Modeling defensive resource allocation in multilayered systems under probabilistic and strategic risks.

Confronting the continuing risk of an attack, security systems have adopted target-hardening strategies through the allocation of security measures. Most previous work on defensive resource allocation considers the security system as a monolithic architecture. However, systems such as schools are typically characterized by multiple layers, where each layer is interconnected to help prevent single points of failure. In this paper, we study the defensive resource allocation problem in a multilayered system. We develop two new resource allocation models accounting for probabilistic and strategic risks, and provide analytical solutions and illustrative examples. We use real data for school shootings to illustrate the performance of the models, where the optimal investment strategies and sensitivity analysis are presented. We show that the defender would invest more in defending outer layers over inner layers in the face of probabilistic risks. While countering strategic risks, the defender would split resources in each layer to make the attacker feel indifferent between any individual layer. This paper provides new insights on resource allocation in layered systems to better enhance the overall security of the system.

Applying a modified streamlined disease risk analysis framework to a platypus conservation translocation, with special consideration for the conservation of ecto- and endoparasites.

Platypuses are the world's most evolutionarily distinct mammal and have several host-specific ecto- and endoparasites. With platypus populations declining, consideration should also be given to preserving these high conservation priority parasites alongside their charismatic host. A disease risk analysis (DRA) was performed for a platypus conservation translocation, using a modified streamlined methodology that incorporated a parasite conservation framework. DRA frameworks rarely consider parasite conservation. Rather, parasites are typically considered myopically in terms of the potential harm they may cause their host. To address this, a previously proposed parasite conservation framework was incorporated into an existing streamlined DRA methodology. Incorporation of the two frameworks was achieved readily, although there is opportunity for further refinement of this process. This DRA is significant as it is the first performed for any monotreme species, and implements the emerging approach of balancing the health and disease risk of the host with parasite conservation.

Risk Analysis Index Predicts Non-home Discharge following Resection of Cavernous Malformations.

OBJECTIVE: Intracranial cavernous malformations (CMs) are benign vascular lesions associated with hemorrhage, seizures, and corresponding neurological deficits. Recent evidence shows that frailty predicts neurosurgical adverse outcomes with superior discrimination compared to greater patient age. Therefore, we utilized the Risk Analysis Index (RAI) to predict adverse outcomes following cavernous malformations resection (CMR). METHODS: This retrospective study utilized the Nationwide Inpatient Sample (NIS) to identify patients who underwent craniotomy for CMR (2019-2020). Multivariate analysis used RAI to assess the ability of frailty to predict non-home discharge (NHD), extended length of stay (eLOS) and postoperative adverse outcomes. Receiver operating characteristic (ROC) curve analysis evaluated the discriminatory accuracy of RAI for prediction of NHD. RESULTS: 1200 CMR patients were identified. Mean patient age was 38 ± 1.2 years, 53.3% (N = 640) were female, and 58.3% (N = 700) had private insurance. Patients were stratified into four frailty tiers based on RAI scores, "robust" (0-20, R): N = 905 (80.8%), "normal" (21-30, N), N = 110 (9.8%), "frail" (31-40, F) N= 25 (2.2%), and "very frail" (41+, VF): 80 (7.1%). Increasing frailty was associated with eLOS and higher rates of NHD (p< 0.05). The RAI demonstrated strong discriminatory accuracy (C-statistic = 0.722) for prediction of NHD following CMR in AUROC. CONCLUSION: Preoperative frailty independently predicts adverse outcomes, including eLOS and NHD in patients undergoing resection of cranial CMs. Integrating RAI into preoperative frailty risk assessment may optimize risk stratification and improve patient selection and reallocate perioperative management resources for better patient outcomes.

Baseline Frailty Measured by the Risk Analysis Index and 30-Day Mortality After Surgery for Spinal Malignancy: Analysis of a Prospective Registry (2011-2020).

