Community-Based Cluster-Randomized Trial to Reduce Opioid Overdose Deaths.

BACKGROUND: Evidence-based practices for reducing opioid-related overdose deaths include overdose education and naloxone distribution, the use of medications for the treatment of opioid use disorder, and prescription opioid safety. Data are needed on the effectiveness of a community-engaged intervention to reduce opioid-related overdose deaths through enhanced uptake of these practices. METHODS: In this community-level, cluster-randomized trial, we randomly assigned 67 communities in Kentucky, Massachusetts, New York, and Ohio to receive the intervention (34 communities) or a wait-list control (33 communities), stratified according to state. The trial was conducted within the context of both the coronavirus disease 2019 (Covid-19) pandemic and a national surge in the number of fentanyl-related overdose deaths. The trial groups were balanced within states according to urban or rural classification, previous overdose rate, and community population. The primary outcome was the number of opioid-related overdose deaths among community adults. RESULTS: During the comparison period from July 2021 through June 2022, the population-averaged rates of opioid-related overdose deaths were similar in the intervention group and the control group (47.2 deaths per 100,000 population vs. 51.7 per 100,000 population), for an adjusted rate ratio of 0.91 (95% confidence interval, 0.76 to 1.09; P = 0.30). The effect of the intervention on the rate of opioid-related overdose deaths did not differ appreciably according to state, urban or rural category, age, sex, or race or ethnic group. Intervention communities implemented 615 evidence-based practice strategies from the 806 strategies selected by communities (254 involving overdose education and naloxone distribution, 256 involving the use of medications for opioid use disorder, and 105 involving prescription opioid safety). Of these evidence-based practice strategies, only 235 (38%) had been initiated by the start of the comparison year. CONCLUSIONS: In this 12-month multimodal intervention trial involving community coalitions in the deployment of evidence-based practices to reduce opioid overdose deaths, death rates were similar in the intervention group and the control group in the context of the Covid-19 pandemic and the fentanyl-related overdose epidemic. (Funded by the National Institutes of Health; HCS ClinicalTrials.gov number, NCT04111939.).

Post-Acute Cardiovascular Outcomes of COVID-19 in Children and Adolescents: An EHR Cohort Study from the RECOVER Project.

Background: The risk of cardiovascular outcomes in the post-acute phase of SARS-CoV-2 infection has been quantified among adults and children. This paper aimed to assess a multitude of cardiac signs, symptoms, and conditions, as well as focused on patients with and without congenital heart defects (CHDs), to provide a more comprehensive assessment of the post-acute cardiovascular outcomes among children and adolescents after COVID-19. Methods: This retrospective cohort study used data from the RECOVER consortium comprising 19 US children's hospitals and health institutions between March 2020 and September 2023. Every participant had at least a six-month follow-up after cohort entry. Absolute risks of incident post-acute COVID-19 sequelae were reported. Relative risks (RRs) were calculated by contrasting COVID-19-positive with COVID-19-negative groups using a Poisson regression model, adjusting for demographic, clinical, and healthcare utilization factors through propensity scoring stratification. Results: A total of 1,213,322 individuals under 21 years old (mean[SD] age, 7.75[6.11] years; 623,806 male [51.4%]) were included. The absolute rate of any post-acute cardiovascular outcome in this study was 2.32% in COVID-19 positive and 1.38% in negative groups. Patients with CHD post-SARS-CoV-2 infection showed increased risks of any cardiovascular outcome (RR, 1.63; 95% confidence interval (CI), 1.47-1.80), including increased risks of 11 of 18 post-acute sequelae in hypertension, arrhythmias (atrial fibrillation and ventricular arrhythmias), myocarditis, other cardiac disorders (heart failure, cardiomyopathy, and cardiac arrest), thrombotic disorders (thrombophlebitis and thromboembolism), and cardiovascular-related symptoms (chest pain and palpitations). Those without CHDs also experienced heightened cardiovascular risks after SARS-CoV-2 infection (RR, 1.63; 95% CI, 1.57-1.69), covering 14 of 18 conditions in hypertension, arrhythmias (ventricular arrhythmias and premature atrial or ventricular contractions), inflammatory heart disease (pericarditis and myocarditis), other cardiac disorders (heart failure, cardiomyopathy, cardiac arrest, and cardiogenic shock), thrombotic disorders (pulmonary embolism and thromboembolism), and cardiovascular-related symptoms (chest pain, palpitations, and syncope). Conclusions: Both children with and without CHDs showed increased risks for a variety of cardiovascular outcomes after SARS-CoV-2 infection, underscoring the need for targeted monitoring and management in the post-acute phase.

