Daily Decisions Research Articles

The Impact of Health Literacy on Diabetes Control

Abstract Introdution People with diabetes have a significant impact on treatment outcomes through their daily decisions. Therefore, health literacy (HL) is crucial for effectively managing the disease and maintaining overall health. This study aimed to explore the relationships between different dimensions of health literacy, self-care behaviors, and Diabetes Control (HbA1c). Methods HLwas assessed using the Health Literacy Questionnaire. 706 individuals with diabetes participated in the study, the majority of whom were male (60.2%), had more than 9 years of schooling (84.7%), and over half were employed (52.4%). To examine the relationship between dimensions of HLand HbA1c, multiple linear regression analysis was conducted. Results The study revealed a significant association between higher levels of HLand lower HbA1c levels. There is a statistically significant positive linear correlation between adherence to general nutrition and HLdimensions. In terms of physical activity, a positive correlation was also found with HLdimensions, and blood glucose monitoring showed a positive correlation with health literacy. Greater adherence to nutrition was linked to a decrease in HbA1c levels, while higher adherence to self-monitoring and medication was associated with an increase in HbA1c levels Conclusions This study emphasizes the importance of HLin managing diabetes. It underscores the impact of HLin diabetes compensation. The results reveal that higher levels of feeling understood and supported by healthcare professionals, having sufficient information to manage health, actively managing health, and appraising health information among people with diabetes lead to better adherence to blood glucose self-monitoring. Based on these findings, a crucial aspect of effectively managing diabetes will involve empowering individuals with the necessary skills for self-management of their condition, overall health, and treatment regimen. Key messages • The present research reinforces the importance of health literacy for diabetes compensation and self care activies. • One critical success factor in dealing with diabetes will be investing of health literacy of people with diabetes and health care providers responsiveness.

Different approaches to regulate digital health applications in seven European countries

Abstract Background Demographic ageing, shortages in health workforce and increased use of digital tools in daily life kindle decision makers’ interest to utilize digital health applications (DHA). While there are several reviews that provide an overview across remuneration frameworks, no synthesis between additional regulatory aspects and frequency of remuneration approval has been conducted. Methods European countries with either strong status in digital health in general or regulation for health apps in particular were chosen for analysis (BE, DK, DE, EE, EN, FR, NL). Country specific information was collected from scientific and grey literature, legal and stakeholder webpages. Semi-structured interviews were conducted with country experts via video call or e-mail and analyzed using Mayring’s structured, qualitative content analysis. Preliminary results We find three approaches concerning DHT-definitions: For BE, DE, FR, specific regulations define national remuneration requirements. EN and NL define only minimum requirements while decentralized payors make financing decisions. DK and EE fit DHTs into existing financing schemes. Among countries with a national financing framework, DE achieved the largest number of approvals, followed by FR, while BE has not yet issued a (lasting) financing approval. Evaluation requirements focus on clinical and economic outcomes, largely ignoring non-clinical improvements for patients. Conclusions The German regulation stands out with a peculiar definition that might help clarify evaluation criteria, increase the number of financing approvals but also empower patients while reducing the role of health workforce in their application. BE and NL regulations necessitate involvement of health workers, thus addressing structurally different applications. Key messages • Drawing lessons for DHT regulations across countries needs to address differences in national definitions and evaluation criteria. • A standardization system for DHT may help to speed utilization of effective tools and clarify evaluation requirements.

Punitive Subjectivities and Emotions in Immigration Detention

In immigration detention centres, emotions run high; tensions, conflicts, anxiety, and affection occur amid bureaucratic procedures, paperwork, files, lists of people, systematisation of cases, buses that come and go with detainees, and people who will be deported. Although immigration detention belongs to administrative law, in practice, detention centres operate closer to penal detention. Little is known about the operation of these places in Mexico, including how punishment takes place in daily practice. Even less is known about the people who work there, especially the rationale and emotions behind their daily decisions and the different ways in which they collaborate with a system that promotes punishment as a central element of immigration detention. In this article, I study how fear and disgust are emotions embedded in institutional practices that reinforce punishment in immigration detention, while empathy can challenge it. I analyse working conditions and daily interactions in detention centres, immigration control facilities and their surroundings. I argue that immigration agents can develop punitive subjectivities to channel emotions derived from anxieties and frustrations of daily work, as well as to embrace a sense of institutional belonging and the illusion of order and control. However, border officers also show empathy towards migrants to cope with emotional distress and humanise their daily work. I intend to answer the questions in this paper: Under what institutional conditions do emotions become power in immigration detention settings? What do emotions reveal about the functioning of punishment in immigration detention centres? How do emotions expressed by INM agents (such as fear, disgust and empathy) enhance or challenge punitive subjectivities?

