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.

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.

Cost-effectiveness analysis of once-weekly semaglutide vs. once-daily liraglutide administered subcutaneously in patients with overweight and obesity: a decision analysis.

OBJECTIVE: Obesity presents an enduring and multifaceted dilemma that impacts individuals, society, economies, and healthcare systems alike. Glucagon-like peptide-1 (GLP-1) receptor agonists, including liraglutide and semaglutide, have received FDA approval for obesity treatment. This study aims to present a cost-effectiveness analysis to compare the cost and clinical outcomes of semaglutide vs. liraglutide on weight loss in people with overweight and obesity. MATERIALS AND METHODS: A cost-effectiveness analysis was conducted to compare the cost and the clinical outcomes of adding weekly 2.4 mg SC semaglutide vs. daily 3.0 mg SC liraglutide or placebo to physical activity and diet control in overweight and obese patients. A clinical outcome of achieving ≥15% weight loss was chosen. A simple decision analysis model from a third-payer perspective was applied. Drug costs were based on the retail price of the USA market. One-way sensitivity analyses were performed. RESULTS: Results showed that 2.4 mg weekly semaglutide, when added to physical activity and diet control, was the most cost-effective choice in terms of ≥15% weight loss (ICER: $ 7,056/patient/68 weeks). The model was robust against the 50% increase in the unit cost of semaglutide and the 50% decrease in the unit cost of liraglutide, as well as the changes in probabilities by the corresponding 95% confidence intervals across the model. CONCLUSIONS: This cost-effectiveness analysis suggests that employing once-weekly 2.4 mg semaglutide emerges as a remarkably cost-effective option when contrasted with once-daily 3.0 mg liraglutide in patients with overweight and obesity when added to physical activity and diet control.

An interactive, online decision aid assessing patient goals and preferences for treatment of aortic stenosis to support physician-led shared decision-making: Early feasibility pilot study.

BACKGROUND: Guidelines recommend shared decision making when choosing treatment for severe aortic stenosis but implementation has lagged. We assessed the feasibility and impact of a novel decision aid for severe aortic stenosis at point-of-care. METHODS: This prospective multi-site pilot cohort study included adults with severe aortic stenosis and their clinicians. Patients were referred by their heart team when scheduled to discuss treatment options. Outcomes included shared decision-making processes, communication quality, decision-making confidence, decisional conflict, knowledge, stage of decision making, decision quality, and perceptions of the tool. Patients were assessed at baseline (T0), after using the intervention (T1), and after the clinical encounter (T2); clinicians were assessed at T2. Before the encounter, patients reviewed the intervention, Aortic Valve Improved Treatment Approaches (AVITA), an interactive, online decision aid. AVITA presents options, frames decisions, clarifies patient goals and values, and generates a summary to use with clinicians during the encounter. RESULTS: 30 patients (9 women [30.0%]; mean [SD] age 70.4 years [11.0]) and 14 clinicians (4 women [28.6%], 7 cardiothoracic surgeons [50%]) comprised 28 clinical encounters Most patients [85.7%] and clinicians [84.6%] endorsed AVITA. Patients reported AVITA easy to use [89.3%] and helped them choose treatment [95.5%]. Clinicians reported the AVITA summary helped them understand their patients' values [80.8%] and make values-aligned recommendations [61.5%]. Patient knowledge significantly improved at T1 and T2 (p = 0.004). Decisional conflict, decision-making stage, and decision quality improved at T2 (p = 0.0001, 0.0005, and 0.083, respectively). Most patients [60%] changed treatment preference between T0 and T2. Initial treatment preferences were associated with low knowledge, high decisional conflict, and poor decision quality; final preferences were associated with high knowledge, low conflict, and high quality. CONCLUSIONS: AVITA was endorsed by patients and clinicians, easy to use, improved shared decision-making quality and helped patients and clinicians arrive at a treatment that reflected patients' values. TRIAL REGISTRATION: Trial ID: NCT04755426, Clinicaltrials.gov/ct2/show/NCT04755426.

[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.

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.

From Trendelenburg to PERTs: Evolution in the Management of Massive Pulmonary Embolism.

Massive pulmonary embolism (MPE) is a serious condition affecting the pulmonary arteries and is difficult to diagnose, triage, and treat. The American College of Chest Physicians (AHA) and the European Society of Cardiology (ESC) have different classification approaches for PE, with the AHA defining three subtypes and the ESC four. Misdiagnosis is common, leading to delayed or inadequate treatment. The incidence of PE-related death rates has been increasing over the years, and mortality rates vary depending on the subtype of PE, with MPE having the highest mortality rate. The current definition of MPE originated from early surgical embolectomy cases and discussions among experts. However, this definition fails to capture patients at the point of maximal benefit because it is based on late findings of MPE. Pulmonary Embolism Response Teams (PERTs) have emerged as a fundamental shift in the management of MPE, with a focus on high-risk and MPE cases and a goal of rapidly connecting patients with appropriate therapies based on up-to-date evidence. This review highlights the challenges in diagnosing and managing MPE and emphasizes the importance of PERTs and risk stratification scores in improving outcomes for patients with PE.

Pulmonary Embolism Triage: When to Do What.

Anticoagulation has been the standard therapy for treating pulmonary embolism. However, newly developed pharmacological and interventional treatment options have been shown to provide benefit for certain patient populations, depending on how they present. This column highlights the use of massive pulmonary embolism risk stratification in determining the presence of cor pulmonale and offers several key points to remember when caring for patients with a pulmonary embolism.