Limitations of Noninvasive Tests-Based Population-Level Risk Stratification Strategy for Nonalcoholic Fatty Liver Disease.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) are highly prevalent but underdiagnosed. AIMS: We used an electronic health record data network to test a population-level risk stratification strategy using noninvasive tests (NITs) of liver fibrosis. METHODS: Data were obtained from PCORnet® sites in the East, Midwest, Southwest, and Southeast United States from patients aged [Formula: see text] 18 with or without ICD-10-CM diagnosis codes for NAFLD, NASH, and NASH-cirrhosis between 9/1/2017 and 8/31/2020. Average and standard deviations (SD) for Fibrosis-4 index (FIB-4), NAFLD fibrosis score (NFS), and Hepatic Steatosis Index (HSI) were estimated by site for each patient cohort. Sample-wide estimates were calculated as weighted averages across study sites. RESULTS: Of 11,875,959 patients, 0.8% and 0.1% were coded with NAFLD and NASH, respectively. NAFLD diagnosis rates in White, Black, and Hispanic patients were 0.93%, 0.50%, and 1.25%, respectively, and for NASH 0.19%, 0.04%, and 0.16%, respectively. Among undiagnosed patients, insufficient EHR data for estimating NITs ranged from 68% (FIB-4) to 76% (NFS). Predicted prevalence of NAFLD by HSI was 60%, with estimated prevalence of advanced fibrosis of 13% by NFS and 7% by FIB-4. Approximately, 15% and 23% of patients were classified in the intermediate range by FIB-4 and NFS, respectively. Among NAFLD-cirrhosis patients, a third had FIB-4 scores in the low or intermediate range. CONCLUSIONS: We identified several potential barriers to a population-level NIT-based screening strategy. HSI-based NAFLD screening appears unrealistic. Further research is needed to define merits of NFS- versus FIB-4-based strategies, which may identify different high-risk groups.

Neutralization escape of Omicron XBB, BR.2, and BA.2.3.20 subvariants.

New Omicron subvariants continue to emerge throughout the world. In particular, the XBB subvariant, which is a recombinant virus between BA.2.10.1.1 and BA.2.75.3.1.1.1, as well as the BA.2.3.20 and BR.2 subvariants that contain mutations distinct from BA.2 and BA.2.75, are currently increasing in proportion of variants sequenced. Here we show that antibodies induced by 3-dose mRNA booster vaccination as well as BA.1- and BA.4/5-wave infection effectively neutralize BA.2, BR.2, and BA.2.3.20 but have significantly reduced efficiency against XBB. In addition, the BA.2.3.20 subvariant exhibits enhanced infectivity in the lung-derived CaLu-3 cells and in 293T-ACE2 cells. Overall, our results demonstrate that the XBB subvariant is highly neutralization resistant, which highlights the need for continued monitoring of the immune escape and tissue tropism of emerging Omicron subvariants.

Enhanced evasion of neutralizing antibody response by Omicron XBB.1.5, CH.1.1, and CA.3.1 variants.

Omicron subvariants continuingly challenge current vaccination strategies. Here, we demonstrate nearly complete escape of the XBB.1.5, CH.1.1, and CA.3.1 variants from neutralizing antibodies stimulated by three doses of mRNA vaccine or by BA.4/5 wave infection, but neutralization is rescued by a BA.5-containing bivalent booster. CH.1.1 and CA.3.1 show strong immune escape from monoclonal antibody S309. Additionally, XBB.1.5, CH.1.1, and CA.3.1 spike proteins exhibit increased fusogenicity and enhanced processing compared with BA.2. Homology modeling reveals the key roles of G252V and F486P in the neutralization resistance of XBB.1.5, with F486P also enhancing receptor binding. Further, K444T/M and L452R in CH.1.1 and CA.3.1 likely drive escape from class II neutralizing antibodies, whereas R346T and G339H mutations could confer the strong neutralization resistance of these two subvariants to S309-like antibodies. Overall, our results support the need for administration of the bivalent mRNA vaccine and continued surveillance of Omicron subvariants.

