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Abstract Background Surrogate endpoints, such as those of interest in chronic kidney disease (CKD), are often evaluated using Bayesian meta-regression. Trials used for the analysis can evaluate a variety of interventions for different sub-classifications of disease, which can introduce two additional goals in the analysis. The first is to infer the quality of the surrogate within specific trial subgroups defined by disease or intervention classes. The second is to generate more targeted subgroup-specific predictions of treatment effects on the clinical endpoint. Methods Using real data from a collection of CKD trials and a simulation study, we contrasted surrogate endpoint evaluations under different hierarchical Bayesian approaches. Each approach we considered induces different assumptions regarding the relatedness (exchangeability) of trials within and between subgroups. These include partial-pooling approaches, which allow subgroup-specific meta-regressions and, yet, facilitate data adaptive information sharing across subgroups to potentially improve inferential precision. Because partial-pooling models come with additional parameters relative to a standard approach assuming one meta-regression for the entire set of studies, we performed analyses to understand the impact of the parameterization and priors with the overall goals of comparing precision in estimates of subgroup-specific meta-regression parameters and predictive performance. Results In the analyses considered, partial-pooling approaches to surrogate endpoint evaluation improved accuracy of estimation of subgroup-specific meta-regression parameters relative to fitting separate models within subgroups. A random rather than fixed effects approach led to reduced bias in estimation of meta-regression parameters and in prediction in subgroups where the surrogate was strong. Finally, we found that subgroup-specific meta-regression posteriors were robust to use of constrained priors under the partial-pooling approach, and that use of constrained priors could facilitate more precise prediction for clinical effects in trials of a subgroup not available for the initial surrogacy evaluation. Conclusion Partial-pooling modeling strategies should be considered for surrogate endpoint evaluation on collections of heterogeneous studies. Fitting these models comes with additional complexity related to choosing priors. Constrained priors should be considered when using partial-pooling models when the goal is to predict the treatment effect on the clinical endpoint.

Introduction SCALE-UP II aims to investigate the effectiveness of population health management interventions using text messaging (TM), chatbots and patient navigation (PN) in increasing the uptake of at-home COVID-19 testing among patients in historically marginalised communities, specifically, those receiving care at community health centres (CHCs).Methods and analysis The trial is a multisite, randomised pragmatic clinical trial. Eligible patients are >18 years old with a primary care visit in the last 3 years at one of the participating CHCs. Demographic data will be obtained from CHC electronic health records. Patients will be randomised to one of two factorial designs based on smartphone ownership. Patients who self-report replying to a text message that they have a smartphone will be randomised in a 2×2×2 factorial fashion to receive (1) chatbot or TM; (2) PN (yes or no); and (3) repeated offers to interact with the interventions every 10 or 30 days. Participants who do not self-report as having a smartphone will be randomised in a 2×2 factorial fashion to receive (1) TM with or without PN; and (2) repeated offers every 10 or 30 days. The interventions will be sent in English or Spanish, with an option to request at-home COVID-19 test kits. The primary outcome is the proportion of participants using at-home COVID-19 tests during a 90-day follow-up. The study will evaluate the main effects and interactions among interventions, implementation outcomes and predictors and moderators of study outcomes. Statistical analyses will include logistic regression, stratified subgroup analyses and adjustment for stratification factors.Ethics and dissemination The protocol was approved by the University of Utah Institutional Review Board. On completion, study data will be made available in compliance with National Institutes of Health data sharing policies. Results will be disseminated through study partners and peer-reviewed publications.Trial registration number ClinicalTrials.gov: NCT05533918 and NCT05533359.

