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Diabetes is a chronic condition that has reached epidemic proportions in the United States, affecting nearly 34 million adults, and disproportionately affecting vulnerable populations, such as ethnic minorities, the elderly and individuals with low socioeconomic status. This study addresses the impact of the Health Extension for Diabetes (HED) program, a community-based diabetes self-management support program, on adult diabetes self-care behaviors. The Summary of Diabetes Self-Care Activities (SDSCA) was utilized to evaluate improvement in diabetes self-care behaviors. Descriptive statistics, univariate and multivariable regression models were conducted. Significant increases were observed among program participants (N = 149) in all five subscales of the SDSCA (general diet, specific diet, blood glucose testing, exercise and foot care; "P"-values < 0.001). A priority of this diabetes education program was helping underserved populations; over half (62%) of participants self-identified as Black/African Americans. After program participation, scores on all SDSCA subscales increased significantly among Black/African Americans (n = 93) by approximately 1 day per week. White/other races (n = 56) showed similar increases in four of the SDSCA subscales post-HED program participation. This study shows that increasing participation in community-based, diabetes self-management support programs, such as HED, can increase engagement in diabetes self-care behaviors among underserved groups.

Objective: The American Diabetes Association Standards of Care recommends that individuals with diabetes receive self-management education, but the utilization of these services remains low. This study explores primary care providers' knowledge and perceptions of diabetes self-management education and support (DSMES)., Study Design: A convergent mixed methods study design grounded in the Theoretical Domains Framework was conducted with an initial provider survey, followed by semi-structured interview of a purposeful sub-sample of providers. The survey was distributed via REDCap and interviews were recorded and transcribed verbatim., Results: A total of 140 PCP's responded to the survey (response rate 37.63 %) and 17 participated in interviews. The average knowledge score of the correct selection of DSMES referral time points was 70.35 %. Five themes emerged in provider interviews: procedural knowledge, ability, beliefs, reinforcement, and cultural norms. Providers wanted bidirectional communication with the DSMES program and were more likely to refer if they had a cultural norm of referring., Conclusion: Providers have limited knowledge of the appropriate time to refer to DSMES but expressed a willingness to refer. They emphasized the importance of providing their patients with appropriate self-management education and support., Competing Interests: Declaration of Competing Interest The authors have no conflicts of interest to disclose., (Copyright © 2024 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.)

Objectives: Mobile health clinics (MHCs) effectively provide healthcare to underserved communities. However, their application during health emergencies is understudied. We described the implementation of an MHC program delivering vaccinations during the COVID-19 pandemic, examined the program's reach to medically underserved communities, and investigated characteristics of vaccination uptake in order to inform the utility of MHCs during health emergencies., Study Design: The study observed COVID-19 MHC vaccination rates and factors associated with uptake between February 20th, 2021, and February 17th, 2022., Methods: Prisma Health deployed six MHCs to underserved communities. We described the characteristics of individuals who utilized the MHCs and evaluated census tract-level community factors associated with use of the MHCs through generalized linear mixed effects models., Results: The MHCs conducted 260 visits at 149 unique sites in South Carolina, providing 12,102 vaccine doses to 8545 individuals: 2890 received a partial dose, 4355 received a primary series, and 1300 received a booster dose. Among individuals utilizing the MHC, the median age was 42 years (IQR: 22-58), 44.0 % were Black, 49.2 % were male, and 44.2 % were uninsured. Black, Hispanic, and uninsured individuals were significantly more likely to utilize MHC services for COVID-19 vaccination. During periods when vaccines were limited, MHC utilization was significantly greater in communities facing access barriers to healthcare., Conclusions: The high COVID-19 vaccination uptake at MHCs demonstrated that the MHC framework is an effective and acceptable intervention among medically underserved populations during health emergencies, especially when resources are scarce. The identified factors associated with vaccination uptake demonstrated that the MHCs had the greatest impact in higher-risk communities and can be used to inform allocation of such field-level interventions in future health emergencies., Competing Interests: This study was funded by the National Library of Medicine of the National Institutes of Health and the Center for Forecasting and Outbreak Analytics of the Centers for Disease Control and Prevention. The MHC program was supported by The Greenville County CARES Program; the Coronavirus Aid, Relief, and Economic Security Act; and Prisma Health. LR, FG, IJ, KJB, AHL, and KKS received support from the National Library of Medicine of the National Institutes of Health (R01LM014193) during this study; LR, FG, KAH, KJB, AHL, and KKS received support from the Centers for Disease Control and Prevention (NU38FT000011). The funders had no role in the design, conduct, reporting of the study, or decision to submit for publication.This study was funded by the National Library of Medicine of the National Institutes of Health and the Center for Forecasting and Outbreak Analytics of the Centers for Disease Control and Prevention. The MHC program was supported by The Greenville County CARES Program as part of a Covid-19 Funding Program. LR, FG, IJ, KJB, AHL, and KKS received support from the National Library of Medicine of the National Institutes of Health (R01LM014193) during this study; LR, FG, KAH, KJB, AHL, and KKS received support from the Centers for Disease Control and Prevention (NU38FT000011). The funders had no role in the design, conduct, reporting of the study, or decision to submit for publication., (© 2024 The Authors.)

Clinical decision support systems (CDSS) are routinely employed in clinical settings to improve quality of care, ensure patient safety, and deliver consistent medical care. However, rule-based CDSS, currently available, do not feature reusable rules. In this study, we present CDSS with reusable rules. Our solution includes a common CDSS module, electronic medical record (EMR) specific adapters, CDSS rules written in the clinical quality language (CQL) (derived from CDC immunization recommendations), and patient records in fast healthcare interoperability resources (FHIR) format. The proposed CDSS is entirely browser-based and reachable within the user's EMR interface at the client-side. This helps to avoid the transmission of patient data and privacy breaches. Additionally, we propose to provide means of managing and maintaining CDSS rules to allow the end users to modify them independently. Successful implementation and deployment were achieved in OpenMRS and OpenEMR during initial testing.

Ontology is essential for achieving health information and information technology application interoperability in the biomedical fields and beyond. Traditionally, ontology construction is carried out manually by human domain experts (HDE). Here, we explore an active learning approach to automatically identify candidate terms from publications, with manual verification later as a part of a deep learning model training and learning process. We introduce the overall architecture of the active learning pipeline and present some preliminary results. This work is a critical and complementary component in addition to manually building the ontology, especially during the long-term maintenance stage.

Background: Children and youth with special health care needs (CYSHCN) comprise 23 % of the pediatric population in South Carolina (SC), compared to state prevalences of 13.6 %-24 % nationwide. While occupational therapy (OT) is critical to maximizing CYSHCN's participation in daily activities, there are significant disparities in rehabilitation access in the Southeast region., Objective: This study examines associations between patient-and community-level factors and outpatient OT utilization., Methods: This study analyzes OT utilization data among CYSHCN (N = 1913) in a health system in SC from 07/01/2022-06/31/2023, merged with Child Opportunity Index 2.0 zip-code level social drivers of health (SDOH) data. SDOH are non-medical factors that affect individual's long-term health, with estimates ranging from "very low" to "very high" opportunity. Structural equation modeling was conducted to understand complex associations between observed and latent variables in a real-world context., Results: CYSHCN were diagnosed with congenital (40.77 %), developmental (37.87 %), and neurological/neuromuscular conditions (21.36 %). CYSHCN who were non-Hispanic Black or Hispanic and were hospitalized were associated with living in lower opportunity areas. CYSHCN with private or military/other insurance/self-pay were associated with living in higher opportunity areas than Medicaid-insured CYSHCN. CYSHCN who were female and ≥12 years demonstrated lower OT utilization. CYSHCN who participated in speech and/or physical therapy demonstrated higher OT utilization. OT utilization increased with each increase in SDOH., Conclusion: With these findings, healthcare providers may consider accessibility barriers, including transportation, when referring CYSHCN to OT services. Further research is needed to examine the impact of household-level SDOH on OT access across SC., Competing Interests: Declaration of competing interest Authors have indicated no conflicts of interest to report., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Children with medical complexity (CMC) comprise < 1% of the pediatric population, but account for nearly one-third of healthcare expenditures. Further, while CMC account for up to 80% of pediatric inpatient hospital costs, only 2% of Medicaid spending is attributed to home healthcare. As a result, the current health system heavily relies on family caregivers to fill existing care gaps. This study aimed to: (1) examine factors associated with hospital admissions among CMC and (2) contextualize the potential for home nursing care to improve outcomes among CMC and their families in South Carolina (SC)., Methods: This mixed-methods study was conducted among CMC, their family caregivers, and physicians in SC. Electronic health records data from a primary care clinic within a large health system (7/1/2022-6/30/2023) was analyzed. Logistic regression examined factors associated with hospitalizations among CMC. In-depth interviews (N = 15) were conducted among physicians and caregivers of CMC statewide. Patient-level quantitative data is triangulated with conceptual findings from interviews., Results: Overall, 39.87% of CMC experienced ≥ 1 hospitalization in the past 12 months. CMC with higher hospitalization risk were dependent on respiratory or neurological/neuromuscular medical devices, not non-Hispanic White, and demonstrated higher healthcare utilization. Interview findings contextualized efforts to reduce hospitalizations, and suggested adaptations related to capacity and willingness to provide complex care for CMC and their families., Conclusions: Findings may inform multi-level solutions for accessible, high-quality home nursing care among CMC and their families. Providers may learn from caregivers' insight to emphasize family-centered care practices, acknowledging time and financial constraints while optimizing the quality of medical care provided in the home., (© 2024. The Author(s).)

