EDUCATE: An international, randomized controlled trial for teaching electrocardiography.

INTRODUCTION: Despite the critical role of electrocardiograms (ECGs) in patient care, evident gaps exist in ECG interpretation competency among healthcare professionals across various medical disciplines and training levels. Currently, no practical, evidence-based, and easily accessible ECG learning solution is available for healthcare professionals. The aim of this study was to assess the effectiveness of web-based, learner-directed interventions in improving ECG interpretation skills in a diverse group of healthcare professionals. METHODS: In an international, prospective, randomized controlled trial, 1206 healthcare professionals from various disciplines and training levels were enrolled. They underwent a pre-intervention test featuring 30 12-lead ECGs with common urgent and non-urgent findings. Participants were randomly assigned to four groups: (i) practice ECG interpretation question bank (question bank), (ii) lecture-based learning resource (lectures), (iii) hybrid question- and lecture-based learning resource (hybrid), or (iv) no ECG learning resources (control). After four months, a post-intervention test was administered. The primary outcome was the overall change in ECG interpretation performance, with secondary outcomes including changes in interpretation time, self-reported confidence, and accuracy for specific ECG findings. Both unadjusted and adjusted scores were used for performance assessment. RESULTS: Among 1206 participants, 863 (72 %) completed the trial. Following the intervention, the question bank, lectures, and hybrid intervention groups each exhibited significant improvements, with average unadjusted score increases of 11.4 % (95 % CI, 9.1 to 13.7; P<0.01), 9.8 % (95 % CI, 7.8 to 11.9; P<0.01), and 11.0 % (95 % CI, 9.2 to 12.9; P<0.01), respectively. In contrast, the control group demonstrated a non-significant improvement of 0.8 % (95 % CI, -1.2 to 2.8; P=0.54). While no differences were observed among intervention groups, all outperformed the control group significantly (P<0.01). Intervention groups also excelled in adjusted scores, confidence, and proficiency for specific ECG findings. CONCLUSION: Web-based, self-directed interventions markedly enhanced ECG interpretation skills across a diverse range of healthcare professionals, providing an accessible and evidence-based solution.

Predictors of ECG Interpretation Proficiency in Healthcare Professionals.

Accurate ECG interpretation is vital, but variations in skills exist among healthcare professionals. This study aims to identify factors contributing to ECG interpretation proficiency. Survey data and ECG interpretation test scores from participants in the EDUCATE Trial were analyzed to identify predictors of performance for 30 sequential 12-lead ECGs. Nonmodifiable factors (being a physician, clinical experience, patient care impact) and modifiable factors (weekly interpretation volume, training hours, expert supervision frequency) were analyzed. Bivariate and multivariate analyses were used to generate a Comprehensive Model (incorporating all factors) and Actionable Model (incorporating modifiable factors only). Among 1206 participants analyzed, there were 72 (6.0%) primary care physicians, 146 (12.1%) cardiology fellows-in-training, 353 (29.3%) resident physicians, 182 (15.1%) medical students, 84 (7.0%) advanced practice providers, 120 (9.9%) nurses, and 249 (20.7%) allied health professionals. Among them, 571 (47.3%) were physicians and 453 (37.6%) were nonphysicians. The average test score was 56.4% ± 17.2%. Bivariate analysis demonstrated significant associations between test scores and >10 weekly ECG interpretations, being a physician, >5 training hours, patient care impact, and expert supervision but not clinical experience. In the Comprehensive Model, independent associations were found with weekly interpretation volume (9.9 score increase; 95% CI, 7.9-11.8; P < 0.001), being a physician (9.0 score increase; 95% CI, 7.2-10.8; P < 0.001), and training hours (5.7 score increase; 95% CI, 3.7-7.6; P < 0.001). In the Actionable Model, scores were independently associated with weekly interpretation volume (12.0 score increase; 95% CI, 10.0-14.0; P < 0.001) and training hours (4.7 score increase; 95% CI, 2.6-6.7; P < 0.001). The Comprehensive and Actionable Models explained 18.7% and 12.3% of the variance in test scores, respectively. Predictors of ECG interpretation proficiency include nonmodifiable factors like physician status and modifiable factors such as training hours and weekly ECG interpretation volume.