Abstract Background Short sleep duration, defined as

Abstract Background The OPTIMIZE trial is a multi-site, comparative effectiveness research (CER) study that uses a Sequential Multiple Assessment Randomized Trial (SMART) designed to examine the effectiveness of complex health interventions (cognitive behavioral therapy, physical therapy, and mindfulness) for adults with chronic low back pain. Modifications are anticipated when implementing complex interventions in CER. Disruptions due to COVID have created unanticipated challenges also requiring modifications. Recent methodologic standards for CER studies emphasize that fully characterizing modifications made is necessary to interpret and implement trial results. The purpose of this paper is to outline the modifications made to the OPTIMIZE trial using the Framework for Reporting Adaptations and Modifications to Evidence-Based Interventions (FRAME) to characterize modifications to the OPTIMIZE trial in response to the COVID pandemic and other challenges encountered. Methods The FRAME outlines a strategy to identify and report modifications to evidence-based interventions or implementation strategies, whether planned or unplanned. We use the FRAME to characterize the process used to modify the aspects of the OPTIMIZE trial. Modifications were made to improve lower-than-anticipated rates of treatment initiation and COVID-related restrictions. Contextual modifications were made to permit telehealth delivery of treatments originally designed for in-person delivery. Training modifications were made with study personnel to provide more detailed information to potential participants, use motivational interviewing communication techniques to clarify potential participants’ motivation and possible barriers to initiating treatment, and provide greater assistance with scheduling of assigned treatments. Results Modifications were developed with input from the trial’s patient and stakeholder advisory panels. The goals of the modifications were to improve trial feasibility without compromising the interventions’ core functions. Modifications were approved by the study funder and the trial steering committee. Conclusions Full and transparent reporting of modifications to clinical trials, whether planned or unplanned, is critical for interpreting the trial’s eventual results and considering future implementation efforts. Trial registration ClinicalTrials.gov NCT03859713. Registered on March 1, 2019

Abstract Background Both short sleep duration and circadian rhythm misalignment are risk factors for metabolic dysfunction, but the underlying mechanisms are unknown. The goal of this study is to examine how sleep duration and circadian alignment predict changes in cardiometabolic risk factors over a 12-month period, and test cognitive function and hedonic eating tendencies as potential mechanisms. Methods We will recruit a sample of 120 working aged adults with BMI 25–35 kg/m2 (overweight to class I obesity). The protocol includes 5 visits over a 12-month period. Study visits include wrist actigraphy to measure sleep behaviors, 24-h diet recalls, dim light melatonin collection, a computerized neurobehavioral assessment, eating in the absence of hunger task, and frequently sampled IV glucose tolerance test. Discussion The results of the TIME study will advance the understanding of how both short sleep duration and circadian misalignment contribute to behavioral aspects of obesity and metabolic dysfunction. Trial registration ClinicalTrials.Gov, NCT04759755 , registered retrospectively February 13, 2021.

Abstract Background In the development of prediction models for a clinical event, it is common to use the static prediction modeling (SPM), a regression model that relates baseline predictors to the time to event. In many situations, the data used in training and validation are from longitudinal studies, where predictor variables are time-varying and measured at clinical visits. But these data are not used in SPM. The landmark analysis (LA), previously proposed for dynamic prediction with longitudinal data, has interpretational difficulty when the baseline is not a risk-changing clinical milestone, as is often the case in observational studies of chronic disease without intervention. Methods This paper studies the generalized landmark analysis (GLA), a statistical framework to develop prediction models for longitudinal data. The GLA includes the LA as a special case, and generalizes it to situations where the baseline is not a risk-changing clinical milestone with a more useful interpretation. Unlike the LA, the landmark variable does not have to be time since baseline in the GLA, but can be any time-varying prognostic variable. The GLA can also be viewed as a longitudinal generalization of localized prediction, which has been studied in the context of low-dimensional cross-sectional data. We studied the GLA using data from the Chronic Renal Insufficiency Cohort (CRIC) Study and the Wisconsin Allograft Replacement Database (WisARD) and compared the prediction performance of SPM and GLA. Results In various validation populations from longitudinal data, the GLA generally had similarly or better predictive performance than SPM, with notable improvement being seen when the validation population deviated from the baseline population. The GLA also demonstrated similar or better predictive performance than LA, due to its more general model specification. Conclusions GLA is a generalization of the LA such that the landmark variable does not have to be the time since baseline. It has better interpretation when the baseline is not a risk-changing clinical milestone. The GLA is more adaptive to the validation population than SPM and is more flexible than LA, which may help produce more accurate prediction.

