Independent Experts Research Articles

Advanced 3D-TEE tools for mitral annular calcification characterisation. Correlation with CT scan

Abstract Background Mitral annular calcification (MAC) is a degenerative process that leads to development of mitral regurgitation (MR). Its presence is associated with worse therapeutic results, due to technical challenges and risk of complications. The precise characterization has gained special importance in recent years. Due to the accuracy of the CT to detect calcium compared to transesophageal echocardiography (TEE), different prognostic scores based on this technique have been proposed. Purpose Our objective was to assess the usefulness of new tools based on 3D-TEE to determine the severity of MAC compared to CT in patients with MR. Methods Between 2019 -2022, patients with severe MR with different degrees of MAC were selected and evaluated by 3D-TEE and CT. Two independent expert observers blindly performed a quantitative standardized characterization of severity (1-10), applying the score proposed by Guerrero et al. based on four parameters: Calcium thickness, radial extension, involvement of trigones and leaflets both by CT (Figure 1, A) and advanced 3D-TEE tools (transillumination/True-Vue (Figure 1, B-C) and multiplanar/iSlice reconstruction (Figure 1, D). The agreement and correlation of both techniques were compared for each of the categories, as well as for the final classification of severity (Mild: 0-3, Moderate: 4-7, Severe 8-10). Results 38 patients were included (Mean age: 80±5.7 years), 76% women. The MAC score measured by TEE was 6.1±0.4 vs. 8±0.4 by CT (p=0.03) with a very good agreement between both techniques estimated by the ICC (r=0.9) with an average difference of 1.2±1.4. Regarding the qualitative estimation, the concordance was good except for the estimation of the of the leaflet’s calcification (Table 1). Conclusions The use of advanced 3D-TEE imaging tools provides an excellent estimation and extension of the severity of MAC compared to CT, slightly overestimating the severity. These tools not only bring qualitative but also quantitative information and could be a first approximation before performing CT. This result highlights the usefulness and necessity of using multimodality imaging in the evaluation of degenerative mitral regurgitation.Figure 1Table 1

The Best Scientific Data for the Establishment of Zonally Linked Management Instruments: International Legal Characteristics

The use of the criterion «best available scientific data» when establishing zonally linked management tools is a reflection of the common practice of their formation. The widespread use of this criterion in numerous regulatory acts and guidance documents is accompanied only by prescriptions for improving the quality, reliability and accessibility of scientific information, without its legal content consolidation. The purpose of the study is to identify the normative content of the criterion «the best available scientific data».The formation of the criterion the «best scientific data available» is associated with the strengthening of environmental cooperation between states and is a reflection of the precautionary principle. When scientific evidence is insufficient and there is a risk of harm, it is necessary to act in accordance with the due care obligation and precautionary requirements.The practice of applying the criterion under study allows us to distinguish its three essential elements: the best nature of data, the scientific nature of data and the availability (availability) of data. The best nature of data is disclosed by the national courts through a number of features: completeness of the information, its proper nature, reliability, taking into account and evaluation of various scientific data. The presence of «minor inaccuracies» does not indicate that the data are not the best. The availability of data implies that authorities should make decisions based on scientific data received by them or presented by the scientific community at the time of decision-making. The best «available» data does not mean the best «possible» data. The authorities are not obliged to produce new scientific data. The scientific nature of data implies the use of appropriate, objective, impartial, transparent, final, interpretable data obtained using appropriate research methods, reflecting any inaccuracies and risks of their use, as well as having passed an independent expert assessment.International and national judicial authorities avoid defining scientific data and consider issues related to the assessment of scientific nature of information through the prism of scientific research requirements.

Diagnostic Accuracy of a Real-Time Host-Protein Testfor Infection.