OBJECTIVE: To evaluate the prognostic utility of baseline frailty, measured by the Risk Analysis Index (RAI), for prediction of postoperative mortality among patients with spinal malignancy (SM) undergoing resection. METHODS: SM surgery cases were queried from the American College of Surgeons - National Surgical Quality Improvement Program database (2011-2020). The relationship between preoperative RAI frailty score and increasing rate of primary endpoint (mortality or discharge to hospice within 30 days, "mortality/hospice") were assessed. Discriminatory accuracy was assessed by computation of C-statistics (with 95% confidence interval [CI]) in receiver operating characteristic (ROC) curve analysis. RESULTS: A total of 2,235 cases were stratified by RAI score: 0-20, 22.7%; 21-30, 11.9%; 31-40, 54.7%; and ≥ 41, 10.7%. The rate of mortality/hospice was 6.5%, which increased linearly with increasing RAI score (p < 0.001). RAI was also associated with increasing rates of major complication, extended length of stay, and nonhome discharge (all p < 0.05). The RAI demonstrated acceptable discriminatory accuracy for prediction of primary endpoint (C-statistic, 0.717; 95% CI, 0.697-0.735). In pairwise ROC comparison, RAI demonstrated superiority versus modified frailty index-5 and chronological age (p < 0.001). CONCLUSION: Preoperative frailty, as measured by RAI, is a robust predictor of mortality/ hospice after SM surgery. The frailty score may be applied in clinical settings using a user-friendly calculator, deployed here: https://nsgyfrailtyoutcomeslab.shinyapps.io/spinalMalignancyRAI/.

Prognostic impact of new-onset atrial fibrillation in myocardial infarction with and without improved ejection fraction.

AIMS: Improvement in left ventricular ejection fraction (impEF) often presents in contemporary acute myocardial infarction (AMI) patients. New-onset atrial fibrillation (NOAF) during AMI is an important predictor of subsequential heart failure (HF), while its impact on the trajectory of post-MI left ventricular ejection fraction (LVEF) and prognostic implication in patients with and without impEF remains undetermined. We aimed to investigate the prognostic impacts of NOAF in AMI patients with and without impEF. METHODS AND RESULTS: Consecutive AMI patients without a prior history of AF between February 2014 and March 2018 with baseline LVEF ≤ 40% and had ≥1 LVEF measurement after baseline were included. ImpEF was defined as a baseline LVEF ≤ 40% and a re-evaluation showed both LVEF > 40% and an absolute increase of LVEF ≥ 10%. Persistently reduced EF (prEF) was defined as the second measurement of LVEF either ≤40% or an absolute increase of LVEF < 10%. The primary endpoint was a major adverse cardiac event (MACE) that was composed of cardiovascular death and HF hospitalization. Cox regression analysis and competing risk analysis were performed to assess the association of post-MI NOAF with MACE. Among 293 patients (mean age: 66.6 ± 11.3 years, 79.2% of males), 145 (49.5%) had impEF and 67 (22.9%) developed NOAF. Higher heart rate (odds ratio [OR]: 0.84, 95% confidence interval [CI]: 0.73-0.97; P = 0.015), prior MI (OR: 0.25, 95% CI: 0.09-0.69; P = 0.008), and STEMI (OR: 0.40, 95% CI: 0.21-0.77; P = 0.006) were independent predictors of post-MI impEF. Within up to 5 years of follow-up, there were 22 (15.2%) and 53 (35.8%) MACE in patients with impEF and prEF, respectively. NOAF was an independent predictor of MACE in patients with impEF (hazard ratio [HR]: 7.34, 95% CI: 2.49-21.59; P < 0.001) but not in those with prEF (HR: 0.78, 95% CI: 0.39-1.55; P = 0.483) after multivariable adjustment. Similar results were obtained when accounting for the competing risk of all-cause death (subdistribution HR and 95% CIs in impEF and prEF were 6.47 [2.32-18.09] and 0.79 [0.39-1.61], respectively). CONCLUSIONS: The NOAF was associated with an increased risk of cardiovascular outcomes in AMI patients with impEF.

Risk Analysis Index Frailty Score as a Predictor of Otolaryngology Surgical Outcomes.

