Association between the stress hyperglycemia ratio and 28-day all-cause mortality in critically ill patients with sepsis: a retrospective cohort study and predictive model establishment based on machine learning.

BACKGROUND: Sepsis is a severe form of systemic inflammatory response syndrome that is caused by infection. Sepsis is characterized by a marked state of stress, which manifests as nonspecific physiological and metabolic changes in response to the disease. Previous studies have indicated that the stress hyperglycemia ratio (SHR) can serve as a reliable predictor of adverse outcomes in various cardiovascular and cerebrovascular diseases. However, there is limited research on the relationship between the SHR and adverse outcomes in patients with infectious diseases, particularly in critically ill patients with sepsis. Therefore, this study aimed to explore the association between the SHR and adverse outcomes in critically ill patients with sepsis. METHODS: Clinical data from 2312 critically ill patients with sepsis were extracted from the MIMIC-IV (2.2) database. Based on the quartiles of the SHR, the study population was divided into four groups. The primary outcome was 28-day all-cause mortality, and the secondary outcome was in-hospital mortality. The relationship between the SHR and adverse outcomes was explored using restricted cubic splines, Cox proportional hazard regression, and Kaplan‒Meier curves. The predictive ability of the SHR was assessed using the Boruta algorithm, and a prediction model was established using machine learning algorithms. RESULTS: Data from 2312 patients who were diagnosed with sepsis were analyzed. Restricted cubic splines demonstrated a "U-shaped" association between the SHR and survival rate, indicating that an increase in the SHR is related to an increased risk of adverse events. A higher SHR was significantly associated with an increased risk of 28-day mortality and in-hospital mortality in patients with sepsis (HR > 1, P < 0.05) compared to a lower SHR. Boruta feature selection showed that SHR had a higher Z score, and the model built using the rsf algorithm showed the best performance (AUC = 0.8322). CONCLUSION: The SHR exhibited a U-shaped relationship with 28-day all-cause mortality and in-hospital mortality in critically ill patients with sepsis. A high SHR is significantly correlated with an increased risk of adverse events, thus indicating that is a potential predictor of adverse outcomes in patients with sepsis.

Shared decision-making approach to type 2 diabetes management.

OBJECTIVE: To provide an online interactive decision aid to facilitate shared decision making in the context of medication choices for patients with type 2 diabetes mellitus (T2DM). SOURCES OF INFORMATION: The best available clinical prediction model for patients with T2DM was selected based on a review of guidelines, DynaMed, and UpToDate and a search of PubMed. A list of pharmacotherapeutic options for T2DM was compiled based on a review of guidelines, narrative reviews, and expert opinion. To determine the benefits and harms of each treatment, federated search engines were searched for meta-analyses of randomized controlled trials, supplemented by individual randomized controlled trials for outcomes not reported in meta-analyses. MAIN MESSAGE: Approximately 2.1 million Canadians have T2DM, with a resulting increased risk of death, cardiovascular disease, and microvascular outcomes. While more than a dozen medication options are available, decisions regarding these medications are challenging, as patients vary in their preferences. Shared decision making has the potential to individualize these difficult decisions, but the number of diabetes-related outcomes and available treatment options have made this historically impractical. It is within this context that the PEER Diabetes Medication Decision Aid was developed. This decision aid provides patients with personalized 10-year risk estimates for 6 clinically important diabetes-related outcomes. The tool also allows patients to focus on the outcome that matters most to them and to compare the benefits and harms of up to 12 different treatment options. This information is displayed in personalized absolute numbers, along with practical considerations such as cost. CONCLUSION: The PEER Diabetes Medication Decision Aid provides a practical tool that can enable patients with T2DM to come to autonomous and well-informed medication decisions.

Risk factors and clinical prediction models for prolonged mechanical ventilation after heart valve surgery.