Determining infection etiology can be difficult because viral and bacterial diseases often manifest similarly. A host protein test that computationally integrates the circulating levels of TNF-related apoptosis-induced ligand, interferon γ-induced protein-10, and C-reactive protein to differentiate between bacterial and viral infection (called MMBV) demonstrated high performance in multiple prospective clinical validation studies. Here, MMBV's diagnostic accuracy is evaluated in febrile children for whom physicians were uncertain about etiology when applied at the physician's discretion. Patients aged 3 months to 18 years were retrospectively recruited (NCT03075111; SPIRIT study; 2014-2017). Emergency department physician's etiological suspicion and certainty level were recorded in a questionnaire at blood-draw. MMBV results are based on predefined score thresholds: viral/non-bacterial etiology (0 ≤ score <35), equivocal (35 ≤ score ≤65), and bacterial or coinfection (65 < score ≤100). Reference standard etiology (bacterial/viral/indeterminate) was adjudicated by 3 independent experts based on all available patient data. Experts were blinded to MMBV. MMBV and physician's etiological suspicion were assessed against the reference standard. Of 3003 potentially eligible patients, the physicians were uncertain about infection etiology for 736 of the cases assigned a reference standard (128 bacterial, 608 viral). MMBV performed with sensitivity 89.7% (96/107; 95% confidence interval 82.4-94.3) and specificity 92.6% (498/538; 95% confidence interval 90.0-94.5), significantly outperforming physician's etiological suspicion (sensitivity 49/74 = 66.2%, specificity 265/368 = 72.0%; P < .0001). MMBV equivocal rate was 12.4% (91/736). MMBV was more accurate in determining etiology compared with physician's suspicion and had high sensitivity and specificity according to the reference standard.

Abstract 275: Hypothesizing After Results are Known (HARKing) in Neurovascular Research Induced by Meeting Abstract Preparation Guidelines

Introduction A “reproducibility crisis” has afflicted the recent medical literature, affecting 75‐89% of major reported findings. An important cause of the inability to replicate results is hypothesizing after the results are known (HARKing): presenting a post hoc hypothesis according with findings as if it were a confirmed a priori hypothesis. Meeting abstract instructions may affect the frequency of HARKing. Methods We tested the hypothesis that, compared with abstract instructions NOT indicating a "hypothesis" should be stated, instructions indicating THAT a "hypothesis" should be stated would increase the proportion of abstracts judged by field content experts to exhibit HARKing. [Hypothesis pre‐registered at AsPredicted.org (#5019)]. We analyzed randomly sampled abstracts from 4 International Stroke Conference (ISC) meeting years with highly forceful (2015), moderately forceful (2017), and non‐forceful (2013 and 2022) requirements for statement of a “hypothesis” in abstract preparation instructions, regardless of whether a hypothesis statement was appropriate (confirmatory science) or inappropriate (exploratory science). Results The 163 abstracts (39 to 43 in each meeting year) equally sampled the 14‐17 ISC topic categories. Explicit “hypothesis” statements were more common in the highly and moderately forceful instruction years (30% and 27%) than in the non‐forceful instruction years (9% and 13%) (p = 0.006). Among the total 32 hypothesis statements, 81% were deemed falsifiable, and 19% non‐falsifiable. None (0%) of hypotheses were stated as pre‐registered prior to study conduct. Overall, 59% (19/32) of the hypothesis statements were adjudicated by two independent content experts as likely to be hypothesizing after the results were known (HARKing). HARKing was more common in the highly and moderately forceful instruction years (20% and 15%) than the non‐forceful instruction years (9% and 3%) (p = 0.03). Conclusion Abstract preparation instructions requiring the use of a hypothesis statement promoted hypothesizing after the results are known, with HARKing present in 1 out of every 5 meeting abstracts. To improve reproducibility of neurovascular research studies, appropriate meeting abstract preparation instructions are desirable, recommending hypothesis statements only for the small proportion of stroke studies that are of confirmatory, rather than exploratory, design.

An Easily Implemented, Inexpensive, Useful Novel Surgical Intern Wellness Initiative

Determine whether use of reflective questions asked on a twice monthly basis is a useful addition to our intern wellness curriculum, with a goal of longitudinal development. Prior studies have demonstrated the use of reflection in processing educational experiences toward professional growth at both the medical student and resident level. During the first year, every 2 weeks, the 13 interns were asked and answered 2 reflective prompts by email. Their responses went to a single faculty member and were then blinded for analysis. The second year of the program, prompts were discussed by participants in a closed group setting. Participation was voluntary. The questions fell into 6 major categories: role expectations, role assessment, role affirmation, role reflection, emotional self-assessment, work-life integration, and boundaries. Thematic analysis of the responses was performed using an inductive approach by 2 independent expert reviewers. Brown General Surgery Residency Program, academic years 2021 to 2022 and 2022 to 2023. Use of reflective questions is a valuable tool as part of an intern wellness curriculum and can be easily implemented. It is inexpensive, does not require a huge time commitment, and is easily adaptable to a program's specific needs. It encourages developing surgeons to recognize and share in their emotions as they encounter the new and stressful experiences inherent in residency and may help to prevent burnout. Sustained participation through the year and robust responses suggest good resident engagement and acceptance of the program.