Background: Opioid overdose and related diseases remain a growing public health crisis in the USA. Identifying sociostructural and other contextual factors associated with adverse health outcomes is needed to improve prediction models to inform policy and interventions. We aimed to identify high-risk communities for targeted delivery of screening and prevention interventions for opioid use disorder and hepatitis C virus (HCV)., Methods: In this ecological and modelling study, we fit mixed-effects negative binomial regression models to identify factors associated with, and predict, opioid-related and HCV-related hospitalisations for ZIP code tabulation areas (ZCTAs) in South Carolina, USA. All individuals aged 18 years or older living in South Carolina from Jan 1, 2016, to Dec 31, 2021, were included. Data on opioid-related and HCV-related hospitalisations, as well as data on additional individual-level variables, were collected from medical claims records, which were obtained from the South Carolina Revenue and Fiscal Affairs Office. Demographic and socioeconomic variables were obtained from the United States Census Bureau (American Community Survey, 2021) with additional structural health-care barrier data obtained from South Carolina's Center for Rural and Primary Health Care, and the American Hospital Directory., Findings: Between Jan 1, 2016, and Dec 31, 2021, 41 691 individuals were hospitalised for opioid misuse and 26 860 were hospitalised for HCV. There were a median of 80 (IQR 24-213) opioid-related hospitalisations and 61 (21-196) HCV-related hospitalisations per ZCTA. A standard deviation increase in ZCTA-level uninsured rate (relative risk 1·24 [95% CI 1·17-1·31]), poverty rate (1·24 [1·17-1·31]), mortality (1·18 [1·12-1·25]), and social vulnerability index (1·17 [1·10-1·24]) was significantly associated with increased combined opioid-related and HCV-related hospitalisation rates. A standard deviation increase in ZCTA-level income (0·79 [0·75-0·84]) and unemployment rate (0·87 [0·82-0·93]) was significantly associated with decreased combined opioid-related and HCV-related hospitalisations. Using 2016-20 hospitalisations as training data, our models predicted ZCTA-level opioid-related hospitalisations in 2021 with a median of 80·4% (IQR 66·8-91·1) accuracy and HCV-related hospitalisations in 2021 with a median of 75·2% (61·2-87·7) accuracy. Several underserved high-risk ZCTAs were identified for delivery of targeted interventions., Interpretation: Our results suggest that individuals from economically disadvantaged and medically under-resourced communities are more likely to have an opioid-related or HCV-related hospitalisation. In conjunction with hospitalisation forecasts, our results could be used to identify and prioritise high-risk, underserved communities for delivery of field-level interventions., Funding: South Carolina Center for Rural and Primary Healthcare, National Institute on Drug Abuse, and National Library of Medicine., Competing Interests: Declaration of interests FG, AHL, and LR received salary support from South Carolina Center for Rural and Primary Healthcare (SCCRPH2015593). FG, AHL, LR, and NKM received salary support from the National Institute on Drug Abuse (R61DA059892) and the National Library of Medicine (R01 LM014193) during this study. LR and AHL received support from the Health Resources and Services Administration (HRSA HB1RH47075-01-00) during this study. KAH declares no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: University spring break carries a two-pronged SARS-CoV-2 variant transmission risk. Circulating variants from universities can spread to spring break destinations, and variants from spring break destinations can spread to universities and surrounding communities. Therefore, it is critical to implement SARS-CoV-2 variant surveillance and testing strategies to limit community spread before and after spring break to mitigate virus transmission and facilitate universities safely returning to in-person teaching., Methods: We examined the SARS-CoV-2 positivity rate and changes in variant lineages before and after the university spring break for two consecutive years. 155 samples were sequenced across four time periods: pre- and post-spring break 2021 and pre- and post-spring break 2022; following whole genome sequencing, samples were assigned clades. The clades were then paired with positivity and testing data from over 50,000 samples., Results: In 2021, the number of variants in the observed population increased from four to nine over spring break, with variants of concern being responsible for most of the cases; Alpha percent composition increased from 22.2% to 56.4%. In 2022, the number of clades in the population increased only from two to three, all of which were Omicron or a sub-lineage of Omicron. However, phylogenetic analysis showed the emergence of distantly related sub-lineages. 2022 saw a greater increase in positivity than 2021, which coincided with a milder mitigation strategy. Analysis of social media data provided insight into student travel destinations and how those travel events may have impacted spread., Conclusions: We show the role that repetitive testing can play in transmission mitigation, reducing community spread, and maintaining in-person education. We identified that distantly related lineages were brought to the area after spring break travel regardless of the presence of a dominant variant of concern., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: SW is currently employed by Illumina. BK, SP, JP, RD, LI, and AS are employed by Labcorp. The other authors declare no competing interest. This does not alter our adherence to PLOS ONE policies on sharing data and materials., (Copyright: © 2024 Napolitano et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objective: Assessment of predictive values of clinical symptoms for COVID-19 diagnosis in young adults. Participants: Nonresidential university students (ages 18-25) participating in surveillance testing and mandatory symptom survey between 9/9/2020 and 11/25/2020. Methods: Retrospective study of test results and symptom survey data. Results: Among 6,489 individuals, 288 (4.4%) tested positive for COVID-19, 90 (31.3%) of whom reported symptoms. COVID-19 prevalence among individuals reporting and not reporting symptoms was 17.2% and 3.3%, respectively. The four symptoms with highest positive predictive values (PPVs) were smell/taste loss (PPV = 38.5%), chills (PPV = 31.5%), muscle/joint pain (PPV = 26.0%), and fever (PPV = 25.9%). Conclusions: Institutions should emphasize COVID-19 risk for highly predictive symptoms in public health messaging to inform individuals on when to seek testing or self-isolation. However, low COVID-19 diagnostic accuracy of clinical symptoms and the high pre-symptomatic/asymptomatic rate (69%) highlight the limitations of voluntary testing strategies employed by higher education institutions during the original strain of SARS-CoV-2.

Institutions have an enhanced ability to implement tailored mitigation measures during infectious disease outbreaks. However, macro-level predictive models are inefficient for guiding institutional decision-making due to uncertainty in local-level model input parameters. We present an institutional-level modeling toolkit used to inform prediction, resource procurement and allocation, and policy implementation at Clemson University throughout the Covid-19 pandemic. Through incorporating real-time estimation of disease surveillance and epidemiological measures based on institutional data, we argue this approach helps minimize uncertainties in input parameters presented in the broader literature and increases prediction accuracy. We demonstrate this through case studies at Clemson and other university settings during the Omicron BA.1 and BA.4/BA.5 variant surges. The input parameters of our toolkit are easily adaptable to other institutional settings during future health emergencies. This methodological approach has potential to improve public health response through increasing the capability of institutions to make data-informed decisions that better prioritize the health and safety of their communities while minimizing operational disruptions., (© 2024. The Author(s).)

