OBJECTIVE: Systematic reviews and medical guidelines are widely used in clinical practice. However, these are often not up-to-date and focussed on the average patient. We therefore aimed to evaluate a guideline add-on, TherapySelector (TS), which is based on monthly updated data of all available high-quality studies, classified in specific patient profiles.
METHODS: We evaluated the TS for the treatment of hepatitis C (HCV) in an international cohort of patients treated with direct-acting antivirals between 2015 and 2020. The primary outcome was the number of patients receiving one of the two preferred treatment options of the HCV TS, based on the highest level of evidence, cure rate, absence of ribavirin-associated adverse effects, and treatment duration.
RESULTS: We enrolled 567 patients. The number of patients treated with one of the two preferred treatment options according to the HCV TS ranged between 27% (2015) and 60% (2020; p < 0.001). Most of the patients received a regimen with a longer treatment-duration (up to 34%) and/or addition of ribavirin (up to 14%). The effect on the expected cure-rate was minimal (1-6% higher) when the first preferred TherapySelector option was given compared to the actual treatment.
CONCLUSIONS: Medical decision-making can be optimised by a guideline add-on; in HCV its use appears to minimise adverse effects and cost. The use of such an add-on might have a greater impact in diseases with suboptimal cure-rates, high costs or adverse effects, for which treatment options rely on specific patient characteristics.

BACKGROUND: Guidelines must be interpreted comprehensively and correctly to standardize the clinical process. However, this process is challenging and requires interpreters to have a medical background and qualifications. In this study, the accuracy of ChatGPT3.5 in answering clinical questions related to the 2019 guidelines for severe acute pancreatitis was evaluated.
RESULTS: An observational study was conducted using the 2019 guidelines for severe acute pancreatitis. The study compared the accuracy of ChatGPT3.5 in English versus Chinese and found that it was more accurate in English (71%) than in Chinese (59%) (P value: 0.203). Additionally, the study assessed the accuracy of ChatGPT3.5 in answering short-answer questions versus true/false questions and found that it was more accurate in answering short-answer questions (76%) than in answering true/false questions (60%) (P value: 0.405).
CONCLUSIONS: For clinicians managing severe acute pancreatitis, ChatGPT3.5 may have potential value. However, it should not be relied upon excessively for clinical decision making.

OBJECTIVE: In a time of exponential growth of new evidence supporting clinical decision-making, combined with a labor-intensive process of selecting this evidence, methods are needed to speed up current processes to keep medical guidelines up-to-date. This study evaluated the performance and feasibility of active learning to support the selection of relevant publications within medical guideline development and to study the role of noisy labels.
METHODS: We used a mixed-methods design. Two independent clinicians\' manual process of literature selection was evaluated for 14 searches. This was followed by a series of simulations investigating the performance of random reading versus using screening prioritization based on active learning. We identified hard-to-find papers and checked the labels in a reflective dialogue.
METHODS: Inter-rater reliability was assessed using Cohen\'s Kappa (ĸ). To evaluate the performance of active learning, we used the Work Saved over Sampling at 95% recall (WSS@95) and percentage Relevant Records Found at reading only 10% of the total number of records (RRF@10). We used the average time to discovery (ATD) to detect records with potentially noisy labels. Finally, the accuracy of labeling was discussed in a reflective dialogue with guideline developers.
RESULTS: Mean ĸ for manual title-abstract selection by clinicians was 0.50 and varied between - 0.01 and 0.87 based on 5.021 abstracts. WSS@95 ranged from 50.15% (SD = 17.7) based on selection by clinicians to 69.24% (SD = 11.5) based on the selection by research methodologist up to 75.76% (SD = 12.2) based on the final full-text inclusion. A similar pattern was seen for RRF@10, ranging from 48.31% (SD = 23.3) to 62.8% (SD = 21.20) and 65.58% (SD = 23.25). The performance of active learning deteriorates with higher noise. Compared with the final full-text selection, the selection made by clinicians or research methodologists deteriorated WSS@95 by 25.61% and 6.25%, respectively.
CONCLUSIONS: While active machine learning tools can accelerate the process of literature screening within guideline development, they can only work as well as the input given by human raters. Noisy labels make noisy machine learning.