OBJECTIVE: The Risk Analysis Index (RAI) score is a screening tool to assess patient frailty. It has been shown to be predictive of postoperative outcomes and mortality in orthopedic, urologic, and neurosurgical patient populations. We sought to evaluate the predictive ability of RAI score for surgical outcomes in an otolaryngology patient population. STUDY DESIGN: Retrospective study. SETTING: Academic tertiary medical center. METHODS: A retrospective study was conducted of adult patients undergoing otolaryngology surgery at a tertiary medical care center over 21 months. Patients were sent electronic RAI survey questionnaires via direct messaging, which was completed prior to surgery. Endpoint data were analyzed, including demographics, RAI score, and patient outcome data. Univariate analysis, ROC curves, and predictive modeling were utilized. RESULTS: A total of 517 patients responded to the RAI questionnaire, resulting in a 59.6% response rate. Mean RAI score was 21.38 ± 11.83. Higher RAI scores were associated with increased 30-day readmissions (P < .0015), postoperative complications (P < .001), hospital length of stay (P < .001), and discharge with home health (P < .001). Predictive models for RAI score and postoperative outcomes were created, and a cutoff score of RAI = 30 was established to identify frail patients. CONCLUSION: We evaluated if RAI scoring predicted postoperative complications in an otolaryngology patient population. Increased RAI score is significantly associated with poorer surgical outcomes, including increased hospital length of stay, 30-day readmissions, and postoperative complications. We propose a predictive model with suggested RAI cutoff scoring for use in the otolaryngology surgical population.

Perspective on the influence of suspension manufacturing unit operations on bioburden viability and selection of sampling points at the pilot scale.

The suspension wet media milling manufacturing process is a complex multi-unit operation, resulting in drug substance comminution to a target particle size. As a result of this complexity, microbial contamination is of paramount concern, particularly for suspensions dosed for parenteral use. This perspective sought to review the influence of (4) critical manufacturing unit operations using a quality risk management approach to better identify and articulate impact of each unit operation on bioburden viability. The manufacturing unit operations in scope included slurry compounding, deaeration, milling, and filling. Bow tie risk analysis was used as a visual gap analysis tool to evaluate if conventional controls were appropriate to detect and mitigate potential for microbial contamination. A deep dive into these unit operations clarified that mechanisms such as turbohypobiosis, cavitation during deaeration, high energy milling, and inert overlay may have an appreciable influence on bioburden viability and proliferation. The resultant analysis also explicated that endotoxin oversight must be closely monitored through barriers (input material controls, water quality controls) to minimize impact to the product and patient. The identified manufacturing unit operations were not appropriate as mitigating controls for endotoxin. The output of this article relates risk intersections for microbial contamination during wet media milling and offers insights in critical areas for intervention.

Travel bubble policies for low-risk air transport recovery during pandemics.

Global pandemics restrict long-haul mobility and international trade. To restore air traffic, a policy named "travel bubble" was implemented during the recent COVID-19 pandemic, which seeks to re-establish air connections among specific countries by permitting unrestricted passenger travel without mandatory quarantine upon arrival. However, travel bubbles are prone to bursting for safety reasons, and how to develop an effective restoration plan through travel bubbles is under-explored. Thus, it is vital to learn from COVID-19 and develop a formal framework for implementing travel bubble therapy for future public health emergencies. This article conducts an analytical investigation of the air travel bubble problem from a network design standpoint. First, a link-based network design problem is established with the goal of minimizing the total infection risk during air travel. Then, based on the relationship between origin-destination pairs and international candidate links, the model is reformulated into a path-based one. A Lagrangian relaxation-based solution framework is proposed to determine the optimal restored international air routes and assign the traffic flow. Finally, computational experiments on both hypothetical data and real-world cases are conducted to examine the algorithm's performance. The results demonstrate the effectiveness and efficiency of the proposed model and algorithm. In addition, compared to a benchmark strategy, it is found that the infection risk under the proposed travel bubble strategy can be reduced by up to 45.2%. More importantly, this work provides practical insights into developing pandemic-induced air transport recovery schemes for both policymakers and aviation operations regulators.

Predictive Role of NLR, dNLR, PLR, NLPR, and Other Laboratory Markers in Diagnosing SIRS in Premature Newborns.