Abstract Introduction Survivors of acute respiratory failure (ARF) commonly experience long-lasting physical, cognitive, and/or mental health impairments. Unmet medication needs occurring immediately after hospital discharge may have an important effect on subsequent recovery. Methods and analysis In this multicenter prospective cohort study, we enrolled ARF survivors who were discharged directly home from their acute care hospitalization. The primary exposure was unmet medication needs. The primary outcome was hospital readmission or death within 3 months after discharge. We performed a propensity score analysis, using inverse probability weighting for the primary exposure, to evaluate the exposure–outcome association, with an a priori sample size of 200 ARF survivors. Results We enrolled 200 ARF survivors, of whom 107 (53%) were female and 77 (39%) were people of color. Median (IQR) age was 55 (43–66) years, APACHE II score 20 (15–26) points, and hospital length of stay 14 (9–21) days. Of the 200 participants, 195 (98%) were in the analytic cohort. One hundred fourteen (57%) patients had at least one unmet medication need; the proportion of medication needs that were unmet was 6% (0–15%). Fifty-six (29%) patients were readmitted or died by 3 months; 10 (5%) died within 3 months. Unmet needs were not associated (risk ratio 1.25; 95% CI 0.75–2.1) with hospital readmission or death, although a higher proportion of unmet needs may have been associated with increased hospital readmission (risk ratio 1.7; 95% CI 0.96–3.1) and decreased mortality (risk ratio 0.13; 95% CI 0.02–0.99). Discussion Unmet medication needs are common among survivors of acute respiratory failure shortly after discharge home. The association of unmet medication needs with 3-month readmission and mortality is complex and requires additional investigation to inform clinical trials of interventions to reduce unmet medication needs. Study registration number: NCT03738774 . The study was prospectively registered before enrollment of the first patient.

We aimed to generate an unbiased estimate of the incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in 4 urban counties in Utah, USA. We used a multistage sampling design to randomly select community-representative participants >12 years of age. During May 4–June 30, 2020, we collected serum samples and survey responses from 8,108 persons belonging to 5,125 households. We used a qualitative chemiluminescent microparticle immunoassay to detect SARS-CoV-2 IgG in serum samples. We estimated the overall seroprevalence to be 0.8%. The estimated seroprevalence-to-case count ratio was 2.5, corresponding to a detection fraction of 40%. Only 0.2% of participants from whom we collected nasopharyngeal swab samples had SARS-CoV-2–positive reverse transcription PCR results. SARS-CoV-2 antibody prevalence during the study was low, and prevalence of PCR-positive cases was even lower. The comparatively high SARS-CoV-2 detection rate (40%) demonstrates the effectiveness of Utah’s testing strategy and public health response.

Introduction: The Frequent Hemodialysis Network (FHN) Daily and Nocturnal trials aimed to compare the effects of hemodialysis (HD) given 6 versus 3 times per week. More frequent in-center HD significantly reduced left-ventricular mass (LVM), with more pronounced effects in patients with low urine volumes. In this study, we aimed to explore another potential effect modifier: the predialysis serum sodium (SNa) and related proxies of plasma tonicity. Methods: Using data from the FHN Daily and Nocturnal Trials, we compared the effects of frequent HD on LVM among patients stratified by SNa, dialysate-to-predialysis serum-sodium gradient (GNa), systolic and diastolic blood pressure, time-integrated sodium-adjusted fluid load (TIFL), and extracellular fluid volume estimated by bioelectrical impedance analysis. Results: In 197 enrolled subjects in the FHN Daily Trial, the treatment effect of frequent HD on ∆LVM was modified by SNa. When the FHN Daily Trial participants are divided into lower and higher predialysis SNa groups (less and greater than 138 mEq/L), the LVM reduction in the lower group was substantially higher (−28.0 [95% CI −40.5 to −15.4] g) than in the higher predialysis SNa group (−2.0 [95% CI −15.5 to 11.5] g). Accounting for GNa, TIFL also showed more pronounced effects among patients with higher GNa or higher TIFL. Results in the Nocturnal Trial were similar in direction and magnitude but did not reach statistical significance. Discussion/Conclusion: In the FHN Daily Trial, the favorable effects of frequent HD on left-ventricular hypertrophy were more pronounced among patients with lower predialysis SNa and higher GNa and TIFL. Whether these metrics can be used to identify patients most likely to benefit from frequent HD or other dialytic or nondialytic interventions remains to be determined. Prospective, adequately powered studies studying the effect of GNa reduction on mortality and hospitalization are needed.

