Results Of Measures Research Articles

Cost optimization and ANFIS computing for M/M/(R+c)/N queue under admission control policy and server breakdown

This study focuses on a finite queueing model with multiple servers, incorporating an admission control F-policy and considerations for customers’ balking and server breakdown. The F-policy concept is used to control the flow of incoming customers, making the model formulation more realistic. Implementing the admission control F-policy, along with adding additional servers, can effectively alleviate congestion issues for customers by reducing the formation of queues and decreasing the frequency of customers opting out of the queue due to extended waiting time. In order to conduct a mathematical analysis of the model and establish probability distributions, we formulate the steady-state Chapman–Kolmogorov (C–K) equations and solve them using a recursive technique. The probability distributions allow us to develop several system performance measures, including the expected system size, the expected number of busy permanent servers, the probability of server breakdown, etc. These measures are utilized to assess the effectiveness of the model. The impact of system input parameters on several performance measures in the multi-server queueing model is presented using a numerical example. The accuracy of the results of performance measures is validated by implementing the adaptive neuro-fuzzy inference system (ANFIS) approach, enhancing the reliability and robustness of the findings. The non-linear cost function is also created to compute the optimal values of the decision variables, including the number of permanent servers, admission control threshold, service rate, and joining probabilities of customers. Grey wolf optimization (GWO) and particle swarm optimization (PSO) algorithms are applied to deal with the cost optimization problem. A comparative study of the GWO and PSO algorithms for cost optimization is also conducted. This optimization enables decision-makers to efficiently manage the system’s operations and resources. The findings of the study suggest that the proposed model can be applied in diverse real-life scenarios, such as electric vehicle charging stations (EVCSs), restaurants, and various other locations.

The Italian version of the Majeed pelvic score: translation, cross-cultural adaptation and validation.

The assessment of functional outcomes after pelvic ring fracture remains a controversial topic. The Majeed pelvic score (MPS) is the most commonly used pelvic-specific questionnaire in the literature. The aim of this study is translation, cross-cultural adaptation and validation of the Italian version of MPS. The study was articulated in two phases. Phase 1 consisted in translation and cross-cultural adaptation of MPS, from English into Italian. The psychometric properties were tested on 52 Italian patients (Phase 2). Construct validity was assessed by correlation with Short-Form 12 (SF-12). 33 patients repeated the questionnaire after 14days to assess its reproducibility. All data were subsequently analyzed (descriptive statistics, multitrait analysis, reliability and construct validity assessment). The questionnaire was clear and easily understood (no missing data). A ceiling effect was detected for all items of the scale. Multitrait analysis showed good results for each outcome measure, except for the item "walking distance" that showed poor item discriminant validity. A significant correlation between the MPS and the physical component summary (PCS) of the SF-12 was found, while there was a weak correlation with the mental component summary (MCS). The questionnaire showed high internal consistency (Cronbach's alpha: 0.91-0.99) and very good test-retest reliability (intraclass correlation coefficients: 0.92-0.96). The Italian version of the MPS has demonstrated to be reliable and valid in the evaluation of patients with pelvic ring fractures. There is still however a need for an instrument capable of evaluating the mental component in these types of injuries.

Effect of office-based vergence and anti-suppression therapy on binocular vision and accommodation in small-to-moderate angle intermittent exotropia: A randomised clinical trial.

To evaluate the short-term (1 week after completion of treatment) effect of office-based vergence and anti-suppression therapy (OBVAT) on binocular vision and accommodative function when compared to observation alone in children with small-to-moderate angle intermittent exotropia (IXT). In this single-masked (examiner masked), two-arm, single-centre randomised clinical trial, 40 participants, 6 to <18 years of age with untreated IXT were randomly assigned to OBVAT or observation alone. Participants assigned to therapy received 16 weeks of OBVAT (60 min per visit, once per week) with home reinforcement (15 min per day, 5 days a week). Therapy included vergence, accommodation and anti-suppression techniques. This paper reports the results of clinical measures of binocular vision and accommodation, including fusional vergence, near point of convergence, vergence facility, amplitude of accommodation, the Worth 4-dot test and the Fusion Maintenance Score (FMS). Treatment group differences at the primary outcome visit significantly favoured the OBVAT group (n = 20) over the observation group (n = 16) in negative fusional vergence break point at both distance (p ≤ 0.001; r = 0.58) and near (adjusted mean difference: 12.3 Δ; 95% CI: 5.3-19.3 Δ; p = 0.001; partial eta squared: 0.28), positive fusional vergence break point at both distance (p = 0.009; r = 0.43) and near (adjusted mean difference: 20.6 Δ; 95% CI: 11.8-29.4 Δ; p ≤ 0.001; partial eta squared: 0.41), vergence facility (adjusted mean difference: 5.6 cpm; 95% CI: 1.9-9.4 cpm; p = 0.005; partial eta squared: 0.22) and the FMS (p = 0.007; r = 0.44). In this randomised clinical trial of participants aged 6 to <18 years with IXT, those in the OBVAT group had a significantly better fusional vergence range, vergence facility, near Worth 4-dot test result and FMS than the observation group at the 17-week visit. The improvement in these areas further support the effectiveness of OBVAT for improving IXT.

