Folate Receptor Alpha Autoantibodies in the Pediatric Acute-Onset Neuropsychiatric Syndrome (PANS) and Pediatric Autoimmune Neuropsychiatric Disorders Associated with Streptococcal Infections (PANDAS) Population.

The folate receptor alpha autoantibodies (FRAAs) are associated with cerebral folate deficiency (CFD) and autism spectrum disorder (ASD). Both of these syndromes have overlapping characteristics with Pediatric Autoimmune Neuropsychiatric Disorders Associated with Streptococcal Infections (PANDAS) and Pediatric Acute-Onset Neuropsychiatric Syndrome (PANS). Thus, we propose that the FRAAs may contribute to the symptomatology of PANS/PANDAS. To test this hypothesis, 1 mL of serum from 47 patients (age range = 6-18 years old) clinically diagnosed with PANS/PANDAS was sent to Vascular Strategies (Plymouth Meeting, PA, USA) for analysis of FRAAs. Moreover, 63.8% of PANS/PANDAS patients (male = 15; female = 15) were found to have either the blocking and/or blinding FRAAs, with 25 (83.3%; male = 14; female = 11) having binding FRAAs, two (6.7%; all female = 2) having blocking FRAAs, and 3 (10%; male = 1; female = 2) having both binding and blocking. Furthermore, surprisingly, ASD was associated with a 0.76 lower binding titer (p = 0.02), and severe tics were associated with a 0.90 higher binding titer (p = 0.01). A case of a FRAA-positive patient is provided to illustrate that a treatment plan including leucovorin can result in symptom improvement in patients with PANS/PANDAS who are FRAA-positive. These data, for the first time, demonstrate that PANS/PANDAS is associated with FRAAs and suggest folate metabolism abnormalities may contribute to PANS/PANDAS symptomatology. Further studies investigating the therapeutic nature of leucovorin in the treatment of PANS/PANDAS are needed. Such studies may open up an alternative, safe, and well-tolerated treatment for those with the PANS/PANDAS diagnosis.

Considerations for reporting variants in novel candidate genes identified during clinical genomic testing.

Since the first novel gene discovery for a Mendelian condition was made via exome sequencing (ES), the rapid increase in the number of genes known to underlie Mendelian conditions coupled with the adoption of exome (and more recently, genome) sequencing by diagnostic testing labs has changed the landscape of genomic testing for rare disease. Specifically, many individuals suspected to have a Mendelian condition are now routinely offered clinical ES. This commonly results in a precise genetic diagnosis but frequently overlooks the identification of novel candidate genes. Such candidates are also less likely to be identified in the absence of large-scale gene discovery research programs. Accordingly, clinical laboratories have both the opportunity, and some might argue a responsibility, to contribute to novel gene discovery which should in turn increase the diagnostic yield for many conditions. However, clinical diagnostic laboratories must necessarily balance priorities for throughput, turnaround time, cost efficiency, clinician preferences, and regulatory constraints, and often do not have the infrastructure or resources to effectively participate in either clinical translational or basic genome science research efforts. For these and other reasons, many laboratories have historically refrained from broadly sharing potentially pathogenic variants in novel genes via networks like Matchmaker Exchange, much less reporting such results to ordering providers. Efforts to report such results are further complicated by a lack of guidelines for clinical reporting and interpretation of variants in novel candidate genes. Nevertheless, there are myriad benefits for many stakeholders, including patients/families, clinicians, researchers, if clinical laboratories systematically and routinely identify, share, and report novel candidate genes. To facilitate this change in practice, we developed criteria for triaging, sharing, and reporting novel candidate genes that are most likely to be promptly validated as underlying a Mendelian condition and translated to use in clinical settings.

Ambulatory Care Coordination Data Gathering and Use.

