological and ecotoxicological indicators will be proposed to reflect the protection goal of long‐term soil fertility in agricultural soils. For this objective, standardised and/or well‐established bioindicator methods will be selected for the key soil organisms that support soil fertility. To integrate SGVs and the biomonitoring toolbox, an adapted TRIAD approach is proposed, where generic SGVs are used as a screening tool to identify monitoring sites potentially at risk and to trigger more detailed monitoring. Detailed monitoring will refine the SGVs based on site‐specific characteristics and implement the bioindicator toolbox to measure the effects of PPP residues and their risk to long‐term soil fertility. As a novel integrated framework, it is essential to use the data generated in detailed assessments to calibrate and refine the SGVs and bioindicator tools and improve the monitoring over time.

When tomorrow comes: A prospective risk assessment of a future artificial general intelligence-based uncrewed combat aerial vehicle system

There are concerns that Artificial General Intelligence (AGI) could pose an existential threat to humanity; however, as AGI does not yet exist it is difficult to prospectively identify risks and develop requisite controls. We applied the Work Domain Analysis Broken Nodes (WDA-BN) and Event Analysis of Systemic Teamwork-Broken Links (EAST-BL) methods to identify potential risks in a future ‘envisioned world’ AGI-based uncrewed combat aerial vehicle system. The findings suggest five main categories of risk in this context: sub-optimal performance risks, goal alignment risks, super-intelligence risks, over-control risks, and enfeeblement risks. Two of these categories, goal alignment risks and super-intelligence risks, have not previously been encountered or dealt with in conventional safety management systems. Whereas most of the identified sub-optimal performance risks can be managed through existing defence design lifecycle processes, we propose that work is required to develop controls to manage the other risks identified. These include controls on AGI developers, controls within the AGI itself, and broader sociotechnical system controls.

A prospective ecological risk assessment of high-efficiency III-V/silicon tandem solar cells.

III-V/Silicon tandem solar cells offer one of the most promising avenues for high-efficiency, high-stability photovoltaics. However, a key concern is the potential environmental release of group III-V elements, especially arsenic. To inform long-term policies on the energy transition and energy security, we develop and implement a framework that fully integrates future PV demand scenarios with dynamic stock, emission, and fate models in a probabilistic ecological risk assessment. We examine three geographical scales: local (including a floating utility-scale PV and waste treatment), regional (city-wide), and continental (Europe). Our probabilistic assessment considers a wide range of possible values for over one hundred uncertain technical, environmental, and regulatory parameters. We find that III-V/silicon PV integration in energy grids at all scales presents low-to-negligible risks to soil and freshwater organisms. Risks are further abated if recycling of III-V materials is considered at the panels' end-of-life.

Pesticides in Agricultural Soils: Major Findings from Various Monitoring Campaigns in Switzerland.

Synthetic pesticides are widely applied in modern agriculture, where they are used against diseases, pests, and weeds to secure crop yield and quality. However, their intensive application has led to widespread contamination of the environment, including soils. Due to their inherent toxicity, they might pose a risk to soil health by causing harm to non-target organisms and disrupting ecosystem services in both agricultural and other exposed soils. Following the Swiss National Action Plan on the reduction of pesticide risks, Agroscope has conducted several soil monitoring studies that are briefly presented here. All of them resort to different multi-residue trace analytical approaches to simultaneously quantify up to about 150 modern pesticides by either accelerated solvent, or Quick, Easy, Cheap, Efficient, Rugged, Safe (QuEChERS) extraction, followed by separation and detection with liquid chromatography-triple quadrupole mass spectrometry. While partly still in progress, our investigations led to the following major findings this far: Multiple pesticides are commonly present in soils, with individual concentrations in agricultural soils often reaching up to a few tens of µg/kg. Pesticide occurrence and concentrations in agricultural soils primarily depend on land use, land use history and cultivated crops. Pesticides can prevail much longer than predicted by their half-lives, and were found in soils even decades after conversion from conventional to organic farming. Corresponding residual fractions can be in the order of a few percent of the originally applied amounts. We further found negative associations of pesticide residues with the abundance of beneficial soil life, underpinning their potential risk to the fertility of agricultural soils. Traces of pesticides are also detected in soils to which they were never applied, indicating contamination, e.g., via spray drift or atmospheric deposition. These results confirm the general notion of both scientists and legislators that prospective risk assessments (RA; as executed during registration and use authorization) should be confirmed and adjusted by retrospective RA (e.g., by environmental monitoring studies of currently used compounds) to jointly lead to an overall reduced environmental risk of pesticides.