Background: Although treatment for Hepatitis C Virus (HCV) is effective, individuals face access barriers. The utility of mobile health clinics (MHC), effective mechanisms for providing healthcare to underserved populations, is understudied for HCV-related interventions. We aimed to describe implementation of, and factors associated with, screening and treatment via MHCs., Methods: Clemson Rural Health implemented a novel MHC program to reach and treat populations at-risk for HCV with a focus on care for uninsured individuals. We examined HCV screening and treatment initiation/completion indicators between May 2021 and January 2023., Findings: Among 607 individuals screened across 31 locations, 94 (15.5%) tested positive via antibody and viral load testing. Treatment initiation and completion rates were 49.6% and 86.0%, respectively. Among those screened, the majority were male (57.5%), White (61.3%; Black/Hispanic: 28.2%/7.7%), and without personal vehicle as primary transportation mode (54.4%). Injection drug use (IDU) was 27.2% and uninsured rate was 42.8%. Compared to HCV-negative, those infected included more individuals aged 30-44 (52.1% vs. 36.4%, p  = 0.023), male (70.2% vs. 55.2%, p  = 0.009), White (78.5% vs. 60.2%, p  < 0.0001), without personal vehicle (58.5% vs. 43.5%, p  = 0.028), IDU (83.7% vs. 21.0%, p  < 0.0001), and uninsured (61.2% vs. 48.8%, p  = 0.050). Uninsured rates were higher among those initiating compared to not initiating treatment (74.5% vs. 45.3%, p  = 0.004)., Interpretation: The MHC framework successfully reaching its target population: at-risk individuals with access barriers to healthcare. The high HCV screening and treatment initiation/completion rates demonstrate the utility of MHCs as effective and acceptable intervention settings among historically difficult-to-treat populations., Funding: Gilead Sciences, Inc., and SC Center for Rural and Primary Healthcare., Competing Interests: The program was supported by Gilead Sciences, Inc., (IN-US-987-5892) with additional funding specifically for uninsured patients from South Carolina Center for Rural and Primary Healthcare (2015593). KB, RG, CMK, PR, and AHL received support from South Carolina Center for Rural and Primary Healthcare during this study. KB, CMK, and AC received support from Gilead Sciences, Inc., during this study. KB received support for leading a round table discussion at a conference from International Network on Health and Hepatitis in Substance Users, speaking on a panel at a conference from Gilead Sciences, Inc., and travel to a conference from International Network on Health and Hepatitis in Substance Users. LR and FG received support from the National Library of Medicine of the National Institutes of Health (R01 LM014193-01A1) during this study. The funders had no role in the design, conduct, reporting of the study, or decision to submit for publication. Payments were made to our institution. AHL has served on the advisory boards for Gilead Sciences, Inc., and AbbVie., (© 2023 The Author(s).)

Objective: The goals of this study were to determine whether completion of a community-based diabetes self-management support (DSMS) program delivered through a university Cooperative Extension network increased Patient Activation Measure (PAM) scores and to examine predictors of improvement in PAM score in individuals participating in the DSMS., Methods: The Health Extension for Diabetes (HED) is a 4-month program delivered via a paraprofessional extension agent in partnership with an established diabetes self-management education and support program. The study population included 148 adults (median age 69 years; interquartile range 60-74 years) with diabetes recruited from local community organizations. Data for the analysis were collected before and after participation in the intervention as part of a longitudinal study, using the PAM and Self-Efficacy for Diabetes instruments. Descriptive statistics were gathered, and hypothesis tests and simple and multivariable regression analyses were conducted., Results: The mean PAM score increased by 6.58 points, with a 5-point change considered clinically significant. From pre- to post-intervention, PAM scores significantly decreased for 23 participants, decreased for 6, did not change for 14, increased for 21, and significantly increased for 84. Higher pre-intervention PAM scores, younger age, greater educational attainment, and higher baseline self-efficacy scores were associated with increased post-intervention PAM scores when not controlling for potential covariates. Age was no longer associated with higher PAM scores after controlling for covariates., Conclusion: Community-based DSMS interventions can be effective in generating positive change in individuals' activation. HED provides a feasible and accessible DSMS option that addresses key diabetes self-management components while effectively improving individuals' activation. It is recommended that people living with diabetes attend a DSMS program such as HED to increase their ability to effectively self-manage various components of their chronic condition., Competing Interests: No potential conflicts of interest relevant to this article were reported., (© 2023 by the American Diabetes Association.)

Prior research suggests that food security status may have an effect on the home food environment. Further, the literature suggests that food access factors may function to influence said relationship. The purpose of this research is to fill a gap in the literature on this relationship, as well as to identify potential food access effect modifiers. This research employs linear mixed effects modeling with a random intercept variable (zip codes). Eleven food access variables are included in regression analyses and are tested as potential effect modifiers in the association between food security status and the home food environment. Food security status is significantly associated with the home food environment (95% CI = 0.1-1.38) in the unadjusted model. In the adjusted model, food pantry usage is found to be a significant effect modifier on the association between food security status and the home food environment. This research concludes that food security status has a significant but disparate effect on the home food environment depending on participant food pantry usage. Practical implications from this research would be for relevant stakeholders to potentially improve rural food pantry access in order to increase the home food environment among rural and food insecure populations.

Background: Cognitive reserve (CR) is the ability to maintain cognitive performance despite brain pathology. CR is built through lifecourse experiences (e.g., education) and is a key construct in promoting healthy aging. However, the operationalization of CR and its estimated association with late-life cognition varies. The purpose of this study was to systematically examine the operationalization of CR and the relationship between its operationalization and late-life cognition., Methods: We performed a comprehensive review of experiences (proxies) used to operationalize CR. The review informed quantitative analyses using data from 1366 participants of the Memory and Aging Project to examine 1) relationships between proxies and 2) the relationship between operationalization and late-life cognition. We also conducted a factor analysis with all identified CR experiences to create a composite lifecourse CR score. Generalized linear mixed models examined the relationship between operationalizations and global cognition, with secondary outcomes of five domains of cognition to examine consistency., Results: Based on a review of 753 articles, we found the majority (92.3%) of the 28 commonly used proxies have weak to no correlation between one another. There was substantial variability in the association between operationalizations and late-life global cognition (median effect size: 0.99, IQR: 0.34 to 1.39). There was not strong consistency in the association between CR operationalizations and the five cognitive domains (mean consistency: 56.1%). The average estimate for the 28 operationalizations was 0.91 (SE = 0.48), compared to 2.48 (SE = 0.40) for the lifecourse score and it was associated with all five domains of cognition., Conclusions: Inconsistent methodology is theorized as a major limitation of CR research and barrier to identification of impactful experiences for healthy cognitive aging. Based on the weak associations, it is not surprising that the relationship between CR and late-life cognition is dependent on the experience used to operationalize CR. Scores using multiple experiences across the lifecourse may help overcome such limitations. Adherence to a lifecourse approach and collaborative movement towards a consensus operationalization of CR are imperative shifts in the study of CR that can better inform research on risk factors related to cognitive decline and ultimately aid in the promotion of healthy aging., (© 2023. BioMed Central Ltd., part of Springer Nature.)

There is growing concern about the over-prescription of opioids and the risks of long-term use. This study examined the relationship between initial need (pre-operative, post-operative, and discharge pain) and dosage of opioids in the first prescription after surgery with continued opioid use through opioid refills over 12 months, while considering patient-level characteristics. A total of 9262 opioid-naïve patients underwent elective surgery, 7219 of whom were prescribed opioids following surgery. The results showed that 17% of patients received at least one opioid refill within one year post-surgery. Higher initial opioid doses, measured in morphine milligram equivalent (MME), were associated with a greater likelihood of continued use. Patients receiving a dose greater than 90 MME were 1.57 times more likely to receive a refill compared to those receiving less than 90 MME (95% confidence interval: 1.30-1.90, p < 0.001). Additionally, patients who experienced pain before or after surgery were more likely to receive opioid refills. Those experiencing moderate or severe pain were 1.66 times more likely to receive a refill (95% confidence interval: 1.45-1.91, p < 0.001). The findings highlight the need to consider surgery-related factors when prescribing opioids and the importance of developing strategies to balance the optimization of pain management with the risk of opioid-related harms.