Coronary artery disease severity and risk stratification of patients with non ST-elevation acute coronary syndrome using CHA2DS2-VASc-HSF score.

BACKGROUND: Risk stratification assessment of patients with non-ST elevation acute coronary syndrome (NSTE ACS) plays an important role in optimal management and defines the patient's prognosis. This study aimed to evaluate the ability of CHA2DS2-VASc-HSF score (comprising of the components of the CHA2DS2-VASc score with a male instead of female sex category, hyperlipidemia, smoking, and family history of coronary artery disease respectively) to predict the severity and complexity of CAD and its efficacy in stratification for major adverse cardiovascular events (MACE) in patients with NSTE ACS without known atrial fibrillation. METHODS: This study included 200 patients (males 72.5%, mean age 55.8 ± 10.1 years) who were admitted with NSTE ACS. CHA2DS2-VASC-HSF score was calculated on admission. Patients were classified into three groups according to their CHA2DS2-VASC-HSF score: low score group (< 2; 29 patients), intermediate score group (2-4; 83 patients), and high score group (≥ 5; 88 patients). Coronary angiography was conducted and the Syntax score (SS) was calculated. Clinical follow-up at 6 months of admission for the development of MACE was recorded. RESULTS: SS was significantly high in the high CHA2DS2-VASc-HSF score group compared with low and intermediate score groups. CHA2DS2-VASc-HSF score had a significant positive strong correlation with syntax score (r = 0.64, P < 0.001). Smoking, vascular disease, hyperlipidemia, and CHA2DS2-VASc-HSF score were independent predictors of high SS. For the prediction of severe and complex CAD, CHA2DS2-VASc-HSF score had a good predictive power at a cut-off value ≥ 5 with a sensitivity of 86% and specificity of 65%. Hypertension, vascular disease, high SS, and CHA2DS2-VASc-HSF score were independent predictors of MACE. CHA2DS2-VASC-HSF score ≥ 4 was identified as an effective cut-off point for the development of MACE with 94% sensitivity and 70% specificity. CONCLUSIONS: CHA2DS2-VASC-HSF score is proposed to be a simple bedside score that could be used for the prediction of the severity and complexity of CAD as well as a risk stratification tool for the development of MACE in NSTE ACS patients.

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.

Shared Decision Making in Oncology and Its Implementation in Cervical Cancer Management in the Philippines: A Narrative Review.

PURPOSE: Shared decision making (SDM) is an approach where clinicians and patients make decisions together using the best available evidence. Although much studied, recognized to be ethically imperative, and recommended in international health policies, it remains poorly implemented. In the Philippines, there are limited studies on patient decision making preferences and SDM. Practical guidance on the implementation of SDM or use of patient decision aids (PtDAs) is often not detailed in existing national clinical practice guidelines in oncology. METHODS: We performed a systematic search of Philippine literature on SDM in oncology and an iterative review of international literature on the philosophy and methods of SDM, the utility and effectiveness of PtDAs, and the facilitators and barriers to implementation or usage. We contextualized our review to the cervical cancer management and health service delivery in the Philippines. RESULTS: Local literature is limited to five scientific publications and two registered studies. International literature encompasses patient decisional preferences, the role of PtDAs and the standards for their development and evaluation, their effectiveness, and barriers and facilitators to their use in cancer-related decision making. We discussed the implications on the management of cervical cancer in the Philippines, challenges in health service delivery and standards, and SDM research. CONCLUSION: Local SDM research is limited. Our preliminary experience in a multicenter clinical trial in Manila on PtDA use in the framework of SDM in cervical cancer suggest good patient and clinician acceptability. Challenges to implementation such as unfavorable financial situations, urgency of clinical decisions, low patient or caregiver educational attainment, and poor integration of multidisciplinary and SDM in organizational workflows will be important when implementing SDM in different settings.

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.

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.

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.

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.

Multi-criteria decision analysis: technique for order of preference by similarity to ideal solution for selecting greener analytical method in the determination of mifepristone in environmental water samples.

This work proposes the use of multi-criteria decision analysis (MCDA) to select a more environmentally friendly analytical procedure. TOPSIS, which stands for Technique for Order of Preference by Similarity to Ideal Solution, is an example of a MCDA method that may be used to rank or select best alternative based on various criteria. Thirteen analytical procedures were used in this study as TOPSIS input choices for mifepristone determination in water samples. The input data, which consisted of these choices, was described using assessment criteria based on 12 principles of green analytical chemistry (GAC). Based on the objective mean weighting (MW), the weights for each criterion were assigned equally. The most preferred analytical method according to the ranking was solid phase extraction with micellar electrokinetic chromatography (SPE-MEKC), while solid phase extraction combined with ultra-high performance liquid chromatography tandem mass spectrometry (SPE-UHPLC-MS/MS) was ranked last. TOPSIS ranking results were also compared to the green metrics NEMI, Eco-Scale, GAPI, AGREE, and AGREEprep that were used to assess the greenness of thirteen analytical methods for mifepristone determination. The results demonstrated that only the AGREE metric tool correlated with TOPSIS; however, there was no correlation with other metric tools. The analysis results suggest that TOPSIS is a very useful tool for ranking or selecting the analytical procedure in terms of its greenness and that it can be easily integrated with other green metrics tools for method greenness assessment.

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.