A dynamic discrete choice modelling approach for forward-looking travel mode choices

In this paper, we present a systematic approach based on dynamic discrete choice models (DDCM) to investigate individuals’ forward-looking mode choice behaviours in daily travel tours with multiple destinations. We propose a novel network transformation model that encompasses the entire decision space of all feasible mode combinations for every observed trip/tour in the dataset. By applying the well-established Recursive Logit model structure commonly used in path choice modelling, we address the tour mode choice problem effectively and quantify forward looking considerations in the mode choice process. The proposed model captures the complex considerations individuals take into account when making mode choices. The network transformation incorporates downstream mode limitations into the preceding mode choice options, enabling us to model individuals’ forward-looking behaviour and gain insights into how considerations of future trips such as a shopping in the evening, or school pick-up trip influence previous mode choice decisions earlier in the day. Uncovering and quantifying these hidden forward-looking factors can help modellers better explain the private car usage usually observed for the entire sequences of daily trips, even in presence of competitive alternative modes. The proposed network transformation also enables us to measure the effect of the requirement/preference to return private vehicles (car, motorcycle, and bicycle) home on mode choices in home-bound trips, and subsequently, on the entire daily mode choice decisions. To validate the proposed model, we utilise the VISTA household travel survey data from the Melbourne Metropolitan area in Australia. The model is compared against baseline models, demonstrating its statistical advantages. Additionally, intuitive illustrations using the data showcase the model’s efficacy. From transport planning and policy perspective, tour-based mode choice modelling provides a more comprehensive and precise understanding of travel behaviour by considering the sequence of trips made by an individual. This can help capture the interactions and dependencies between different trips, which trip-based models may overlook. The proposed model is more suitable for analysing the effects of policy interventions like congestion pricing, public transport investments, or new mobility initiatives, as they can better represent the cascading effects of such policies across multiple trips.

Self-Reported Financial Difficulties Among Patients with Multiple Myeloma and Chronic Lymphocytic Leukemia Treated at U.S. Community Oncology Clinics (Alliance A231602CD).

To estimate the proportion and correlates of self-reported financial difficulty among patients with multiple myeloma (MM) or chronic lymphocytic leukemia (CLL). 23 U.S. community and minority oncology practice sites affiliated with the National Cancer Institute Community Oncology Research Program (NCORP). 521 patients (≥18 years) with MM or CLL were consented and 416 responded to a survey (completion rate=79.8%). Respondents had a MM diagnosis (74.0%), an associate degree or higher (53.4%), were White (89.2%), insured (100%) and treated with clinician-administered drugs (68.0%). Observational, prospective, protocol-based survey administered in 2019-2020. Financial difficulty was assessed using a single-item standard measure, the EORTC QLQC30: "Has your physical condition or medical treatment caused you financial difficulties in the past year?" and using an 'any-or-none' composite measure of 22 items assessing financial difficulty, worries and the use of cost-coping strategies. Multivariable logistic regression models assessed the association between financial difficulty, diagnosis, and socioeconomic and treatment characteristics. 16.8% reported experiencing financial difficulty using the single-item measure and 60.3% using the composite measure. Most frequently endorsed items in the composite measure were financial worry about having to pay large medical bills related to cancer and difficulty paying medical bills. Financial difficulty using the single-item measure was associated with having MM versus CLL (adjusted odds ratio [aOR], 0.34; 95% CI, 0.13-0.84; P=.02), having insurance other than Medicare (aOR, 2.53; 95% CI, 1.37-4.66; P=.003), being non-White (aOR, 2.21; 95% CI, 1.04-4.72; P=.04), and having a high school education or below (aOR, 0.36; 95% CI, 0.21-0.64; P=.001). Financial difficulty using the composite measure was associated with having a high school education or below (aOR, 0.62; 95% CI, 0.41-0.94; P=.03). U.S. patients with blood cancer report financial difficulty, especially those with low socio-economic status. Evidence-based and targeted interventions are needed.