On the trajectory of discrimination: A meta-analysis and forecasting survey capturing 44 years of field experiments on gender and hiring decisions

A preregistered meta-analysis, including 244 effect sizes from 85 field audits and 361,645 individual job applications, tested for gender bias in hiring practices in female-stereotypical and gender-balanced as well as male-stereotypical jobs from 1976 to 2020. A “red team” of independent experts was recruited to increase the rigor and robustness of our meta-analytic approach. A forecasting survey further examined whether laypeople (n = 499 nationally representative adults) and scientists (n = 312) could predict the results. Forecasters correctly anticipated reductions in discrimination against female candidates over time. However, both scientists and laypeople overestimated the continuation of bias against female candidates. Instead, selection bias in favor of male over female candidates was eliminated and, if anything, slightly reversed in sign starting in 2009 for mixed-gender and male-stereotypical jobs in our sample. Forecasters further failed to anticipate that discrimination against male candidates for stereotypically female jobs would remain stable across the decades.

Development and validation of Ayurveda based assessment scale for anxiety

BackgroundAnxiety scale based on Ayurveda would help Ayurveda physicians to measure and initiate appropriate treatment strategies. ObjectivesThe objective of the study was to develop a clinical assessment scale for anxiety based on Ayurveda science. Materials and methodsAyurveda assessment scale for anxiety (AAA) was developed and subjected to various psychometric evaluations. Patients of generalized anxiety disorder with social phobia (GAD with SP) (n = 31) meeting DSM-IV-TR criteria and age, sex-matched healthy subjects (n = 31) were enrolled from NIMHANS Psychiatry OPD. Two independent Ayurveda experts evaluated both patients and healthy subjects using AAA, Hamilton Anxiety Rating Scale (HARS), and Beck Anxiety Inventory (BAI). Reliability and validity assessments were carried out. The sensitivity to treatment-induced change was evaluated in a randomized controlled clinical trial. 72 patients of GAD with SP meeting DSM-IV-TR criteria, aged between 20 and 55 years, and either sex participated in the study. The duration of intervention was 30 days. The assessments were done through HARS, BAI, Beck Depression Inventory (BDI), AAA and Clinical Global Impression scales (Severity, Improvement, and Efficacy). ResultsThe Interrater reliability was between - good to very good score. Validity of AAA with HARS and BAI was significant (p < 0.001). Scales recorded significant differences when compared between patients and healthy subjects (p < 0.001). AAA also recorded the sensitivity to treatment-induced changes in a randomized controlled study and noted a large effect size (>0.60). ConclusionsThe psychometric properties such as interrater reliability, validity (criteria, convergent, divergent, face) and sensitivity to change of AAA were promising.

Validation of the Georgian version of a Stigma Scale of Epilepsy

IntroductionStigma Scale of Epilepsy (SSE), initially developed in Brazil, is accepted worldwide as a sensitive tool for assessing epilepsy-related stigma. We adapted and validated a Georgian version of SSE. Materials and methodsThe SSE originated in Brazil and was translated into Georgian by three independent experts through forward and backward translation. The final version was generated for validation after handling gross or conceptual inconsistencies between the source and the new format.We used Cronbach's alpha to assess the internal consistency of the Georgian version of SSE. To explore the construct of SSE subscales in the Georgian version, we used principal components and factor analysis. Varimax rotation was applied. The Kaiser-Meyer-Olkin Measure and Bartlett's test of sphericity were employed to assess the sampling adequacy. A probability <0.05 was considered statistically significant. Results87 adults, 32 (37 %) with epilepsy and 55 (63 %) without epilepsy were enrolled. The overall mean score of SSE was 19.5 (SD 10.1; min. 2, max. 53), and the differences between people with [20.7 (SD 8.9; min. 2, max. 53)] and without epilepsy [17.5 (SD 10.4; min. 3, max. 42)] were not statistically significant. Cronbach's alpha for the overall sample was 0.854; for the epilepsy cohort it was 0.876, and for individuals without epilepsy 0.823, indicating good SSE internal consistency. Kaiser-Meyer-Olkin Measure was 0.705 and Bartlett's test of sphericity was 926.2 (df 276; p < 0.001), suggesting acceptable sample adequacy. DiscussionThe Georgian version of the SSE is a valid and reliable measurement tool for assessing epilepsy-related stigma determinants among the country's population.