Data based individualization in early writing: the importance and measurement of implementation fidelity

In this paper we describe the process of monitoring fidelity of implementation for a teacher-implemented early writing intervention. As part of a large, federally funded project, teachers who worked with students in grades 1 through 3 in schools across two states in the US were recruited and then randomly assigned to implementation and control conditions. Using Data-Based Individualization (DBI) as a framework for best practice in assessment and intervention, teachers in the implementation group received professional development on early writing intervention and assessment and then implemented these practices with their students who had significant writing challenges. Coaches, who were part of the research project, supported teachers and also observed teachers in both the implementation and control conditions at least twice during the course of the 20-week study. This paper focuses on the results of the fidelity measures that were administered throughout the project. An overview of the importance of fidelity checks is followed by a description of the fidelity tools used, as well as data from those tools. Areas of strength and challenge for teachers when implementing early writing assessment and intervention and engaging in data-based decision making with fidelity are discussed, along with recommendations regarding the practical and research importance of fidelity checks.

Применение экосистемного подхода к ликвидации и возмещению накопленного вреда окружающей среде

The process of formation and recognition of responsibility for accumulated environmental damage is considered. The possibilities of applying the ecosystem approach to the legal regulation of organizing the elimination of accumulated environmental harm are explored, including assessing the results of the restoration measures taken and the formation of criteria for recognizing objects of accumulated harm as liquidated. A justification is given for the need to apply an ecosystem approach to eliminating accumulated environmental damage in order to achieve the goal of rational environmental management (restoring and increasing the sustainability of natural ecological systems and ensuring their equilibrium state).

Vállalati energiahatékonyság a gyakorlatban. Egy magyarországi kismintás elemzés tanulságai

Achieving the EU’s climate neutrality target requires each Member State to reduce its energy consumption. Member States, including Hungary, are paying particular attention to encouraging businesses to modernise their energy consumption. Our research focuses on the results of energy efficiency measures implemented by large companies with more than 1,000 employees, based on the company energy efficiency reports available online between 2017 and 2021. Our research also incorporates results from four interviews conducted with companies and two interviews conducted with energy efficiency experts. The sample of 24 companies obtained through data reduction is not representative, but the analysis shows that the most commonly implemented measures in the 5 years analysed were raising employee awareness and lighting upgrades. The four company and two expert interviews confirmed that companies prefer energy efficiency investments that pay off in the short to medium term. By ownership structure, there were differences in the type of measures implemented. The main driver for energy efficiency measures is cost reduction, complemented by sustainability considerations such as reducing carbon emissions.

Impact of Sliding Window Variation and Neuronal Time Constants on Acoustic Anomaly Detection Using Recurrent Spiking Neural Networks in Automotive Environment