Data-driven sensegiving and sensemaking: a phenomenological investigation

PurposeBusiness analytics (BA) is a new frontier of technology development and has enormous potential for value creation. Information systems research shows ample evidence of its positive business impacts and organizational performance. However, there is limited understanding of how decision-makers or users of BA outcomes actually engage with data analysts in the process of data-driven insight generation and how they improve their understanding of business environments using BA outcomes. To aid this engagement and understanding, this study investigates the interaction between decision-makers and data analysts when they attempt to uncover data capacities and business needs and acquire business insights from BA tools.Design/methodology/approachThis study employs an interpretive field study with thematic analysis. The authors conducted interviews with 31 participants who all relied on BA in their daily decisions. The study participants were engaged in different BA roles, including data analysts and decision-makers. They validated the applicability and usefulness of our findings through a focus group with eight practitioners, including decision-makers and data analysts from the same companies.FindingsThis study proposes a process model of data-driven sensemaking and sensegiving based on Weick’s sensemaking framework. The findings exhibit that decision-makers are engaged in sensemaking by identifying areas of focus, determining BA scope, evaluating generated insights and turning BA into action. The findings also show that data analysts engage in sensemaking by consolidating data, data understanding, preparing preliminary outcomes and generating actionable reports. This study shows how sensemaking processes and sensegiving activities work together over time through immediate enactment, selection and decision cycles.Originality/valueThis study is a first attempt to understand interactions in the context of BA using the perspective of sensemaking and sensegiving.

Diabetes and Technology in Romania: A Patient's Perspective.

Professional medical care in the case of diabetes is of utmost importance to ensure patient health, compliance, and comfort. In the past decades, the emergence of healthcare medical devices has also brought important advancements in diabetology. However, this also raised new provocations for patients and healthcare professionals as well, regarding the acceptance, use, and contentment of sensors and pumps in the everyday lives of diabetic patients. The present study aimed to bring more evidence into the possibilities and pitfalls of these medical devices by interrogating 185 diabetic patients through online questionnaires from Romania. The results revealed that the medical devices can complement traditional medical care, and pre-, post-prandial, and nighttime glycemia can be more precisely achieved. Patients have also reported that the sensors and pumps can augment their daily decision-making about glycemic control and ease their daily routine. Contrariwise, the use of these medical devices is related to comfortlessness during sleeping and physical activity. Researchers acknowledge that patients' information, education, and diabetes management, through the opinion of the patients, can augment patient-focused decision-making in the daycare of diabetic patients.

Determining Clinicopathologic Factors That Influence Treatment in Advanced Breast Cancer in Argentina After CDK4/6 Inhibitors.

The optimal treatment sequence for hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) advanced breast cancer (ABC) after progression on first-line cyclin-dependent kinase 4/6 inhibitor (CDKi) and endocrine therapy is unclear. Clinical and biological factors influencing treatment choices and outcomes in the second-line setting need to be elucidated. This is a retrospective analysis of a real-world cohort including patients with HR+/HER2- ABC who received CDKi and endocrine therapy in the first-line setting and progressed, requiring second-line treatment. Clinical and biological factors were analyzed to evaluate their association with daily treatment decisions and the prognostic role of progression-free survival (PFS) in the second-line setting. Two hundred thirty-five patients were included. Second-line treatments were hormone therapy (HT) based in 60% and chemotherapy based in 40% of patients. The second-line median PFS was 6.6 months, with no difference between treatment types. In multivariable analysis, postmenopausal status, lower Ki-67 expression, and non-de novo stage IV disease were associated with improved second-line (2L) PFS. Menopausal status significantly interacted with treatment type, with reduced PFS in premenopausal patients receiving HT-based treatments (4.7 v 8.7 months, P = .00045). In our study, treatment decisions reflected the current algorithm incorporated in our clinical guidelines, and prior treatment response was the most relevant factor to determine 2L treatment decision. Menopausal status interacted with the subsequent therapy efficacy in this setting. Hence, we consider that menopausal status should be routinely evaluated in the subgroup analysis of clinical trials.