BACKGROUND: Premature newborns are at a significant risk for Systemic Inflammatory Response Syndrome SIRS, a condition associated with high morbidity and mortality. This study aimed to evaluate the predictive and diagnostic capability of laboratory markers like Neutrophil to Lymphocyte Ratio (NLR), derived Neutrophil to Lymphocyte Ratio (dNLR), Platelet-to-Lymphocyte Ratio (PLR), and Neutrophil-to-Lymphocyte-to-Platelet Ratio (NLPR) in diagnosing SIRS in premature newborns. METHODS: Premature newborns with and without SIRS were evaluated in a prospective design during a one-year period. Among 136 newborns, early and 72 h post-birth analyses were performed. RESULTS: At 24 h, NLR's cutoff value was 8.69, yielding sensitivity and specificity rates of 52.77% and 83.47% (p = 0.0429), respectively. The dNLR showed a cutoff of 5.61, with corresponding rates of 63.27% and 84.15% (p = 0.0011), PLR had a cutoff of 408.75, with rates of 51.89% and 80.22% (p = 0.1026), and NLPR displayed a cutoff of 0.24, with rates of 75.85% and 86.70% (p = 0.0002). At 72 h, notable sensitivity and specificity improvements were observed, particularly with NLPR having a cutoff of 0.17, showing sensitivity of 77.74% and specificity of 95.18% (p < 0.0001). NLR above the cutoff indicated a 33% increase in SIRS risk, with a hazard ratio (HR)of 1.33. The dNLR was associated with a twofold increase in risk (HR 2.04). NLPR demonstrated a significant, over threefold increase in SIRS risk (HR 3.56), underscoring its strong predictive and diagnostic value for SIRS development. CONCLUSION: Integrating these findings into clinical practice could enhance neonatal care by facilitating the early identification and management of SIRS, potentially improving outcomes for this vulnerable population.

Clinical effects of re-evaluating a lung SBRT failure mode and effects analysis in a radiotherapy department.

PURPOSE: The increasing complexity of radiation treatments can hinder its clinical success. This study aimed to better understand evolving risks by re-evaluating a Failure Mode and Effects Analysis (FMEA) in lung SBRT. METHODS: An experienced multidisciplinary team conducted an FMEA and made a reassessment 3 years later. A process map was developed with potential failure modes (FMs) identified. High-risk FMs and their possible causes and corrective actions were determined. The initial FMEA analysis was compared to gain a deeper perspective. RESULTS: We identified 232 FMs. The high-risk processes were plan approval, target contouring, and patient evaluation. The corrective measures were based on stricter standardization of plan approval, pre-planning peer review, and a supporting pretreatment checklist, which substantially reduced the risk priority number in the revised FMEA. In the FMEA reassessment, we observed that the increased complexity and number of patients receiving lung SBRT conditioned a more substantial presence of human factors and communication errors as causal conditions and a potential wrong dose as a final effect. CONCLUSIONS: Conducting a lung SBRT FMEA analysis has identified high-risk conditions that have been effectively mitigated in an FMEA reanalysis. Plan approval has shown to be a weak link in the process. The increasing complexity of treatments and patient numbers have shifted causal factors toward human failure and communication errors. The potential of a wrong dose as a final effect augments in this scenario. We propose that digital and artificial intelligence options are needed to mitigate potential errors in high-complexity and high-risk RT scenarios.

A novel STPA approach to software safety and security in autonomous maritime systems.

With higher autonomy in maritime systems, tasks and responsibilities are moved from the human operator to software, increasing the complexity and the importance of safe and reliable functionality. Software failures, however, may be introduced from the early life cycle phases intentionally or unintentionally, and these must therefore be mitigated by safe and secure design approaches. A challenge is that existing methods are not particularly well-suited for analyzing software risks. Thus, the objective of this paper is to propose a systematic and efficient software failure identification approach by extending the Systems-Theoretic Process Analysis (STPA) with a software failure taxonomy and the System Modeling Language (SysML). This enables the control structure in STPA to cover both the dynamic and static aspects of the software functions. Combined with an implementation platform independent questionnaire, this gives a more systematic and guided search for potential software failures than existing approaches. To demonstrate the proposed approach, a case study on a ferry's navigation system that operates in manual control or semi-autonomous mode is performed. In the case study, the focus is on creating an avoidance map data structure, including both moving and static obstacles to be avoided by the ferry, and the subsequent process of collision risk warning calculation. Software failures are identified and evaluated in collision scenarios where the ferry operates under foggy conditions. The paper shows that the proposed systematic approach provides an improved process for identifying and analyzing critical software failures. This facilitates enhanced risk mitigation in the design and testing phases contributing to autonomous systems' safety and security.

Risk analysis index predicts mortality and non-home discharge following posterior lumbar interbody fusion: a nationwide inpatient sample analysis of 429,380 patients (2019-2020).

