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Aims: To measure pimecrolimus blood concentrations and to evaluate tolerability and efficacy in children and infants treated topically for atopic dermatitis with pimecrolimus cream 1% for three weeks. Methods: Three [...]

Knowledge engineering is the process of creating and maintaining knowledge-producing systems. Throughout the history of computer science and AI, knowledge engineering workflows have been widely used given the importance of high-quality knowledge for reliable intelligent agents. Meanwhile, the scope of knowledge engineering, as apparent from its target tasks and use cases, has been shifting, together with its paradigms such as expert systems, semantic web, and language modeling. The intended use cases and supported user requirements between these paradigms have not been analyzed globally, as new paradigms often satisfy prior pain points while possibly introducing new ones. The recent abstraction of systemic patterns into a boxology provides an opening for aligning the requirements and use cases of knowledge engineering with the systems, components, and software that can satisfy them best, however, this direction has not been explored to date. This paper proposes a vision of harmonizing the best practices in the field of knowledge engineering by leveraging the software engineering methodology of creating reference architectures. We describe how a reference architecture can be iteratively designed and implemented to associate user needs with recurring systemic patterns, building on top of existing knowledge engineering workflows and boxologies. We provide a six-step roadmap that can enable the development of such an architecture, consisting of scope definition, selection of information sources, architectural analysis, synthesis of an architecture based on the information source analysis, evaluation through instantiation, and, ultimately, instantiation into a concrete software architecture. We provide an initial design and outcome of the definition of architectural scope, selection of information sources, and analysis. As the remaining steps of design, evaluation, and instantiation of the architecture are largely use-case specific, we provide a detailed description of their procedures and point to relevant examples. We expect that following through on this vision will lead to well-grounded reference architectures for knowledge engineering, will advance the ongoing initiatives of organizing the neurosymbolic knowledge engineering space, and will build new links to the software architectures and data science communities.

Knowledge engineering is a discipline that focuses on the creation and maintenance of processes that generate and apply knowledge. Traditionally, knowledge engineering approaches have focused on knowledge expressed in formal languages. The emergence of large language models and their capabilities to effectively work with natural language, in its broadest sense, raises questions about the foundations and practice of knowledge engineering. Here, we outline the potential role of LLMs in knowledge engineering, identifying two central directions: 1) creating hybrid neuro-symbolic knowledge systems; and 2) enabling knowledge engineering in natural language. Additionally, we formulate key open research questions to tackle these directions.

Background: The High-STEACS (High-Sensitivity Troponin in the Evaluation of Patients With Acute Coronary Syndrome) pathway risk stratifies emergency department patients with possible acute coronary syndrome. This study aims to determine if the High-STEACS hs-cTnT (high-sensitivity cardiac troponin T) pathway can achieve the ≥99% negative predictive value (NPV) safety threshold for 30-day cardiac death or myocardial infarction (CDMI) in a multisite US cohort of patients with and without known coronary artery disease (CAD)., Methods: A secondary analysis of the STOP-CP (High-Sensitivity Cardiac Troponin T [Gen 5 STAT Assay] to Optimize Chest Pain Risk Stratification) cohort, which enrolled adult emergency department patients with possible acute coronary syndrome at 8 US sites (January 25, 2017-September 6, 2018). Participants were classified into outpatient and admission dispositions using the High-STEACS hs-cTnT pathway. Known CAD was defined as prior MI, coronary revascularization, or ≥70% coronary stenosis. Outcomes included 30-day CDMI and efficacy, defined as the proportion identified for outpatient disposition. NPVs and negative likelihood ratios for 30-day CDMI were calculated. NPVs were compared between CAD subgroups using a Fisher exact test., Results: Among 1351 patients, 53.2% (719/1351) were male, 31.4% (424/1351) had known CAD, and the mean age was 57.4±12.8 years. At 30 days, CDMI occurred in 13.8% (187/1351). High-STEACS classified 63.4% (857/1351) to outpatient disposition, of which 2.0% (17/857) had 30-day CDMI, corresponding to an NPV of 98.0% (95% CI, 96.8-98.8) and negative likelihood ratio of 0.13 (95% CI, 0.08-0.20). In patients with CAD, 46.9% (199/424) were classified to outpatient disposition, of which 4.0% (8/199) had 30-day CDMI. Among patients without CAD, 71.0% (658/927) were classified to outpatient disposition with 1.4% (9/658) having 30-day CDMI. The NPV for 30-day CDMI was 96.0% (95% CI, 92.2-98.2) in patients with CAD versus 98.6% (95% CI, 97.4-99.4) among patients without CAD ( P =0.04). The negative likelihood ratio for 30-day CDMI among patients with CAD was 0.16 (95% CI, 0.08-0.31) and 0.12 (95% CI, 0.06-0.22) among patients without CAD., Conclusions: The High-STEACS hs-cTnT pathway had high efficacy but was unable to achieve the ≥99% NPV safety threshold for 30-day CDMI., Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02984436.