OBJECTIVES: Prolonged mechanical ventilation (PMV) is a common complication following cardiac surgery linked to unfavorable patient prognosis and increased mortality. This study aimed to search for the factors associated with the occurrence of PMV after valve surgery and to develop a risk prediction model. METHODS: The patient cohort was divided into two groups based on the presence or absence of PMV post-surgery. Comprehensive preoperative and intraoperative clinical data were collected. Univariate and multivariate logistic regression analyses were employed to identify risk factors contributing to the incidence of PMV. Based on the logistic regression results, a clinical nomogram was developed. RESULTS: The study included 550 patients who underwent valve surgery, among whom 62 (11.27%) developed PMV. Multivariate logistic regression analysis revealed that age (odds ratio [OR] = 1.082, 95% confidence interval [CI] = 1.042-1.125; P < 0.000), current smokers (OR = 1.953, 95% CI = 1.007-3.787; P = 0.047), left atrial internal diameter index (OR = 1.04, 95% CI = 1.002-1.081; P = 0.041), red blood cell count (OR = 0.49, 95% CI = 0.275-0.876; P = 0.016), and aortic clamping time (OR = 1.031, 95% CI = 1.005-1.057; P < 0.017) independently influenced the occurrence of PMV. A nomogram was constructed based on these factors. In addition, a receiver operating characteristic (ROC) curve was plotted, with an area under the curve (AUC) of 0.782 and an accuracy of 0.884. CONCLUSION: Age, current smokers, left atrial diameter index, red blood cell count, and aortic clamping time are independent risk factors for PMV in patients undergoing valve surgery. Furthermore, the nomogram based on these factors demonstrates the potential for predicting the risk of PMV in patients following valve surgery.

Predicting Helicobacter pylori infection from endoscopic features.

BACKGROUND: Helicobacter pylori infection, prevalent in more than half of the global population, is associated with various gastrointestinal diseases, including peptic ulcers and gastric cancer. The effectiveness of early diagnosis and treatment in preventing gastric cancer highlights the need for improved diagnostic methods. This study aimed to develop a simple scoring system based on endoscopic findings to predict H. pylori infection. METHODS: A retrospective analysis was conducted on 1,007 patients who underwent upper gastrointestinal endoscopy at Asan Medical Center from January 2019 to December 2021. Exclusion criteria included prior H. pylori treatment, gastric surgery, or gastric malignancies. Diagnostic techniques included rapid urease and 13C-urea breath tests, H. pylori culture, and assessment of endoscopic features following the Kyoto gastritis classification. A new scoring system based on endoscopic findings including regular arrangement of collecting venules (RAC), nodularity, and diffuse or spotty redness was developed for predicting H. pylori infection, utilizing logistic regression analysis in the development set. RESULTS: The scoring system demonstrated high predictive accuracy for H. pylori infection in the validation set. Scores of 2 and 3 were associated with 96% and 99% infection risk, respectively. Additionally, there was a higher prevalence of diffuse redness and sticky mucus in cases where the initial H. pylori eradication treatment failed. CONCLUSION: Our scoring system showed potential for improving diagnostic accuracy in H. pylori infection. H. pylori testing should be considered upon spotty redness, diffuse redness, nodularity, and RAC absence on endoscopic findings as determined by the predictive scoring system.

[BRCA mutations and decision regret: a comprehensive analysis of existing research through a scoping review and reflections from a nursing perspective.] / Mutazioni BRCA e rimpianto decisionale: un'analisi approfondita della ricerca esistente tramite scoping review e riflessioni da una prospettiva infermieristica.

INTRODUCTION: Given the significance of healthcare decisions in women with BRCA1 and BRCA2 mutations and their impact on patients' lives, this study aims to map the existing literature on decision regret in women with BRCA1 and BRCA2 mutations. METHODS: A scoping review was conducted in the following databases: PubMed, Embase, Scopus, CINAHL, Cochrane, and Google Scholar. Inclusion criteria focused on decision regret in the female population with BRCA1 and/or BRCA2 mutations, with no restrictions on the methodologies of the included studies, but only in the English language. The selection process led to the inclusion of 13 studies. RESULTS: The analysis revealed a significant trend toward decision regret among patients facing complex medical choices. The quality of healthcare communication, decision support, and genetic counselling emerged as key factors influencing patients' perceptions and experiences, with direct implications for their quality of life and psychological well-being. The results suggest that these decisions considerably impact patients, both in terms of clinical outcomes and emotional experiences. DISCUSSION: The investigation highlights the vital importance of a personalized care approach, emphasizing the critical role of managing patients' emotional and psychological complexity. Managing decision regret requires acute attention to individual needs and effective communication to mitigate emotional impact and improve patient outcomes. CONCLUSIONS: Insights from a nursing perspective in the analysis of results indicate the need for informed, empathetic, and integrated care that considers the emotional complexity of women with BRCA1 and/or BRCA2 mutations in their lives and health choices.