PURPOSE: Frailty is an independent risk factor for adverse postoperative outcomes following spine surgery. The ability of the Risk Analysis Index (RAI) to predict adverse outcomes following posterior lumbar interbody fusion (PLIF) has not been studied extensively and may improve preoperative risk stratification. METHODS: Patients undergoing PLIF were queried from Nationwide Inpatient Sample (NIS) (2019-2020). The relationship between RAI-measured preoperative frailty and primary outcomes (mortality, non-home discharge (NHD)) and secondary outcomes (extended length of stay (eLOS), complication rates) was assessed via multivariate analyses. The discriminatory accuracy of the RAI for primary outcomes was measured in area under the receiver operating characteristic (AUROC) curve analysis. RESULTS: A total of 429,380 PLIF patients (mean age = 61y) were identified, with frailty cohorts stratified by standard RAI convention: 0-20 "robust" (R)(38.3%), 21-30 "normal" (N)(54.3%), 31-40 "frail" (F)(6.1%) and 41+ "very frail" (VF)(1.3%). The incidence of primary and secondary outcomes increased as frailty thresholds increased: mortality (R 0.1%, N 0.1%, F 0.4%, VF 1.3%; p < 0.001), NHD (R 6.5%, N 18.1%, F 36.9%, VF 42.0%; p < 0.001), eLOS (R 18.0%, N 21.9%, F 31.6%, VF 43.8%; p < 0.001) and complication rates (R 6.6%, N 8.8%, F 11.1%, VF 12.2%; p < 0.001). The RAI demonstrated acceptable discrimination for NHD (C-statistic: 0.706) and mortality (C-statistic: 0.676) in AUROC curve analysis. CONCLUSION: Increasing RAI-measured frailty is significantly associated with increased NHD, eLOS, complication rates, and mortality following PLIF. The RAI demonstrates acceptable discrimination for predicting NHD and mortality, and may be used to improve frailty-based risk assessment for spine surgeons.

Cumulative veterinary drug and pesticide dietary exposure assessments: a global overview and Brazilian framework considerations.

Pesticides and veterinary drugs are widely employed to support food production. Assessing potential risks associated with the dietary consumption of pesticide and veterinary drug residues is, however, essential. Potential risks depend on the toxicity degree of the analyzed residue and population exposure levels. Human populations are exposed to numerous chemical substances through different pathways with varying exposure times, leading to increased health risks when compared to exposure to individual chemicals. Cumulative exposure assessments usually assess combined exposures to multiple chemicals through multiple exposure pathways. In this sense, this comprehensive review aims to provide insights into cumulative dietary pesticide and veterinary drug residue exposures. The main methodologies, strategies, and legislation employed by international agencies to this end are discussed. A review concerning articles that apply existing methodologies and approaches, as well as the challenges in this context faced by Brazil is also presented. As this is a critical issue not only for Brazilian public health but also for the global community, regulatory agencies should prioritize formulating regulations that incorporate exposure assessments regarding the simultaneous presence of residues and contaminants in foodstuffs.

Origin of the H1N1 (Russian influenza) pandemic of 1977-A risk assessment using the modified Grunow-Finke tool (mGFT).

In 1977, the Soviet Union (Union of Soviet Socialist Republics [USSR]) notified the World Health Organization (WHO) about an outbreak of H1N1 influenza, which later spread to many countries. The H1N1 strain of 1977 reappeared after being absent from the world for over 20 years. This pandemic simultaneously spread to several cities in the USSR and China. Many theories have been postulated to account for the emergence of this pandemic, including natural and unnatural origins. The purpose of this study was to use the modified Grunow-Finke risk assessment tool (modified Grunow-Finke tool [mGFT]) to investigate the origin of the 1977 H1N1 pandemic. Data was collected from WHO archives and published documents. The assessment of the pandemic's origin involved the utilization of a modified version of the original Grunow-Finke risk assessment tool (GFT). Using the mGFT, the final score was 37 out of 60 points (probability: 62%), indicating a high likelihood that the Russian influenza pandemic of 1977 was of unnatural origin. Several variables supported this finding, including the sudden re-emergence of a previously extinct strain, a genetic signature of laboratory modification for vaccine development, and unusual epidemiology. Inter-rater reliability was moderate to high. By applying the mGFT to the 1977 Russian influenza pandemic, we established a high probability that this pandemic was of unnatural origin. Although this is not definitive, it is consistent with the possibility that it originated from an incompletely attenuated live influenza vaccine. The mGFT is a useful risk analysis tool to evaluate the origin of epidemics.

A Stratified Analysis of Supersaturation and Precipitation Effects Based on the Refined Developability Classification System (rDCS).