Introduction: The History, Electrocardiogram, and Troponin (HET) score is a simplified alternative to the HEART score for risk stratifying emergency department (ED) patients with chest pain. This study evaluates the safety and efficacy of the HET score for 30-day cardiac death or myocardial infarction (MI)., Methods: We conducted a secondary analysis of the STOP-CP multisite cohort study. Risk score components were determined prospectively by the treating provider. Patients were classified into low-, intermediate-, and high-risk strata based on HEART and HET scores. Negative predictive value (NPV) was calculated for the primary safety outcome of cardiac death or MI at 30 days. Consistent with prior studies, the commonly accepted threshold of NPV ≥ 99 % was used to define safety. Efficacy was the proportion of patients classified as low risk. NPV and efficacy were compared between HET and HEART scores using generalized score statistic and McNemar's test, respectively., Results: Among 1460 patients, 46.3 % (676/1460) were women and the mean age was 57.6 ± 12.8 years. Cardiac death or MI at 30 days occurred in 12.7 % (186/1460). Among patients with a low-risk HET score, 1.4 % (4/286) experienced 30-day cardiac death or MI, while 2.2 % (12/534) of patients with a low-risk HEART score had 30-day cardiac death or MI. This yielded a NPV for 30-day of 98.6 % (95 % CI 96.5-99.6 %) for the HET score vs 97.8 % (95 % CI 96.1-98.8 %) for the HEART score (p = 0.29).Efficacy of the HET score was 19.6 % (286/1460, 95 % CI 17.6-21.6 %) vs 36.6 % (534/1460, 95 % CI 34.1-39.1 %) for the HEART score (p < 0.001)., Conclusion: In a multisite US cohort study, neither the HET score nor the HEART score achieved a safe NPV. The HET score had significantly lower efficacy than the HEART score., Trial Registration: High-Sensitivity Cardiac Troponin T to Optimize Chest Pain Risk Stratification (STOP-CP; ClinicalTrials.gov: NCT02984436; https://clinicaltrials.gov/ct2/show/NCT02984436)., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:, (Copyright © 2024 Elsevier Inc. All rights reserved.)

Objectives: This study aimed to assess the effectiveness of a continuous quality improvement initiative at the University of Florida Health Physicians practice in reducing the time to administer factor replacement therapy (FRT) for hemophilia patients presenting with bleeding in the emergency department (ED)., Methods: The study, a quasi-experimental, interventional design, was conducted between January 2020 and January 2023. The intervention, implemented in September 2021, involved training ED physicians, creating a specialized medication order set within the electronic health record (EHR), and a rapid triage system. The effectiveness was measured by comparing the time from ED arrival to factor administration before and after the intervention and benchmarking it against the National Bleeding Disorders Foundation's Medical and Scientific Advisory Council (MASAC)-recommended 1-hour timeline for factor administration. An interrupted time series (ITS) analysis with a generalized least squares model assessed the intervention's impact., Results: A total of 43 ED visits (22 pre-intervention and 21 post-intervention) were recorded. Post-intervention, the average time from ED arrival to factor administration decreased from 5.63 to 3.15 hours. There was no significant increase (27% vs. 29%) in the patients receiving factor within 1-hour of ED arrival. The ITS analysis predicted a 20-hour reduction in the average quarterly time to administer factor by the end of the study, an 84% decrease., Conclusions: The quality improvement program decreased the time to administer FRT for patients with hemophilia in the ED. However, the majority of patients did not achieve the 1-hour MASAC-recommended timeline for factor administration after ED arrival., Competing Interests: Scott Martin Vouri is a current employee at Pfizer, Inc., but was previously employed by the UF College of Pharmacy for the duration of this project. Tung T. Wynn is conducting research with Sanofi, Genentech, Takeda, AMAG, and Sobi. Tung T. Wynn's wife was employed by Takeda from June 2023 to October 2023. The remaining authors declare no conflicts of interest., (© 2024 The Authors. Journal of the American College of Emergency Physicians Open published by Wiley Periodicals LLC on behalf of American College of Emergency Physicians.)