ECG Interpretation Proficiency of Healthcare Professionals.

ECG interpretation is essential in modern medicine, yet achieving and maintaining competency can be challenging for healthcare professionals. Quantifying proficiency gaps can inform educational interventions for addressing these challenges. Medical professionals from diverse disciplines and training levels interpreted 30 12-lead ECGs with common urgent and nonurgent findings. Average accuracy (percentage of correctly identified findings), interpretation time per ECG, and self-reported confidence (rated on a scale of 0 [not confident], 1 [somewhat confident], or 2 [confident]) were evaluated. Among the 1206 participants, there were 72 (6%) primary care physicians (PCPs), 146 (12%) cardiology fellows-in-training (FITs), 353 (29%) resident physicians, 182 (15%) medical students, 84 (7%) advanced practice providers (APPs), 120 (10%) nurses, and 249 (21%) allied health professionals (AHPs). Overall, participants achieved an average overall accuracy of 56.4% ± 17.2%, interpretation time of 142 ± 67 seconds, and confidence of 0.83 ± 0.53. Cardiology FITs demonstrated superior performance across all metrics. PCPs had a higher accuracy compared to nurses and APPs (58.1% vs 46.8% and 50.6%; P < 0.01), but a lower accuracy than resident physicians (58.1% vs 59.7%; P < 0.01). AHPs outperformed nurses and APPs in every metric and showed comparable performance to resident physicians and PCPs. Our findings highlight significant gaps in the ECG interpretation proficiency among healthcare professionals.

Education curriculum assessment for teaching electrocardiography: Rationale and design for the prospective, international, randomized controlled EDUCATE trial.

BACKGROUND: Electrocardiogram (ECG) interpretation training is a fundamental component of medical education across disciplines. However, the skill of interpreting ECGs is not universal among medical graduates, and numerous barriers and challenges exist in medical training and clinical practice. An evidence-based and widely accessible learning solution is needed. DESIGN: The EDUcation Curriculum Assessment for Teaching Electrocardiography (EDUCATE) Trial is a prospective, international, investigator-initiated, open-label, randomized controlled trial designed to determine the efficacy of self-directed and active-learning approaches of a web-based educational platform for improving ECG interpretation proficiency. Target enrollment is 1000 medical professionals from a variety of medical disciplines and training levels. Participants will complete a pre-intervention baseline survey and an ECG interpretation proficiency test. After completion, participants will be randomized into one of four groups in a 1:1:1:1 fashion: (i) an online, question-based learning resource, (ii) an online, lecture-based learning resource, (iii) an online, hybrid question- and lecture-based learning resource, or (iv) a control group with no ECG learning resources. The primary endpoint will be the change in overall ECG interpretation performance according to pre- and post-intervention tests, and it will be measured within and compared between medical professional groups. Secondary endpoints will include changes in ECG interpretation time, self-reported confidence, and interpretation accuracy for specific ECG findings. CONCLUSIONS: The EDUCATE Trial is a pioneering initiative aiming to establish a practical, widely available, evidence-based solution to enhance ECG interpretation proficiency among medical professionals. Through its innovative study design, it tackles the currently unaddressed challenges of ECG interpretation education in the modern era. The trial seeks to pinpoint performance gaps across medical professions, compare the effectiveness of different web-based ECG content delivery methods, and create initial evidence for competency-based standards. If successful, the EDUCATE Trial will represent a significant stride towards data-driven solutions for improving ECG interpretation skills in the medical community.

Impact of Computer-Interpreted ECGs on the Accuracy of Healthcare Professionals.