Extraordinary Evasion of Neutralizing Antibody Response by Omicron XBB.1.5, CH.1.1 and CA.3.1 Variants.

Newly emerging Omicron subvariants continue to emerge around the world, presenting potential challenges to current vaccination strategies. This study investigates the extent of neutralizing antibody escape by new subvariants XBB.1.5, CH.1.1, and CA.3.1, as well as their impacts on spike protein biology. Our results demonstrated a nearly complete escape of these variants from neutralizing antibodies stimulated by three doses of mRNA vaccine, but neutralization was rescued by a bivalent booster. However, CH.1.1 and CA.3.1 variants were highly resistant to both monovalent and bivalent mRNA vaccinations. We also assessed neutralization by sera from individuals infected during the BA.4/5 wave of infection and observed similar trends of immune escape. In these cohorts, XBB.1.5 did not exhibit enhanced neutralization resistance over the recently dominant BQ.1.1 variant. Notably, the spike proteins of XBB.1.5, CH.1.1, and CA.3.1 all exhibited increased fusogenicity compared to BA.2, correlating with enhanced S processing. Overall, our results support the administration of new bivalent mRNA vaccines, especially in fighting against newly emerged Omicron subvariants, as well as the need for continued surveillance of Omicron subvariants.

Enhanced neutralization resistance of SARS-CoV-2 Omicron subvariants BQ.1, BQ.1.1, BA.4.6, BF.7, and BA.2.75.2.

The continued evolution of SARS-CoV-2 has led to the emergence of several new Omicron subvariants, including BQ.1, BQ.1.1, BA.4.6, BF.7, and BA.2.75.2. Here, we examine the neutralization resistance of these subvariants against sera from 3-dose vaccinated healthcare workers, hospitalized BA.1-wave patients, and BA.4/5-wave patients. We found enhanced neutralization resistance in all new subvariants, especially in the BQ.1 and BQ.1.1 subvariants driven by N460K and K444T mutations, as well as the BA.2.75.2 subvariant driven largely by its F486S mutation. All Omicron subvariants maintained their weakened infectivity in Calu-3 cells, with the F486S mutation driving further diminished titer for the BA.2.75.2 subvariant. Molecular modeling revealed the mechanisms of antibody-mediated immune evasion by R346T, K444T, F486S, and D1199N mutations. Altogether, these findings shed light on the evolution of newly emerging SARS-CoV-2 Omicron subvariants.

The Ability of the Yeast Wickerhamomyces anomalus to Hydrolyze Immunogenic Wheat Gliadin Proteins.

Gliadins proteins make up around 30% of total wheat flour proteins. They are involved in many immune disorders affecting an increasing number of people who eat foods made with wheat flour. The triggering factor is the accumulation in the gut of immunogenic peptides derived from incomplete degradation of gliadins by gastric proteases. Previous research has revealed the effectiveness of sourdough-fermentation technology or related lactic acid bacteria in reducing wheat flour allergenic proteins. However, there are no single yeast cultures for producing reduced allergenicity wheat products. This study evaluated sourdough-related yeast Wickerhamomyces anomalus strains for their ability to hydrolyze gliadin proteins. All yeast strains were able to degrade gliadins and use them as carbon and nitrogen sources. The proliferation of the yeast strains depended on the gliadin addition; complete hydrolysis was observed after 24 h. The strain showing higher proteolytic activity fermented, acceptably wheat flour dough. The gliadin content of the leavened dough was reduced by 50%. Bread made from the W. anomalus-fermented dough showed a 78% reduction in immunogenic α-gliadins. 50% of the decrease was attributed to the proteolytic activity of the yeast cells, and the other 35% to the baking process. These results show the potential of the yeast W. anomalus as a starter for reducing immunogenicity wheat products.