A qualitative interview study to determine barriers and facilitators of implementing automated decision support tools for genomic data access.

Data access committees (DAC) gatekeep access to secured genomic and related health datasets yet are challenged to keep pace with the rising volume and complexity of data generation. Automated decision support (ADS) systems have been shown to support consistency, compliance, and coordination of data access review decisions. However, we lack understanding of how DAC members perceive the value add of ADS, if any, on the quality and effectiveness of their reviews. In this qualitative study, we report findings from 13 semi-structured interviews with DAC members from around the world to identify relevant barriers and facilitators to implementing ADS for genomic data access management. Participants generally supported pilot studies that test ADS performance, for example in cataloging data types, verifying user credentials and tagging datasets for use terms. Concerns related to over-automation, lack of human oversight, low prioritization, and misalignment with institutional missions tempered enthusiasm for ADS among the DAC members we engaged. Tensions for change in institutional settings within which DACs operated was a powerful motivator for why DAC members considered the implementation of ADS into their access workflows, as well as perceptions of the relative advantage of ADS over the status quo. Future research is needed to build the evidence base around the comparative effectiveness and decisional outcomes of institutions that do/not use ADS into their workflows.

Value contribution of blood-based neurofilament light chain as a biomarker in multiple sclerosis using multi-criteria decision analysis.

Introduction: Multiple sclerosis (MS) is a chronic autoimmune demyelinating disease that represents a leading cause of non-traumatic disability among young and middle-aged adults. MS is characterized by neurodegeneration caused by axonal injury. Current clinical and radiological markers often lack the sensitivity and specificity required to detect inflammatory activity and neurodegeneration, highlighting the need for better approaches. After neuronal injury, neurofilament light chains (NfL) are released into the cerebrospinal fluid, and eventually into blood. Thus, blood-based NfL could be used as a potential biomarker for inflammatory activity, neurodegeneration, and treatment response in MS. The objective of this study was to determine the value contribution of blood-based NfL as a biomarker in MS in Spain using the Multi-Criteria Decision Analysis (MCDA) methodology. Materials and methods: A literature review was performed, and the results were synthesized in the evidence matrix following the criteria included in the MCDA framework. The study was conducted by a multidisciplinary group of six experts. Participants were trained in MCDA and scored the evidence matrix. Results were analyzed and discussed in a group meeting through reflective MCDA discussion methodology. Results: MS was considered a severe condition as it is associated with significant disability. There are unmet needs in MS as a disease, but also in terms of biomarkers since no blood biomarker is available in clinical practice to determine disease activity, prognostic assessment, and response to treatment. The results of the present study suggest that quantification of blood-based NfL may represent a safe option to determine inflammation, neurodegeneration, and response to treatments in clinical practice, as well as to complement data to improve the sensitivity of the diagnosis. Participants considered that blood-based NfL could result in a lower use of expensive tests such as magnetic resonance imaging scans and could provide cost-savings by avoiding ineffective treatments. Lower indirect costs could also be expected due to a lower impact of disability consequences. Overall, blood-based NfL measurement is supported by high-quality evidence. Conclusion: Based on MCDA methodology and the experience of a multidisciplinary group of six stakeholders, blood-based NfL measurement might represent a high-value-option for the management of MS in Spain.

The impact of decision tools during oncological consultation with lung cancer patients: A systematic review within the I3LUNG project.