Objectives: Overprescribing to opioid-naive surgical patients substantially contributes to opioid use disorders, which have become increasingly prevalent. Opioid stewardship programs (OSPs) within healthcare settings provide an avenue for introducing interventions to regulate prescribing. This study examined the association of OSP policies limiting exposure on changes in surgery-related opioid prescriptions and patient pain., Methods: We evaluated policies implemented by an OSP in a large American healthcare system between 2016 and 2018: nonopioid medication during surgery, decrease of available opioid dosage vials in operating rooms, standardization of opioid in-patient practices through electronic health record alerts, and limit to postsurgery opioid supply. Generalized linear mixed effects models examined the association of interventions with outcome changes in 9262 opioid-naive patients undergoing elective surgery. Outcomes were discharge pain, morphine milligram equivalent in the first prescription postsurgery, and opioid prescription refills., Results: Decreases in all prescription outcomes and discharge pain were observed following onset of OSP interventions ( P 's < 0.001). Among individual policies, standardization of in-patient prescribing practices was associated with the strongest decrease in prescribed morphine milligram equivalent. Importantly, there was no evidence of an increase in discharge pain related to any intervention., Conclusions: This study promotes the potential of OSP formation and policies to reduce opioid prescribing without compromising patient pain. The most effective policy, standardization of in-patient prescribing practices through alerts, suggests that reminding prescribers to re-evaluate the patient's need is effective in changing behavior. The findings offer considerations for OSP formation and policy implementation across health systems to improve quality and safety in opioid prescribing., Competing Interests: The authors disclose no conflict of interest., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Phelan-McDermid syndrome (PMS) is a multisystem disorder that is associated with deletions of the 22q13 genomic region or pathogenic variants in the SHANK3 gene. Notable features include developmental issues, absent or delayed speech, neonatal hypotonia, seizures, autism or autistic traits, gastrointestinal problems, renal abnormalities, dolichocephaly, and both macro- and microcephaly. Assessment of the genetic factors that are responsible for abnormal head size in PMS has been hampered by small sample sizes as well as a lack of attention to these features. Therefore, this study was conducted to investigate the relationship between head size and genes on chromosome 22q13. A review of the literature was conducted to identify published cases of 22q13 deletions with information on head size to conduct a pooled association analysis. Across 56 studies, we identified 198 cases of PMS with defined deletion sizes and head size information. A total of 33 subjects (17%) had macrocephaly, 26 (13%) had microcephaly, and 139 (70%) were normocephalic. Individuals with macrocephaly had significantly larger genomic deletions than those with microcephaly or normocephaly ( p < 0.0001). A genomic region on 22q13.31 was found to be significantly associated with macrocephaly with CELSR1 , GRAMD4 , and TBCD122 suggested as candidate genes. Investigation of these genes will aid the understanding of head and brain development.

The coronavirus pandemic has brought about global change in travel behavior. Transit ridership volumes have dropped to record lows. Concerning environmental, health, and social consequences lie in store if transit networks are not able to regain a substantial portion of pre-pandemic users. Transit providers have implemented several interventions aimed at both slowing the spread of the virus and retaining riders as travel restrictions lift. While the effectiveness of these measures has been evaluated with respect to spread rate reduction, little consideration has been given to their impact on riders' feelings of worry regarding virus contraction. By deploying a photo-simulation approach in a randomized control trial, this study finds that level of compliance with safety measures and the conditions of transit spaces themselves significantly impact riders' levels of worry. Given these findings, a series of recommendations are made regarding compliance practices that are expected to lessen rider worry regarding the risks of COVID-19 infection., Competing Interests: None., (© 2022 The Authors.)

Background: Clinical decision support systems (CDSSs) are important for the quality and safety of health care delivery. Although CDSS rules guide CDSS behavior, they are not routinely shared and reused., Objective: Ontologies have the potential to promote the reuse of CDSS rules. Therefore, we systematically screened the literature to elaborate on the current status of ontologies applied in CDSS rules, such as rule management, which uses captured CDSS rule usage data and user feedback data to tailor CDSS services to be more accurate, and maintenance, which updates CDSS rules. Through this systematic literature review, we aim to identify the frontiers of ontologies used in CDSS rules., Methods: The literature search was focused on the intersection of ontologies; clinical decision support; and rules in PubMed, the Association for Computing Machinery (ACM) Digital Library, and the Nursing & Allied Health Database. Grounded theory and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines were followed. One author initiated the screening and literature review, while 2 authors validated the processes and results independently. The inclusion and exclusion criteria were developed and refined iteratively., Results: CDSSs were primarily used to manage chronic conditions, alerts for medication prescriptions, reminders for immunizations and preventive services, diagnoses, and treatment recommendations among 81 included publications. The CDSS rules were presented in Semantic Web Rule Language, Jess, or Jena formats. Despite the fact that ontologies have been used to provide medical knowledge, CDSS rules, and terminologies, they have not been used in CDSS rule management or to facilitate the reuse of CDSS rules., Conclusions: Ontologies have been used to organize and represent medical knowledge, controlled vocabularies, and the content of CDSS rules. So far, there has been little reuse of CDSS rules. More work is needed to improve the reusability and interoperability of CDSS rules. This review identified and described the ontologies that, despite their limitations, enable Semantic Web technologies and their applications in CDSS rules., (©Xia Jing, Hua Min, Yang Gong, Paul Biondich, David Robinson, Timothy Law, Christian Nohr, Arild Faxvaag, Lior Rennert, Nina Hubig, Ronald Gimbel. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 19.01.2023.)

We aim to estimate the effectiveness of 2-dose and 3-dose mRNA vaccination (BNT162b2 and mRNA-1273) against general Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection (asymptomatic or symptomatic) caused by the omicron BA.1 variant. This propensity-score matched retrospective cohort study takes place in a large public university undergoing weekly Coronavirus Disease 2019 (Covid-19) testing in South Carolina, USA. The population consists of 24,145 university students and employees undergoing weekly Covid-19 testing between January 3 rd and January 31 st , 2022. The analytic sample was constructed via propensity score matching on vaccination status: unvaccinated, completion of 2-dose mRNA series (BNT162b2 or mRNA-1273) within the previous 5 months, and receipt of mRNA booster dose (BNT162b2 or mRNA-1273) within the previous 5 months. The resulting analytic sample consists of 1,944 university students (mean [SD] age, 19.64 [1.42] years, 66.4% female, 81.3% non-Hispanic White) and 658 university employees (mean [SD] age, 43.05 [12.22] years, 64.7% female, 83.3% non-Hispanic White). Booster protection against any SARS-CoV-2 infection was 66.4% among employees (95% CI: 46.1-79.0%; P <.001) and 45.4% among students (95% CI: 30.0-57.4%; P <.001). Compared to the 2-dose mRNA series, estimated increase in protection from the booster dose was 40.8% among employees ( P =.024) and 37.7% among students ( P =.001). We did not have enough evidence to conclude a statistically significant protective effect of the 2-dose mRNA vaccination series, nor did we have enough evidence to conclude that protection waned in the 5-month period after receipt of the 2 nd or 3 rd mRNA dose. Furthermore, we did not find evidence that protection varied by manufacturer. We conclude that in adults 18-65 years of age, Covid-19 mRNA booster doses offer moderate protection against general SARS-CoV-2 infection caused by the omicron variant and provide a substantial increase in protection relative to the 2-dose mRNA vaccination series.