Care coordination is a crucial component of healthcare systems. However, little is known about data needs and uses in ambulatory care coordination practice. Therefore, the purpose of this study was to identify information gathered and used to support care coordination in ambulatory settings. Survey respondents (33) provided their demographics and practice patterns, including use of electronic health records, as well as data gathered and used. Most of the respondents were nurses, and they described varying practice settings and patterns. Although most described at least partial use of electronic health records, two respondents described paper documentation systems. More than 25% of respondents gathered and used most of the 72 data elements, with collection and use often occurring in multiple locations and contexts. This early study demonstrates significant heterogeneity in ambulatory care coordination data usage. Additional research is necessary to identify common data elements to support knowledge development in the context of a learning health system.

Using a chat-based informed consent tool in large-scale genomic research.

OBJECTIVE: We implemented a chatbot consent tool to shift the time burden from study staff in support of a national genomics research study. MATERIALS AND METHODS: We created an Institutional Review Board-approved script for automated chat-based consent. We compared data from prospective participants who used the tool or had traditional consent conversations with study staff. RESULTS: Chat-based consent, completed on a user's schedule, was shorter than the traditional conversation. This did not lead to a significant change in affirmative consents. Within affirmative consents and declines, more prospective participants completed the chat-based process. A quiz to assess chat-based consent user understanding had a high pass rate with no reported negative experiences. CONCLUSION: Our report shows that a structured script can convey important information while realizing the benefits of automation and burden shifting. Analysis suggests that it may be advantageous to use chatbots to scale this rate-limiting step in large research projects.

Managing High Cardiac Output Failure in a Patient With Hereditary Hemorrhagic Telangiectasias During Pregnancy.

Hemorrhagic telangiectasias is a rare genetic vascular disorder that may complicate pregnancy. We report a case of a pregnant hemorrhagic telangiectasias patient with innumerable hepatic arteriovenous malformations that developed high output cardiac failure necessitating delivery. Postpartum, the patient was treated with bevacizumab that resulted in clinical improvement.

Increased diagnostic yield from negative whole genome-slice panels using automated reanalysis.

We evaluated the diagnostic yield using genome-slice panel reanalysis in the clinical setting using an automated phenotype/gene ranking system. We analyzed whole genome sequencing (WGS) data produced from clinically ordered panels built as bioinformatic slices for 16 clinically diverse, undiagnosed cases referred to the Pediatric Mendelian Genomics Research Center, an NHGRI-funded GREGoR Consortium site. Genome-wide reanalysis was performed using Moon™, a machine-learning-based tool for variant prioritization. In five out of 16 cases, we discovered a potentially clinically significant variant. In four of these cases, the variant was found in a gene not included in the original panel due to phenotypic expansion of a disorder or incomplete initial phenotyping of the patient. In the fifth case, the gene containing the variant was included in the original panel, but being a complex structural rearrangement with intronic breakpoints outside the clinically analyzed regions, it was not initially identified. Automated genome-wide reanalysis of clinical WGS data generated during targeted panels testing yielded a 25% increase in diagnostic findings and a possibly clinically relevant finding in one additional case, underscoring the added value of analyses versus those routinely performed in the clinical setting.

Perinatal Health Outcomes Across Rural and Nonrural Counties Within a Single Health System Catchment.