INTRODUCTION: To date, lung cancer is one of the most lethal diagnoses worldwide. A variety of lung cancer treatments and modalities are available, which are generally presented during the patient and doctor consultation. The implementation of decision tools to facilitate patient's decision-making and the management of their healthcare process during medical consultation is fundamental. Studies have demonstrated that decision tools are helpful to promote health management and decision-making of lung cancer patients during consultations. The main aim of the present work within the I3LUNG project is to systematically review the implementation of decision tools to facilitate medical consultation about oncological treatments for lung cancer patients. METHODS: In the present study, we conducted a systematic review following the PRISMA guidelines. We used an electronic computer-based search involving three databases, as follows: Embase, PubMed, and Scopus. 10 articles met the inclusion criteria and were included. They explicitly refer to decision tools in the oncological context, with lung cancer patients. RESULTS: The discussion highlights the most encouraging results about the positive role of decision aids during medical consultations about oncological treatments, especially regarding anxiety, decision-making, and patient knowledge. However, no one main decision aid tool emerged as essential. Opting for a more recent timeframe to select eligible articles might shed light on the current array of decision aid tools available. CONCLUSION: Future review efforts could utilize alternative search strategies to explore other lung cancer-specific outcomes during medical consultations for treatment decisions and the implementation of decision aid tools. Engaging with experts in the fields of oncology, patient decision-making, or health communication could provide valuable insights and recommendations for relevant literature or research directions that may not be readily accessible through traditional search methods. The development of guidelines for future research were provided with the aim to promote decision aids focused on patients' needs.

Development of a patient decision aid for children and adolescents following anterior cruciate ligament rupture: an international mixed-methods study.

AIM: To develop and user test an evidence-based patient decision aid for children and adolescents who are considering anterior cruciate ligament (ACL) reconstruction. DESIGN: Mixed-methods study describing the development of a patient decision aid. SETTING: A draft decision aid was developed by a multidisciplinary steering group (including various types of health professionals and researchers, and consumers) informed by the best available evidence and existing patient decision aids. PARTICIPANTS: People who ruptured their ACL when they were under 18 years old (ie, adolescents), their parents, and health professionals who manage these patients. Participants were recruited through social media and the network outreach of the steering group. PRIMARY AND SECONDARY OUTCOMES: Semistructured interviews and questionnaires were used to gather feedback on the decision aid. The feedback was used to refine the decision aid and assess acceptability. An iterative cycle of interviews, refining the aid according to feedback and further interviews, was used. Interviews were analysed using reflexive thematic analysis. RESULTS: We conducted 32 interviews; 16 health professionals (12 physiotherapists, 4 orthopaedic surgeons) and 16 people who ruptured their ACL when they were under 18 years old (7 were adolescents and 9 were adults at the time of the interview). Parents participated in 8 interviews. Most health professionals, patients and parents rated the aid's acceptability as good-to-excellent. Health professionals and patients agreed on most aspects of the decision aid, but some health professionals had differing views on non-surgical management, risk of harms, treatment protocols and evidence on benefits and harms. CONCLUSION: Our patient decision aid is an acceptable tool to help children and adolescents choose an appropriate management option following ACL rupture with their parents and health professionals. A clinical trial evaluating the potential benefit of this tool for children and adolescents considering ACL reconstruction is warranted.

Challenges and Opportunities in Interdisciplinary Research and Real-World Data for Treatment Sequences in Health Technology Assessments.

With an ever-increasing number of treatment options, the assessment of treatment sequences has become crucial in health technology assessment (HTA). This review systematically explores the multifaceted challenges inherent in evaluating sequences, delving into their interplay and nuances that go beyond economic model structures. We synthesised a 'roadmap' of literature from key methodological studies, highlighting the evolution of recent advances and emerging research themes. These insights were compared against HTA guidelines to identify potential avenues for future research. Our findings reveal a spectrum of challenges in sequence evaluation, encompassing selecting appropriate decision-analytic modelling approaches and comparators, deriving appropriate clinical effectiveness evidence in the face of data scarcity, scrutinising effectiveness assumptions and statistical adjustments, considering treatment displacement, and optimising model computations. Integrating methodologies from diverse disciplines-statistics, epidemiology, causal inference, operational research and computer science-has demonstrated promise in addressing these challenges. An updated review of application studies is warranted to provide detailed insights into the extent and manner in which these methodologies have been implemented. Data scarcity on the effectiveness of treatment sequences emerged as a dominant concern, especially because treatment sequences are rarely compared in clinical trials. Real-world data (RWD) provide an alternative means for capturing evidence on effectiveness and future research should prioritise harnessing causal inference methods, particularly Target Trial Emulation, to evaluate treatment sequence effectiveness using RWD. This approach is also adaptable for analysing trials harbouring sequencing information and adjusting indirect comparisons when collating evidence from heterogeneous sources. Such investigative efforts could lend support to reviews of HTA recommendations and contribute to synthesising external control arms involving treatment sequences.