Introduction Although evidence-based guidelines recommend non-pharmacologic treatments as first-line care for chronic low back pain (LBP), uptake has been limited, particularly in rural, low-income and ethnically diverse communities. The BeatPain study will evaluate the implementation and compare the effectiveness of two strategies to provide non-pharmacologic treatment for chronic LBP. The study will use telehealth to overcome access barriers for persons receiving care in federally qualified health centres (FQHCs) in the state of Utah.Methods and analysis BeatPain Utah is a pragmatic randomised clinical trial with a hybrid type I design investigating different strategies to provide non-pharmacologic care for adults with chronic LBP seen in Utah FQHCs. The intervention strategies include a brief pain consult (BPC) and telehealth physical therapy (PT) component provided using either an adaptive or sequenced delivery strategy across two 12-week treatment phases. Interventions are provided via telehealth by centrally located physical therapists. The sequenced delivery strategy provides the BPC, followed by telehealth PT in the first 12 weeks for all patients. The adaptive strategy uses a stepped care approach and provides the BPC in the first 12 weeks and telehealth PT to patients who are non-responders to the BPC component. We will recruit 500 English-speaking or Spanish-speaking participants who will be individually randomised with 1:1 allocation. The primary outcome is the Pain, Enjoyment and General Activity measure of pain impact with secondary outcomes including the additional pain assessment domains specified by the National Institutes (NIH) of Health Helping to End Addiction Long Initiative and implementation measures. Analyses of primary and secondary measures of effectiveness will be performed under longitudinal mixed effect models across assessments at baseline, and at 12, 26 and 52 weeks follow-ups.Ethics and dissemination Ethics approval for the study was obtained from the University of Utah Institutional Review Board. On completion, study data will be made available in compliance with NIH data sharing policies.Trial registration number NCT04923334.

Background The sodium‐glucose cotransporter 2 inhibitor canagliflozin reduced the risk of first cardiovascular composite events in the CREDENCE (Canagliflozin and Renal Events in Diabetes With Established Nephropathy Clinical Evaluation) trial. In this post hoc analysis, we evaluated the effect of canagliflozin on total (first and recurrent) cardiovascular events. Methods and Results The CREDENCE trial compared canagliflozin or matching placebo in 4401 patients with type 2 diabetes, albuminuria, and estimated glomerular filtration rate of 30 to

Abstract Background It is unclear whether faster progression of atherosclerosis explains the higher risk of cardiovascular events in CKD. The objectives of this study were to 1. Characterize the associations of CKD with presence and morphology of atherosclerotic plaques on carotid magnetic resonance imaging (MRI) and 2. Examine the associations of baseline CKD and carotid atherosclerotic plaques with subsequent cardiovascular events. Methods In a subgroup (N = 465) of Systolic Blood Pressure Intervention Trial. (SPRINT) participants, we measured carotid plaque presence and morphology at baseline and after 30-months with MRI. We examined the associations of CKD (baseline eGFR

Abstract Background Low back pain is a prevalent condition that causes a substantial health burden. Despite intensive and expensive clinical efforts, its prevalence is growing. Nonpharmacologic treatments are effective at improving pain-related outcomes; however, treatment effect sizes are often modest. Physical therapy (PT) and cognitive behavioral therapy (CBT) have the most consistent evidence of effectiveness. Growing evidence also supports mindfulness-based approaches. Discussions with providers and patients highlight the importance of discussing and trying options to find the treatment that works for them and determining what to do when initial treatment is not successful. Herein, we present the protocol for a study that will evaluate evidence-based, protocol-driven treatments using PT, CBT, or mindfulness to examine comparative effectiveness and optimal sequencing for patients with chronic low back pain. Methods The Optimized Multidisciplinary Treatment Programs for Nonspecific Chronic Low Back Pain (OPTIMIZE) Study will be a multisite, comparative effectiveness trial using a sequential multiple assessment randomized trial design enrolling 945 individuals with chronic low back pain. The co-primary outcomes will be disability (measured using the Oswestry Disability Index) and pain intensity (measured using the Numerical Pain Rating Scale). After baseline assessment, participants will be randomly assigned to PT or CBT. At week 10, participants who have not experienced at least 50% improvement in disability will be randomized to cross-over phase-1 treatments (e.g., PT to CBT) or to Mindfulness-Oriented Recovery Enhancement (MORE). Treatment will consist of 8 weekly sessions. Long-term outcome assessments will be performed at weeks 26 and 52. Discussion Results of this study may inform referring providers and patients about the most effective nonoperative treatment and/or sequence of nonoperative treatments to treat chronic low back pain. Trial registration This study was prospectively registered on March 1, 2019, with Clinicaltrials.gov under the registration number NCT03859713 ( https://clinicaltrials.gov/ct2/show/NCT03859713 ).