Acoustic perception of the automotive environment has the potential to advance driving potentials with enhanced safety. The challenge arises when these acoustic perception systems need to perform under resource and power constraints on edge devices. Neuromorphic computing has introduced spiking neural networks in the context of ultra-low power sensory edge devices. Spiking architectures leverage biological plausibility to achieve computational capabilities, accurate performance, and great compatibility with neuromorphic hardware. In this work, we explore the depths of spiking neurons and feature components with the acoustic scene analysis task for siren sounds. This research work aims to address the qualitative analysis of sliding windows’ variation on the feature extraction front of the preprocessing pipeline. Optimization of the parameters to exploit the feature extraction stage facilitates the advancement of the performance of the acoustics anomaly detection task. We exploit the parameters for mel spectrogram features and FFT calculations, prone to be suitable for computations in hardware. We conduct experiments with different window sizes and the overlapping ratio within the windows. We present our results for performance measures like accuracy and onset latency to provide an insight on the choice of optimal window. The non-trivial motivation of this research is to understand the effect of encoding behavior of spiking neurons with different windows. We further investigate the heterogeneous nature of membrane and synaptic time constants and their impact on the accuracy of anomaly detection. On a large scale audio dataset comprising of siren sounds and road traffic noises, we obtain accurate predictions of siren sounds using a recurrent spiking neural network. The baseline dataset comprising siren and noise sequences is enriched with a bird dataset to evaluate the model with unseen samples.

Treatment adherence and wellness, nutrition, and physicalactivity outcomes of diabetic patients with comorbiddepression during the 18-month follow-up of the TELE-DD study.

A good adherence to pharmacological treatment in chronic pathologies such as type 2 diabetes and clinical depression is essential to improve illness prognosis. The main goal of the TELE-DD study was to analyze the effectiveness of a telephone, psychoeducational, and individualized intervention carried out by nurses in patients with type 2 diabetes mellitus and comorbid clinical depression with prior nonadherence to pharmacological treatment. In this paper, we describe and analyze secondary outcomes of the trial intervention. A prospective cohort study was used to assess the effectiveness of a telephonic intervention (IG) in n = 191 participants with a similar control group (CG). Adherence to pharmacological treatment was assessed using the patient's self-perceived adherence questionnaire. In addition to clinical (HbAc1, HDL, LDL), physical (body mass index, blood pressure) and psychological measures (Patient Health Questionnaire-9 affective state), and psychosocial distress due to Diabetes Distress Scale Questionnaire at 3, 6, 12, and 18 months of follow-up were also analyzed. The proportion of "Total Adherents" in the IG was higher throughout the study. This was particularly true at month 18 of the intervention. Self-perceived adherence rates increased by 27.1% in the IG and by 1.1% in the CG. Results of clinical and physical measures were higher in the IG than in the CG at month 18 of the intervention. The interview based on positive reinforcement as well as individualized attention and flexibility in making telephone calls and dissemination of the intervention in the media closest to the patients were key to achieving good participation and collaboration as well as continuity in adherence to treatment and self-care.

Efficacy of combined exercise training during different menstrual phases in young students with primary dysmenorrhoea

AbstractObjectivesThe objective of the study was to compare the effectiveness of combined exercise training during different menstrual phases on pain, quality of life and menstrual symptoms.MethodsA total of 72 participants for the study were randomly assigned into three groups: Group 1 (N = 24), Group 2 (N = 24) and Group 3 (N = 24) which had undergone combined exercise training during the follicular, luteal and bleeding phases of their menstrual cycle, respectively. The treatment programme included combined exercise training involving deep breathing exercises, Kegel exercises, core strengthening exercises and stretching exercises. Exercises were repeated 5 times with hold duration of 15 s with total of 30–40 min session with 5–10 min of warm‐up and cooldown sessions. Demographic data and outcome measures (Visual Analogue Scale [VAS], Menstrual Symptom Questionnaire [MSQ], and Working ability, Location, Intensity, Days, Duration [WaLIDD]) were assessed at baseline and assessed again during the first menstrual cycle after the completion of the treatment programme. One‐way ANOVA was used for between‐group comparisons of the normally distributed data.ResultsWithin‐group comparison of the outcome variables except VAS in group 3 showed a statistically significant difference in all groups. Comparison of post‐intervention results of the outcome measures of all the groups revealed a statistically significant difference for the VAS, while there was no statistically significant difference for in between the comparison of the WaLIDD and MSQ scoring.ConclusionCombined exercise training is effective in reducing pain only when performed during follicular and luteal phases and significantly improve quality of life and menstrual symptoms in all phases of the menstrual cycle.

