Bethesda University is a private Christian university in Anaheim, California. It was founded in 1976 by David Yonggi Cho. The university is accredited by the Association for Biblical Higher Education and the Transnational Association of Christian Colleges and Schools and it is approved by the Bureau for Private Postsecondary Education of the State of California.
The diagnosis of idiopathic pulmonary fibrosis (IPF) is predicated on high-resolution computed tomography (HRCT) patterns, elimination of a secondary cause of interstitial lung (ILD) and histopathology when necessary. The Fairfax IPF Clinical Score (FICS) integrates 8 parameters weighted to estimate the clinical probability of IPF within an ILD population. The aim of this study was to evaluate risk stratification for IPF by a diverse panel of independent clinicians in comparison to the FICS. A series of 16 cases were randomly selected from a French ILD tertiary hospital (8 IPF and 8 non-IPF ILD), with their diagnoses established through multidisciplinary discussion. Demographic and clinical data were provided to 15 French and American pulmonologists, 8 of whom work in ILD tertiary care centers. They were asked to evaluate the probability of IPF for each case (defined as low < 30
Abstract Objective To perform a systematic review and meta‐analysis on the utility of circulating tumor DNA (ctDNA) in serum as a biomarker for post‐treatment surveillance of human papillomavirus (HPV)‐positive oropharyngeal squamous cell carcinoma (OPSCC), given the improved treatment response and 10% to 20% recurrence rate in this patient population. Data Sources Articles were sourced from PubMed. Studies were excluded if they focused on HPV‐driven cancers in other anatomical regions, lacked pretreatment and posttreatment HPV viral load data, or were published more than 20 years ago. All literature available in English was considered. Review Methods A PRISMA‐compliant review identified 419 articles, and 20 studies met all inclusion criteria. Data extraction and quality assessment were performed using Oxford Centre for Evidence‐Based Medicine and Newcastle‐Ottawa Scale criteria. Results Across 3505 clinically correlated tests, pooled sensitivity was 80.3% (95% CI 70.9%‐87.2%) and specificity was 95.5% (90.9%‐97.8%). Meta‐analysis of our studies found the overall prevalence of recurrent HPV + OPSCC after curative treatment was 9.70% (95% CI 8.72%‐10.78%). Negative Predictive Value (NPV) at this prevalence was 97.7% (96.7%‐98.5%) and Positive Predictive Value (PPV) was 66.0% (49.5%‐80.3%). A positive test for ctDNA after curative treatment had a 130.3 (95% CI 56.60‐298.71) fold higher odds of disease recurrence compared to a negative test. Conclusions CtDNA is a promising biomarker for early detection of recurrence. Standardized protocols and quantitative thresholds are needed to fully establish its role in clinical practice.
The National Board of Medical Examiners' decision to change Step 1 of the United States Medical Licensing Examination (USMLE) from a three-digit score to Pass/Fail (P/F) represents a disruptive change for students, faculty, and leaders in the academic community. In the context of this change, some schools may re-consider the optimal timing of Step 1 as they strive to align their assessment practices with sound educational principles. Currently, over 20 schools administer USMLE Step 1 after the core clerkships. In this commentary, we review the educational rationale for a post-clerkship Step 1, highlighting how adult learning theories support this placement. We discuss some short-term challenges post-clerkship Step 1 schools may encounter due to the proposed timing of the change in scoring, which creates three unique scenarios for learners that can introduce inequity in the system and provoke anxiety. We review outcomes of potentially heightened importance when Step 1 is P/F, including lower clinical subject exam scores in some clerkships, lower failure rates on Step 1 and stable Step 2 Clinical Knowledge scores with implications for the residency match. We outline the future potential for performance-based time-variable Step 1 study periods that are facilitated by post-clerkship placement of the exam. Finally, we discuss opportunities to achieve the goal of enhancing student well-being, which was a major rationale for eliminating the three-digit score.
In this chapter, we will demonstrate how to query and clone data in the Snowflake Data Cloud. We will provide examples of SQL queries to show you how to get required information out of the data in tables and views within Snowflake. You will also learn how to clone data within Snowflake, which is one of its key differentiated features.
In this chapter, we will cover how the Snowflake Data Cloud handles semi-structured data such as JSON and XML. As data capture and sources have grown significantly in the last few years especially, semi-structured data has also grown. JSON semi-structured data especially grew significantly with the popularity of NoSQL databases. It has become essential for organizations to be able to process semi-structured data and combine it with structured data for analysis. However, analyzing semi-structured data using traditional methods has been more difficult due to added levels of complexity. Many businesses have struggled to combine structured with semi-structured data. Most analytical cloud databases also treated semi-structured data as a second-class data, making it hard to easily use both semi-structured data and structured data.
