Citations

Abstract Background To ensure the Pediatric Infectious Diseases (ID) Certifying Examination remains aligned with current clinical practice, the American Board of Pediatrics (ABP) conducted a comprehensive practice analysis to update the exam content outline. Methods A panel of 9 pediatric ID physicians identified 34 core tasks across 5 performance domains to guide revisions to the existing outline. The panel identified relevant, testable knowledge areas aligned with these tasks and organized them into 22 domains and 186 initial subdomains. A nationwide validation survey of board-certified pediatric ID physicians collected relevance ratings and feedback on missing or outdated topics and suggested exam weights, which were used to guide further revisions. Subsequently, the pediatric ID subboard conducted an item reclassification process, which resulted in additional refinement. Results The final content outline comprises 22 domains and 196 subdomains, with updated domain weights to better reflect the clinical landscape. Notably, domains such as cardiovascular, bone and joint, and urologic infections increased in weight, while antimicrobial principles decreased. Conclusions This rigorous, inclusive process strengthens the exam’s content validity and supports the ABP’s goal of certifying physicians who possess the knowledge needed to deliver safe and effective care.

Abstract Background X and Y chromosome analysis is a critical component of genetic testing, used both diagnostically and as a quality control (QC) metric. Discordances between expected and observed sex chromosome data can arise due to mislabeling, demographic data errors, transplant history, or biological variations. Such discordances pose challenges to laboratories and affect patient care, particularly in marginalized populations and unique clinical contexts. Methods We reviewed cases of sex chromosome discordance identified at our laboratory from January 2021 through August 2023. Cases spanned various testing methods and were categorized by the root cause, including mislabeling, sample mix-ups, transgender individuals, stem cell transplants, and unexplained causes. Case outcomes were assessed, and potential resolutions were analyzed. Results Among 65 cases identified, the leading cause of discordance was mislabeling (n = 20, 31%), followed by other/not identified (n = 16, 25%), sample mix-ups (n = 13, 20%), transgender individuals (n = 9, 14%), and stem cell transplants (n = 7, 11%). Cases required additional QC processes such as reanalysis, clinician contact, and occasionally sample re-collection. The process extended turnaround times by up to 13 business days. Detailed case reviews highlighted the challenges and implications of managing these discordances, emphasizing the importance of accurate data transmission and inclusive practices. Conclusion Using X and Y chromosome data as a QC metric can identify critical errors but also introduces limitations and bias. Improved standardization, inclusive practices, and alternative QC methods are necessary to ensure accuracy and equitable patient care. Collaborative efforts are required to address demographic complexities and reduce testing delays.

Abstract With the goal of preventing more hip fractures, a next generation of the VirtuOst Biomechanical Computed Tomography (BCT) test was developed that integrates measurements from a clinical CT scan related to fall risk, impact force, and femoral strength, the three main determinants of hip fracture. Here, we introduce the test and validate it against BMD and FRAX. Our source population from a large healthcare system comprised of 341364 patients (≥65 yr) with an abdominal-pelvic CT during care. Using data from 3035 patients (1790 with hip fracture), we developed a “BCT Risk Score” (range: 0-100) having input risk factors of age, femoral strength, ratio of trabecular/cortical BMD, muscle area, intramuscular fat, FN volume, hip width, and posterior fat thickness. In a geographically distinct set of 2124 patients (1293 with hip fracture), we then compared the BCT Risk Score against a DXA-equivalent hip BMD T-score (lowest hip value, measured from the CT scan by VirtuOst) and FRAX hip fracture risk (with BMD but without parental fracture history) for predicting a first incident hip fracture within 5 yr. For the women, the c-statistic for predicting fracture was higher for BCT (0.89, 95% CI: 0.87-0.90) than for BMD (0.81, 0.79-0.84) or FRAX (0.85, 0.83-0.87). Using binary thresholds to identify high-risk patients, sensitivity for BCT (Risk Score ≥ 75) was higher than for BMD (T-score ≤ −2.5) and FRAX (hip risk ≥ 3.0%): 81.4% vs 47.8% vs 75.9%, respectively; positive predictive values confirmed comparable high-risk status (BCT 13.6% vs BMD 15.3% vs FRAX 12.7%). Similar trends were observed for the men, 2-yr outcomes, and identifying very-high-risk patients. We conclude that, compared to both BMD and FRAX, the integrative BCT test better predicted hip fracture and its high sensitivity should improve fracture prevention.

Abstract Importance and Objective Upadacitinib, an oral, reversible Janus kinase inhibitor, is approved for the treatment of moderate-to-severe Crohn’s disease (CD). Limiting corticosteroid exposure is an important goal in treating CD. This posthoc analysis evaluated the corticosteroid-sparing effects of upadacitinib in patients with CD. Design and Setting This study included pooled data from two phase 3, multicenter, double-blind induction trials and one maintenance trial. Randomization was stratified by corticosteroid use at induction baseline, with a mandatory corticosteroid taper starting at induction week 4. Efficacy was evaluated by baseline corticosteroid use and by achieving corticosteroid-free outcomes through year 2 of maintenance therapy. Safety was also assessed. Results At baseline, 34.7% (234/674) and 35.7% (124/347) of upadacitinib 45 mg and placebo-treated patients were taking corticosteroids, respectively. At induction week 12 and maintenance week 52, higher rates of upadacitinib-treated patients were corticosteroid-free among all patients and among patients with baseline corticosteroid use compared with placebo; upadacitinib-treated patients achieved higher rates of corticosteroid-free outcomes, compared with placebo, including corticosteroid-free clinical remission (stool frequency/abdominal pain score [SF/APS]: 42.7% vs 16.1%; CD activity index [CDAI]: 41.2% vs 23.4%) and corticosteroid-free endoscopic response (37.0% vs 8.1%), with similar results observed among responders to upadacitinib induction therapy at maintenance week 52. Corticosteroid-free outcomes were sustained through year 2 of maintenance therapy. The safety profile was similar to the overall population, with no new safety risks identified. Conclusions and Relevance The results from pivotal studies demonstrated that upadacitinib effectively induced early and sustainable corticosteroid-free clinical remission with a manageable safety profile in patients with moderate-to-severe CD. Clinical trial identifiers U-EXCEL, U-EXCEED, and U-ENDURE ClinicalTrials.gov numbers, NCT03345849, NCT03345836, and NCT03345823.