Background: Perinatal health outcomes are influenced by a variety of socioeconomic, behavioral, and economic factors that reduce access to health services. Despite these observations, rural communities continue to face barriers, including a lack of resources and the fragmentation of health services. Objective: To evaluate patterns in health outcomes, health behaviors, socioeconomic vulnerability, and sociodemographic characteristics across rural and nonrural counties within a single health system catchment area. Methods: Socioeconomic vulnerability metrics, health care access as determined by licensed provider metrics, and behavioral data were obtained from FlHealthCHARTS.gov and the County Health Rankings. County-level birth and health data were obtained from the Florida Department of Health. The University of Florida Health Perinatal Catchment Area (UFHPCA) was defined as all Florida counties where ≥5% of all infants were delivered at Shands Hospital between June 2011 and April 2017. Results: The UFHPCA included 3 nonrural and 10 rural counties that represented more than 64,000 deliveries. Nearly 1 in 3 infants resided in a rural county, and 7 out of 13 counties did not have a licensed obstetrician gynecologist. Maternal smoking rates (range 6.8%-24.8%) were above the statewide rate (6.2%). Except for Alachua County, breastfeeding initiation rates (range 54.9%-81.4%) and access to household computing devices (range 72.8%-86.4%) were below the statewide rate (82.9% and 87.9%, respectively). Finally, we found that childhood poverty rates (range 16.3%-36.9%) were above the statewide rate (18.5%). Furthermore, risk ratios suggested negative health outcomes for residents of counties within the UFHPCA for each measure, except for infant mortality and maternal deaths, which lacked sample sizes to adequately test. Conclusions: The health burden of the UFHPCA is characterized by rural counties with increased maternal death, neonatal death, and preterm birth, as well as adverse health behaviors that included increased smoking during pregnancy and lower levels of breastfeeding relative to nonrural counties. Understanding perinatal health outcomes across a single health system has potential to not only estimate community needs but also facilitate planning of health care initiatives and interventions in rural and low-resource communities.

Identifying High-Need Primary Care Patients Using Nursing Knowledge and Machine Learning Methods.

BACKGROUND: Patient cohorts generated by machine learning can be enhanced with clinical knowledge to increase translational value and provide a practical approach to patient segmentation based on a mix of medical, behavioral, and social factors. OBJECTIVES: This study aimed to generate a pragmatic example of how machine learning could be used to quickly and meaningfully cohort patients using unsupervised classification methods. Additionally, to demonstrate increased translational value of machine learning models through the integration of nursing knowledge. METHODS: A primary care practice dataset (N = 3,438) of high-need patients defined by practice criteria was parsed to a subset population of patients with diabetes (n = 1233). Three expert nurses selected variables for k-means cluster analysis using knowledge of critical factors for care coordination. Nursing knowledge was again applied to describe the psychosocial phenotypes in four prominent clusters, aligned with social and medical care plans. RESULTS: Four distinct clusters interpreted and mapped to psychosocial need profiles, allowing for immediate translation to clinical practice through the creation of actionable social and medical care plans. (1) A large cluster of racially diverse female, non-English speakers with low medical complexity, and history of childhood illness; (2) a large cluster of English speakers with significant comorbidities (obesity and respiratory disease); (3) a small cluster of males with substance use disorder and significant comorbidities (mental health, liver and cardiovascular disease) who frequently visit the hospital; and (4) a moderate cluster of older, racially diverse patients with renal failure. CONCLUSION: This manuscript provides a practical method for analysis of primary care practice data using machine learning in tandem with expert clinical knowledge.

"Development and Implementation of Novel Chatbot-based Genomic Research Consent".

Objective: To conduct a retrospective analysis comparing traditional human-based consenting to an automated chat-based consenting process. Materials and Methods: We developed a new chat-based consent using our IRB-approved consent forms. We leveraged a previously developed platform (GiaⓇ, or "Genetic Information Assistant") to deliver the chat content to candidate participants. The content included information about the study, educational information, and a quiz to assess understanding. We analyzed 144 families referred to our study during a 6-month time period. A total of 37 families completed consent using the traditional process, while 35 families completed consent using Gia. Results: Engagement rates were similar between both consenting methods. The median length of the consent conversation was shorter for Gia users compared to traditional (44 vs. 76 minutes). Additionally, the total time from referral to consent completion was faster with Gia (5 vs. 16 days). Within Gia, understanding was assessed with a 10-question quiz that most participants (96%) passed. Feedback about the chat consent indicated that 86% of participants had a positive experience. Discussion: Using Gia resulted in time savings for both the participant and study staff. The chatbot enables studies to reach more potential candidates. We identified five key features related to human-centered design for developing a consent chat. Conclusion: This analysis suggests that it is feasible to use an automated chatbot to scale obtaining informed consent for a genomics research study. We further identify a number of advantages when using a chatbot.