OBJECTIVE: The objectives of this study are to assess reporting of evidence-based healthcare (EBHC) e-learning interventions using the Guideline for Reporting Evidence-based practice Educational interventions and Teaching (GREET) checklist and explore factors associated with compliant reporting.
METHODS: Methodological cross-sectional study.
METHODS: Based on the criteria used in an earlier systematic review, we included studies comparing EBHC e-learning and any other form of EBHC training or no EBHC training. We searched Medline, Embase, ERIC, CINAHL, CENTRAL, SCOPUS, Web of Knowledge, PsycInfo, ProQuest and Best Evidence Medical Education up to 4 January 2023. Screening of titles, abstracts, full-text articles and data extraction was done independently by two authors. For each study, we assessed adherence to each of the 17 GREET items and extracted information on possible predictors. Adequacy of reporting for each item of the GREET checklist was judged with yes (provided complete information), no (provided no information), unclear (when insufficient information was provided), or not applicable, when the item was clearly of no relevance to the intervention described (such as for item 8-details about the instructors-in the studies which used electronic, self-paced intervention, without any tutoring). Studies\' adherence to the GREET checklist was presented as percentages and absolute numbers. We performed univariate analysis to assess the association of potential adherence predictors with the GREET checklist. We summarised results descriptively.
RESULTS: We included 40 studies, the majority of which assessed e-learning or blended learning and mostly involved medical and other healthcare students. None of the studies fully reported all the GREET items. Overall, the median number of GREET items met (received yes) per study was 8 and third quartile (Q3) of GREET items met per study was 9 (min. 4 max. 14). When we used Q3 of the number of items met as cut-off point, adherence to the GREET reporting checklist was poor with 7 out of 40 studies (17.5%) reporting items of the checklist on acceptable level (adhered to at least 10 items out of 17). None of the studies reported on all 17 GREET items. For 3 items, 80% of included studies well reported information (received yes for these items): item 1 (brief description of intervention), item 4 (evidence-based practice content) and item 6 (educational strategies). Items for which 50% of included studies reported complete information (received yes for these items) included: item 9 (modes of delivery), item 11 (schedule) and 12 (time spent on learning). The items for which 70% or more of included studies did not provide information (received no for these items) included: item 7 (incentives) and item 13 (adaptations; for both items 70% of studies received no for them), item 14 (modifications of educational interventions-95% of studies received no for this item), item 16 (any processes to determine whether the materials and the educational strategies used in the educational intervention were delivered as originally planned-93% of studies received no for this item) and 17 (intervention delivery according to schedule-100% of studies received no for this item). Studies published after September 2016 showed slight improvements in nine reporting items. In the logistic regression models, using the cut-off point of Q3 (10 points or above) the odds of acceptable adherence to GREET guidelines were 7.5 times higher if adherence to other guideline (Consolidated Standards of Reporting Trials, Strengthening the Reporting of Observational Studies in Epidemiology, etc) was reported for a given study type (p=0.039), also higher number of study authors increased the odds of adherence to GREET guidance by 18% (p=0.037).
CONCLUSIONS: Studies assessing educational interventions on EBHC e-learning still poorly adhere to the GREET checklist. Using other reporting guidelines increased the odds of better GREET reporting. Journals should call for the use of appropriate use of reporting guidelines of future studies on teaching EBHC to increase transparency of reporting, decrease unnecessary research duplication and facilitate uptake of research evidence or result.
BACKGROUND: The Open Science Framework (https://doi.org/10.17605/OSF.IO/V86FR).