The interpretation of electrocardiograms (ECGs) involves a dynamic interplay between computerized ECG interpretation (CEI) software and human overread. However, the impact of computer ECG interpretation on the performance of healthcare professionals remains largely unexplored. The aim of this study was to evaluate the interpretation proficiency of various medical professional groups, with and without access to the CEI report. Healthcare professionals from diverse disciplines, training levels, and countries sequentially interpreted 60 standard 12-lead ECGs, demonstrating both urgent and nonurgent findings. The interpretation process consisted of 2 phases. In the first phase, participants interpreted 30 ECGs with clinical statements. In the second phase, the same 30 ECGs and clinical statements were randomized and accompanied by a CEI report. Diagnostic performance was evaluated based on interpretation accuracy, time per ECG (in seconds [s]), and self-reported confidence (rated 0 [not confident], 1 [somewhat confident], or 2 [confident]). A total of 892 participants from various medical professional groups participated in the study. This cohort included 44 (4.9%) primary care physicians, 123 (13.8%) cardiology fellows-in-training, 259 (29.0%) resident physicians, 137 (15.4%) medical students, 56 (6.3%) advanced practice providers, 82 (9.2%) nurses, and 191 (21.4%) allied health professionals. The inclusion of the CEI was associated with a significant improvement in interpretation accuracy by 15.1% (95% confidence interval, 14.3-16.0; P < 0.001), decrease in interpretation time by 52 s (-56 to -48; P < 0.001), and increase in confidence by 0.06 (0.03-0.09; P = 0.003). Improvement in interpretation accuracy was seen across all professional subgroups, including primary care physicians by 12.9% (9.4-16.3; P = 0.003), cardiology fellows-in-training by 10.9% (9.1-12.7; P < 0.001), resident physicians by 14.4% (13.0-15.8; P < 0.001), medical students by 19.9% (16.8-23.0; P < 0.001), advanced practice providers by 17.1% (13.3-21.0; P < 0.001), nurses by 16.2% (13.4-18.9; P < 0.001), allied health professionals by 15% (13.4-16.6; P < 0.001), physicians by 13.2% (12.2-14.3; P < 0.001), and nonphysicians by 15.6% (14.3-17.0; P < 0.001).CEI integration improves ECG interpretation accuracy, efficiency, and confidence among healthcare professionals.

Exploring Factors Influencing ECG Interpretation Proficiency of Medical Professionals.

The electrocardiogram (ECG) is a crucial diagnostic tool in medicine with concerns about its interpretation proficiency across various medical disciplines. Our study aimed to explore potential causes of these issues and identify areas requiring improvement. A survey was conducted among medical professionals to understand their experiences with ECG interpretation and education. A total of 2515 participants from diverse medical backgrounds were surveyed. A total of 1989 (79%) participants reported ECG interpretation as part of their practice. However, 45% expressed discomfort with independent interpretation. A significant 73% received less than 5 hours of ECG-specific education, with 45% reporting no education at all. Also, 87% reported limited or no expert supervision. Nearly all medical professionals (2461, 98%) expressed a desire for more ECG education. These findings were consistent across all groups and did not vary between primary care physicians, cardiology FIT, resident physicians, medical students, APPs, nurses, physicians, and nonphysicians. This study reveals substantial deficiencies in ECG interpretation training, supervision, and confidence among medical professionals, despite a strong interest in increased ECG education.

Small-molecule inhibition of TNF-alpha.

We have identified a small-molecule inhibitor of tumor necrosis factor alpha (TNF-alpha) that promotes subunit disassembly of this trimeric cytokine family member. The compound inhibits TNF-alpha activity in biochemical and cell-based assays with median inhibitory concentrations of 22 and 4.6 micromolar, respectively. Formation of an intermediate complex between the compound and the intact trimer results in a 600-fold accelerated subunit dissociation rate that leads to trimer dissociation. A structure solved by x-ray crystallography reveals that a single compound molecule displaces a subunit of the trimer to form a complex with a dimer of TNF-alpha subunits.

Tethering: fragment-based drug discovery.