Peripartum women's perspectives on research study participation in the OneFlorida Clinical Research Consortium during COVID-19 pandemic.

Introduction: The COVID-19 pandemic created an unprecedented need for population-level clinical trials focused on the discovery of life-saving therapies and treatments. However, there is limited information on perception of research participation among perinatal populations, a population of particular interest during the pandemic. Methods: Eligible respondents were 18 years or older, were currently pregnant or had an infant (≤12 months old), and lived in Florida within 50 miles of sites participating in the OneFlorida Clinical Research Consortium. Respondents were recruited via Qualtrics panels between April and September 2020. Respondents completed survey items about barriers and facilitators to participation and answered sociodemographic questions. Results: Of 533 respondents, most were between 25 and 34 years of age (n = 259, 49%) and identified as White (n = 303, 47%) and non-Hispanic (n = 344, 65%). Facebook was the most popular social media platform among our respondents. The most common barriers to research participation included poor explanation of study goals, discomforts to the infant, and time commitment. Recruitment through healthcare providers was perceived as the best way to learn about clinical research studies. When considering research participation, "myself" had the greatest influence, followed by familial ties. Noninvasive biological samples were highly acceptable. Hispanics had higher positive perspectives on willingness to participate in a randomized study (p = 0.009). Education (p = 0.007) had significant effects on willingness to release personal health information. Conclusion: When recruiting women during the pregnancy and postpartum periods for perinatal studies, investigators should consider protocols that account for common barriers and preferred study information sources. Social media-based recruitment is worthy of adoption.

Zonular and capsular bag disorders: a hypothetical perspective based on recent pathophysiological insights.

The purpose of this article was to look at the pathophysiology behind and devise a classification system for the causes of zonular apparatus-capsular bag (ZACB) insufficiency. Also discussed is dystrophic bag syndrome, including clinical cases and addressing where it lies on the ZACB spectrum. There has been interest in the emergence of in-the-bag intraocular lens (IOL) subluxation, the prevalence of which is increasing. There has also been a recent report of dead bag syndrome, which the authors believe is part of the same disease spectrum. The authors put these phenomena into perspective and provide a classification system based on the possible causes of what they have termed ZACB insufficiency. The basic aspects of capsular bag-IOL ocular pathophysiology are summarized with a focus on functional aspects and the consequences for IOL fastening. Within this framework, dystrophic bag syndrome is a form of primary capsular ZACB insufficiency. The contribution of factors such as intraocular drugs may suggest a reconsideration of agents used and their mode of application.

The effect of abnormal placentation on maternal serum fetal fraction of cell-free DNA.

OBJECTIVES: Abnormal placentation may affect the maternal serum fraction of cell-free fetal DNA (fetal fraction) determined as part of non-invasive prenatal screening (NIPS). This study aimed to assess whether the fetal fraction can predict placenta accreta spectrum (PAS) with or without placenta previa (PP). We also investigated the impact of trophoblastic invasion depth on the fetal fraction. METHODS: This is a retrospective case-control study of pregnant women with and without abnormal placentation carrying a singleton and having undergone NIPS prior to 20 weeks of gestation. The eligible subjects were selected from a cohort managed at our institution for PAS suspected antenatally. We compared women with normal placentation (controls) to PAS, PP, or PAS + PP cases. Data were abstracted from electronic medical records, and PAS was confirmed histologically. RESULTS: Of the 146 patients in our cohort, 8 controls, 10 PP, 6 PAS, and 7 PAS + PP cases were eligible for the study. Among the groups, there were no significant differences in baseline demographic and clinical characteristics except the median number of prior uterine surgeries. Also, the groups did not significantly differ in their median fetal fraction. The fetal fraction did not discriminate any group when stratified according to the depth of placental invasion, i.e., no PAS, abnormally adherent, and abnormally invasive placenta. CONCLUSIONS: The maternal serum fraction of cell-free fetal DNA measured before 20 weeks of gestation is not predictive of PAS with or without concurrent PP or the depth of trophoblastic invasion.