Whole-genome methylation profiling reveals regions associated with painful temporomandibular disorders and active recovery processes.

Temporomandibular disorders (TMDs), collectively representing one of the most common chronic pain conditions, have a substantial genetic component, but genetic variation alone has not fully explained the heritability of TMD risk. Reasoning that the unexplained heritability may be because of DNA methylation, an epigenetic phenomenon, we measured genome-wide DNA methylation using the Illumina MethylationEPIC platform with blood samples from participants in the Orofacial Pain: Prospective Evaluation and Risk Assessment (OPPERA) study. Associations with chronic TMD used methylation data from 496 chronic painful TMD cases and 452 TMD-free controls. Changes in methylation between enrollment and a 6-month follow-up visit were determined for a separate sample of 62 people with recent-onset painful TMD. More than 750,000 individual CpG sites were examined for association with chronic painful TMD. Six differentially methylated regions were significantly ( P < 5 × 10 -8 ) associated with chronic painful TMD, including loci near genes involved in the regulation of inflammatory and neuronal response. A majority of loci were similarly differentially methylated in acute TMD consistent with observed transience or persistence of symptoms at follow-up. Functional characterization of the identified regions found relationships between methylation at these loci and nearby genetic variation contributing to chronic painful TMD and with gene expression of proximal genes. These findings reveal epigenetic contributions to chronic painful TMD through methylation of the genes FMOD , PM20D1 , ZNF718 , ZFP57 , and RNF39 , following the development of acute painful TMD. Epigenetic regulation of these genes likely contributes to the trajectory of transcriptional events in affected tissues leading to resolution or chronicity of pain.

Quantitative fluid overload in severe aortic stenosis refines cardiac damage and associates with worse outcomes

Abstract Background Cardiac decompensation in aortic stenosis (AS) involves extra-valvular cardiac damage (CD) and progressive fluid overload (FO). FO can be objectively quantified using bioimpedance spectroscopy (BIS). Objectives We aimed to assess the prognostic value of FO beyond established CD markers to guide risk stratification. Methods Consecutive patients with severe AS scheduled for transcatheter aortic valve implantation (TAVI) underwent prospective risk assessment with BIS and echocardiography. FO by BIS was defined as ≥1.0L (0.0L=euvolemia). The extent of CD was assessed by echocardiography according to an established staging classification. Right-sided CD (rCD) was defined as pulmonary vasculature/tricuspid/right ventricular CD. Heart failure hospitalization (HHF) and/or death served as primary endpoint. Results In total, 880 patients (81±7y/o, 47% female) undergoing TAVI were included. 360 (41%) had FO. Clinical examination in patients with FO was unremarkable for congestion signs in &amp;gt;50%. A quarter had FO but no rCD (FO+/rCD-). FO+/rCD+ had the highest CD markers, including NT-proBNP levels. After 2.4±1.0 years of follow-up, 236 patients (27%) had reached the primary endpoint (29 HHF, 194 deaths, 13 both). Quantitatively, every 1.0L increase in BIS was associated with a 12% increase in event hazard (adjHR 1.12, 95% CI 1.05-1.20, P=0.001). FO provided incremental prognostic value to traditional risk markers (NT-proBNP, EuroSCORE-II, CD on echocardiography). Stratification according to FO and rCD yielded worse outcomes for FO+/rCD+ and FO+/rCD-, but not FO-/rCD+, compared to FO-/rCD-. Conclusion Quantitative FO in patients with severe AS improves risk prediction of worse post-interventional outcomes compared to traditional risk assessment.