The genomics revolution has provided a deluge of new targets for drug discovery. To facilitate the drug discovery process, many researchers are turning to fragment-based approaches to find lead molecules more efficiently. One such method, Tethering1, allows for the identification of small-molecule fragments that bind to specific regions of a protein target. These fragments can then be elaborated, combined with other molecules, or combined with one another to provide high-affinity drug leads. In this review we describe the background and theory behind Tethering and discuss its use in identifying novel inhibitors for protein targets including interleukin-2 (IL-2), thymidylate synthase (TS), protein tyrosine phosphatase 1B (PTP-1B), and caspases.

Integrating fragment assembly and biophysical methods in the chemical advancement of small-molecule antagonists of IL-2: an approach for inhibiting protein-protein interactions.

Fragment assembly has shown promise for discovering small-molecule antagonists for difficult targets, including protein-protein interactions. Here, we describe a process for identifying a 60 nM inhibitor of the interleukin-2 (IL-2)/IL-2 receptor (IL-2Ralpha) interaction. By use of fragment-based approaches, a compound with millimolar affinity was evolved to a hit series with low micromolar activity, and these compounds were optimized into a lead series with nanomolar affinity. Fragment assembly was useful not only for hit identification, but also for lead optimization. Throughout the discovery process, biophysical methods and structural biology demonstrated that compounds bound reversibly to IL-2 at the IL-2 receptor binding site.

Discovery and characterization of cooperative ligand binding in the adaptive region of interleukin-2.

The cytokine hormone interleukin-2 (IL-2) contains a highly adaptive region that binds small, druglike molecules. The binding properties of this adaptive region have been explored using a "tethering" method that relies on the formation of a disulfide bond between the protein and small-molecule ligands. Using tethering, surface plasmon resonance (SPR), and X-ray crystallography, we have discovered that the IL-2 adaptive region contains at least two cooperative binding sites where the binding of a first ligand to one site promotes or antagonizes the binding of a second ligand to the second site. Cooperative energies of interaction of -2 kcal/mol are observed. The observation that the adaptive region contains two adjacent sites may lead to the development of tight-binding antagonists of a protein-protein interaction. Cooperative ligand binding in the adaptive region of IL-2 underscores the importance of protein dynamics in molecular recognition. The tethering approach provides a novel and general strategy for discovering such cooperative binding interactions in specific, flexible regions of protein structure.

Discovery of a potent small molecule IL-2 inhibitor through fragment assembly.

Using a site-directed fragment discovery method called tethering, we have identified a 60 nM small molecule antagonist of a cytokine/receptor interaction (IL-2/IL2Ralpha) with cell-based activity. Starting with a low micromolar hit, we employed a combination of tethering, structural biology, and computational analysis to design a focused set of 20 compounds. Eight of these compounds were at least 5-fold more active than the original hit. One of these compounds showed a 50-fold enhancement and represents the highest affinity inhibitor reported against this protein-protein target class. This method of coupling selected fragments with a low micromolar hit shows great potential for generating high-affinity lead compounds.

Binding of small molecules to an adaptive protein-protein interface.

Understanding binding properties at protein-protein interfaces has been limited to structural and mutational analyses of natural binding partners or small peptides identified by phage display. Here, we present a high-resolution analysis of a nonpeptidyl small molecule, previously discovered by medicinal chemistry [Tilley, J. W., et al. (1997) J. Am. Chem. Soc. 119, 7589-7590], which binds to the cytokine IL-2. The small molecule binds to the same site that binds the IL-2 alpha receptor and buries into a groove not seen in the free structure of IL-2. Comparison of the bound and several free structures shows this site to be composed of two subsites: one is rigid, and the other is highly adaptive. Thermodynamic data suggest the energy barriers between these conformations are low. The subsites were dissected by using a site-directed screening method called tethering, in which small fragments were captured by disulfide interchange with cysteines introduced into IL-2 around these subsites. X-ray structures with the tethered fragments show that the subsite-binding interactions are similar to those observed with the original small molecule. Moreover, the adaptive subsite tethered many more compounds than did the rigid one. Thus, the adaptive nature of a protein-protein interface provides sites for small molecules to bind and underscores the challenge of applying structure-based design strategies that cannot accurately predict a dynamic protein surface.