Validation of the BCIS CHIP Score in chronic total occlusion percutaneous coronary intervention.

BACKGROUND: The complex high-risk indicated percutaneous coronary intervention (CHIP) score is a tool developed using the British Cardiovascular Intervention Society (BCIS) database to define CHIP cases and predict in-hospital major adverse cardiac or cerebrovascular events (MACCE). AIM: To assess the validity of the CHIP score in chronic total occlusion (CTO) percutaneous coronary intervention (PCI). METHODS: We evaluated the performance of the CHIP score on 8341 CTO PCIs from the Prospective Global Registry for the Study of Chronic Total Occlusion Intervention (PROGRESS-CTO) performed at 44 centers between 2012 and 2023. RESULTS: In our cohort, 7.8% (n = 647) of patients had a CHIP score of 0, 50.2% (n = 4192) had a CHIP score of 1-2, 26.2% (n = 2187) had a CHIP score of 3-4, 11.7% (n = 972) had a CHIP score of 5-6, 3.3% (n = 276) had a CHIP score of 7-8, and 0.8% (n = 67) had a CHIP score of 9+. The incidence of MACCE for a CHIP score of 0 was 0.6%, reaching as high as 8.7% for a CHIP score of 9+, confirming that a higher CHIP score is associated with a higher risk of MACCE. The estimated increase in the risk of MACCE per one score unit increase was 100% (95% confidence interval [CI]: 65%-141%). The AUC of the CHIP score model for predicting MACCE in our cohort was 0.63 (95% CI: 0.58-0.67). There was a positive correlation between the CHIP score and the PROGRESS-CTO MACE score (Spearman's correlation: 0.37; 95% CI: 0.35-0.39; p < 0.001). CONCLUSIONS: The CHIP score has modest predictive capacity for MACCE in CTO PCI.

On subjective measures of decision quality.

In times of person-centered care, it is all the more important to support patients in making good decisions about their care. One way to offer such support to patients is by way of Patient Decision Aids (PDAs). Ranging from patient brochures to web-based tools, PDAs explicitly state the decisions patients face, inform them about their medical options, help them to clarify and discuss their values, and ultimately make a decision. However, lingering discussions surround effectiveness research on PDAs. In this article, I focus on two subjective measures of decision quality that are widely used as outcome measures in effectiveness research on PDAs (i.e., the Decisional Conflict Scale (DCS) and measures of regret). Although these measurement instruments have attracted critical attention in the scientific literature, bioethicists have hardly engaged with them. Therefore, I set myself to analyze the relationship between (the different subscales of) the DCS and measures of regret, on the one hand, and ethical principles such as beneficence and autonomy, on the other hand. In light of that analysis, I will clarify some discussions regarding the use of these measures of decision quality in effectiveness research on PDAs. This should help us to align the way we evaluate PDAs with ethical principles and avoid that our attempts to support patients in making good decisions about their care that is so central to person-centered care point in unethical directions.

Value of Information for Clinical Trial Design: The Importance of Considering All Relevant Comparators.

Value of Information (VOI) analyses calculate the economic value that could be generated by obtaining further information to reduce uncertainty in a health economic decision model. VOI has been suggested as a tool for research prioritisation and trial design as it can highlight economically valuable avenues for future research. Recent methodological advances have made it increasingly feasible to use VOI in practice for research; however, there are critical differences between the VOI approach and the standard methods used to design research studies such as clinical trials. We aimed to highlight key differences between the research design approach based on VOI and standard clinical trial design methods, in particular the importance of considering the full decision context. We present two hypothetical examples to demonstrate that VOI methods are only accurate when (1) all feasible comparators are included in the decision model when designing research, and (2) all comparators are retained in the decision model once the data have been collected and a final treatment recommendation is made. Omitting comparators from either the design or analysis phase of research when using VOI methods can lead to incorrect trial designs and/or treatment recommendations. Overall, we conclude that incorrectly specifying the health economic model by ignoring potential comparators can lead to misleading VOI results and potentially waste scarce research resources.