EXAMINING FINANCIAL LITERACY LEVELS AMONG UNIVERSITY STUDENTS: A SURVEY STUDY IN AFYONKARAHISAR

Individuals' awareness of their daily financial decisions directly affects their economic well-being. Therefore, it is crucial for educational institutions to provide students with basic financial knowledge through curriculum programs supporting financial literacy. This study aims to assess the impact of financial management and accounting courses in universities on the body of financial literacy knowledge of students. The study draws on the data obtained from a survey of the students at the Faculty of Economics and Administrative Sciences at Afyon Kocatepe University. The survey was conducted on a sample of 838 students during the spring semester of the 2021-2022 academic year. Research data were analyzed using frequency analysis and chi-square test with the SPSS 23.0 software package. The findings reveal that, overall, students have low levels of financial literacy. However, the results indicate that finance and accounting courses play a significant role in increasing financial literacy levels.

Improving Healthcare Quality with a LHS: From Patient-Generated Health Data to Evidence-Based Recommendations.

One approach to enriching the Learning Health System (LHS) is leveraging vital signs and data from wearable technologies. Blood oxygen, heart rate, respiration rates, and other data collected by wearables (like sleep and exercise patterns) can be used to monitor and predict health conditions. This data is already being collected and could be used to improve healthcare in several ways. Our approach will be health data interoperability with HL7 FHIR (for data exchange between different systems), openEHR (to store researchable data separated from software but connected to ontologies, external terminologies and code sets) and maintain the semantics of data. OpenEHR is a standard that has an important role in modelling processes and clinical decisions. The six pillars of Lifestyle Medicine can be a first attempt to change how patients see their daily decisions, affecting the mid to long-term evolution of their health. Our objective is to develop the first stage of the LHS based on a co-produced personal health recording (CoPHR) built on top of a local LLM that interoperates health data through HL7 FHIR, openEHR, OHDSI and terminologies that can ingest external evidence and produces clinical and personal decision support and, when combined with many other patients, can produce or confirm evidence.

Mobility practices in a changing climate: Understanding shifts in car ownership and use across the life course

Mobility practices in everyday life are often highly routinised and resistant to change. But they can also change significantly over the life course, reflecting sudden ruptures linked to incisive life events and more gradual shifts related to changing societal and environmental conditions. Combining insights from practice-theoretical mobility studies and mobility biographies research, this paper critically examines the role of material, social and cultural elements in transforming routine mobility practices, focusing on car ownership and use across the life course. Drawing on mobility-biographical interviews with people who live in Munich (Germany) and who do not own a car, it reveals the complexity of both one-off and daily decisions that help to establish and routinise carless mobility practices, linking them to social and material conditions past and present. The paper also documents the role of environmental and climate-related arguments in the transition towards carlessness, alongside shifts in infrastructure, social and economic circumstances and mobility-related skills and meanings. It concludes with some recommendations for sustainable mobility policy that works with the dynamics of car ownership and use across the life course and that incorporates both social and material aspects underpinning people’s decision to give up their private car.

‘The Hideous Old Lady of Fashion’: dressing the ageing body in Victorian Britain

Abstract This article explores how the biological realities and cultural constructions of ageing combined to influence a daily decision taken by Victorian women: what to wear. The cartoons found in Punch, and the guidance given by fashion papers and journalistic and literary sources highlight the individualized experience of dressing the ageing body, and the knowledge and skill needed to chart a course of compromise between ageing and the expectations that came with longer-held identities such as class, gender and sexuality. The difficulties in navigating this transition demonstrate how ageing was an art, and doing it well was a merit.