Distinct Neutralizing Antibody Escape of SARS-CoV-2 Omicron Subvariants BQ.1, BQ.1.1, BA.4.6, BF.7 and BA.2.75.2.

Continued evolution of SARS-CoV-2 has led to the emergence of several new Omicron subvariants, including BQ.1, BQ. 1.1, BA.4.6, BF.7 and BA.2.75.2. Here we examine the neutralization resistance of these subvariants, as well as their ancestral BA.4/5, BA.2.75 and D614G variants, against sera from 3-dose vaccinated health care workers, hospitalized BA.1-wave patients, and BA.5-wave patients. We found enhanced neutralization resistance in all new subvariants, especially the BQ.1 and BQ.1.1 subvariants driven by a key N460K mutation, and to a lesser extent, R346T and K444T mutations, as well as the BA.2.75.2 subvariant driven largely by its F486S mutation. The BQ.1 and BQ.1.1 subvariants also exhibited enhanced fusogenicity and S processing dictated by the N460K mutation. Interestingly, the BA.2.75.2 subvariant saw an enhancement by the F486S mutation and a reduction by the D1199N mutation to its fusogenicity and S processing, resulting in minimal overall change. Molecular modelling revealed the mechanisms of receptor-binding and non-receptor binding monoclonal antibody-mediated immune evasion by R346T, K444T, F486S and D1199N mutations. Altogether, these findings shed light on the concerning evolution of newly emerging SARS-CoV-2 Omicron subvariants.

Performance of model-based vs. permutation tests in the HEALing (Helping to End Addiction Long-termSM) Communities Study, a covariate-constrained cluster randomized trial.

BACKGROUND: The HEALing (Helping to End Addiction Long-termSM) Communities Study (HCS) is a multi-site parallel group cluster randomized wait-list comparison trial designed to evaluate the effect of the Communities That Heal (CTH) intervention compared to usual care on opioid overdose deaths. Covariate-constrained randomization (CCR) was applied to balance the community-level baseline covariates in the HCS. The purpose of this paper is to evaluate the performance of model-based tests and permutation tests in the HCS setting. We conducted a simulation study to evaluate type I error rates and power for model-based and permutation tests for the multi-site HCS as well as for a subgroup analysis of a single state (Massachusetts). We also investigated whether the maximum degree of imbalance in the CCR design has an impact on the performance of the tests. METHODS: The primary outcome, the number of opioid overdose deaths, is count data assessed at the community level that will be analyzed using a negative binomial regression model. We conducted a simulation study to evaluate the type I error rates and power for 3 tests: (1) Wald-type t-test with small-sample corrected empirical standard error estimates, (2) Wald-type z-test with model-based standard error estimates, and (3) permutation test with test statistics calculated by the difference in average residuals for the two groups. RESULTS: Our simulation results demonstrated that Wald-type t-tests with small-sample corrected empirical standard error estimates from the negative binomial regression model maintained proper type I error. Wald-type z-tests with model-based standard error estimates were anti-conservative. Permutation tests preserved type I error rates if the constrained space was not too small. For all tests, the power was high to detect the hypothesized 40% reduction in opioid overdose deaths for the intervention vs. comparison group both for the overall HCS and the subgroup analysis of Massachusetts (MA). CONCLUSIONS: Based on the results of our simulation study, the Wald-type t-test with small-sample corrected empirical standard error estimates from a negative binomial regression model is a valid and appropriate approach for analyzing cluster-level count data from the HEALing Communities Study. TRIAL REGISTRATION: ClinicalTrials.gov http://www. CLINICALTRIALS: gov ; Identifier: NCT04111939.

Development of a distributed international patient data registry for hairy cell leukemia.

Hairy cell leukemia (HCL) is a rare lymphoproliferative disorder, comprising only 2% of all leukemias. The Hairy Cell Leukemia Foundation (HCLF) has developed a patient data registry to enable investigators to better study the clinical features, treatment outcomes, and complications of patients with HCL. This system utilizes a centralized registry architecture. Patients are enrolled at HCL Centers of Excellence (COE) or via a web-based portal. All data are de-identified, which reduces regulatory burden and increases opportunities for data access and re-use. To date, 579 patients have been enrolled in the registry. Efforts are underway to engage additional COE's to expand access to patients across the globe. This international PDR will enable researchers to study outcomes in HCL in ways not previously possible due to the rarity of the disease and will serve as a platform for future prospective research.