Application of Multi-Criteria Decision Analysis (MCDA) to Prioritize Real-World Evidence Studies for Health Technology Management: Outcomes and Lessons Learned by the Canadian Real-World Evidence for Value of Cancer Drugs (CanREValue) Collaboration.

Multi-criteria decision analysis (MCDA) is a value assessment tool designed to help support complex decision-making by incorporating multiple factors and perspectives in a transparent, structured approach. We developed an MCDA rating tool, consisting of seven criteria evaluating the importance and feasibility of conducting potential real-world evidence (RWE) studies aimed at addressing uncertainties stemming from initial cancer drug funding recommendations. In collaboration with the Canadian Agency for Drugs and Technologies in Health's Provincial Advisory Group, a validation exercise was conducted to further evaluate the application of the rating tool using RWE proposals varying in complexity. Through this exercise, we aimed to gain insight into consensus building and deliberation processes and to identify efficiencies in the application of the rating tool. An experienced facilitator led a multidisciplinary committee, consisting of 11 Canadian experts, through consensus building, deliberation, and prioritization. A total of nine RWE proposals were evaluated and prioritized as low (n = 4), medium (n = 3), or high (n = 2) priority. Through an iterative process, efficiencies and recommendations to improve the rating tool and associated procedures were identified. The refined MCDA rating tool can help decision-makers prioritize important and feasible RWE studies for research and can enable the use of RWE for the life-cycle evaluation of cancer drugs.

Decision analysis of PPP project's parties based on deep consumer participation.

Although PPP(Public-private partnership) mode has been applied for a long time in infrastructural project, the success rate is not very high. The sustainability of PPP projects is still influenced by many factors. In order to examine the evolutionary stable strategies (ESSs) of social capital, government, and paying consumers, a tripartite evolutionary game model is established in this work. In order to further promote consumer participation, it is necessary to make the assumption that customer oversight and review can have an impact on service prices. The results show: i)The strategy choice of consumer depends on the comparison between supervision cost of consumer and price coefficient for consumer to social capital. ii)Consumer supervision can promote the provision of high-quality services by social capital. iii)The difference between high-quality cost and low-quality cost, subsidy coefficient, price coefficient and supervision cost of consumer are critical factors influencing both evolutionary results and trajectories. This paper also puts forward policy implications for the three stakeholders to promote social capital's high-quality strategy so as to maintain the sustainability of PPP projects.

Preliminary testing of "roadmap to parenthood" decision aid and planning tool for family building after cancer: Results of a single-arm pilot study.

OBJECTIVE: Many young adult female cancer survivors need to use reproductive medicine, surrogacy, or adoption to have a child. This study pilot tested Roadmap to Parenthood, a web-based, self-guided decision aid and planning tool for family building after cancer (disease agnostic). METHODS: A single-arm pilot study tested feasibility, acceptability, and obtained effect size estimates of the Roadmap tool. Participants, recruited via hospital-based and social media strategies, completed a baseline survey (T1), accessed the Roadmap tool (website), then completed surveys at one- and 3-months (T2 and T3, respectively). Feasibility and acceptability were evaluated with rates of eligibility, enrollment, and survey completion, and feedback. Pairwise t-tests and repeated measures ANOVA evaluated usage effects. Effect size estimates were calculated. RESULTS: Participants (N = 98) averaged 31 years old (SD = 5.61); 71% were nulliparous. Enrollment rate was 73%, T1-T2 completion rate was 80%, and 93% accessed the website. From T1-T2, participants reported improvements in decisional conflict (p < 0.001; Cohen's d = 0.85), unmet information needs (p < 0.001; Cohen's d = 0.70), self-efficacy (p = 0.003; Cohen's d = 0.40), and self-efficacy for managing negative emotions (p = 0.03; Cohen's d = 0.29); effects were sustained at T3. There was no change in reproductive distress (p = 0.22). By T3, 94% reported increased consideration of preparatory actions and 20%-61% completed such actions. CONCLUSIONS: The Roadmap intervention was feasible to conduct, acceptable to users, and led to improvements in key psychosocial outcomes. Future directions will test intervention efficacy in a randomized controlled trial with a larger sample and over a longer period. A web-based tool may help women make decisions about family building after cancer and prepare for potential challenges.