Organizational and Legal Directions for Improving the Rule-Making Activity of the Cabinet of Ministers of Ukraine

The article substantiates the need for a long-term comprehensive reform of the rule-making activity of the Cabinet of Ministers of Ukraine and the relevant organizational and legal directions of such reform, considering the need to ensure the leading role of the Government in improving the rule-making activity of the executive power, increasing the level of its system, proper planning, close coordination, and effective control. As such organizational and legal directions, the issue of improving the examination of draft government acts and the existing system of monitoring the implementation of government acts, improving the activities of government committees, giving greater weight and significance to public consultations with representatives of interested parties regarding draft acts of the Cabinet of Ministers, as well as the formation of the Public Council at Cabinet of Ministers of Ukraine. Strengthening the influence of government committees would be facilitated by the legislative consolidation of the principles of organizing their activities as working collegial bodies of the Cabinet of Ministers, formed for the preliminary consideration and settlement of disputed positions regarding the projects of legislative acts submitted to the government for consideration.The system of normative acts regulating the monitoring of government decisions could consist of three levels: the upper level – the Regulations of the Cabinet of Ministers of Ukraine, which would contain the initial organizational and legal aspects of such monitoring; medium level in the form of a separate general resolution, which would focus on the original principles and provisions for monitoring the implementation of regulatory and other governmental acts; and primary level in the form of special government decisions regarding the monitoring of individual government documents. The need for more complete provision of free access to information regarding draft government decisions being prepared for the Government’s consideration, their public discussion and independent expert assessment, consideration of their results in draft decisions before their adoption by the Government is substantiated.

Predicting the distribution of Ixodes ricinus and Dermacentor reticulatus in Europe: a comparison of climate niche modelling approaches

BackgroundThe ticks Ixodes ricinus and Dermacentor reticulatus are two of the most important vectors in Europe. Climate niche modelling has been used in many studies to attempt to explain their distribution and to predict changes under a range of climate change scenarios. The aim of this study was to assess the ability of different climate niche modelling approaches to explain the known distribution of I. ricinus and D. reticulatus in Europe.MethodsA series of climate niche models, using different combinations of input data, were constructed and assessed. Species occurrence records obtained from systematic literature searches and Global Biodiversity Information Facility data were thinned to different degrees to remove sampling spatial bias. Four sources of climate data were used: bioclimatic variables, WorldClim, TerraClimate and MODIS satellite-derived data. Eight different model training extents were examined and three modelling frameworks were used: maximum entropy, generalised additive models and random forest models. The results were validated through internal cross-validation, comparison with an external independent dataset and expert opinion.ResultsThe performance metrics and predictive ability of the different modelling approaches varied significantly within and between each species. Different combinations were better able to define the distribution of each of the two species. However, no single approach was considered fully able to capture the known distribution of the species. When considering the mean of the performance metrics of internal and external validation, 24 models for I. ricinus and 11 models for D. reticulatus of the 96 constructed were considered adequate according to the following criteria: area under the receiver-operating characteristic curve > 0.7; true skill statistic > 0.4; Miller’s calibration slope 0.25 above or below 1; Boyce index > 0.9; omission rate < 0.15.ConclusionsThis comprehensive analysis suggests that there is no single ‘best practice’ climate modelling approach to account for the distribution of these tick species. This has important implications for attempts to predict climate-mediated impacts on future tick distribution. It is suggested here that climate variables alone are not sufficient; habitat type, host availability and anthropogenic impacts, not included in current modelling approaches, could contribute to determining tick presence or absence at the local or regional scale.Graphical abstract

3.C. Skills building seminar: Guidance on using natural experiments to evaluate population health interventions