Background: MetaMap is a valuable tool for processing biomedical texts to identify concepts. Although MetaMap is highly configurative, configuration decisions are not straightforward., Objective: To develop a systematic, data-driven methodology for configuring MetaMap for optimal performance., Methods: MetaMap, the word2vec model, and the phrase model were used to build a pipeline. For unsupervised training, the phrase and word2vec models used abstracts related to clinical decision support as input. During testing, MetaMap was configured with the default option, one behavior option, and two behavior options. For each configuration, cosine and soft cosine similarity scores between identified entities and gold-standard terms were computed for 40 annotated abstracts (422 sentences). The similarity scores were used to calculate and compare the overall percentages of exact matches, similar matches, and missing gold-standard terms among the abstracts for each configuration. The results were manually spot-checked. The precision, recall, and F-measure ( β =1) were calculated., Results: The percentages of exact matches and missing gold-standard terms were 0.6-0.79 and 0.09-0.3 for one behavior option, and 0.56-0.8 and 0.09-0.3 for two behavior options, respectively. The percentages of exact matches and missing terms for soft cosine similarity scores exceeded those for cosine similarity scores. The average precision, recall, and F-measure were 0.59, 0.82, and 0.68 for exact matches, and 1.00, 0.53, and 0.69 for missing terms, respectively., Conclusion: We demonstrated a systematic approach that provides objective and accurate evidence guiding MetaMap configurations for optimizing performance. Combining objective evidence and the current practice of using principles, experience, and intuitions outperforms a single strategy in MetaMap configurations. Our methodology, reference codes, measurements, results, and workflow are valuable references for optimizing and configuring MetaMap., Competing Interests: None declared., (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).)

Wastewater surveillance of SARS-CoV-2 RNA has become an important tool for tracking the presence of the virus and serving as an early indicator for the onset of rapid transmission. Nevertheless, wastewater data are still not commonly used to predict the number of infected individuals in a sewershed. The main objective of this study was to calibrate a susceptible-exposed-infectious-recovered (SEIR) model using RNA copy rates in sewage (i.e., gene copies per liter times flow rate) and the number of SARS-CoV-2 saliva-test-positive infected individuals in a university student population that was subject to repeated weekly testing during the Spring 2021 semester. A strong correlation was observed between the RNA copy rates and the number of infected individuals. The parameter in the SEIR model that had the largest impact on calibration was the maximum shedding rate, resulting in a mean value of 7.72 log 10 genome copies per gram of feces. Regressing the saliva-test-positive infected individuals on predictions from the SEIR model based on the RNA copy rates yielded a slope of 0.87 (SE=0.11), which is statistically consistent with a 1:1 relationship between the two. These findings demonstrate that wastewater surveillance of SARS-CoV-2 can be used to estimate the number of infected individuals in a sewershed.

Data on effectiveness and protection duration of Covid-19 vaccines and previous infection against general SARS-CoV-2 infection in general populations are limited. Here we evaluate protection from Covid-19 vaccination (primary series) and previous infection in 21,261 university students undergoing repeated surveillance testing between 8/8/2021-12/04/2021, during which B.1.617 (delta) was the dominant SARS-CoV-2 variant. Estimated mRNA-1273, BNT162b2, and AD26.COV2.S effectiveness against any SARS-CoV-2 infection is 75.4% (95% CI: 70.5-79.5), 65.7% (95% CI: 61.1-69.8), and 42.8% (95% CI: 26.1-55.8), respectively. Among previously infected individuals, protection is 72.9% when unvaccinated (95% CI: 66.1-78.4) and increased by 22.1% with full vaccination (95% CI: 15.8-28.7). Statistically significant decline in protection is observed for mRNA-1273 (P < .001), BNT162b2 (P < .001), but not Ad26.CoV2.S (P = 0.40) or previous infection (P = 0.12). mRNA vaccine protection dropped 29.7% (95% CI: 17.9-41.6) six months post- vaccination, from 83.2% to 53.5%. We conclude that the 2-dose mRNA vaccine series initially offers strong protection against general SARS-CoV-2 infection caused by the delta variant in young adults, but protection substantially decreases over time. These findings indicate that vaccinated individuals may still contribute to community spread. While previous SARS-CoV-2 infection consistently provides moderately strong protection against repeat infection from delta, vaccination yields a substantial increase in protection., (© 2022. The Author(s).)

Truncation is a statistical phenomenon that occurs in many time-to-event studies. For example, autopsy-confirmed studies of neurodegenerative diseases are subject to an inherent left and right truncation, also known as double truncation. When the goal is to study the effect of risk factors on survival, the standard Cox regression model cannot be used when the survival time is subject to truncation. Existing methods that adjust for both left and right truncation in the Cox regression model require independence between the survival times and truncation times, which may not be a reasonable assumption in practice. We propose an expectation-maximization algorithm to relax the independence assumption in the Cox regression model under left, right, or double truncation to an assumption of conditional independence on the observed covariates. The resulting regression coefficient estimators are consistent and asymptotically normal. We demonstrate through extensive simulations that the proposed estimator has little bias and has a similar or lower mean-squared error compared to existing estimators. We implement our approach to assess the effect of occupation on survival in subjects with autopsy-confirmed Alzheimer's disease., (© 2021 The International Biometric Society.)

Background: Higher viral loads in SARS-CoV-2 infections may be linked to more rapid spread of emerging variants of concern (VOC). Rapid detection and isolation of cases with highest viral loads, even in pre- or asymptomatic individuals, is essential for the mitigation of community outbreaks., Methods and Findings: In this study, we analyze Ct values from 1297 SARS-CoV-2 positive patient saliva samples collected at the Clemson University testing lab in upstate South Carolina. Samples were identified as positive using RT-qPCR, and clade information was determined via whole genome sequencing at nearby commercial labs. We also obtained patient-reported information on symptoms and exposures at the time of testing. The lowest Ct values were observed among those infected with Delta (median: 22.61, IQR: 16.72-28.51), followed by Alpha (23.93, 18.36-28.49), Gamma (24.74, 18.84-30.64), and the more historic clade 20G (25.21, 20.50-29.916). There was a statistically significant difference in Ct value between Delta and all other clades (all p.adj<0.01), as well as between Alpha and 20G (p.adj<0.05). Additionally, pre- or asymptomatic patients (n = 1093) showed the same statistical differences between Delta and all other clades (all p.adj<0.01); however, symptomatic patients (n = 167) did not show any significant differences between clades. Our weekly testing strategy ensures that cases are caught earlier in the infection cycle, often before symptoms are present, reducing this sample size in our population., Conclusions: COVID-19 variants Alpha and Delta have substantially higher viral loads in saliva compared to more historic clades. This trend is especially observed in individuals who are pre- or asymptomatic, which provides evidence supporting higher transmissibility and more rapid spread of emerging variants. Understanding the viral load of variants spreading within a community can inform public policy and clinical decision making., Competing Interests: The authors have declared that no competing interests exist.

Background: Although efforts to treat hepatitis C virus (HCV) in people who inject drugs (PWID) yield high rates of sustained virologic response (SVR), the relationship between successful HCV treatment and health-related quality of life (HRQOL) among PWID is poorly understood. We examined HRQOL changes throughout HCV treatment and post-treatment for PWID achieving SVR., Methods: Participants included 141 PWID who achieved SVR following HCV treatment onsite at 3 opioid agonist treatment (OAT) clinics in the Bronx, New York. EQ-5D-3L assesses 5 health dimensions (mobility, self-care, usual activities, pain/discomfort, and anxiety/depression), producing an index of HRQOL ranging from 0 to 1. EQ-5D-3L was measured at baseline; 4, 8, and 12 weeks during treatment; and 12 and 24 weeks post-treatment. Linear mixed effects regression models assessed changes in the mean EQ-5D-3L index over time., Results: Mean EQ-5D-3L index baseline was 0.66 (standard error [SE] = 0.02). While over half the population reported no baseline problems with self-care (85.1%), usual activities (56.0%), and mobility (52.5%), at least two-thirds reported problems with pain/discomfort (78.0%) and anxiety/depression (66.0%). Twenty-four weeks post-treatment, proportions reporting pain/discomfort and anxiety/depression decreased by 25.7% and 24.0%, respectively. Mean EQ-5D-3L index significantly improved during treatment (P < .0001), and improvement was sustained following treatment completion, with mean EQ-5D-3L index of 0.77 (SE = 0.02) 12 weeks post-SVR., Conclusions: HCV treatment led to sustained improvement in HRQOL for PWID on OAT who achieved SVR. Future research is necessary to determine whether improvements in HRQOL can be sustained beyond 12 weeks post-SVR., (© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