Midwives' ability during third stage of childbirth to estimate postpartum haemorrhage.

Objective: Correctly assessing the amount of blood loss is crucial in order to adequately treat postpartum haemorrhage (PPH) at an early stage and diminish any related symptoms and/or complications.The aim of our study is to analyse correctness in visually estimated blood loss during labour and to measure the differences between subjectively measured and weighted blood losses (ml). Design: Cross-sectional study. Setting: A Swedish maternity unit with 6000 annual births. Participants: Midwives employed at a big maternity unit at a hospital in northern Stockholm, Sweden. Intervention: Midwives assisting 192 vaginal births were asked to visually estimate the blood loss from the assisted delivery. Coasters and sanitary pads were weighed following the birth. We analysed if there were any differences between subjective measured blood loss (ml) and weighted blood loss. These two methods were also compared to quantify concordance between estimated blood volume and the actual volume. Findings: The number of overestimates of blood loss was 45.3 % ( n = 87 ) with an average of 72.9 ml; the number of underestimates was 49.4 % ( n = 95 ) with an average of 73.8 ml. Exact correct estimations of blood loss were done in 5.2 % of the cases ( n = 10 ).The largest overestimation of a postpartum bleeding was by 520 ml; the largest underestimation was by 745 ml. Conclusion: There was both underestimation and overestimation of blood loss. We found small but significant overestimates in PPH < 300 ml (16 ml). In PPH > 300 ml, there was a small but not significant underestimates (34 ml). Based upon our findings, we conclude that it is reasonable to start weighing blood loss when it exceeds 300 ml.

COVID-19 Booster Uptake among First Responders and Their Household Members May Be Lower than Anticipated.

(1) Background: COVID-19 vaccination status varies widely among law enforcement and emergency medical services professionals. Though at high risk of exposure, these first responders have demonstrated significant vaccine hesitancy, with only 70% reportedly vaccinated. We sought to understand whether similar vaccine hesitancy exists for first responders and their household contacts around COVID-19 boosters. (2) Methods: In a prospective longitudinal cohort of first responders and their household contacts, survey data was collected, including demographics, medical history, COVID-19 exposure risks, and vaccination and/or booster status. The statistical analysis focused on primary vaccination and booster rates of both the first responders and their household contacts. (3) Results: Across 119 study participants, 73% reported having received some combination of vaccine and/or booster, and 26% were unvaccinated. Vaccinated individuals were older, reported less prior exposure to COVID-19 and had more comorbidities. Only 23% reported having received a COVID-19 booster. Pairing of the data for household contacts demonstrated a 60% agreement to receive primary vaccination but only a 20% agreement for boosters within households. (4) Conclusions: This study provides insight into the vaccination and booster rates of first responders and household contacts. Focused efforts to enhance vaccinations is essential for the protection and maintenance of this critical workforce.

Analysis of Urine Drug Test Results From Substance Use Disorder Treatment Practices and Overdose Mortality Rates, 2013-2020.