Abstract There has been a substantial increase in the conduct of natural experimental evaluations since original guidance was published. There have been advances in relevant methodologies, greater availability of big datasets, and a rise in demand for ‘what works’ evidence amenable to natural experimental evaluation. Therefore, it is important that researchers, public health practitioners, funders, and users of intervention research are aware of recent developments and of the strengths, weaknesses, and applicability of natural experimental evaluations. Updated and extended guidance has been developed for using natural experiments to evaluate population health interventions. Guidance was developed from three international workshops and an online consultation with researchers, journal editors and end users of natural experimental evaluations. The project was funded by The UK Medical Research Council and the National Institute for Health and Care Research, and the project team comprised researchers with expertise in natural experimental evaluations. The project had a funder-assigned oversight group and an advisory group of independent experts, including researchers and practitioners with experience of commissioning natural experimental evaluations. This updated and extended guidance provides an integrated guide to the use of natural experimental methods to evaluate population health interventions, offering a range of tools to support its use and detailed, evidence-based information for researchers, funders, publishers, and users of evidence. The objective of this skills building seminar is to upskill public health researchers and practitioners on the design and use of natural experimental methods. The seminar will present key aspects of the guidance and provide the opportunity to discuss and explore each aspect. The first presentation will highlight important considerations when designing and planning a natural experimental evaluation and introduce recommendations for planning, commissioning, conducting, and using evidence from natural experimental evaluations. The second presentation will outline the value and roles of qualitative methods, explaining how qualitative evidence strengthens evaluations. There will then be a discussion and collaborative learning session, providing an opportunity for researchers and public health practitioners to share experiences and engage with the guidance. The discussions will be prompted by examples of natural experimental evaluations relevant to the presentations. Key messages • Natural experimental evaluations are valuable for assessing the impacts of population health interventions. • This workshop provides an opportunity to engage with and discuss new guidance, highlighting good practice in the design, planning, conduct and use of evidence from natural experimental evaluations.

Designing and planning natural experimental evaluations with good practice recommendations

Abstract Background There have been significant developments in methods, infrastructure, and data availability for natural experimental evaluations. The rise in the use of natural experimental approaches means it is important that researchers, public health practitioners, funders, and users of intervention research understand the phases involved when designing and planning a natural experimental evaluation and are aware of good practice considerations. Methods Guidance was developed from three international workshops and an online consultation with researchers, journal editors and end users of natural experimental evaluations. The project team comprised researchers with expertise in natural experimental evaluations. The project included an oversight group and an advisory group of independent experts. Results The design and planning of an evaluation involves understanding the definition of a natural experiment, being aware of opportunities for a natural experimental evaluation and the relevance of a systems perspective and mixed methods approaches. The practicalities of planning an evaluation involve assessing the evaluability and feasibility of the evaluation and identifying and involving stakeholders throughout the process. Good practice considerations include understanding the evaluation design and planning processes, engaging stakeholders, and recognising the respective strengths of different analytical approaches. Recommendations for policymakers, public health practitioners and commissioners of evaluations include recognising and using high quality evaluations and incorporating evaluation plans into the implementation of new policies and programmes. Conclusions Understanding the processes involved in designing and planning a natural experimental evaluation are important to successfully conducting and evaluating natural experiment interventions.

Value and roles of qualitative methods in natural experimental evaluations

Abstract Background For natural experimental evaluations that estimate effect sizes of population health interventions, qualitative evidence contributes multiple benefits. Incorporating qualitative methods strengthens natural experimental evaluations, particularly when studying interventions in complex systems, and contributes to minimising evaluation design weaknesses. Methods Guidance was developed from three international workshops and an online consultation with researchers, journal editors and end users of natural experimental evaluations. The project team comprised researchers with expertise in natural experimental evaluations. The project included an oversight group and an advisory group of independent experts, including researchers, a journal editor, and scientific and public health advisors on central and local government. Results The guidance recommends that most evaluations of natural experiments will require the inclusion of qualitative evidence. Qualitative methods are valuable when describing the natural experiment intervention, the system and context it exists within, and theories of change. Qualitative work can help appropriately define exposed and unexposed groups, investigate causal mechanisms, facilitate meaningful selection of outcomes, and understand stakeholder perspectives on the intervention and its effects. Conclusions Gaining an understanding of the value and application of qualitative evidence will help producers and users of natural experimental evaluations conduct and identify robust evaluations. To fully benefit the evaluation, qualitative methods should be integrated throughout.