Supersaturation and precipitation within the gastrointestinal tract can influence oral absorption of active pharmaceutical ingredients (APIs). Supersaturation of weakly basic APIs upon transfer from the stomach into the small intestine may enhance their absorption, while salt forms of poorly soluble weak acids may generate supersaturated solutions in both stomach and intestine. Likewise, APIs with solubility-limited absorption may be developed as enabling formulations intended to produce supersaturated solutions of the API in the gut. Integrating the supersaturation/precipitation characteristics of the API into the biopharmaceutical risk classification enables comprehensive mapping of potential developability risks and guides formulation selection towards optimizing oral bioavailability (BA). The refined Developability Classification System (rDCS) provides an approach for this purpose. In this work, the rDCS strategy is revisited and a stratified approach integrating the in vitro supersaturation and precipitation behavior of APIs and their formulations is proposed.

The Roles of NOTCH3 p.R544C and Thrombophilia Genes in Vietnamese Patients With Ischemic Stroke: Study Involving a Hierarchical Cluster Analysis.

BACKGROUND: The etiology of ischemic stroke is multifactorial. Several gene mutations have been identified as leading causes of cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), a hereditary disease that causes stroke and other neurological symptoms. OBJECTIVE: We aimed to identify the variants of NOTCH3 and thrombophilia genes, and their complex interactions with other factors. METHODS: We conducted a hierarchical cluster analysis (HCA) on the data of 100 patients diagnosed with ischemic stroke. The variants of NOTCH3 and thrombophilia genes were identified by polymerase chain reaction with confronting 2-pair primers and real-time polymerase chain reaction. The overall preclinical characteristics, cumulative cutpoint values, and factors associated with these somatic mutations were analyzed in unidimensional and multidimensional scaling models. RESULTS: We identified the following optimal cutpoints: creatinine, 83.67 (SD 9.19) µmol/L; age, 54 (SD 5) years; prothrombin (PT) time, 13.25 (SD 0.17) seconds; and international normalized ratio (INR), 1.02 (SD 0.03). Using the Nagelkerke method, cutpoint 50% values of the Glasgow Coma Scale score; modified Rankin scale score; and National Institutes of Health Stroke Scale scores at admission, after 24 hours, and at discharge were 12.77, 2.86 (SD 1.21), 9.83 (SD 2.85), 7.29 (SD 2.04), and 6.85 (SD 2.90), respectively. CONCLUSIONS: The variants of MTHFR (C677T and A1298C) and NOTCH3 p.R544C may influence the stroke severity under specific conditions of PT, creatinine, INR, and BMI, with risk ratios of 4.8 (95% CI 1.53-15.04) and 3.13 (95% CI 1.60-6.11), respectively (Pfisher<.05). It is interesting that although there are many genes linked to increased atrial fibrillation risk, not all of them are associated with ischemic stroke risk. With the detection of stroke risk loci, more information can be gained on their impacts and interconnections, especially in young patients.

Wasm-iCARE: a portable and privacy-preserving web module to build, validate, and apply absolute risk models.

Objectives: Absolute risk models estimate an individual's future disease risk over a specified time interval. Applications utilizing server-side risk tooling, the R-based iCARE (R-iCARE), to build, validate, and apply absolute risk models, face limitations in portability and privacy due to their need for circulating user data in remote servers for operation. We overcome this by porting iCARE to the web platform. Materials and Methods: We refactored R-iCARE into a Python package (Py-iCARE) and then compiled it to WebAssembly (Wasm-iCARE)-a portable web module, which operates within the privacy of the user's device. Results: We showcase the portability and privacy of Wasm-iCARE through 2 applications: for researchers to statistically validate risk models and to deliver them to end-users. Both applications run entirely on the client side, requiring no downloads or installations, and keep user data on-device during risk calculation. Conclusions: Wasm-iCARE fosters accessible and privacy-preserving risk tools, accelerating their validation and delivery.

The low-carbon risk society: Dilemmas of risk-risk tradeoffs in energy innovations, transitions, and climate policy.