Importance: Drug overdose deaths in the US are currently the highest ever recorded; data collected from public health surveillance sources can help to identify emerging drug use patterns associated with overdose mortality rates, but the time lag in results often limits utility. Urine drug testing (UDT) is one potentially underused source that could augment surveillance efforts through timely data collection. Objective: To evaluate the correlation between real-time UDT results from a proprietary national database and overdose mortality data from the National Vital Statistics System. Design, Setting, and Participants: This retrospective cross-sectional study included 500 000 urine specimens submitted for UDT by substance use disorder (SUD) treatment health care practices and collected between January 1, 2013, and December 31, 2020. Real-time UDT data were obtained from the Millennium Health proprietary national database, and overdose mortality data were obtained from the National Vital Statistics System of the Centers for Disease Control and Prevention (CDC WONDER). Specimens were analyzed for specific drugs in 5 categories (cocaine, heroin, methamphetamine, synthetic opioids, and other opioids) using liquid chromatography-tandem mass spectrometry. Participants were adults aged 18 years and older who provided urine specimens at SUD treatment practices. Exposures: Urine drug testing. Main Outcomes and Measures: The primary outcome was the correlation between UDT positivity rates and overdose mortality rates at national, state, and county levels. Univariate and multivariate regression models were also used to evaluate the association between state- and county-level overdose mortality and standardized UDT positivity rates. Results: Among 500 000 unique patient specimens collected from SUD treatment practices between 2013 and 2020, 288 534 specimens (57.7%) were from men, and the median age of the study population was 34 years (IQR, 17-51 years). On a national level, synthetic opioids and methamphetamine were highly correlated with overdose mortality (Spearman ρ = 0.96 for both). When synthetic opioids were coinvolved, methamphetamine (ρ = 0.98), heroin (ρ = 0.78), cocaine (ρ = 0.94), and other opioids (ρ = 0.83) were also highly correlated with overdose mortality. In the absence of synthetic opioids, all drug categories were highly correlated (ρ = 0.75 for other opioids, 0.81 for heroin, and 0.88 for methamphetamine), with the exception of cocaine (ρ = -0.37). Synthetic opioids (ρ = 0.77) and methamphetamine (ρ = 0.80) had the strongest state-level correlations over time, whereas other opioids had the lowest correlation for both total positivity (ρ = 0.31) and positivity in the absence of synthetic opioids (ρ = 0.23). In Ohio, county-level correlation was strongest for synthetic opioids (ρ = 0.71), followed by heroin (ρ = 0.69) and methamphetamine (ρ = 0.67). At the state level, the multivariate incidence rate ratio (IRR) for synthetic opioids was 1.16 (95% CI, 1.14-1.19; P < .001), and at the county level, the IRR was 1.13 (95% CI, 1.09-1.17; P < .001), suggesting that for every 1-SD increase in the UDT positivity rate, there were 16.2% and 12.8% increases, respectively, in monthly overdose deaths. Both methamphetamine (11.7% increase per 1-SD increase in UDT positivity rate; IRR, 1.12; 95% CI, 1.09-1.14; P < .001) and cocaine (5.1% increase per 1-SD increase in UDT positivity rate; IRR, 1.05; 95% CI, 1.03-1.07; P < .001) also had significant positive associations with mortality rates, but the effect sizes were smaller than that of synthetic opioids (IRR, 1.16). Conclusions and Relevance: In this study, UDT results were highly correlated with mortality rates at national, state, and county levels. These findings suggest that real-time UDT surveillance can help to quickly identify changes in drug use patterns that might inform targeted harm reduction strategies designed to prevent overdose deaths.

Stromal p53 Regulates Breast Cancer Development, the Immune Landscape, and Survival in an Oncogene-Specific Manner.

Coevolution of tumor cells and adjacent stromal elements is a key feature during tumor progression; however, the precise regulatory mechanisms during this process remain unknown. Here, we show stromal p53 loss enhances oncogenic KrasG12D, but not ErbB2, driven tumorigenesis in murine mammary epithelia. Stroma-specific p53 deletion increases both epithelial and fibroblast proliferation in mammary glands bearing the KrasG12D oncogene in epithelia, while concurrently increasing DNA damage and/or DNA replication stress and decreasing apoptosis in the tumor cells proper. Normal epithelia was not affected by stromal p53 deletion. Tumors with p53-null stroma had a significant decrease in total, cytotoxic, and regulatory T cells; however, there was a significant increase in myeloid-derived suppressor cells, total macrophages, and M2-polarized tumor-associated macrophages, with no impact on angiogenesis or connective tissue deposition. Stroma-specific p53 deletion reprogrammed gene expression in both fibroblasts and adjacent epithelium, with p53 targets and chemokine receptors/chemokine signaling pathways in fibroblasts and DNA replication, DNA damage repair, and apoptosis in epithelia being the most significantly impacted biological processes. A gene cluster in p53-deficient mouse fibroblasts was negatively associated with patient survival when compared with two independent datasets. In summary, stroma-specific p53 loss promotes mammary tumorigenesis in an oncogene-specific manner, influences the tumor immune landscape, and ultimately impacts patient survival. IMPLICATIONS: Expression of the p53 tumor suppressor in breast cancer tumor stroma regulates tumorigenesis in an oncogene-specific manner, influences the tumor immune landscape, and ultimately impacts patient survival.