The influence of socioeconomic status on individual attitudes and experience with clinical trials

BackgroundCharacterizing perceptions of clinical trials among the socioeconomically disadvantaged is necessary for understanding how social determinants of health such as socioeconomic disparities in education and income can affect people’s awareness of and exposure to clinical trialsMethodsA survey was distributed in spring 2023 among a survey taking sample stratified by demographic variables to reflect the U.S. population. The survey assessed the socioeconomic status of the respondent and related covariates, as well as outcome measures including interest in joining a clinical trial, concerns relating to participation, and whether the respondent had previously been asked to participate. Multiple and logistic regression were used to assess the relationship between predictor and outcome variablesResultsHere we show the results of outcome measures regressed on main predictors related to socioeconomic status and related demographic predictors. Education, employment status, insurance coverage, and English proficiency were significant predictors of interest in clinical trial participation. Education and the presence of a healthcare professional or former clinical trial participant in the respondent’s personal network were significant predictors of whether the respondent had previously been asked to participate in a clinical trialConclusionsThe results of the analysis reveal how socioeconomically vulnerable groups, including those from low income and low education groups, are being excluded in clinical research. Analyses also uncovered the impact of clinical trial social influence—the presence of having a family or friend in one’s social network who participated in a clinical trial—on willingness to participate and exposure to clinical trials.

Limitations of Separating Athletes into High or Low-Risk Groups based on a Cut-Off. A Clinical Commentary.

Athlete injury risk assessment and management is an important, yet challenging task for sport and exercise medicine professionals. A common approach to injury risk screening is to stratify athletes into risk groups based on their performance on a test relative to a cut-off threshold. However, one potential reason for ineffective injury prevention efforts is the over-reliance on identifying these 'at-risk' groups using arbitrary cut-offs for these tests and measures. The purpose of this commentary is to discuss the conceptual and technical issues related to the use of a cut-off in both research and clinical practice. How can we better assess and interpret clinical tests or measures to enable a more effective injury risk assessment in athletes? Cut-offs typically lack strong biologic plausibility to support them; and are typically derived in a data-driven manner and thus not generalizable to other samples. When a cut-off is used in analyses, information is lost, leading to potentially misleading results and less accurate injury risk prediction. Dichotomizing a continuous variable using a cut-off should be avoided. Using continuous variables on its original scale is advantageous because information is not discarded, outcome prediction accuracy is not lost, and personalized medicine can be facilitated. Researchers and clinicians are encouraged to analyze and interpret the results of tests and measures using continuous variables and avoid relying on singular cut-offs to guide decisions. Injury risk can be predicted more accurately when using continuous variables in their natural form. A more accurate risk prediction will facilitate personalized approaches to injury risk mitigation and may lead to a decline in injury rates. 5.

Some results of anti-leukemia measures in farms of the Dagestan Republic

Some results of anti-leukemia measures in farms of the Dagestan Republic

The effect of rehabilitation measures on the severity of endotoxicosis and its relationship with changes in hemorheology in acute poisoning

Introduction. The use of multidimensional statistical analysis methods (factorial and cluster methods) to study the pathogenesis and sanogenesis of acute poisoning (AP) with psychopharmacological agents (pPPhA), neurotoxicants (pNT) and corrosive substances (pCS) did not allow us to judge the presence of a direct connection between the hemorhealogy system (HR). We received a positive answer to this question earlier with the help of pair correlation analysis (PCA). New data on the sanogenetic effect of the applied methods of rehabilitation treatment in terms of changes in the indicators of HR and endotoxicosis (ET) and the relationship between them are also interesting. The purpose of the work is to assess the initial state of the indicators of HR and ET and the effect on them of a combination of medicinal and non–medicinal products used as part of rehabilitation measures for AP. Material and methods. Paired correlation analysis of the block structure of the obtained correlation matrices was applied to 52 patients with severe pPPhA, pNT and pCS. This analysis established the relationship between two indicators – both before the start of rehabilitation measures (the use of ethylmethylhydroxypyridine succinate, laser hemotherapy, hyperbaric oxygenation and mesodiencephalic modulation in accordance with the type of AP), and after their completion, before the discharge of patients from the hospital. Results. Statistically significant correlations were established between the indicators of HR and ET both before the start of treatment (0.44–0.94, without sign) and after its completion (0.49–0.99, without sign), which allowed us to confirm at a higher level a direct link between the development of HR and ET disorders, as well as to draw a conclusion about the sanogenetic effect of rehabilitation treatment. Limitations. The study has no limitations for further use of this methodological approach. Conclusion. The obtained data can serve as a justification for the introduction into practice of the proposed methods of mathematical analysis of the results of treatment measures.