INTEGRATION OF ISLAMIC RELIGIOUS EDUCATION LEARNING METHODS IN THE 21st CENTURY AT MA NAHDHOTUT THOLIBIN

In facing education challenges in the modern era, Islamic Religious Education (PAI) learning at MA Nahdlotut Tholibin seeks to integrate religious values relevant to the times' needs. The PAI curriculum, which still uses many traditional methods, is considered less effective in attracting the interest of students who grow up in the era of globalization, which further erodes moral and ethical values. Surveys conducted in several educational institutions found that although students understand religious concepts, they often have difficulty implementing them in real life. This research aims to develop a more relevant and applicable learning methodology which is theoretical and supports the practice of students' daily lives. This study uses a descriptive qualitative approach by conducting in-depth interviews, classroom observations, and document analysis to evaluate the application and suitability of 21st-century learning methods. Participants in this study include PAI teachers, students, and administrators from MA Nahdlotut Tholibin. The data was analyzed using content analysis techniques. The study results show that learning methods with 21st-century skills such as Communication, Collaboration, Critical Thinking and Problem Solving, and Creativity and Innovation can increase students' understanding and motivation to learn. This approach helps students become critical thinkers and practitioners of good religious values in modern society. This research provides insight into the importance of designing a curriculum responsive to changing times. It supports the development of students' interpersonal skills and strengthens their ability to integrate religious teachings into daily decision-making.

Development and psychometric evaluation of the type 1 diabetes mellitus self-management scale for parents

Background/aimDiabetes has become a global epidemic, necessitating effective self-management strategies. This is particularly crucial for parents of children with type 1 diabetes mellitus, as they must make numerous daily decisions and perform complex care activities. Therefore, the aim of this study was to develop a comprehensive diabetes self-management scale specifically for parents of children with type 1 diabetes. This scale aims to holistically address behaviors impacting diabetes self-management and to evaluate its psychometric properties.Materials and methodsA methodological, correlational, and cross-sectional study was conducted with a sample of 190 parents of children with type 1 diabetes mellitus. The scale items were reviewed by five experts to ensure they adequately covered the parents' evaluation of their children's diabetes self-management. Following this, a Turkish language expert assessed the draft scale for language accuracy, comprehensibility, and grammar. The data were analyzed using descriptive statistics (numbers and percentages), Cronbach's α reliability coefficient, factor analysis, and correlation analysis.ResultsThe Cronbach's alpha for the overall scale was 0.893, and the Cronbach's alpha for the subscales was between 0.757 and 0.845. The item-total score correlations ranged between 0.408 and 0.660 (p < .05). The exploratory factor analysis showed that the scale explained 61.427% of the total variance, and the factor loadings of items ranged from 0.574 to 0.859. The confirmatory factor analysis also showed that the factor loadings of the scale items ranged from 0.574 to 0.859.Conclusion: The validity and reliability analyses revealed that the scale is a valid and reliable measurement tool for the Turkish culture.

Digital health literacy among primary and secondary school teachers-a quantitative study.

Digital health literacy (DHL) is a key competency for individuals' daily decisions toward their health behavior and wellbeing. While there is much focus on health literacy (HL) among the general population, teachers have been rarely addressed. Given the shortages in the teaching workforce in Europe and the impact of demanding working conditions on their health, it is important to address DHL in teachers. This paper examines the DHL of primary and secondary teachers and its associations with sociodemographic and school-related factors. An online cross-sectional study was conducted with 1,600 German primary and secondary school teachers between October and December 2022. To assess DHL, the Digital Health Literacy Instrument (DHLI) including seven subscales was used. Statistical analyses were conducted on item and subscale level and an overall DHL score was calculated. Next to descriptive analyses, bivariate and regression analyses were conducted to explore potential associations with sociodemographic and school-related factors. The frequency of difficulty in using digital health information varied across DHL dimensions and was greatest for protecting privacy (70.9%) and evaluating reliability (40.0%). In multivariate analysis, females more often reported a sufficient ability of adding content (OR = 1.61, CI = 1.05-2.48), while males more often reported a sufficient ability to protect their privacy (OR = 0.45, CI = 0.27-0.75). Teachers with leadership positions more often reported a sufficient ability in adding content (OR = 1.78, CI = 1.07-2.98). Regarding the ability to determine the relevance of online health-related information, no associations with a predictor variable were found. The results suggest that it is important to examine the individual dimensions of DHL and their distinct associations with sociodemographic and school-level factors, rather than just to rely on the overall level of DHL. The differential patterns identified in this study suggest a greater intervention need for teachers from higher age groups, primary and secondary general schools, and those without leadership roles. However, based on the limited predictive power of the variables included, further individual and school-level factors and their potential association with DHL should be investigated in the future. The promotion of DHL should be integrated into both teacher education and in-service training.