Psychometric Evaluation of the Affect Regulation Checklist: Clinical and Community Samples, Parent-Reports and Youth Self-Reports.

The Affect Regulation Checklist (ARC) was designed to capture affect dysregulation, suppression, and reflection. Importantly, affect dysregulation has been established as a transdiagnostic mechanism underpinning many forms of psychopathology. We tested the ARC psychometric properties across clinical and community samples and through both parent-report and youth self-report information. Clinical sample: Participants included parents (n = 814; Mage = 43.86) and their child (n = 608; Mage = 13.98). Community sample: Participants included independent samples of parents (n = 578; Mage = 45.12) and youth (n = 809; Mage = 15.67). Exploratory structural equation modeling supported a three-factor structure across samples and informants. Dysregulation was positively associated with all forms of psychopathology. In general, suppression was positively associated with many forms of psychopathology, and reflection was negatively associated with externalizing problems and positively associated with internalizing problems.

KAMRA presbyopic inlay refractive outcomes: a Canadian perspective.

OBJECTIVE: To retrospectively analyze the visual outcomes of KAMRA (AcuFocus Inc, Irvine, Calif.) inlay insertion in a cohort of patients reporting success of procedure, complications, patient satisfaction, and refractive outcomes. DESIGN: Retrospective trial at the TLC Laser Centre, Toronto. METHODS: A total of 5 surgeons at the practice inserted 35 KAMRA inlays in 35 patients between October 2012 and June 2014. Some patients had a sole KAMRA inlay insertion, whereas others had combined laser vision correction (LVC) and KAMRA inlay on either the same day or sequentially. There was a small cohort of patients who had previous unrelated LVC. Mean time of follow-up was 299 days. RESULTS: After KAMRA inlay insertion there was a significant improvement in uncorrected near visual acuity (p = 0.00009), uncorrected intermediate visual acuity (p = 0.00006), and uncorrected distance visual acuity (p = 0.02), but levels of patient dissatisfaction were 43%. The most common cause for dissatisfaction was requirements for readers (23%), followed by dysphotopsias (11%). The explantation rate was 11.42%, and 28.5% of patients required enhancements after inlay insertion. CONCLUSIONS: The KAMRA corneal inlay has significant improvements in uncorrected near visual acuity, uncorrected intermediate visual acuity, and uncorrected distance visual acuity when used in isolation or combined with LVC. Appropriate patient selection is crucial. This procedure should not be used as first-line presbyopia management because of low levels of patient satisfaction, biocompatibility concerns, and explantation rates.

Inpatient clinician workload: a scoping review protocol to understand the definition, measurement and impact of non-procedural clinician workloads.

INTRODUCTION: Clinicians that care for hospitalised patients face unprecedented work conditions with exposure to highly infectious disease, exceedingly high patient numbers, and unpredictable work demands, all of which have resulted in increases in stress and burnout. Preliminary studies suggest that increasing workloads negatively affect inpatient clinician well-being and may negatively affect job performance; yet high workloads may be prioritised secondary to financial drivers or from workforce shortages. Despite this, the correlation between workload and these negative outcomes has not been fully quantified. Additionally, there are no clear measures for inpatient clinician workload and no standards to define ideal workloads. Using the protocol described here, we will perform a scoping review of the literature to generate a comprehensive understanding of how clinician workload of medical patients is currently defined, measured in clinical settings and its impact on the workforce, patients and institutional outcomes. METHODS AND ANALYSIS: We will follow the methodology outlined by Joanna Briggs Institute and Arksey and O'Malley to conduct a comprehensive search of major electronic databases including Ovid Medline (PubMed), Embase (Embase.com), PsycINFO, ProQuest Dissertations and Google Scholar. All relevant published peer-reviewed and dissertaion grey literature will be included. Data will be extracted using a standardised form to capture key article information. Results will be presented in a descriptive narrative format. ETHICS AND DISSEMINATION: This review does not require ethics approval though all included studies will be screened to ensure appropriate approval. The synthesis of this literature will provide a better understanding of the current state of work for inpatient clinicians, associated outcomes, and will identify gaps in the literature. These findings will be used in conjunction with an expert Delphi panel to identify measures of inpatient clinician workload to then guide the development of a novel workforce mobile application to actively track clinician work. We aim to lay the groundwork for future workforce studies to understand the optimal workloads that drive key outcomes for clinicians, patients and institutions.