Design of a multiple criteria decision analysis framework for prioritizing high-impact health technologies in a regional health service.

OBJECTIVES: This study aims to develop a framework for establishing priorities in the regional health service of Murcia, Spain, to facilitate the creation of a comprehensive multiple criteria decision analysis (MCDA) framework. This framework will aid in decision-making processes related to the assessment, reimbursement, and utilization of high-impact health technologies. METHOD: Based on the results of a review of existing frameworks for MCDA of health technologies, a set of criteria was proposed to be used in the context of evaluating high-impact health technologies. Key stakeholders within regional healthcare services, including clinical leaders and management personnel, participated in a focus group (n = 11) to discuss the proposed criteria and select the final fifteen. To elicit the weights of the criteria, two surveys were administered, one to a small sample of healthcare professionals (n = 35) and another to a larger representative sample of the general population (n = 494). RESULTS: The responses obtained from health professionals in the weighting procedure exhibited greater consistency compared to those provided by the general public. The criteria more highly weighted were "Need for intervention" and "Intervention outcomes." The weights finally assigned to each item in the multicriteria framework were derived as the equal-weighted sum of the mean weights from the two samples. CONCLUSIONS: A multi-attribute function capable of generating a composite measure (multicriteria) to assess the value of high-impact health interventions has been developed. Furthermore, it is recommended to pilot this procedure in a specific decision context to evaluate the efficacy, feasibility, usefulness, and reliability of the proposed tool.

Impacts of decision support systems on cognition and performance for intelligence-gathering path planning.

Decision Support Systems (DSS) are tools designed to help operators make effective choices in workplace environments where discernment and critical thinking are required for effective performance. Path planning in military operations and general logistics both require individuals to make complex and time-sensitive decisions. However, these decisions can be complex and involve the synthesis of numerous tradeoffs for various paths with dynamically changing conditions. Intelligence collection can vary in difficulty, specifically in terms of the disparity between locations of interest and timing restrictions for when and how information can be collected. Furthermore, plans may need to be changed adaptively mid-operation, as new collection requirements appear, increasing task difficulty. We tested participants in a path planning decision-making exercise with scenarios of varying difficulty in a series of two experiments. In the first experiment, each map displayed two paths simultaneously, relating to two possible routes for the two available trucks. Participants selected the optimal path plan, representing the best solution across multiple routes. In the second experiment, each map displayed a single path, and participants selected the best two paths sequentially. In the first experiment, utilizing the DSS was predictive of adoption of more heuristic decision strategies, and that strategic approach yielded more optimal route selection. In the second experiment, there was a direct effect of the DSS on increased decision performance and a decrease in perceived task workload.

Assessment of nomogram model for the prediction of esophageal variceal hemorrhage in hepatitis B-induced hepatic cirrhosis.

BACKGROUND: Esophageal variceal (EV) hemorrhage is a life-threatening consequence of portal hypertension in hepatitis B virus (HBV) -induced cirrhotic patients. Screening upper endoscopy and endoscopic variceal ligation to find EVs for treatment have complications, contraindications, and high costs. We sought to identify the nomogram models (NMs) as alternative predictions for the risk of EV hemorrhage. METHODS: In this case-control study, we retrospectively analyzed 241 HBV-induced liver cirrhotic patients treated for EVs at the Second People's Hospital of Fuyang City, China from January 2021 to April 2023. We applied univariate analysis and multivariate logistic regression to assess the accuracy of various NMs in EV hemorrhage. The area under the curve (AUC) and calibration curves of the receiver's operating characteristics were used to evaluate the predictive accuracy of the nomogram. Decision curve analysis (DCA) was used to determine the clinically relevant of nomograms. RESULTS: In the prediction group, multivariate logistic regression analysis identified platelet distribution and spleen length as independent risk factors for EVs. We applied NMs as the independent risk factors to predict EVs risk. The NMs fit well with the calibration curve and have good discrimination ability. The AUC and DCA demonstrated that NMs with a good net benefit. The above results were validated in the validation cohort. CONCLUSION: Our non-invasive NMs based on the platelet distribution width and spleen length may be used to predict EV hemorrhage in HBV-induced cirrhotic patients. NMs can help clinicians to increase diagnostic performance leading to improved treatment measures.