Barrett\'s esophagus (BE) is the precursor to esophageal adenocarcinoma (EAC). Endoscopic eradication therapy (EET) can be effective in eradicating BE and related neoplasia and has greater risk of harms and resource use than surveillance endoscopy. This clinical practice guideline aims to inform clinicians and patients by providing evidence-based practice recommendations for the use of EET in BE and related neoplasia.
The Grading of Recommendations Assessment, Development and Evaluation framework was used to assess evidence and make recommendations. The panel prioritized clinical questions and outcomes according to their importance for clinicians and patients, conducted an evidence review, and used the Evidence-to-Decision Framework to develop recommendations regarding the use of EET in patients with BE under the following scenarios: presence of (1) high-grade dysplasia, (2) low-grade dysplasia, (3) no dysplasia, and (4) choice of stepwise endoscopic mucosal resection (EMR) or focal EMR plus ablation, and (5) endoscopic submucosal dissection vs EMR. Clinical recommendations were based on the balance between desirable and undesirable effects, patient values, costs, and health equity considerations.
The panel agreed on 5 recommendations for the use of EET in BE and related neoplasia. Based on the available evidence, the panel made a strong recommendation in favor of EET in patients with BE high-grade dysplasia and conditional recommendation against EET in BE without dysplasia. The panel made a conditional recommendation in favor of EET in BE low-grade dysplasia; patients with BE low-grade dysplasia who place a higher value on the potential harms and lower value on the benefits (which are uncertain) regarding reduction of esophageal cancer mortality could reasonably select surveillance endoscopy. In patients with visible lesions, a conditional recommendation was made in favor of focal EMR plus ablation over stepwise EMR. In patients with visible neoplastic lesions undergoing resection, the use of either endoscopic mucosal resection or endoscopic submucosal dissection was suggested based on lesion characteristics.
This document provides a comprehensive outline of the indications for EET in the management of BE and related neoplasia. Guidance is also provided regarding the considerations surrounding implementation of EET. Providers should engage in shared decision making based on patient preferences. Limitations and gaps in the evidence are highlighted to guide future research opportunities.

BACKGROUND: Despite the strong evidence supporting guideline-directed medical therapy (GDMT) in patients with heart failure with reduced ejection fraction (HFrEF), prescription rates in clinical practice are still lacking.
METHODS: A survey containing 20 clinical vignettes of patients with HFrEF was answered by a national sample of 127 cardiologists and 68 internal/family medicine physicians. Each vignette had 4-5 options for adjusting GDMT and the option to make no medication changes. Survey respondents could only select one option. For analysis, responses were dichotomized to the answer of interest.
RESULTS: Cardiologists were more likely to make GDMT changes than general medicine physicians (91.8% vs. 82.0%; OR 1.84 [1.07-3.19]; p = 0.020). Cardiologists were more likely to initiate beta-blockers (46.3% vs. 32.0%; OR 2.38 [1.18-4.81], p = 0.016), angiotensin receptor blocker/neprilysin inhibitor (ARNI) (63.8% vs. 48.1%; OR 1.76 [1.01-3.09], p = 0.047), and hydralazine and isosorbide dinitrate (HYD/ISDN) (38.2% vs. 23.7%; OR 2.47 [1.48-4.12], p < 0.001) compared to general medicine physicians. No differences were found in initiating angiotensin-converting enzyme inhibitor/angiotensin receptor blocker (ACEi/ARBs), initiating mineralocorticoid receptor antagonist (MRA), sodium-glucose transporter protein 2 (SGLT2) inhibitors, digoxin, or ivabradine.
CONCLUSIONS: Our results demonstrate cardiologists were more likely to adjust GDMT than general medicine physicians. Future focus on improving GDMT prescribing should target providers other than cardiologists to improve care in patients with HFrEF.