Uninsurance in North Carolina: Progress and Opportunities.

Virtually all of the Healthy North Carolina 2030 goals rely on access to affordable health care. This commentary provides an overview of how North Carolina's coverage gap impacts the state's health status and how expanding Medicaid could improve the odds of reaching Healthy NC 2030 goals.

Using Artificial Intelligence-based Methods to Address the Placebo Response in Clinical Trials.

The placebo response is a highly complex psychosocial-biological phenomenon that has challenged drug development for decades, particularly in neurological and psychiatric disease. While decades of research have aimed to understand clinical trial factors that contribute to the placebo response, a comprehensive solution to manage the placebo response in drug development has yet to emerge. Advanced data analytic techniques, such as artificial intelligence (AI), might be needed to take the next leap forward in mitigating the negative consequences of high placebo-response rates. The objective of this review was to explore the use of techniques such as AI and the sub-discipline of machine learning (ML) to address placebo response in practical ways that can positively impact drug development. This examination focused on the critical factors that should be considered in applying AI and ML to the placebo response issue, examples of how these techniques can be used, and the regulatory considerations for integrating these approaches into clinical trials.

Lens Epithelial Cell Removal in Routine Phacoemulsification: Is It Worth the Bother?

PURPOSE: To review the literature on crystalline lens epithelial cell (LEC) removal in routine phacoemulsification and determine whether it should be incorporated as part of a surgeon's standard technique. DESIGN: Perspective. METHODS: Expert commentary with video demonstrations on techniques of removal of LECs and associated potential complications. Discussion incorporates the importance of LEC removal, a review of techniques to prevent posterior capsular opacification (PCO), and the effects of intraocular lens design on LEC proliferation and PCO. RESULTS: The evidence suggests that LEC removal should be routinely performed as it can be carried out safely and with considerable short- and long-term benefits for patients. With effective cleanup, there is reduced anterior capsule opacification, fibrosis, and decentration of the capsular bag as well as reduced rates of posterior capsular opacification. Techniques for removal are easy to learn, with very low complication rates, and can reduce the risk of the long-term need for technically complex procedures such as intraocular lens explantation. CONCLUSIONS: LEC removal from both the anterior and posterior capsule is part of a continuous, incremental improvement of cataract surgery and should be introduced to ophthalmology trainees during their formative years as part of their regular cataract surgery armamentarium.

Intraocular lens explantation following cataract surgery: Indications, techniques, and video demonstrations.

As techniques for modern cataract surgery have expanded and premium intraocular lens (IOL) use is now widespread, patient expectations are high. The need for IOL explantation, whilst still low, remains an ongoing issue. Intraocular lens explantation can be challenging for a number of reasons and as such we have introduced an additional technique to add to the surgeon's repertoire. Bimanual haptic stripping of fibrosis at the specific area where the haptic is adherent to the capsular bag is an effective strategy to aid in dissection of haptics without compromising the capsule or zonules. Given the challenges associated with IOL explantation, newly designed IOLs need to avoid these "sticking points" at which the IOLs interact with the fibrosed capsule. Techniques we have evolved and which are described below should assist anterior segment surgeons to facilitate IOL removal in an efficient and safe way.