Background: The European Society of Cardiology (ESC) 0/1-h high sensitivity troponin T (hs-cTnT) algorithm does not differentiate risk based on known coronary artery disease (CAD: prior myocardial infarction [MI], coronary revascularization, or ≥ 70% coronary stenosis). We recently evaluated its performance among patients with known CAD at 30-days, but little is known about its longer-term risk prediction. The objective of this study is to determine and compare the performance of the algorithm at 90-days among patients with and without known CAD., Methods: We performed a pre-planned subgroup analysis of the STOP-CP cohort, which prospectively enrolled ED patients ≥21 years old with symptoms suggestive of ACS without ST-elevation on initial ECG across 8 US sites (1/25/2017-9/6/2018). Participants with 0- and 1-h hs-cTnT measures (Roche, Basel, Switzerland) were stratified into rule-out, observe, and rule-in groups using the ESC 0/1-h algorithm. Algorithm performance was tested among patients with or without known CAD, as determined by the treating provider. The primary outcome was cardiac death or MI at 90-days. Fisher's exact tests were used to compare 90-day event and rule-out rates between patients with and without known CAD. Negative predictive values (NPVs) for 90-day cardiac death or MI with exact 95% confidence intervals were calculated and compared using Fisher's exact test., Results: The STOP-CP study accrued 1430 patients, of which 31.4% (449/1430) had known CAD. Cardiac death or MI at 90 days was more common in patients with known CAD than in those without [21.2% (95/449) vs. 10.0% (98/981); p < 0.001]. Using the ESC 0/1-h algorithm, 39.6% (178/449) of patients with known CAD and 66.1% (648/981) of patients without known CAD were ruled-out (p < 0.001). Among rule-out patients, 90-day cardiac death or MI occurred in 3.4% (6/178) of patients with known CAD and 1.2% (8/648) without known CAD (p = 0.09). NPV for 90-day cardiac death or MI was 96.6% (95%CI 92.8-98.8) among patients with known CAD and 98.8% (95%CI 97.6-99.5) in patients without known CAD (p = 0.09)., Conclusion: Patients with known CAD who were ruled-out using the ESC 0/1-h hs-cTnT algorithm had a high rate of missed 90-day cardiac events, suggesting that the ESC 0/1-h hs-cTnT algorithm may not be safe for use among patients with known CAD., Trial Registration: High-Sensitivity Cardiac Troponin T to Optimize Chest Pain Risk Stratification (STOP-CP; ClinicalTrials.gov: NCT02984436; https://clinicaltrials.gov/ct2/show/NCT02984436)., Competing Interests: Declaration of competing interest Dr. Ashburn receives funding from AHRQ (R01HS029017). Dr. Snavely receives funding from Abbott, HRSA (1H2ARH399760100), and AHRQ (R01HS029017). Dr. Stopyra receives research funding from HRSA (H2ARH39976–01-00), AHRQ (R01HS029017), AHRQ (1R21HS029234-01A1), The Duke Endowment, Roche Diagnostics, Abbott Laboratories, Pathfast, Genetesis, Cytovale, Forest Devices, Vifor Pharma, and Chiesi Farmaceutici. Dr. Mahler receives funding/support from Roche Diagnostics, Abbott Laboratories, QuidelOrtho, Siemens, Grifols, Pathfast, Beckman Coulter, Genetesis, Cytovale, The Duke Endowment, Brainbox, HRSA (1H2ARH399760100), and AHRQ (R01HS029017). He is a consultant for Roche, Quidel, Abbott, Siemens, Inflammatix, and Radiometer and is the Chief Medical Officer for Impathiq Inc. Dr. Allen receives research funding/support from