Marginal modeling in community randomized trials with rare events: Utilization of the negative binomial regression model.

BACKGROUND/AIMS: This work is motivated by the HEALing Communities Study, which is a post-test only cluster randomized trial in which communities are randomized to two different trial arms. The primary interest is in reducing opioid overdose fatalities, which will be collected as a count outcome at the community level. Communities range in size from thousands to over one million residents, and fatalities are expected to be rare. Traditional marginal modeling approaches in the cluster randomized trial literature include the use of generalized estimating equations with an exchangeable correlation structure when utilizing subject-level data, or analogously quasi-likelihood based on an over-dispersed binomial variance when utilizing community-level data. These approaches account for and estimate the intra-cluster correlation coefficient, which should be provided in the results from a cluster randomized trial. Alternatively, the coefficient of variation or R coefficient could be reported. In this article, we show that negative binomial regression can also be utilized when communities are large and events are rare. The objectives of this article are (1) to show that the negative binomial regression approach targets the same marginal regression parameter(s) as an over-dispersed binomial model and to explain why the estimates may differ; (2) to derive formulas relating the negative binomial overdispersion parameter k with the intra-cluster correlation coefficient, coefficient of variation, and R coefficient; and (3) analyze pre-intervention data from the HEALing Communities Study to demonstrate and contrast models and to show how to report the intra-cluster correlation coefficient, coefficient of variation, and R coefficient when utilizing negative binomial regression. METHODS: Negative binomial and over-dispersed binomial regression modeling are contrasted in terms of model setup, regression parameter estimation, and formulation of the overdispersion parameter. Three specific models are used to illustrate concepts and address the third objective. RESULTS: The negative binomial regression approach targets the same marginal regression parameter(s) as an over-dispersed binomial model, although estimates may differ. Practical differences arise in regard to how overdispersion, and hence the intra-cluster correlation coefficient is modeled. The negative binomial overdispersion parameter is approximately equal to the ratio of the intra-cluster correlation coefficient and marginal probability, the square of the coefficient of variation, and the R coefficient minus 1. As a result, estimates corresponding to all four of these different types of overdispersion parameterizations can be reported when utilizing negative binomial regression. CONCLUSION: Negative binomial regression provides a valid, practical, alternative approach to the analysis of count data, and corresponding reporting of overdispersion parameters, from community randomized trials in which communities are large and events are rare.

Assessment of Fall-Related Emergency Medical Service Calls and Transports after a Community-Level Fall-Prevention Initiative.

Background: Getting effective fall prevention into the homes of medically and physically vulnerable individuals is a critical public health challenge. Community paramedicine is emerging globally as a new model of care that allows emergency medical service units to evaluate and treat patients in non-emergency contexts for prevention efforts and chronic care management. The promise of community paramedicine as a delivery system for fall prevention that scales to community-level improvements in outcomes is compelling but untested.Objective: To study the impact of a community paramedic program's optimization of a fall prevention system entailing a clinical pathway and learning health system (called Community-FIT) on community-level fall-related emergency medical service utilization rates.Methods: We used an implementation science framework and quality improvement methods to design and optimize a fall prevention model of care that can be embedded within community paramedic operations. The model was implemented and optimized in an emergency medical service agency servicing a Midwestern city in the United States (∼35,000 residents). Primary outcome measures included relative risk reduction in the number of community-level fall-related 9-1-1 calls and fall-related hospital transports. Interrupted time series analysis was used to evaluate relative risk reduction from a 12-month baseline period (September 2016 - August 2017) to a 12-month post-implementation period (September 2018-August 2019).Results: Community paramedic home visits increased from 25 in 2017, to 236 in 2018, to 517 in 2019, indicating a large increase in the number of households that benefited from the efforts. A relative risk reduction of 0.66 (95% [CI] 0.53, 0.76) in the number of fall calls and 0.63 (95% [CI] 0.46, 0.75) in the number of fall-related calls resulting in transports to the hospital were observed.Conclusions: Community-FIT may offer a powerful mechanism for community paramedics to reduce fall-related 9-1-1 calls and transports to hospitals that can be implemented in emergency medical agencies across the country.