Challenges in implementing treat-to-target in rheumatoid arthritis: a perspective from Brazilian rheumatologists

BackgroundPatient management in rheumatoid arthritis (RA) has evolved to a “treat-to-target” (T2T) approach, which entails intensive treatment and regular follow-up with the goal of achieving low levels of disease activity or clinical remission. Even though a T2T approach is endorsed by professional organizations and yields superior outcomes, its implementation remains incomplete. EVEREST (EleVatE care in RhEumatoid arthritiS with Treat-to-target) is a quality-improvement initiative designed to improve the widespread implementation of a personalized T2T strategy and enable patients with RA to reach their full potential for remission. We describe the Brazilian results from the Global T2T Survey, first part of the EVEREST program.MethodsBetween June and September 2022, we conducted an online survey targeting rheumatologists in Brazil. Our objective was to evaluate the barriers and knowledge gaps hindering the effective implementation of T2T strategies. To achieve this, we employed a set of multiple-choice questions specifically crafted to elicit responses categorized in a structured order.Results166 rheumatologists participated in the survey, 51% of them with more than 21 years of experience in rheumatology. Regarding the perceived challenges in the management of RA in clinical practice, the highest percentage of agreement/strong agreement among the participants was related to the contradictory results of disease activity measures (60%). In terms of the main barriers to assess the disease activity in clinical practice, the lack of adherence to treatment and contradictory assessments between patient-reported outcomes and composite measures were indicated by 75% and 59% of the participants, respectively, as a moderate/serious barrier. The most frequently knowledge and skill gaps related to the management of RA pointed out by the participants were on the difficulty to assess patients’ health literacy (54% stated to have no more than intermediate knowledge on standardized methods to assess it and 43% no more than intermediate skills on determining the level of health literacy of the patients). In general, the use of tools to support the management of RA patients in clinical practice was indicated to be unusual by the participants. Self-reflection questionnaires, patient education materials and treatment consideration checklists were pointed out as the least frequently used tools (85%, 64% and 62% of the participants stated to use them never, rarely, or only sometimes, respectively).ConclusionsOur findings indicate a greater need for design, selection, and uptake of practical strategies to further improve communication between healthcare providers and patients with RA, as well as for promoting well-informed, collaborative decision-making in their care.

Shockwave therapy in persons with a spinal cord injury and spasticity: A multiple single-case experimental design study

Objective To determine whether ESWT is able to safely and positively influence specific ADL activities in people with SCI and spasticity, measured by Goal Attainment Scaling (GAS). Study Design Multiple single-case experimental design with a randomized baseline length. Setting Rehabilitation centre. Subjects This study included 11 participants with SCI, aged >18 years (mean (SD) 63 (12.2) years), mean (SD) duration after injury 9 (8.1) years, with hindering spasticity in the upper or lower limb. Methods During the 3-week treatment phase, radial ESWT in the plantar flexors of the calf (n = 6) or in the flexors of the wrist/hand (n = 5) was applied weekly, followed by a 12-week follow-up phase. The primary outcome measure consisted of the Goal Attainment Scaling (GAS), in which three individual goals were set. Secondary outcome measures included range of joint motion, pain (0–10), 10-m walking test and Van-Lieshout-hand-function-test-for-Tetraplegia (short form). Results At descriptive level, in total, 28 of the 33 GAS items improved after ESWT and these effects generally were maintained during the follow-up phase. The results of all secondary outcome measures varied. No serious adverse events occurred. Conclusions In this study, ESWT resulted in improved performance of specific ADL items in most persons with SCI. More research is needed to confirm these results in a larger cohort.