As countries and communities grapple with climate change, they seek to rapidly decarbonize their economies and cultures. A low-carbon future will likely depend on more distributed solar energy, the electrification of mobility, and more efficient homes and buildings. But what emergent risks are evident within this low-carbon society? This exploratory study first reviews the existing literature to identify 75 risk-risk tradeoffs by their category, medium of distribution, and type. It builds on these 75 examples to apply a typology of Risk Offsets, Risk Substitution, Risk Transfer, and Risk Transformation. Based on extensive document analysis, it applies that typology to three low-carbon innovations: solar energy, battery electric vehicles, and building energy efficiency retrofits, identifying 36 distinct risk-risk tradeoffs in total. As such, the paper moves to discuss complexities and challenges in risk management. In doing so, it calls for a more refined risk assessment that better accounts for decision-making considerations such as the magnitude or probability of risk, size of population exposed, certainty in risk estimation, severity of adverse outcome, distributional considerations, and the timing of risk impacts. It also summarizes emergent research gaps. Risk management in the context of climate action becomes a three-dimensional chess game of weighing risk transmission, risk mediums, and risk categories.

Re-evaluation of the prospective risk analysis for artificial-intelligence driven cone beam computed tomography-based online adaptive radiotherapy after one year of clinical experience.

Cone-beam computed tomography (CBCT)-based online adaptation is increasingly being introduced into many clinics. Upon implementation of a new treatment technique, a prospective risk analysis is required and enhances workflow safety. We conducted a risk analysis using Failure Mode and Effects Analysis (FMEA) upon the introduction of an online adaptive treatment programme (Wegener et al., Z Med Phys. 2022). A prospective risk analysis, lacking in-depth clinical experience with a treatment modality or treatment machine, relies on imagination and estimates of the occurrence of different failure modes. Therefore, we systematically documented all irregularities during the first year of online adaptation, namely all cases in which quality assurance detected undesired states potentially leading to negative consequences. Additionally, the quality of automatic contouring was evaluated. Based on those quantitative data, the risk analysis was updated by an interprofessional team. Furthermore, a hypothetical radiation therapist-only workflow during adaptive sessions was included in the prospective analysis, as opposed to the involvement of an interprofessional team performing each adaptive treatment. A total of 126 irregularities were recorded during the first year. During that time period, many of the previously anticipated failure modes (almost) occurred, indicating that the initial prospective risk analysis captured relevant failure modes. However, some scenarios were not anticipated, emphasizing the limits of a prospective risk analysis. This underscores the need for regular updates to the risk analysis. The most critical failure modes are presented together with possible mitigation strategies. It was further noted that almost half of the reported irregularities applied to the non-adaptive treatments on this treatment machine, primarily due to a manual plan import step implemented in the institution's workflow.

Postoperative Medial Malleolar Fractures in Total Ankle Replacement Are Associated With Decreased Medial Malleolar Width and Varus Malalignment: A Case-Control Study.

BACKGROUND: There are limited data regarding risk factors associated with periprosthetic medial malleolar fractures in total ankle arthroplasty (TAA). This case-control study aimed to identify the risk factors and analyze the effect of prophylactic screw fixation in preventing a medial malleolar fracture after TAA. METHODS: A case-control study was conducted on 149 patients who underwent primary TAA. Twenty patients with postoperative medial malleolar fractures >4 weeks postoperatively (cases) were identified. An additional 129 patients (controls) were randomly selected from the TAA database. Radiographic evaluation included tibial component coronal alignment and postoperative medial malleolar width. Demographics and radiographic variables were compared between cohorts. Logistic regression was used to investigate the association between medial malleolar fracture and postoperative coronal alignment, medial malleolar width, and prophylactic fixation of the medial malleolus. RESULTS: Mean (SD) medial malleolar width was significantly smaller in the fracture cohort (8.52 mm [1.6]) than in the control group (11.78 mm [1.74]) (P < .001). Mean (SD) tibial component coronal alignment was 92.17 degrees (2.77) in the fracture cohort and 90.21 degrees (1.66) in the control group (P = .002). Regression analysis identified a significant negative association between postoperative medial malleolar width and the probability of fracture (OR = 0.06, 95% CI 0.01, 0.26, P < .001). Varus malalignment of the tibial component was positively associated with the probability of fracture (OR = 1.90, 95% CI 1.27, 2.86, P = .002). Prophylactic screw fixation resulted in more than 90% reduction in the odds of a fracture (OR = 0.04, 95% CI 0.01, 0.45, P = .01). ROC curve analysis determined a medial malleolar width of 10.3 mm as a potential threshold for predicting fracture. CONCLUSION: Decreased medial malleolar width and postoperative varus malalignment were associated with an increased risk of postoperative medial malleolar fracture. Therefore, surgeons should consider prophylactic screw fixation in patients with a medial malleolar width <10.3 mm or at risk of postoperative varus deformity.