Medical decision making

PURPOSE: Management reasoning is a distinct subset of clinical reasoning. We sought to explore features to be considered when designing assessments of management reasoning. METHODS: This is a hybrid empirical research study, narrative review, and expert perspective. In 2021, we reviewed and discussed 10 videos of simulated (staged) physician-patient encounters, actively seeking actions that offered insights into assessment of management reasoning. We analyzed our own observations in conjunction with literature on clinical reasoning assessment, using a constant comparative qualitative approach...

INTRODUCTION: An important obstacle in the fight against diabetic retinopathy (DR) is the use of a classification system based on old imaging techniques and insufficient data to accurately predict its evolution. New imaging techniques generate new valuable data, but we lack an adapted classification based on these data. The main objective of the Evaluation Intelligente de la Rétinopathie Diabétique, Intelligent evaluation of DR (EviRed) project is to develop and validate a system assisting the ophthalmologist in decision-making during DR follow-up by improving the prediction of its evolution...

UNLABELLED: OObjective: Prognostic models aid clinical practice with decision-making on treatment and hospitalization in exacerbation of chronic obstructive lung disease (ECOPD). Although there are many studies with prognostic models, diagnostic accuracy is variable within and between models. SUBJECTS AND METHODS: We compared prognostic performance of the BAP65 score, DECAF score, PEARL score and modified early warning score (MEWS) in hospitalized patients with ECOPD, to estimate ventilatory support need...

Information may be required within a short time-frame for making decisions about programmes and interventions in health professions education. Rapid research methods have been increasingly used in healthcare, especially for qualitative research studies and literature reviews. An essential aspect of using rapid research methods is pragmatism, in which there is a balance between the constraints of the short time frame (typically less than 3 months), the available resources, and the rigour for an appropriate standard of quality...

Evaluating the rehabilitation status of individuals with serious mental illnesses (SMI) necessitates a comprehensive analysis of multimodal data, including unstructured text records and structured diagnostic data. However, progress in the effective assessment of rehabilitation status remains limited. Our study develops a deep learning model integrating Bidirectional Encoder Representations from Transformers (BERT) and TabNet through a late fusion strategy to enhance rehabilitation prediction, including referral risk, dangerous behaviors, self-awareness, and medication adherence, in patients with SMI...

Expanding loco-regional nodes harvesting is expected to increase survival. This improvement may be associated to stage migration (SM). However, the great bulk of harvested lymph nodes observed in large dissections is negative. M&M: 830 patients who received R0 gastrectomy for adenocarcinoma were included. pN+ patients with <26 nodes (n = 209) were included for a simulation to "offer 26 nodes" - SM (proportional and exponential based) was simulated and analysed through machine learning algorithms...

Though assumptions about language underlie all bioethical work, the field has rarely partaken of theories of language. This article encourages a more linguistically engaged bioethics. We describe the tacit conception of language that is frequently upheld in bioethics-what we call the representational view , which sees language essentially as a means of description. We examine how this view has routed the field's theories and interventions down certain paths. We present an alternative model of language-the pragmatic view -and explore how it expands and clarifies traditional bioethical concerns...

Aiming at early detection and accurate prediction of cardiovascular disease (CVD) to reduce mortality rates, this study focuses on the development of an intelligent predictive system to identify individuals at risk of CVD. The primary objective of the proposed system is to combine deep learning models with advanced data mining techniques to facilitate informed decision-making and precise CVD prediction. This approach involves several essential steps, including the preprocessing of acquired data, optimized feature selection, and disease classification, all aimed at enhancing the effectiveness of the system...

Covid-19 has challenged health systems around the world and increased the global competition for medical professionals. This article investigates if the pandemic and its management became an important push factor influencing the migration intentions of medical students and junior doctors and how this factor compared in importance to others. A mixed methods study-a survey and in-depth interviews-was conducted with final-year students at public medical universities in Poland, a country already suffering from a significant emigration of medical staff...

Interpersonal communication facilitates symptom measures of autistic sociability to enhance clinical decision-making in identifying children with autism spectrum disorder (ASD). Traditional methods are carried out by clinical practitioners with assessment scales, which are subjective to quantify. Recent studies employ engineering technologies to analyze children's behaviors with quantitative indicators, but these methods only generate specific rule-driven indicators that are not adaptable to diverse interaction scenarios...

BACKGROUND: People seeking abortion in early pregnancy have the choice between medication and procedural options for care. The choice is preference-sensitive-there is no clinically superior option and the choice depends on what matters most to the individual patient. Patient decision aids (PtDAs) are shared decision-making tools that support people in making informed, values-aligned health care choices. OBJECTIVE: We aimed to develop and evaluate the usability of a web-based PtDA for the Canadian context, where abortion care is publicly funded and available without legal restriction...