Incorporating climate projections in the environmental risk assessment of pesticides in aquatic ecosystems.

Global climate change will significantly impact the biodiversity of freshwater ecosystems, both directly and indirectly via the exacerbation of impacts from other stressors. Pesticides form a prime example of chemical stressors that are expected to synergize with climate change. Aquatic exposures to pesticides might change in magnitude due to increased runoff from agricultural fields, and in composition, as application patterns will change due to changes in pest pressures and crop types. Any prospective chemical risk assessment that aims to capture the influence of climate change should properly and comprehensively account for the variabilities and uncertainties that are inherent to projections of future climate. This is only feasible if they probabilistically propagate extensive ensembles of climate model projections. However, current prospective risk assessments typically make use of process-based models of chemical fate that do not typically allow for such high-throughput applications. Here, we describe a Bayesian network model that does. It incorporates a two-step univariate regression model based on a 30-day antecedent precipitation index, circumventing the need for computationally laborious mechanistic models. We show its feasibility and application potential in a case study with two pesticides in a Norwegian stream: the fungicide trifloxystrobin and herbicide clopyralid. Our analysis showed that variations in pesticide application rates as well as precipitation intensity lead to variations in in-stream exposures. When relating to aquatic risks, the influence of these processes is reduced and distributions of risk are dominated by effect-related parameters. Predicted risks for clopyralid were negligible, but the probability of unacceptable future environmental risks due to exposure to trifloxystrobin (i.e., a risk quotient >1) was 8%-12%. This percentage further increased to 30%-35% when a more conservative precautionary factor of 100 instead of 30 was used. Integr Environ Assess Manag 2024;20:384-400. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Characterization of Common Genetic Variants in P2RX7 and Their Contribution to Chronic Pain Conditions

The adenosine triphosphate (ATP)-gated channel P2X7 is encoded by a gene enriched for common nonsynonymous variants. Many of these variants have functional cellular effects, and some have been implicated in chronic pain. In this study, we first systematically characterized all 17 common nonsynonymous variants using whole-cell patch clamp electrophysiology. Then, we analyzed these variants for statistical association with chronic pain phenotypes using both individual P2RX7 variants as predictors and cumulative allele counts of same-direction cellular effect in univariate models. Association and validation analyses were conducted in the Orofacial Pain: Prospective Evaluation and Risk Assessment (OPPERA) cohort (N = 3260) and in the Complex Persistent Pain Conditions (CPPC) cohort (N = 900), respectively. Our results showed an association between allele A of rs7958311 and an increased risk of chronic pelvic pain, with convergent evidence for contribution to fibromyalgia and irritable bowel syndrome, confirmed in a meta-analysis. This allelic variant produced a unique cellular phenotype: a gain-of-function in channel opening, and a loss-of-function in pore opening. A computational study using a 12-state Markov model of ATP binding to the P2X7 receptor suggested that this cellular phenotype arises from an increased ATP binding affinity and an increased open channel conductance combined with a loss of sensitization. Cumulative allele count analysis did not provide additional insights. In conclusion, our results go beyond reproducing association for rs7958311 with chronic pain and suggest that its unique combination of gain-of-function in channel and loss-of-function in pore activity may explain why it is likely the only common P2RX7 variant with contribution to chronic pain. PerspectiveThis study characterizes all common P2RX7 variants using cellular assays and statistical association analyses with chronic pain, with Markov state modeling of the most robustly associated variant.

