Assessing Risk Factors for Cognitive Decline Using Electronic Health Record Data: A Scoping Review.

Background: The data and information contained within electronic health records (EHR) provide a rich, diverse, longitudinal view of real-world patient histories, offering valuable opportunities to study antecedent risk factors for cognitive decline. However, the extent to which such records' data have been utilized to elucidate the risk factors of cognitive decline remains unclear. Methods: A scoping review was conducted following the PRISMA guideline, examining articles published between January 2010 and April 2023, from PubMed, Web of Science, and CINAHL. Inclusion criteria focused on studies using EHR to investigate risk factors for cognitive decline. Each article was screened by at least two reviewers. Data elements were manually extracted based on a predefined schema. The studied risk factors were classified into categories, and a research gap was identified. Results: From 1,593 articles identified, 80 were selected. The majority (87.5%) were retrospective cohort studies, with 66.3% using datasets of over 10,000 patients, predominantly from the US or UK. Analysis showed that 48.8% of studies addressed medical conditions, 31.3% focused on medical interventions, and 17.5% on lifestyle, socioeconomic status, and environmental factors. Most studies on medical conditions were linked to an increased risk of cognitive decline, whereas medical interventions addressing these conditions often reduced the risk. Conclusions: EHR data significantly enhanced our understanding of medical conditions, interventions, lifestyle, socioeconomic status, and environmental factors related to the risk of cognitive decline.

Orthopaedic Surgery Residency Program Websites: Assessing Information Gaps and Opportunities for Attracting Applicants.

INTRODUCTION: The quality and volume of information on orthopaedic surgery residency program websites are helpful for informed decision making of prospective applicants. The purpose of this study was to evaluate the content on orthopaedic surgery residency program websites and identify areas for improvement. METHODS: In November 2023, 203 orthopaedic surgery residency programs were reviewed using the Association of American Medical Colleges Residency Explorer tool. Fourteen nonfunctional websites were excluded, leaving n = 189. Websites were assessed for 11 variables: resources for assisting resident research (eg, biomechanics laboratory, research assistant, and advisors), residents' past institutional affiliations, current resident profiles (including hometown and interests), alumni data, fellowship matches, American Board of Orthopedic Surgery I/II pass rates, Alpha Omega Alpha Society affiliation, target United States Medical Licensing Examination/ Comprehensive Osteopathic Medical Learning Exam Step 2 scores, educational activities (journal club, grand rounds, didactics), evaluation methods, and mentorship. RESULTS: Website variables differed markedly among identified program types, which included community programs, university programs (UPs), and affiliated programs (APs). Disparities were noted in the disclosure of residents' previous institutions ( P = 0.001), the availability of alumni names ( P = 0.001), research resources ( P = 0.001), academic activities ( P = 0.007), assigned mentorship programs ( P = 0.006), and fellowship match information ( P = 0.027). Notably, community programs shared statistically significantly less information in these areas compared with UPs and APs ( P = 0.001). While there was a proportionate sharing of information between UPs and APs, UPs exhibited a slightly higher overall percentage of websites sharing more detailed information. CONCLUSION: The quality and comprehensiveness of information on orthopaedic surgery residency program websites vary markedly. Most of the orthopaedic surgery residency programs provided information on residents' past institutions and academic activities. However, very few provided information on designated mentorship programs or objective measures such as target Step 2 examination scores and ABOS pass rates. Improving the quality of information available on program websites will enhance transparency and consistency, enabling prospective applicants to make more informed decisions about where to apply and interview.

Phase response theory explains cluster formation in sparsely but strongly connected inhibitory neural networks and effects of jitter due to sparse connectivity.

We show how to predict whether a neural network will exhibit global synchrony (a one-cluster state) or a two-cluster state based on the assumption of pulsatile coupling and critically dependent upon the phase response curve (PRC) generated by the appropriate perturbation from a partner cluster. Our results hold for a monotonically increasing (meaning longer delays as the phase increases) PRC, which likely characterizes inhibitory fast-spiking basket and cortical low-threshold-spiking interneurons in response to strong inhibition. Conduction delays stabilize synchrony for this PRC shape, whereas they destroy two-cluster states, the former by avoiding a destabilizing discontinuity and the latter by approaching it. With conduction delays, stronger coupling strength can promote a one-cluster state, so the weak coupling limit is not applicable here. We show how jitter can destabilize global synchrony but not a two-cluster state. Local stability of global synchrony in an all-to-all network does not guarantee that global synchrony can be observed in an appropriately scaled sparsely connected network; the basin of attraction can be inferred from the PRC and must be sufficiently large. Two-cluster synchrony is not obviously different from one-cluster synchrony in the presence of noise and may be the actual substrate for oscillations observed in the local field potential (LFP) and the electroencephalogram (EEG) in situations where global synchrony is not possible. Transitions between cluster states may change the frequency of the rhythms observed in the LFP or EEG. Transitions between cluster states within an inhibitory subnetwork may allow more effective recruitment of pyramidal neurons into the network rhythm. NEW & NOTEWORTHY We show that jitter induced by sparse connectivity can destabilize global synchrony but not a two-cluster state with two smaller clusters firing alternately. On the other hand, conduction delays stabilize synchrony and destroy two-cluster states. These results hold if each cluster exhibits a phase response curve similar to one that characterizes fast-spiking basket and cortical low-threshold-spiking cells for strong inhibition. Either a two-cluster or a one-cluster state might provide the oscillatory substrate for neural computations.