Background: Interferon-based regimens exacerbated depressive symptoms, which interfered with treating hepatitis C virus (HCV) among people who inject drugs (PWID). Direct-acting antivirals (DAA) are not associated with worsening depressive symptoms; however, the impact of depressive symptoms on adherence remains little known. We examined the association between depressive symptoms and adherence to DAA among HCV-infected PWID. A secondary aim was to identify the optimal cut-off for major depressive disorder for this population., Methods: Participants were 150 HCV-infected PWID on maintenance treatment enrolled in a randomized clinical trial testing three HCV care models. Severity of depressive symptoms were assessed using the Beck Depression Inventory-II (BDI-II) at baseline and every 4 weeks during treatment. Current major depressive disorder at baseline was diagnosed by the Mini-International Neuropsychiatric Interview. Adherence was measured during treatment (weeks 1-12) using electronic blister packs RESULTS: BDI-II scores ≥ 18 were identified as the optimal threshold for diagnosing major depressive disorder. Participants with BDI scores ≥ 18 at baseline had significantly lower adherence rates at weeks 1-4 of treatment compared to those with BDI scores < 18 (b = -0.23, 95% CI: 0.45-0.01, p = 0.044), but not in any other time intervals (weeks 5-8, b = -0.03, 95% CI: -0.32, 0.26, p = 0.825; weeks 9-12, b = -0.33, 95% CI -0.70, 0.02, p = 0.066)., Conclusions: Elevated depressive symptoms were associated with lower adherence to DAA only during the first 4 weeks of HCV treatment. Neither severe depressive symptoms nor major depressive disorder appears to be a barrier to DAA adherence among PWID., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Determinants of pediatric asthma management include child, family, healthcare, and community factors. The purpose of this study is to investigate how parents/guardians are impacted by and act on these factors to aid in their child's asthma self-management. Interviews were conducted in Fall 2020 with 12 female parents/guardians of Black/African American children who participated in a community paramedic pilot study with their child in South Carolina. Children in the initial study had an asthma diagnosis of moderate persistent asthma, had Medicaid insurance, and were determined high-risk for emergency room presentation. Inductive and deductive qualitative analysis identified that child management self-efficacy and independence, parent/guardian health literacy, parent and child negative experiences related to asthma diagnosis and management, asthma management tools, and social support from multiple sources impact child self-management. Findings from this study highlight the importance of clear asthma education and management tool recommendations from healthcare and community providers, particularly for parents/guardians with low health literacy. Health literacy impacted parental responses and likely how families comprehend Medicaid and clinical asthma guidance., Competing Interests: Declaration of Conflicting Interests: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2022.)

By developing a partnership amongst a public university lab, local city government officials and community healthcare providers, we established a drive-through COVID-19 testing site aiming to improve access to SARS-CoV-2 testing in rural Upstate South Carolina. We collected information on symptoms and known exposures of individuals seeking testing to determine the number of pre- or asymptomatic individuals. We completed 71,102 SARS-CoV-2 tests in the community between December 2020-December 2021 and reported 91.49% of results within 24 h. We successfully identified 5,244 positive tests; 73.36% of these tests originated from individuals who did not report symptoms. Finally, we identified high transmission levels during two major surges and compared test positivity rates of the local and regional communities. Importantly, the local community had significantly lower test positivity rates than the regional community throughout 2021 ( p < 0.001). While both communities reached peak case load and test positivity near the same time, the local community returned to moderate transmission as indicated by positivity 4 weeks before the regional community. Our university lab facilitated easy testing with fast turnaround times, which encouraged voluntary testing and helped identify a large number of non-symptomatic cases. Finding the balance of simplicity, accessibility, and community trust was vital to the success of our widespread community testing program for SARS-CoV-2., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Plumb, Ham, Napolitano, King, Swann, Kalbaugh, Rennert and Dean.)

We assess protection from previous SARS-CoV-2 infection in 16,101 university students. Among 2,021 students previously infected in Fall 2020, risk of re-infection during the Spring 2021 semester was 2.2%; estimated protection from previous SARS-CoV-2 infection was 84% (95% CI: 78%-88%)., (© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America.)

Background: Adequate medication adherence is critical for achieving sustained viral response (SVR) of hepatitis C virus (HCV) among people who inject drugs (PWID). However, it is less known which patterns of direct-acting antiviral (DAA) treatment adherence are associated with SVR in this population or what factors are associated with each pattern., Methods: The randomized 3-arm PREVAIL study used electronic blister packs to obtain daily time frame adherence data in opiate agonist therapy program settings. Exact logistic regressions were applied to test the associations between SVR and 6 types of treatment adherence patterns., Results: Of the 113 participants treated with combination DAAs, 109 (96.5%) achieved SVR. SVR was significantly associated with all pattern parameters except for number of switches between adherent and missed days: total adherent daily doses (exact adjusted odds ratio [AOR] = 1.12; 95% confidence interval [CI] = 1.04-1.22), percent total doses (1.09; 1.03-1.16), days on treatment (1.16; 1.05-1.32), maximum consecutive adherent days (1.34; 1.06-2.04), and maximum consecutive nonadherent days (0.85; .74-.95 = 0.003). SVR was significantly associated with total adherent doses in the first 2 months of treatment, it was not in the last month. While alcohol intoxication was significantly associated with frequent switches, drug use was not associated with any adherence pattern., Conclusions: Consistent maintenance of adequate total dose adherence over the entire course of HCV treatment is important in achieving SVR among PWID. Additional integrative addiction and medical care may be warranted for treating PWID who experience alcohol intoxication., (© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

Background: Wastewater-based epidemiology provides an opportunity for near real-time, cost-effective monitoring of community-level transmission of SARS-CoV-2. Detection of SARS-CoV-2 RNA in wastewater can identify the presence of COVID-19 in the community, but methods for estimating the numbers of infected individuals on the basis of wastewater RNA concentrations are inadequate., Methods: This is a wastewater-based epidemiology study using wastewater samples that were collected weekly or twice a week from three sewersheds in South Carolina, USA, between either May 27 or June 16, 2020, and Aug 25, 2020, and tested for SARS-CoV-2 RNA. We developed a susceptible-exposed-infectious-recovered (SEIR) model based on the mass rate of SARS-CoV-2 RNA in the wastewater to predict the number of infected individuals, and have also provided a simplified equation to predict this. Model predictions were compared with the number of confirmed cases identified by the Department of Health and Environmental Control, South Carolina, USA, for the same time period and geographical area., Findings: We plotted the model predictions for the relationship between mass rate of virus release and numbers of infected individuals, and we validated this prediction on the basis of estimated prevalence from individual testing. A simplified equation to estimate the number of infected individuals fell within the 95% confidence limits of the model. The rate of unreported COVID-19 cases, as estimated by the model, was approximately 11 times that of confirmed cases (ie, ratio of estimated infections for every confirmed case of 10·9, 95% CI 4·2-17·5). This rate aligned well with an independent estimate of 15 infections for every confirmed case in the US state of South Carolina., Interpretation: The SEIR model provides a robust method to estimate the total number of infected individuals in a sewershed on the basis of the mass rate of RNA copies released per day. This approach overcomes some of the limitations associated with individual testing campaigns and thereby provides an additional tool that can be used to inform policy decisions., Funding: Clemson University, USA., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: Autosomal dominant polycystic kidney disease (ADPKD) is a genetic disorder characterized by the development of multiple cysts in the kidneys. It is often caused by pathogenic mutations in PKD1 and PKD2 genes that encode polycystin proteins. Although the molecular mechanisms for cystogenesis are not established, concurrent inactivating germline and somatic mutations in PKD1 and PKD2 have been previously observed in renal tubular epithelium (RTE)., Methods: To further investigate the cellular recessive mechanism of cystogenesis in RTE, we conducted whole-genome DNA sequencing analysis to identify germline variants and somatic alterations in RTE of 90 unique kidney cysts obtained during nephrectomy from 24 unrelated participants., Results: Kidney cysts were overall genomically stable, with low burdens of somatic short mutations or large-scale structural alterations. Pathogenic somatic "second hit" alterations disrupting PKD1 or PKD2 were identified in 93% of the cysts. Of these, 77% of cysts acquired short mutations in PKD1 or PKD2 ; specifically, 60% resulted in protein truncations (nonsense, frameshift, or splice site) and 17% caused non-truncating mutations (missense, in-frame insertions, or deletions). Another 18% of cysts acquired somatic chromosomal loss of heterozygosity (LOH) events encompassing PKD1 or PKD2 ranging from 2.6 to 81.3 Mb. 14% of these cysts harbored copy number neutral LOH events, while the other 3% had hemizygous chromosomal deletions. LOH events frequently occurred at chromosomal fragile sites, or in regions comprising chromosome microdeletion diseases/syndromes. Almost all somatic "second hit" alterations occurred at the same germline mutated PKD1/2 gene., Conclusions: These findings further support a cellular recessive mechanism for cystogenesis in ADPKD primarily caused by inactivating germline and somatic variants of PKD1 or PKD2 genes in kidney cyst epithelium., (Copyright © 2021 by the American Society of Nephrology.)