Glycogen Synthase Kinase-3 Maleimide Inhibitors As Potential PET-Tracers for Imaging Alzheimer's Disease: 11C-Synthesis and In Vivo Proof of Concept.

Herein we present the evaluation of 11C-labeled-maleimides as radiotracers for positron emission tomography imaging of GSK-3 associated with Alzheimer's disease (AD). 3-Acetyl-4-(1-[11C]-methyl-1H-indol-3-yl)[1H]pyrrole-2,5-dione ([11C]-2) was obtained by direct methylation using [11C]-CH3I and Cs2CO3 in DMF with a 31 ± 4% radiochemical yield and a radiochemical purity of 97.7 ± 0.8%. [11C]-2 was stable both in its final formulation and in human plasma for 120 min and had a plasma protein binding of 70 ± 1% and a LogD7.4 value of 1.84 ± 0.04. [11C]-2 ex vivo biodistributions in healthy animals demonstrated significant brain uptake and retention, showing its ability to penetrate the intact blood-brain barrier. In vivo PET imaging in mice bearing AD showed, with respect to normal animals, significant differences in uptake in the hypothalamus, the striatum, and the amygdala and a significant increase in amygdala uptake in later stages of the pathology. These results are very promising, and further studies are being performed for a complete validation of this compound as novel tracer for AD.

[18F] Sodium Fluoride Dose Reduction Enabled by Digital Photon Counting PET/CT for Evaluation of Osteoblastic Activity.

The aim of the study was to assess the quality and reproducibility of reducing the injected [18F] sodium fluoride ([18F]NaF) dose while maintaining diagnostic imaging quality in bone imaging in a preclinical skeletal model using digital photon counting PET (dPET) detector technology. Beagles (n = 9) were administered three different [18F]NaF doses: 111 MBq (n = 5), 20 MBq (n = 5), and 1.9 MBq (n = 9). Imaging started ≃45 min post-injection for ≃30 min total acquisition time. Images were reconstructed using Time-of-Flight, ultra-high definition (voxel size of 1 × 1 × 1 mm3), with 3 iterations and 3 subsets. Point spread function was modeled and Gaussian filtering was applied. Skeleton qualitative and quantitative molecular image assessment was performed. The overall diagnostic quality of all images scored excellent (61%) and acceptable (39%) by all the reviewers. [18F]NaF SUVmean showed no statistically significant differences among the three doses in any of the region of interest assessed. This study demonstrated that a 60-fold [18F]NaF dose reduction was not significantly different from the highest dose, and it had not significant effect on overall image quality and quantitative accuracy. In the future, ultra-low dose [18F]NaF dPET/CT imaging may significantly decrease PET radiation exposure to preclinical subjects and personnel.

Variance formulae for multiphase stepped wedge cluster randomized trial.

In a multiphase stepped wedge cluster randomized trial (MSW-CRT), more than one intervention will be initiated on each sequence in a fixed order. Hence, with the MSW-CRT design, the effect of the first intervention can be evaluated when compared to control, as well as the added-on effects of the subsequent interventions. Studies that use MSW-CRT have been proposed, but properties of this design have not been explicitly studied. We derive closed-form variance formulae to test the interventions' effects, which can be readily used for sample size and power calculation. Additionally, we provide relationships between variances to test the interventions' effects and design parameters. Under special conditions, some important properties include: (i) the variances to test different interventions' effects (ie, the first intervention effect and the second intervention effect) may be same; (ii) as the cluster-period mean autocorrelation increases, the variance to test an intervention effect may first increase and then decrease; (iii) as the amount of periods between the initiations of two interventions (ie, lag) increases, the variance to test an intervention effect may remain unchanged. We illustrate the relationships between power and design parameters using the variance formulae. From a few illustrative examples, we observe that the statistical test that uses data only relevant to a specific intervention has inferior power (relative power loss <15%) compared to the test when using all the study data. Also, power is reduced when both the total number of periods and lag are decreased simultaneously (relative power loss <20%).