OBJECTIVE: There are no globally agreed on strategies on early detection and first response management of postpartum haemorrhage (PPH) during and after caesarean birth. Our study aimed to develop an international expert\'s consensus on evidence-based approaches for early detection and obstetric first response management of PPH intraoperatively and postoperatively in caesarean birth.
METHODS: Systematic review and three-stage modified Delphi expert consensus.
METHODS: International.
METHODS: Panel of 22 global experts in PPH with diverse backgrounds, and gender, professional and geographic balance.
METHODS: Agreement or disagreement on strategies for early detection and first response management of PPH at caesarean birth.
RESULTS: Experts agreed that the same PPH definition should apply to both vaginal and caesarean birth. For the intraoperative phase, the experts agreed that early detection should be accomplished via quantitative blood loss measurement, complemented by monitoring the woman\'s haemodynamic status; and that first response should be triggered once the woman loses at least 500 mL of blood with continued bleeding or when she exhibits clinical signs of haemodynamic instability, whichever occurs first. For the first response, experts agreed on immediate administration of uterotonics and tranexamic acid, examination to determine aetiology and rapid initiation of cause-specific responses. In the postoperative phase, the experts agreed that caesarean birth-related PPH should be detected primarily via frequently monitoring the woman\'s haemodynamic status and clinical signs and symptoms of internal bleeding, supplemented by cumulative blood loss assessment performed quantitatively or by visual estimation. Postoperative first response was determined to require an individualised approach.
CONCLUSIONS: These agreed on proposed approaches could help improve the detection of PPH in the intraoperative and postoperative phases of caesarean birth and the first response management of intraoperative PPH. Determining how best to implement these strategies is a critical next step.

OBJECTIVE: This study aimed to assess the feasibility of GPT-4 for answering questions related to contrast media with and without the context of the European Society of Urogenital Radiology (ESUR) guideline on contrast agents. The overarching goal was to determine whether contextual enrichment by providing guideline information improves answers of GPT-4 for clinical decision-making in radiology.
METHODS: A set of 64 questions, based on the ESUR guideline on contrast agents mirroring pertinent sections, was developed and posed to GPT-4 both directly and after providing the guideline using a plugin. Responses were graded by experienced radiologists for quality of information and accuracy in pinpointing information from the guideline as well as by radiology residents for utility, using Likert-scales.
RESULTS: GPT-4\'s performance improved significantly with the guideline. Without the guideline, average quality rating was 3.98, which increased to 4.33 with the guideline (p = 0036). In terms of accuracy, 82.3% of answers matched the information from the guideline. Utility scores also reflected a significant improvement with the guideline, with average scores of 4.1 (without) and 4.4 (with) (p = 0.008) with a Fleiss´ Kappa of 0.44.
CONCLUSIONS: GPT-4, when contextually enriched with a guideline, demonstrates enhanced capability in providing guideline-backed recommendations. This approach holds promise for real-time clinical decision-support, making guidelines more actionable. However, further refinements are necessary to maximize the potential of large language models (LLMs). Inherent limitations need to be addressed.

A comprehensive evaluation of risk, using multiple indices, is necessary to provide reliable prognostic information and guide therapy in pulmonary arterial hypertension (PAH). The current ESC/ERS guidelines suggest using a three-strata model for incident (newly diagnosed) patients and a four-strata model for prevalent patients with PAH. The four-strata model serves as a fundamental risk-stratification tool and relies on a minimal dataset of indicators that must be considered during follow-up. Nevertheless, there are still areas of vagueness and ambiguity when classifying and managing patients in the intermediate-risk category. For these patients, considerations should include right heart imaging, hemodynamics, as well as individual factors such as age, sex, genetic profile, disease type, comorbidities, and kidney function. The aim of this report is to present case studies, with a specific focus on patients ultimately classified as intermediate risk. We aim to emphasize the challenges and complexities encountered in the realms of diagnosis, classification, and treatment for these particular patients.

Individual and social factors are important for clinical decision-making in patients with neurogenic bladder secondary to spinal cord injury (SCI). These factors include the availability of caregivers, social infrastructure, and personal preferences, which all can drive bladder management decisions. These elements can be overlooked in clinical decision-making; therefore, there is a need to elicit and prioritize patient preferences and values into neurogenic bladder care to facilitate personalized bladder management choices. For the purposes of this article, we review the role of guideline-based care and shared decision-making in the SCI population with neurogenic lower urinary tract dysfunction.