Deep learning assisted measurement of echocardiographic left heart parameters: improvement in interobserver variability and workflow efficiency.

Machine learning techniques designed to recognize views and perform measurements are increasingly used to address the need for automation of the interpretation of echocardiographic images. The current study was designed to determine whether a recently developed and validated deep learning (DL) algorithm for automated measurements of echocardiographic parameters of left heart chamber size and function can improve the reproducibility and shorten the analysis time, compared to the conventional methodology. The DL algorithm trained to identify standard views and provide automated measurements of 20 standard parameters, was applied to images obtained in 12 randomly selected echocardiographic studies. The resultant measurements were reviewed and revised as necessary by 10 independent expert readers. The same readers also performed conventional manual measurements, which were averaged and used as the reference standard for the DL-assisted approach with and without the manual revisions. Inter-reader variability was quantified using coefficients of variation, which together with analysis times, were compared between the conventional reads and the DL-assisted approach. The fully automated DL measurements showed good agreement with the reference technique: Bland-Altman biases 0-14% of the measured values. Manual revisions resulted in only minor improvement in accuracy: biases 0-11%. This DL-assisted approach resulted in a 43% decrease in analysis time and less inter-reader variability than the conventional methodology: 2-3 times smaller coefficients of variation. In conclusion, DL-assisted approach to analysis of echocardiographic images can provide accurate left heart measurements with the added benefits of improved reproducibility and time savings, compared to conventional methodology.

Identifying fake conclusions of forensic medical examinations using an artificial intelligence technology based on the experience in the Republic of Kazakhstan: a Review

This review discusses the legal aspects on the use of mathematical statistics and machine learning (hereinafter referred to as artificial intelligence) in forensic activities to identify both expert errors and fake expert opinions.&#x0D; An attempt has been made to establish the criteria for evaluating conclusions of forensic examinations by determining their relevance, admissibility, reliability, and objectivity, as well as the objective possibility of distinguishing expert errors from deliberately false and fake expert opinions.&#x0D; A SWOT analysis on the use of artificial intelligence was carried out to solve the issue of its application in the field under consideration, which revealed its advantages, and disadvantages.&#x0D; The use of mathematical statistics and machine learning methods is not a universal method to identify fakes in expert opinions. However, given that this method can give both false-positive and false-negative results, its outcomes should be verified by independent experts. In addition, to effectively prevent the facts of falsification, comprehensive measures should be taken, including not only the detection of manipulations but also the prevention of the possibility of their occurrence, as well as the punishment of the perpetrators. Thus, this review proposed several amendments and additions to the current legislation of the Republic of Kazakhstan.

Active learning for extracting surgomic features in robot-assisted minimally invasive esophagectomy: a prospective annotation study

BackgroundWith Surgomics, we aim for personalized prediction of the patient's surgical outcome using machine-learning (ML) on multimodal intraoperative data to extract surgomic features as surgical process characteristics. As high-quality annotations by medical experts are crucial, but still a bottleneck, we prospectively investigate active learning (AL) to reduce annotation effort and present automatic recognition of surgomic features.MethodsTo establish a process for development of surgomic features, ten video-based features related to bleeding, as highly relevant intraoperative complication, were chosen. They comprise the amount of blood and smoke in the surgical field, six instruments, and two anatomic structures. Annotation of selected frames from robot-assisted minimally invasive esophagectomies was performed by at least three independent medical experts. To test whether AL reduces annotation effort, we performed a prospective annotation study comparing AL with equidistant sampling (EQS) for frame selection. Multiple Bayesian ResNet18 architectures were trained on a multicentric dataset, consisting of 22 videos from two centers.ResultsIn total, 14,004 frames were tag annotated. A mean F1-score of 0.75 ± 0.16 was achieved for all features. The highest F1-score was achieved for the instruments (mean 0.80 ± 0.17). This result is also reflected in the inter-rater-agreement (1-rater-kappa > 0.82). Compared to EQS, AL showed better recognition results for the instruments with a significant difference in the McNemar test comparing correctness of predictions. Moreover, in contrast to EQS, AL selected more frames of the four less common instruments (1512 vs. 607 frames) and achieved higher F1-scores for common instruments while requiring less training frames.ConclusionWe presented ten surgomic features relevant for bleeding events in esophageal surgery automatically extracted from surgical video using ML. AL showed the potential to reduce annotation effort while keeping ML performance high for selected features. The source code and the trained models are published open source.Graphical abstract

Assessing Serious Spinal Pathology Using Bayesian Network Decision Support: Development and Validation Study.