Dynamics of Dental Care for the Population of the Ryazan Region in COVID-19 Pandemic

INTRODUCTION: Identification of morbidity (based on requests) and the population’s need for dental care optimizes the planning and distribution of compulsory health insurance (CHI) funds between medical organizations at the regional level. However, due to a decrease in the population’s demand for medical care in the context of the new coronavirus infection (Corona Virus Disease 2019, COVID-19), the dynamics of the provision of dental care and the structure of dental morbidity taken into account in the compulsory medical insurance system, have changed. AIM: To study the structure and dynamics of the provision of dental care in the period 2018–2021 (pre-pandemic and COVID-19 pandemic period) based on the volume of dental care paid for in the compulsory medical insurance system provided to citizens of the Ryazan region (RR). MATERIALS AND METHODS: The analysis was carried out on the basis of registers of bills accepted for payment submitted by medical organizations, taking into account the results of control and expert measures. All completed cases of treatment of insured persons with dental diseases in medical organizations of the Ryazan Region for 2018–2021 were selected for study according to territorial compulsory medical insurance programs. RESULTS: In the structure of outpatient primary health care in 2021, cases of its provision in the ‘Dentistry’ profile amounted to 7.40 ± 0.10%, taking 3rd place; the total number of cases of providing medical care to patients with this pathology decreased by 5.60% compared to 2018. Despite the reduction in the volume of primary dental care, the volume of dental examinations of the population of the RR increased by 30.46%. There was also a 34.08% reduction in completed cases of treatment of chronic periodontitis (p 0.02). For the 2018–2021 period 73,049 medical and economic examinations (MEE) and 1,626 examinations of medical care quality (EMCQ) were carried out, and 1,966 violations were identified (1,316 based on the results of the MEE and 650 based on the results of the EMСQ). The vast majority of these concerned non-compliance with standards of care and clinical guidelines. CONCLUSION: The results of the study indicate a reduction in the number of cases of insured persons seeking medical care for dental diseases during the COVID-19 pandemic. Owing to the approval of Order No. 231n of the Ministry of Health of Russia of March 19, 2021, obliging medical insurance organizations to carry out control and expert measures in each medical organization in a certain amount of dental care cases accepted for payment, the number of examinations has increased, and, as a result, the identification of violations in the provision of dental care.

Two approximation results for divergence free measures

In this paper, we prove two approximation results for divergence free measures. The first is a form of an assertion of J. Bourgain and H. Brezis concerning the approximation of solenoidal charges in the strict topology: Given F \in M_{b}(\mathbb{R}^{d};\mathbb{R}^{d}) such that \operatorname*{div}F=0 in the sense of distributions, there exist oriented C^{1} loops \Gamma_{i,l} with associated measures \mu_{\Gamma_{i,l}} such that \begin{align*}F= \lim_{l \to \infty}\frac{\|F\|_{M_b(\mathbb{R}^d;\mathbb{R}^d)}}{n_{l} \cdot l}\sum_{i=1}^{n_l}\mu_{\Gamma_{i,l}}\end{align*} weakly-star in the sense of measures and \begin{align*}\lim_{l \to \infty}\frac{1}{n_{l} \cdot l}\sum_{i=1}^{n_l}\|\mu_{\Gamma_{i,l}}\|_{M_b(\mathbb{R}^d;\mathbb{R}^d)}= 1.\end{align*} The second, which is an almost immediate consequence of the first, is that smooth compactly supported functions are dense in \{ F \in M_{b}(\mathbb{R}^{d};\mathbb{R}^{d}): \operatorname*{div}F=0 \} with respect to the strict topology.

Probabilistic Risk Assessment in Cybersecurity: Bayesian Methods for Quantifying and Mitigating Cyber Risks

In today's digital world, where everything is linked, privacy dangers are a big problem for businesses, states, and people. When it comes to cybersecurity, traditional ways of assessing risk don't always work because online threats are always changing. By combining statistical models with existing data and expert knowledge, Bayesian methods, on the other hand, look like a potential way to measure and reduce online risks. This essay looks at how Bayesian methods can be used in probabilistic risk assessment (PRA) in the field of hacking. Bayesian reasoning is used by PRA to get a fuller picture of cyber risks by taking into account doubt, variation, and personal opinions during the risk assessment process. By using likelihood functions, posterior distributions, and prior probabilities, Bayesian methods give us a sensible way to update risk predictions as new information comes in. One of the best things about Bayesian PRA is that it can take into account how different online risks and weaknesses are connected and depend on each other. By using statistical modeling to look at these connections, businesses can find possible chain reactions and decide how to best stop them. Additionally, Bayesian methods let you use expert opinions and personal data, which makes it possible to look at online risks in a more complete way than just using numbers. One of Bayesian PRA's strengths is that it can work with little data and unknown input values. When there isn't enough or a lot of good actual data, Bayesian methods let analysts combine information from different sources, like past data, threat intelligence, and expert opinions, in a planned way to get more accurate risk predictions. Bayesian methods can be used to make decisions about how to reduce security risks as well as how to measure those risks. In a probabilistic framework, organizations can figure out the best ways to lower their general cyber risk exposure by modeling the possible results of different mitigating measures. Overall, this study shows how Bayesian methods could help the area of computer risk assessment grow. By accepting doubt and using a variety of information sources, Bayesian PRA provides a powerful set of tools for measuring cyber risks and helping risk managers make decisions in a danger situation that is becoming more complicated.