Abstract Introduction This study investigated the impact of visual editing of sleep recordings for use in predicting neurodegenerative disorder (NDD) risk. Methods All participants underwent in-home Sleep Profiler studies. Forty-four were diagnosed with mild cognitive impartment (MCI = 40) or Alzheimer’s disease (AD = 4)(MCI/AD: 55% women, 72.6+/-8.6 years), 26 with REM sleep behavior disorder (RBD: women = 27%, age = 67+/-9.8), and 29 were controls (NC: women = 69%, age = 63+/-11.5). A 4-class machine learning algorithm used age plus eight sleep biomarkers to assign NDD risk probabilities. Records with CG-assigned probabilities >70% were labeled Probably-Normal, and from 45-70% Likely-Normal. Similar thresholds were used to assign Likely- or Probably-Abnormal. NDD risk characterizations were generated based on auto-scoring (“auto”), and again after the recordings were visually edited for accuracy (“edited”). Results Comparing the auto- vs. edited-NDD classifications in the MCI/AD group, the same NDD risk classifications were observed in 91% (39/43), with 2 cases shifting from Likely-Normal to Probably-Normal, one shifted from Likely-AD to Likely-Normal with AD Indications, and one changed from Probably-AD to Likely-AD. The same NDD risk classifications were observed in 81% (21/26) of the RBD cases, 3 shifted from Probably-Abnormal to Likely-Abnormal, one shifted from Likely-Normal to Probably-Normal, and one changed from Likely-Abnormal to Likely-Normal. The same NDD risk classifications were observed in 86% of the NC group, with 4 cases shifting from Likely-Normal to Probably-Normal. Conclusions These findings suggest that the likelihood of a gross misclassification of NDD risk resulting from auto-detected sleep biomarkers is relatively low with inconsistencies directed toward slightly increased NDD risk classifications.

Abstract Introduction This study investigated differences in opinions about neurodegenerative disorders (NDD) in countries with large populations and expanded access to healthcare. Methods A 5-point Likert scale survey assessed opinions of 30–59-year-olds, pertaining to their parents and NDD conditions. 100 surveys, translated into native languages, were acquired in eight developed countries. Positive (somewhat- or strongly-agree) vs. other responses, sex, and country were submitted to logistic regression and Chi-squared analyses. Results “It is important for me to know if my parent has a risk for developing a NDD condition in the future, even if nothing can be currently done to prevent or cure those diseases” had higher positive responses in Australia (92%) compared to Germany (74%) and the USA (78%). “I believe that knowing about my parent’s risk for developing a NDD condition will help me assist in the planning of their future” had higher number of positive responses in Australia (91%) versus Japan (70%), Germany (76%), Italy (80%) and UK (80%). “If my parent(s) was found to be at risk for a NDD condition, I would want to learn more about medications and adaptive therapies that could delay onset” was responded to more positively in Australia (92%), Canada (78%), France (87%), Germany (78%), Italy (88%), UK (88%), and USA (81%) versus Japan (60%). Conclusions Australians responded more positively to questions related to care of a parent with a NDD disorder. These findings suggest cultural differences that could influence education and support systems requirements for sleep medicine providers and NDD patients.

ABSTRACT Background As head and neck cancer survival rates improve, there is growing demand for quality survivorship care and tools to predict patient adherence; this study aims to evaluate an advanced practice provider ( APP )‐led survivorship clinic and assess these key metrics. Methods We performed a retrospective review of 213 head and neck cancer patients treated with curative radiation therapy between 2016 and 2023, to assess follow‐up adherence in an advanced practice provider–led survivorship clinic. Results With a median follow‐up of 2.4 years, follow‐up care metrics identified high completion percentages (> 90%) for lung cancer screening, smoking cessation, thyroid screening, dental evaluation, xerostomia, dysphagia, and dysgeusia. The HOUsing ‐based SocioEconomic Status ( HOUSES ) index at diagnosis showed a significant adherence difference (median percentile, 78% vs. 55%, adherent vs. nonadherent; p = 0.03). Conclusions High adherence rates with guideline‐defined care metrics are achievable in an advanced practice provider‐led head and neck cancer survivorship clinic. The HOUSES index may assist in predicting nonadherence; however, further studies are needed.

Developing a scalable multi-layer AI adoption model for 6P medicine (Predictive, Preventive, Personalized, Participatory, Precision-oriented, and Public-centered) requires careful consideration of computational infrastructure, data processing and integration, healthcare-specific requirements, security and privacy, performance optimization, and system interoperability. The described multi-layer architecture in this work provides a flexible conceptual model to accommodate the diverse needs of AI implementation in different healthcare domains while maintaining scalability, security, governance, and efficiency.