The T allele in rs1768208 located in or near the myelin oligodendrocyte basic protein gene (MOBP) is a risk factor for frontotemporal degeneration pathology. We evaluated the hypothesis that the presence of a T allele in rs1768208 will be associated with rate of cognitive decline in behavioral variant frontotemporal degeneration (bvFTD) related to compromised frontal networks. We studied 81 individuals clinically diagnosed with bvFTD who were genotyped for rs1768208 and coded using a dominant model reflecting the presence (i.e., MOBP +) or absence (MOBP -) of the T risk allele. Linear mixed-effects models assessed the association of genotype on neuropsychological performance over time. Regression analyses examined differences in network structure by MOBP genotype. We found a genotype by time interaction for declining cognitive performance, whereby MOBP + individuals demonstrated faster rates of decline in executive function. The presence of a MOBP risk allele was associated with degradation of white matter network features in the frontal lobe. These findings suggest that individual genetic variation may contribute to heterogeneity in clinical progression., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: Several American universities have experienced COVID-19 outbreaks, risking the health of their students, employees, and local communities. Such large outbreaks have drained university resources and forced several institutions to shift to remote learning and send students home, further contributing to community disease spread. Many of these outbreaks can be attributed to the large numbers of active infections returning to campus, alongside high-density social events that typically take place at the semester start. In the absence of effective mitigation measures (e.g., high-frequency testing), a phased return of students to campus is a practical intervention to minimize the student population size and density early in the semester, reduce outbreaks, preserve institutional resources, and ultimately help mitigate disease spread in communities., Methods: We develop dynamic compartmental SARS-CoV-2 transmission models to assess the impact of a phased reopening, in conjunction with pre-arrival testing, on minimizing on-campus outbreaks and preserving university resources (measured by isolation bed capacity). We assumed an on-campus population of N = 7500, 40% of infected students require isolation, 10 day isolation period, pre-arrival testing removes 90% of incoming infections, and that phased reopening returns one-third of the student population to campus each month. We vary the disease reproductive number (R t ) between 1.5 and 3.5 to represent the effectiveness of alternative mitigation strategies throughout the semester., Results: Compared to pre-arrival testing only or neither intervention, phased reopening with pre-arrival testing reduced peak active infections by 3 and 22% (R t  = 1.5), 22 and 29% (R t  = 2.5), 41 and 45% (R t  = 3.5), and 54 and 58% (improving R t ), respectively. Required isolation bed capacity decreased between 20 and 57% for values of R t  ≥ 2.5., Conclusion: Unless highly effective mitigation measures are in place, a reopening with pre-arrival testing substantially reduces peak number of active infections throughout the semester and preserves university resources compared to the simultaneous return of all students to campus. Phased reopenings allow institutions to ensure sufficient resources are in place, improve disease mitigation strategies, or if needed, preemptively move online before the return of additional students to campus, thus preventing unnecessary harm to students, institutional faculty and staff, and local communities., (© 2021. The Author(s).)

Background: Guidelines on timeliness of lung cancer surgery are inconsistent. Lung cancer histologic subtypes have different prognosis and treatment. It is important to understand the consequences of delayed surgery for each lung cancer histologic subtype. This study aimed to examine the association between diagnosis-to-surgery time interval and survival for early stage lung cancer and selected histologic subtypes., Methods: Patients diagnosed with stage I-IIA lung cancer between 2004 and 2015 receiving definitive surgery and being followed up until Dec. 31, 2018, were identified from Surveillance, Epidemiology, and End Results database. Histologic subtypes included adenocarcinoma, squamous or epidermoid carcinoma, bronchioloalveolar carcinoma, large cell carcinoma, adenosquamous carcinoma, carcinoid carcinoma, and small cell carcinoma. Diagnosis-to-surgery interval was treated as multi-categorical variables (<1, 1-2, 2-3, and ≥3 months) and binary variables (≥1 vs . <1 month, ≥2 vs . <2 months, and ≥3 vs . <3 months). Outcomes included cancer-specific and overall survival. Covariates included age at diagnosis, sex, race, marital status, tumor size, grade, surgery type, chemotherapy, radiotherapy, and study period. Kaplan-Meier survival curves and Cox proportional hazards regression models were applied to examine the survival differences., Results: With a median follow-up time of 51 months, a total of 40,612 patients were analyzed, including 40.1% adenocarcinoma and 24.5% squamous or epidermoid carcinoma. The proportion of patients receiving surgery <1, 1-2, 2-3, and ≥3 months from diagnosis were 34.2%, 33.9%, 19.8%, and 12.1%, respectively. Delayed surgery was associated with worse cancer-specific and overall survival for all lung cancers, adenocarcinoma, squamous or epidermoid, bronchioloalveolar, and large cell carcinoma (20-40% increased risk). Dose-dependent effects (longer delay, worse survival) were observed in all lung cancers, adenocarcinoma, and squamous and epidermoid carcinoma. No significant association between surgery delay and survival was observed in adenosquamous, carcinoid, and small cell carcinoma., Conclusions: Our findings support the guidelines of undertaking surgery within 1 month from diagnosis in patients with stage I-IIA lung cancer. The observed dose-dependent effects emphasize the clinical importance of early surgery. Future studies with larger sample size of less frequent histologic subtypes are warranted to provide more evidence for histology-specific lung cancer treatment guidelines., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://dx.doi.org/10.21037/tlcr-21-168). The authors have no conflicts of interest to declare., (2021 Translational Lung Cancer Research. All rights reserved.)