Clinical characteristics and management outcome of acute infectious endophthalmitis.

This study aimed to investigate the demographics, clinical characteristics, and management outcomes of patients with acute infectious endophthalmitis (AIE). This retrospective chart review was conducted on all patients admitted with the clinical diagnosis of infectious endophthalmitis from 2017 to 2022. Demographic data, patients' clinical characteristics, the type of acute infectious endophthalmitis (post-operative, post-traumatic, bleb-associated, and endogenous endophthalmitis), the type of surgical procedure in the post-operative cases, the microbiologic analysis results of vitreous samples, therapeutic measures, and visual outcomes of patients were recorded. In this study, 182 participants, including 122 male (67%) and 60 (33%) female, were involved. The mean age of patients was 54.56 ± 21years, with a range of 1-88years old. The most prevalent type of AIE was post-operative (59.9%), followed by endogenous (19.2%), post-traumatic (17%), and bleb-associated (3.8%). The most common type of intraocular surgery in the post-operative subgroups of AIE patients was phacoemulsification (57.8%). The median (interquartile range) of the primary and final BCVA of patients was 1.5 (1.35, 1.85) and 0.65 (0.35, 1.35), respectively. Vitreous haziness grade (OR, 2.89; 95% CI, 1.11-5.74; p = 0.009) and the primary VA (OR, 60.34; 95% CI, 2.87-126.8; p = 0.008) revealed statistical significance for final vision loss. AIE is a devastating condition with poor visual outcomes, which presents with acute inflammatory signs and symptoms regardless of its type. However, prompt and appropriate treatment leads to visual recovery to a functional level in many patients.

Assessing racial bias in healthcare predictive models: Practical lessons from an empirical evaluation of 30-day hospital readmission models

ObjectiveDespite increased availability of methodologies to identify algorithmic bias, the operationalization of bias evaluation for healthcare predictive models is still limited. Therefore, this study proposes a process for bias evaluation through an empirical assessment of common hospital readmission models. The process includes selecting bias measures, interpretation, determining disparity impact and potential mitigations. MethodsThis retrospective analysis evaluated racial bias of four common models predicting 30-day unplanned readmission (i.e., LACE Index, HOSPITAL Score, and the CMS readmission measure applied as is and retrained). The models were assessed using 2.4 million adult inpatient discharges in Maryland from 2016 to 2019. Fairness metrics that are model-agnostic, easy to compute, and interpretable were implemented and apprised to select the most appropriate bias measures. The impact of changing model’s risk thresholds on these measures was further assessed to guide the selection of optimal thresholds to control and mitigate bias. ResultsFour bias measures were selected for the predictive task: zero-one-loss difference, false negative rate (FNR) parity, false positive rate (FPR) parity, and generalized entropy index. Based on these measures, the HOSPITAL score and the retrained CMS measure demonstrated the lowest racial bias. White patients showed a higher FNR while Black patients resulted in a higher FPR and zero-one-loss. As the models’ risk threshold changed, trade-offs between models’ fairness and overall performance were observed, and the assessment showed all models’ default thresholds were reasonable for balancing accuracy and bias. ConclusionsThis study proposes an Applied Framework to Assess Fairness of Predictive Models (AFAFPM) and demonstrates the process using 30-day hospital readmission model as the example. It suggests the feasibility of applying algorithmic bias assessment to determine optimized risk thresholds so that predictive models can be used more equitably and accurately. It is evident that a combination of qualitative and quantitative methods and a multidisciplinary team are necessary to identify, understand and respond to algorithm bias in real-world healthcare settings. Users should also apply multiple bias measures to ensure a more comprehensive, tailored, and balanced view. The results of bias measures, however, must be interpreted with caution and consider the larger operational, clinical, and policy context.