Neoadjuvant and Adjuvant Treatments for Early Stage Resectable NSCLC: Consensus Recommendations From the International Association for the Study of Lung Cancer

Advances in the multidisciplinary care of early stage resectable NSCLC (rNSCLC) are emerging at an unprecedented pace. Numerous phase 3 trials produced results that have transformed patient outcomes for the better, yet these findings also require important modifications to the patient treatment journey trajectory and reorganization of care pathways. Perhaps, most notably, the need for multispecialty collaboration for this patient population has never been greater. These rapid advances have inevitably left us with important gaps in knowledge for which definitive answers will only become available in several years. To this end, the International Association for the Study of Lung Cancer commissioned a diverse multidisciplinary international expert panel to evaluate the current landscape and provide diagnostic, staging, and therapeutic recommendations for patients with rNSCLC, with particular emphasis on patients with American Joint Committee on Cancer-Union for International Cancer Control TNM eighth edition stages II and III disease. Using a team-based approach, we generated 19 recommendations, of which all but one achieved greater than 85% consensus among panel members. A public voting process was initiated, which successfully validated and provided qualitative nuance to our recommendations. Highlights include the following: (1) the critical importance of a multidisciplinary approach to the evaluation of patients with rNSCLC driven by shared clinical decision-making of a multispecialty team of expert providers; (2) biomarker testing for rNSCLC; (3) a preference for neoadjuvant chemoimmunotherapy for stage III rNSCLC; (4) equipoise regarding the optimal management of patients with stage II between upfront surgery followed by adjuvant therapy and neoadjuvant or perioperative strategies; and (5) the robust preference for adjuvant targeted therapy for patients with rNSCLC and sensitizing EGFR and ALK tumor alterations. Our primary goals were to provide practical recommendations sensitive to the global differences in biology and resources for patients with rNSCLC and to provide expert consensus guidance tailored to the individualized patient needs, goals, and preferences in their cancer care journey as these are areas where physicians must make daily clinical decisions in the absence of definitive data. These recommendations will continue to evolve as the treatment landscape for rNSCLC expands and more knowledge is acquired on the best therapeutic approach in specific patient and disease subgroups.

Human-centred factors of decision-making for financial resilience

ABSTRACT In this paper, we have adapted the components and factors of an existing financial resilience measurement framework, and leveraged a survey that reflects the decision-making of Irish social housing residents in money management and their capacity to cope with unexpected financial shocks. Extending existing financial literacy definitions, this paper shifts the perspective from measuring financial resilience components to exploring the drivers that could impact that resilience at an individual level. This bridging of the objective and subjective domains contributes to the common good by exploring how citizens deal with daily decision-making in a financialised world.

#2714 An AI based tool for hydration management in dialysis patients.

Abstract Background and Aims Hemodialysis patients often experience over-hydration (OH), a critical factor derived from excess extracellular water and associated with cardiovascular complications and overall morbidity. Accurate estimation of pre-dialysis OH is essential for optimizing fluid management and improving patient outcomes. Traditional methods for assessing OH, such as the Body Composition Monitor (BCM) are, in general, time-consuming for clinical staff and costly for healthcare providers. In this study, we present a machine learning model combining data automatically recorded by dialysis machine sensors and medical information captured in electronic chart records to estimate pre-dialysis OH. The aim of this study is to evaluate the possibility of a tool that predicts OH from patient's data without, or less frequently using, a bioimpedance device for OH measurements. Method We collected a comprehensive dataset from a cohort of CKD patients undergoing hemodialysis, including demographic information, clinical parameters, and hydration status parameters. The value of OH was assessed using BCM device. A feature selection approach, guided by a balance between prediction accuracy and model complexity, was used to identify the optimal set of input variables. All variables utilized in the model are either regularly gathered in clinical practice or automatically recorded from the dialysis machine. We tried different combinations of features using an XGBoost regressor algorithm. We focused the study on the comparison of the prediction of OH with the input variable of the average BCM OH value in the past year (Model 1) and without this variable (Model 2). Mean absolute error (MAE), Root mean square error (RMSE), R2, calibration and residuals plots were used to assess the models’ accuracy. The measurement unit is in litres. The models were validated with nested 5-fold cross-validation, dividing the data repeatedly into disjunct train, validation and test folds and 5 outer loops, totalling 25 folds. Results The dataset contains the observations from 37,011 patients for a total of 934,386 BCM assessments collected in the EuCliD database by Fresenius Medical Care clinics in Cech Republic, Italy, Portugal, Slovakia, Spain, and the United Kingdom between January 2016 to September 2023. The average value of OH is 2.06 (std 1.88). Model 1 generalizes on unseen data samples with an MAE of 0.74, RMSE of 1.02 and R2 of 0.57 after evaluating the performance on the test folds. Model 2 MAE is 0.93, RMSE is 1.25 and R2 is 0.36. The degradation of the accuracy between the two models indicates the importance of patients’ past BCM information for the prediction of the next OH. This degradation is also clear in the calibration and residuals plots (Fig. 1). Nevertheless, model 2 is able to predict OH with an acceptable level of accuracy. Conclusion Fluid management is a critical task for physicians and nurses. We present an AI-based tool that can be utilized to support clinicians in their daily decisions about fluid management, with and without the use of a device to measure OH. The results, as expected, show an important degradation of the accuracy between model 1 and 2, however, model 2 has sufficient overall accuracy to consider the approach valuable, meriting further exploration. In general, this approach can be used to reduce the number of direct OH assessments.