A prospective ecological risk assessment method based on exposure and ecological scenarios (ERA-EES) to determine soil ecological risks around metal mining areas

Soil heavy metal (HM) contamination around metal mining areas (MMAs) is a global concern that requires a cost-effective ecological risk assessment (ERA) method for preventive management. Traditional ERAs, comparing environmental HM concentrations with benchmarks, are labor- and cost-intensive in field investigations and chemical analyses, which challenge the management demands of numerous MMAs. In this study, a prospective ecological risk assessment method based on exposure and ecological scenario (ERA-EES) was developed to predict the eco-risk levels (low/medium/high) around MMAs prior to field sampling. Five exposure scenario indicators related to soil HM exposure and three ecological scenario indicators reflecting the soil bioreceptor response were selected and combined with the analytic hierarchy process and fuzzy comprehensive evaluation methods for ERA-EES development. Case application and performance evaluation with 67 MMAs in China demonstrated that the ERA-EES method had an overall effective and conservative performance when referring to potential ecological risk index (PERI) levels, with an accuracy of 0.87, kappa coefficient of 0.7, and low or medium eco-risk levels in PERI classified to high levels in ERA-EES. Overall, the selected scenario indicators could efficiently reflect the risk levels of soil HM pollution from mining activities. Besides, more regulatory efforts should be paid to the MMAs of nonferrous metals, underground and long-term mining and those located in southern China. This work provided a convenient and cost-effective prospective ERA method under the trend of ERA being tiered and refined, facilitating the risk management of various MMAs.

Quantitative fluid overload in severe aortic stenosis refines cardiac damage and associates with worse outcomes.

Cardiac decompensation in aortic stenosis (AS) involves extra-valvular cardiac damage and progressive fluid overload (FO). FO can be objectively quantified using bioimpedance spectroscopy. We aimed to assess the prognostic value of FO beyond established damage markers to guide risk stratification. Consecutive patients with severe AS scheduled for transcatheter aortic valve implantation (TAVI) underwent prospective risk assessment with bioimpedance spectroscopy (BIS) and echocardiography. FO by BIS was defined as ≥1.0 L (0.0 L = euvolaemia). The extent of cardiac damage was assessed by echocardiography according to an established staging classification. Right-sided cardiac damage (rCD) was defined as pulmonary vasculature/tricuspid/right ventricular damage. Hospitalization for heart failure (HHF) and/or death served as primary endpoint. In total, 880 patients (81 ± 7 years, 47% female) undergoing TAVI were included and 360 (41%) had FO. Clinical examination in patients with FO was unremarkable for congestion signs in >50%. A quarter had FO but no rCD (FO+/rCD-). FO+/rCD+ had the highest damage markers, including N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels. After 2.4 ± 1.0 years of follow-up, 236 patients (27%) had reached the primary endpoint (29 HHF, 194 deaths, 13 both). Quantitatively, every 1.0 L increase in bioimpedance was associated with a 13% increase in event hazard (adjusted hazard ratio 1.13, 95% confidence interval 1.06-1.22, p < 0.001). FO provided incremental prognostic value to traditional risk markers (NT-proBNP, EuroSCORE II, damage on echocardiography). Stratification according to FO and rCD yielded worse outcomes for FO+/rCD+ and FO+/rCD-, but not FO-/rCD+, compared to FO-/rCD-. Quantitative FO in patients with severe AS improves risk prediction of worse post-interventional outcomes compared to traditional risk assessment.

A structured FMEA approach to optimizing combinations of plan-specific quality assurance techniques for IMRT and VMAT QA.