RocheDiagnostics, Siemens, and Beckman Coulter. He is a consultant for Roche Diagnostics and Beckman Coulter. Dr. Mumma has research support from the NIH (5K08HL130546) and Roche Diagnostics. Dr. McCord receives research funding/support from Beckman Coulter, Roche Diagnostics, Abbott Laboratories, and Siemens. He is a consultant for Beckman Coulter, Roche Diagnostics, and Siemens. Dr. Wilkerson received research funding from Regeneron Pharmaceuticals, Inc., Lilly USA, LLC, BioAge Labs, Inc., Roche Diagnostics, Global Blood Therapeutics, Inc., Novartis Pharmaceuticals, Egetis Therapeutics AB, EndPoint Health, Inc., Blade Therapeutics, Janssen R&D LLC, ProvePharma, Beckton, Dickinson and Company, and Pfizer Inc. He has received research funding from CoapTech, LLC through an NIH/NIDDK grant (R44DK115325). He has received research support in the form of equipment and supplies from Cepheid and Eldon Biologicals A/S. He is an uncompensated advisor to CSL Behring. Dr. Christenson is a consultant for and receives funding/support from Roche Diagnostics, Siemens Healthineers, Beckman Coulter Diagnostics, Beckton Dickinson and Company, Quidel Corp., and Sphingotec GMBH. The other authors report no conflicts., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: The diagnostic performance of the high-sensitivity troponin T (hs-cTnT) 0/2-h algorithm is unclear among U.S. emergency department (ED) patients with acute chest pain., Methods: A preplanned subgroup analysis of the STOP-CP cohort study was conducted. Participants with 0- and 2-h hs-cTnT measures prospectively enrolled at eight U.S. EDs from January 2017 to September 2018 were stratified into rule-out, observation, and rule-in zones using the hs-cTnT 0/2-h algorithm alone and combined with the history, electrocardiogram, age, and risk factor (HEAR) score. The primary outcome was adjudicated 30-day cardiac death or myocardial infarction (CDMI). The sensitivity and negative predictive value (NPV) of the 0/2-h rule-out zone and specificity and positive predictive value (PPV) of the rule-in zone for 30-day CDMI were calculated., Results: Of the 1307 patients accrued, 53.6% (700/1307) were male and 58.6% (762/1307) were White, with a mean ± SD age of 57.5 ± 12.7 years. At 30 days, CDMI occurred in 12.9% (168/1307) of participants. The 0/2-h algorithm ruled out 61.4% (802/1307) of patients. Among rule-out patients, 1.9% (15/802) experienced 30-day CDMI, resulting in a sensitivity of 91.1% (95% confidence interval [CI] 85.7%-94.9%) and NPV of 98.1% (95% CI 96.9%-98.9%). The 0/2-h algorithm ruled in 12.4% (162/1307) patients of whom 61.7% (100/162) experienced 30-day CDMI. The rule-in zone specificity was 94.6% (95% CI 93.1%-95.8%) and PPV was 61.7% (95% CI 53.8%-69.2%) for 30-day CDMI. The 0/2-h algorithm combined with HEAR score ruled out 30.7% (401/1307) of patients with a sensitivity and NPV for 30-day CDMI of 98.2% (95% CI 94.9%-99.6%) and 99.3% (95% CI 97.8%-99.8%), respectively., Conclusions: The hs-cTnT 0/2-h algorithm ruled out most patients. With NPV of <99% for 30-day CDMI, the hs-cTnT 0/2-h algorithm, many emergency physicians may not consider it safe to use for U.S. ED patients. When combined with a low-risk HEAR score, NPV was >99% for 30-day CDMI at the cost of reduced efficacy., (© 2024 The Authors. Academic Emergency Medicine published by Wiley Periodicals LLC on behalf of Society for Academic Emergency Medicine.)