#2499 Multicenter observational study on the impact of continuous monitoring of vascular access on the survival and quality of life of patients on dialysis

Abstract Background and Aims AVE is a multicenter observational study aimed at evaluating the improvements in dialysis efficiency, AVF longevity and mortality that can be achieved by implementing both monitoring by a multidisciplinary team. The universal goal of AV monitoring is to identify early events such as stenosis and intervene before thrombosis, thus maximizing the longevity of access and minimizing morbidity. Method This study takes advantage of the opportunity to use data from 19 hemodialysis centers and approximately 1000 patients and to correlate and examine variables that are commonly reported with each treatment, trends in AV use, trends in patient characteristics, and the practice associated with VA. The data were collected by nurses in a specific section of the management database at each treatment for 5 years. Results Trends at the beginning and at the end of the study were evaluated, and Kaplan Maier curves were performed regarding the survival of the VA and the survival of the patients. The average age of 1000 patients enrolled was 73.5 years. Native AVF was used by 79%, AVG by 2% and CVC by 19%. With increasing age, the use of CVC goes from 6% (15-39 years) to 50.5% in patients over 85 years old. The most frequent complications were: Thrombosis 16.5%, Infections 5.5%. VA-related hospitalization days are 28.7% of total days. The average dialysis goals achieved were: QB 290 ml/Min; purified blood 69.7 L; KT/V:1.35. The AVE study, the survival curves evaluated in aggregate were not different between men and women during the observation period (year 2018: p = 0.327; year 2019: p = 0.174; year 2020: p = 0.343). This finding was also confirmed when the survival data were analyzed according to gender and chronological age. No difference was observed between genders while the significant difference (p = 0.000) between chronological age levels was confirmed as shown in the Figure Conclusion By interpreting data collection for specific performance measures using accurate reports, healthcare professionals can highlight AV performance/inefficiencies and provide correct information to clinical staff to support them in their daily clinical practice and decision making.

A study on commodity pricing and sales optimization based on linear programming model: a case of vegetable category

In the fresh food retail industry, vegetable commodities require daily replenishment decisions based on historical sales and demand due to their short freshness period and susceptibility to quality. In this paper, the sales volume, wholesale price and unit price of each category are first extracted, and the cost-plus ratio and related data are calculated. The relationship between the sales volume of each category and the cost markup rate is analyzed through linear regression, and it is concluded that the sales volume of most categories decreases with the increase of the markup rate, and through the distribution of the scatter plot of the total sales volume of the vegetable category and the markup rate, it can be seen that there is a negative correlation between the total sales volume of the vegetable category and the cost markup pricing, and then through the establishment of the optimization model and the prediction of the sales volume of each category for the coming week, the wholesale price and the related data, and the profits are used to Pricing to ensure revenue at the maximum markup rate to develop the total daily capture and pricing strategy for the coming week.