Many commercial tools are available for plan-specific quality assurance (QA) of radiotherapy plans, with their functionality assessed in isolation. However, multiple QA tools are required to review the full range of potential errors. It is important to assess their effectiveness in combination with each other to look for ways to both streamline the QA process and to make certain that errors of high impact and/or high occurrence are caught before reaching patient treatment. To develop a structured method to assess the effective risk reduction of combinations of QA methods for IMRT/VMAT treatments. First, a structured prospective risk assessment was performed to establish the major failure modes (FMs) of IMRT/VMAT QA, and assign occurrence (O), severity (S), and baseline detectability (BD) rankings to them. The baseline assumed that chart checks and linear accelerator QA was performed, but no plan-specific secondary dose calculation or measurement was done. Second, the detectability of each FM for two secondary dose calculation methods and four plan measurement methods (point-based dose calculation, Monte-Carlo-based dose calculation, 2D fluence-based measurement, 2.5D phantom-based measurement, log file analysis with dose recalculation, and log file analysis combined with MLC QA) was determined. Third, we used a minimum detectability approach in addition to each FM's occurrence and severity to determine the optimal combination of QA methods.We analyzed the cumulative risk priority number of eight combinations of QA methods. The analysis was done on (1) all FMs, (2) FMs with high severity, (3) FMs with high-risk priority numbers (RPN) of O*S*BD, and (4) on FMs with both high severity and high RPN. Our analysis resulted in 54 FMs, including commissioning, planning, data transfer, and linear accelerator failures. 1D secondary dose calculation plus measurement provided a 19%-22% risk reduction from baseline. 1D/3D secondary dose calculation plus log files created a 25%-32% reduction. 3D secondary dose calculation plus measurement resulted in a 27%-34% reduction. 3D secondary dose calculation plus log files with additional machine QA provided the greatest reduction of 31%-42%. This novel structured approach to comparing combinations of QA methods will allow us to optimize our procedures, with the goal of detecting all clinically significant FMs. Our results show that log-file QA with 3D dose recalculation and supplemental machine QA provides better risk reduction than measurement-based QA. This work builds evidence to justify reducing or eliminating measurement-based PSQA with an independent 3D dose verification, log-file measurement, and appropriate supplementation of machine QA. The process also highlights FMs that cannot be caught by pre-treatment QA, prompting us to consider future directions for on-treatment QA.

Pro-inflammatory proteins associated with frailty and its progression - a longitudinal study in community dwelling women.

The complex pathophysiology underlying biological ageing creates challenges for identifying biomarkers associated with frailty. This longitudinal, non-targeted proteomics study aims to identify proteins associated with frailty, particularly the change from non-frail to frail. The population based OPRA cohort is women, all age 75y at inclusion (n=1044); reassessed at 80y (n=715) and 85y (n=382). A deficits in health frailty index (FI) and 92 plasma proteins (Olink CVD-II panel) were available at all ages. The identical age facilitates differentiating chronological and biological aging. Bi-directional analyses, performed cross-sectionally and longitudinally, used regression models controlled for false discovery rate (FDR), across 5-year and 10-year time-windows and longitudinal mixed models. Frailty outcomes were 'frailty index', 'frail status (frail FI>0.25)', 'change in frailty index' and 'change in frailty status'; together with 'protein-expression' or 'change in protein-expression'. Elevated levels of 32 proteins were positively associated with frailty index, cross-sectionally at all ages (range: β-coefficients 0.22-2.06; FDR 0.021-0.024), of which 18 were also associated with frail status' (range: Odds Ratios 1.40-5.77; FDR 0.022-0.016). Based on the accrued data, eight core proteins (CD4, FGF23, Gal-9, PAR-1, REN, TNFRSF10A TNFRSF11A and TNFRSF10B) are suggested. A one unit change in frailty index additively associated with increased protein expression over 5-years and 10-years (range: β-coefficients 0.52-1.59; p<0.001). Increments in baseline frailty index consistently associated with change in protein expression over time (5-years, β-range 0.05-1.35; 10-years, β-range 0.51-1.48; all p<0.001). A one unit increase in protein expression, was also associated with an increased probability of being frail (FI>0.25) (β-range: 0.14-0.61). Mirroring the multi-system deterioration that typifies frailty, the proteins and their associated biological pathways reflect pathologies including the renal system, skeletal homeostasis and TRAIL-activated apoptotic signaling was enriched. The core proteins, are convincing candidates in understanding the development and progression of frailty with advancing age, including the intrinsic musculoskeletal component. This article is protected by copyright. All rights reserved.