Researchers and scientists can use computational-based models to turn linked data into useful information, aiding in disease diagnosis, examination, and viral containment due to recent artificial intelligence and machine learning breakthroughs. In this paper, we extensively study the role of artificial intelligence and machine learning in delivering efficient responses to the COVID-19 pandemic almost four years after its start. In this regard, we examine a large number of critical studies conducted by various academic and research communities from multiple disciplines, as well as practical implementations of artificial intelligence algorithms that suggest potential solutions in investigating different COVID-19 decision-making scenarios...

Sample surveys are extensively used to provide reliable direct estimates for large areas or domains with enough sample sizes at national and regional levels. However, zones are unplanned domains by the Demographic and Health Survey (DHS) program and need more sample sizes to produce direct survey estimates with adequate precision. Conducting surveys in small areas (like zones) is too expensive and time-consuming, making it unfeasible for developing countries like Ethiopia. Therefore, this study aims to use the Hierarchical Bayes (HB) Small Area Estimation (SAE) model to estimate the Community-Based Health Insurance (CBHI) coverage at the zone levels in Ethiopia...

Sleep apnoea is a common disorder affecting sleep quality by obstructing the respiratory airway. This disorder can also be correlated to certain diseases like stroke, depression, neurocognitive disorder, non-communicable disease, etc. We implemented machine learning techniques for detecting sleep apnoea to make the diagnosis easier, feasible, convenient, and cost-effective. Electrocardiography signals are the main input used here to detect sleep apnoea. The considered ECG signal undergoes pre-processing to remove noise and other artefacts...

INTRODUCTION: Despite substantial research and provision of dental care, significant morbidity remains for children's oral health. Guided by social practice theory (SPT), this research moves away from the often-ineffective focus on changing individual behavior to rethinking the centrality of the social world in promoting or undermining oral health outcomes. We define social practice as a routinized relational activity linking and integrating certain elements (competence, materials, and meanings) into the performance of a practice that is reproduced across time and space...

INTRODUCTION: The 2023 Australian guideline for assessing and managing cardiovascular disease risk provides updated evidence-based recommendations for the clinical assessment and management of cardiovascular disease (CVD) risk for primary prevention. It includes the new Australian CVD risk calculator (Aus CVD Risk Calculator), based on an equation developed from a large New Zealand cohort study, customised and recalibrated for the Australian population. The new guideline replaces the 2012 guideline that recommended CVD risk assessment using the Framingham risk equation...

KEY CLINICAL MESSAGE: Ibuprofen single dose may rarely induce Stevens-Johnson Syndrome, emphasizing the vital need for heightened vigilance in healthcare and public awareness for safer medication practices. ABSTRACT: Stevens-Johnson Syndrome (SJS) is a severe and potentially life-threatening skin disorder associated with certain medications, including ibuprofen. We present a case of a 45-year-old woman who developed SJS following a single dose of ibuprofen. Despite its rarity, this case underscores the importance of heightened vigilance in healthcare and public awareness regarding the potential risks of commonly used medications...

OBJECTIVE: In this short report contributing to the literature on treatment and vaccination adherence, nonadherence was examined from the perspective of decision-making (DM) practice in healthcare. The objective of this study was to survey the rationalities given for treatment nonadherence and their association with DM practice. METHODS: The Ottawa decision Support Framework was used as a theoretical background for the study. Multiple choice and open-text responses indicating nonadherence were drawn from vignette survey data...

Pythagorean cubic fuzzy sets represent an advancement beyond conventional interval-valued Pythagorean sets, integrating the principles of Pythagorean fuzzy sets and interval-valued Pythagorean fuzzy sets. Given the critical significance of distance measures in real-world decision-making and pattern recognition tasks, it is noteworthy that there exists a notable gap in the literature regarding distance measures specifically tailored for Pythagorean cubic fuzzy sets. The objectives of this paper are:•To define novel generalized distance measures between Pythagorean cubic fuzzy sets (PCFSs) to tackle intricate decision-making challenges...

RATIONALE: Alport Syndrome (AS) is a progressive genetic condition characterized by chronic kidney disease (CKD), hearing loss, and eye abnormalities. It is caused by mutations in the genes COL4A3, COL4A4 , and COL4A5 . Heterozygous mutations in COL4A4 and COL4A3 cause autosomal dominant Alport Syndrome (ADAS), and a spectrum of phenotypes ranging from asymptomatic hematuria to CKD, with variable extra-renal features. In the past, heterozygous mutations in these genes were thought to be benign, however recent studies show that about 30% of patients can progress to CKD, and 15% can progress to end stage kidney disease (ESKD)...