People who inject drugs (PWID) have a high prevalence of hepatitis C virus (HCV). Group treatment is a practical option for addressing barriers to treatment in this population. Prior research on group treatment has resulted in mixed conclusions about its effectiveness in addressing barriers to treatment. A patient's perception of the group environment may help to explain this variability. This study sought to explore the association between indicators of group treatment environment and improved outcomes in HCV-infected PWID. This secondary analysis of a randomized controlled trial exploring different models of treatment for HCV in a PWID population consisted of 42 participants randomized to the group treatment branch of the trial. Independent variables consisted of group sessions attended and group climate constructs of engagement, conflict, and avoidance. Dependent variables consisted of medication adherence, social support, and health-related quality of life. The study implemented generalized estimating equations to assess associations with the outcomes at the end of treatment. Factors indicative of group treatment environment were related to medication adherence and other barriers to health for HCV-infected PWID: social support and health-related quality of life. Perceptions of conflict or avoidance were associated with worse outcomes, while increased session attendance was generally associated with better outcomes. The study attests to the importance of examining group environment factors during treatment interventions. Although preliminary, the study provides specific indicators of treatment success for HCV-infected PWID and practical implications to improve patients' health outcomes and better tailor treatment to the patient., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: Despite severe outbreaks of COVID-19 among colleges and universities across the USA during the Fall 2020 semester, the majority of institutions did not routinely test students. While high-frequency repeated testing is considered the most effective strategy for disease mitigation, most institutions do not have the necessary infrastructure or funding for implementation. Therefore, alternative strategies for testing the student population are needed. Our study detailed the implementation and results of testing strategies to mitigate SARS-CoV-2 spread on a university campus, and we aimed to assess the relative effectiveness of the different testing strategies., Methods: For this retrospective cohort study, we included 6273 on-campus students arriving to a large public university in the rural USA (Clemson, SC, USA) for in-person instruction in the Fall 2020 semester (Sept 21 to Nov 25). Individuals arriving after Sept 23, those who tested positive for SARS-CoV-2 before Aug 19, and student athletes and band members were not included in this study. We implemented two testing strategies to mitigate SARS-CoV-2 spread during this period: a novel surveillance-based informative testing (SBIT) strategy, consisting of random surveillance testing to identify outbreaks in residence hall buildings or floors and target them for follow-up testing (Sept 23 to Oct 5); followed by a repeated weekly surveillance testing (Oct 6 to Nov 22). Relative changes in estimated weekly prevalence were examined. We developed SARS-CoV-2 transmission models to compare the relative effectiveness of weekly testing (900 daily surveillance tests), SBIT (450 daily surveillance tests), random surveillance testing (450 daily surveillance tests), and voluntary testing (0 daily surveillance tests) on disease mitigation. Model parameters were based on our empirical surveillance data in conjunction with published sources., Findings: SBIT was implemented from Sept 23 to Oct 5, and identified outbreaks in eight residence hall buildings and 45 residence hall floors. Targeted testing of residence halls was 2·03 times more likely to detect a positive case than random testing (95% CI 1·67-2·46). Weekly prevalence was reduced from a peak of 8·7% to 5·6% during this 2-week period, a relative reduction of 36% (95% CI 27-44). Prevalence continued to decrease after implementation of weekly testing, reaching 0·8% at the end of in-person instruction (week 9). SARS-CoV-2 transmission models concluded that, in the absence of SBIT (ie, voluntary testing only), the total number of COVID-19 cases would have increased by 154% throughout the semester. Compared with SBIT, random surveillance testing alone would have resulted in a 24% increase in COVID-19 cases. Implementation of weekly testing at the start of the semester would have resulted in 36% fewer COVID-19 cases throughout the semester compared with SBIT, but it would require twice the number of daily tests., Interpretation: It is imperative that institutions rigorously test students during the 2021 academic year. When high-frequency testing (eg, weekly) is not possible, SBIT is an effective strategy to mitigate disease spread among the student population that can be feasibly implemented across colleges and universities., Funding: Clemson University, USA., Competing Interests: Declaration of interests DD reports support from the State of South Carolina (CARES act) and US National Institutes of Health (R01 MH111366) during the conduct of this study, and is the founder of Accessible Diagnostics. CCC reports personal fees from Christopher Colenda for public health consulting to Clemson University during the conduct of this study. All other authors declare no competing interests. Clemson University did not influence the work or findings of this report., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Background: Whether maternal vitamin D affects offspring socioemotional development in early childhood has been underexplored., Objectives: This study examined associations between maternal vitamin D during in the 3rd trimester and offspring socioemotional development between 30 and 59 months., Methods: Data from 87 maternal-offspring pairs enrolled in the National Children's Study were used. Total plasma maternal vitamin D (25-hydroxyergocalciferol + 25-hydroxycholecalciferol) was measured between 28 and 35 gestational weeks and categorised as quartiles (Q). Multivariable regression models, adjusting for maternal race/ethnicity, education, and prepregnancy body mass index (BMI [kg/m 2 ]), were used to estimate the association between vitamin D and offspring scores on the Brief Infant-Toddler Social and Emotional Assessment (BITSEA)., Results: The mean (standard deviation) vitamin D concentration was 86.5 (27.8) nmol/L. The median (range) BITSEA problem score was 6.0 (0.0-30.0), and competence score was 19.0 (7.0-22.0). Maternal vitamin D was inversely related to offspring problem scores. Compared to offspring of women with 25(OH)D in Q1, offspring problem scores were -4.80 (95% confidence interval [CI] -8.29, -1.33) units lower for Q2 vs Q1, -5.64 (95% CI -9.60, -1.68) units lower for Q3 vs Q1, and -4.70 (95% CI -8.59, -0.82) units lower for Q4 vs Q1. Vitamin D was not associated with offspring competence score., Conclusions: Higher maternal vitamin D was associated with lower offspring behaviour problems and not associated with socioemotional competence. These data indicate the association of maternal vitamin D and offspring development may be dependent on the specific developmental component being investigated., (© 2020 John Wiley & Sons Ltd.)

Background: Beginning in 2019, stepped-wedge designs (SWDs) were being used in the investigation of interventions to reduce opioid-related deaths in communities across the United States. However, these interventions are competing with external factors such as newly initiated public policies limiting opioid prescriptions, media awareness campaigns, and the COVID-19 pandemic. Furthermore, control communities may prematurely adopt components of the intervention as they become available. The presence of time-varying external factors that impact study outcomes is a well-known limitation of SWDs; common approaches to adjusting for them make use of a mixed effects modeling framework. However, these models have several shortcomings when external factors differentially impact intervention and control clusters., Methods: We discuss limitations of commonly used mixed effects models in the context of proposed SWDs to investigate interventions intended to reduce opioid-related mortality, and propose extensions of these models to address these limitations. We conduct an extensive simulation study of anticipated data from SWD trials targeting the current opioid epidemic in order to examine the performance of these models in the presence of external factors. We consider confounding by time, premature adoption of intervention components, and time-varying effect modification- in which external factors differentially impact intervention and control clusters., Results: In the presence of confounding by time, commonly used mixed effects models yield unbiased intervention effect estimates, but can have inflated Type 1 error and result in under coverage of confidence intervals. These models yield biased intervention effect estimates when premature intervention adoption or effect modification are present. In such scenarios, models incorporating fixed intervention-by-time interactions with an unstructured covariance for intervention-by-cluster-by-time random effects result in unbiased intervention effect estimates, reach nominal confidence interval coverage, and preserve Type 1 error., Conclusions: Mixed effects models can adjust for different combinations of external factors through correct specification of fixed and random time effects. Since model choice has considerable impact on validity of results and study power, careful consideration must be given to how these external factors impact study endpoints and what estimands are most appropriate in the presence of such factors.

Adequate adherence to direct-acting antivirals (DAAs) for hepatitis C virus (HCV) is critical to attaining sustained virologic response (SVR). In this PREVAIL study's secondary analyses, we explored the association between self-reported and objective DAAs adherence among a sample of people who inject drugs (PWID) receiving medications for opioid use disorder (MOUD) (N = 147). Self-reported adherence was recoded 3 times during treatment (weeks 4, 8 and 12) using a visual analog scale (VAS), whereas objective adherence was collected continuously during treatment using electronic blister packs. Participants who reported being perfectly adherent had significantly higher blister pack adherence in each period (weeks 4, 8 and 12; ps < .05) and over the 12-week study (p < .001) compared to those who reported being non-perfectly adherent. Whites were more likely to report perfect adherence (91.7%) than Blacks (48.7%), Latinos (52.2%) and other (75.0%) race groups. Participants who reported recent use of cocaine (63.9%) or polysubstance use (60.0%) and those who had a positive result for cocaine (62.8%) were more likely to be non-perfectly adherent, although none of these factors were associated with blister pack adherence. This study showed that the VAS could serve as a reliable option for assessing DAAs adherence among PWID on MOUD. The implementation of VAS may be an ideal option for monitoring adherence among PWID on MOUD, especially in clinical settings with limited resources. PWID on MOUD who are Black or other races than White, as well as those who report recent cocaine or polysubstance use may require additional support to maintain optimal DAA adherence., (© 2020 John Wiley & Sons Ltd.)