Identifying and managing serious spinal pathology (SSP) such as cauda equina syndrome or spinal infection in patients presenting with low back pain is challenging. Traditional red flag questioning is increasingly criticized, and previous studies show that many clinicians lack confidence in managing patients presenting with red flags. Improving decision-making and reducing the variability of care for these patients is a key priority for clinicians and researchers. We aimed to improve SSP identification by constructing and validating a decision support tool using a Bayesian network (BN), which is an artificial intelligence technique that combines current evidence and expert knowledge. A modified RAND appropriateness procedure was undertaken with 16 experts over 3 rounds, designed to elicit the variables, structure, and conditional probabilities necessary to build a causal BN. The BN predicts the likelihood of a patient with a particular presentation having an SSP. The second part of this study used an established framework to direct a 4-part validation that included comparison of the BN with consensus statements, practice guidelines, and recent research. Clinical cases were entered into the model and the results were compared with clinical judgment from spinal experts who were not involved in the elicitation. Receiver operating characteristic curves were plotted and area under the curve were calculated for accuracy statistics. The RAND appropriateness procedure elicited a model including 38 variables in 3 domains: risk factors (10 variables), signs and symptoms (17 variables), and judgment factors (11 variables). Clear consensus was found in the risk factors and signs and symptoms for SSP conditions. The 4-part BN validation demonstrated good performance overall and identified areas for further development. Comparison with available clinical literature showed good overall agreement but suggested certain improvements required to, for example, 2 of the 11 judgment factors. Case analysis showed that cauda equina syndrome, space-occupying lesion/cancer, and inflammatory condition identification performed well across the validation domains. Fracture identification performed less well, but the reasons for the erroneous results are well understood. A review of the content by independent spinal experts backed up the issues with the fracture node, but the BN was otherwise deemed acceptable. The RAND appropriateness procedure and validation framework were successfully implemented to develop the BN for SSP. In comparison with other expert-elicited BN studies, this work goes a step further in validating the output before attempting implementation. Using a framework for model validation, the BN showed encouraging validity and has provided avenues for further developing the outputs that demonstrated poor accuracy. This study provides the vital first step of improving our ability to predict outcomes in low back pain by first considering the problem of SSP. RR2-10.2196/21804.

ChatGPT Isn't Magic

ChatGPT Isn't Magic

Gamification in Health Care Management: Systematic Review of the Literature and Research Agenda

This research aims to advance the understanding of gamification in health care management using a systematic review of the literature through a multiphase analysis. To do so, first, we extract the relevant bibliographic data for our research according to a methodology of data generation structured in six stages and a descriptive analysis oriented to the technical characterization of the data. Then, we codify all the information, identify the main attributes with the collaboration of two independent experts and check their validity using the evaluation of two focus groups of professionals in gamification and health care management. We found seven attributes: (1) health care users, (2) psychology, (3) behavior, (4) activities, (5) health field, (6) technology, and (7) gamification elements. Within each of these seven attributes, there are a series of main elements that are detailed in the following for each of them. (1) Health care users: their age and the role they play in the health system. (2) Psychology: cognition, positive and negative emotions. (3) Behavior: healthy behavior encouragement, such as compliance, collaboration and responsibility. (4) Activities: physical activity and food. (5) Health field: preventive medicine and chronic diseases. (6) Technology: cell phones. (7) Gamification elements: different elements, but the number of articles in which these elements and their interactions are studied in depth is limited. Our results point toward a promising present and future research agenda that is in parallel with the development of relevant fields for the sector, such as chronic diseases, health education and preventive medicine.

Reduction in Earning Capacity (MdE) Statutory Accident Insurance

Changes in the employment market and improvements in the current prosthetic treatment have encouraged German Statutory Health Insurance e. V. (DGUV) to re-examine the standard values for reduced earning capacity after work related accidents. The new standard values for reduced earning capacity came into force on 01.11.2019. The present article summarises the consensus paper of the group of independent experts.