Abstract Background Tobacco use remains the leading cause of death and disability in the USA and is disproportionately concentrated among low socioeconomic status (SES) populations. Community Health Centers (CHCs) are a key venue for reaching low SES populations with evidence-based tobacco cessation treatment such as Quitlines. Electronic health record (EHR)-based interventions at the point-of-care, text messaging (TM), and phone counseling have the potential to increase Quitline reach and are feasible to implement within CHCs. However, there is a lack of data to inform how, when, and in what combination these strategies should be implemented. The aims of this cluster-randomized trial are to evaluate multi-level implementation strategies to increase the Reach (i.e., proportion of tobacco-using patients who enroll in the Quitline) and Impact (i.e., Reach × Efficacy [efficacy is defined as the proportion of tobacco-using patients who enroll in Quitline treatment that successfully quit]) and to evaluate characteristics of healthcare system, providers, and patients that may influence tobacco-use outcomes. Methods This study is a multilevel, three-phase, Sequential Multiple Assignment Randomized Trial (SMART), conducted in CHCs (N = 33 clinics; N = 6000 patients). In the first phase, clinics will be randomized to two different EHR conditions. The second and third phases are patient-level randomizations based on prior treatment response. Patients who enroll in the Quitline receive no further interventions. In phase two, patients who are non-responders (i.e., patients who do not enroll in Quitline) will be randomized to receive either TM or continued-EHR. In phase three, patients in the TM condition who are non-responders will be randomized to receive either continued-TM or TM + phone coaching. Discussion This project will evaluate scalable, multi-level interventions to directly address strategic national priorities for reducing tobacco use and related disparities by increasing the Reach and Impact of evidence-based tobacco cessation interventions in low SES populations. Trial registration This trial was registered at ClinicalTrials.gov (NCT03900767) on April 4th, 2019.

Community engagement is critical to accelerate and improve implementation of evidence-based interventions to reduce health inequities. Community-engaged dissemination and implementation research (CEDI) emphasizes engaging stakeholders (e.g., community members, practitioners, community organizations, etc.) with diverse perspectives, experience, and expertise to provide tacit community knowledge regarding the local context, priorities, needs, and assets. Importantly, CEDI can help improve health inequities through incorporating unique perspectives from communities experiencing health inequities that have historically been left out of the research process. The community-engagement process that exists in practice can be highly variable, and characteristics of the process are often underreported, making it difficult to discern how engagement of community partners was used to improve implementation. This paper describes the community-engagement process for a multilevel, pragmatic randomized trial to increase the reach and impact of evidence-based tobacco cessation treatment among Community Health Center patients; describes how engagement activities and the resulting partnership informed the development of implementation strategies and improved the research process; and presents lessons learned to inform future CEDI research.

Traditional clinical prediction models focus on parameters of the individual patient. For infectious diseases, sources external to the patient, including characteristics of prior patients and seasonal factors, may improve predictive performance. We describe the development of a predictive model that integrates multiple sources of data in a principled statistical framework using a post-test odds formulation. Our method enables electronic real-time updating and flexibility, such that components can be included or excluded according to data availability. We apply this method to the prediction of etiology of pediatric diarrhea, where 'pre-test’ epidemiologic data may be highly informative. Diarrhea has a high burden in low-resource settings, and antibiotics are often over-prescribed. We demonstrate that our integrative method outperforms traditional prediction in accurately identifying cases with a viral etiology, and show that its clinical application, especially when used with an additional diagnostic test, could result in a 61% reduction in inappropriately prescribed antibiotics.

Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a high risk of transmission in close-contact indoor settings, which may include households. Prior studies have found a wide range of household secondary attack rates and may contain biases due to simplifying assumptions about transmission variability and test accuracy. Methods We compiled serological SARS-CoV-2 antibody test data and prior SARS-CoV-2 test reporting from members of 9,224 Utah households. We paired these data with a probabilistic model of household importation and transmission. We calculated a maximum likelihood estimate of the importation probability, mean and variability of household transmission probability, and sensitivity and specificity of test data. Given our household transmission estimates, we estimated the threshold of non-household transmission required for epidemic growth in the population. Results We estimated that individuals in our study households had a 0.41% (95% CI 0.32%– 0.51%) chance of acquiring SARS-CoV-2 infection outside their household. Our household secondary attack rate estimate was 36% (27%– 48%), substantially higher than the crude estimate of 16% unadjusted for imperfect serological test specificity and other factors. We found evidence for high variability in individual transmissibility, with higher probability of no transmissions or many transmissions compared to standard models. With household transmission at our estimates, the average number of non-household transmissions per case must be kept below 0.41 (0.33–0.52) to avoid continued growth of the pandemic in Utah. Conclusions Our findings suggest that crude estimates of household secondary attack rate based on serology data without accounting for false positive tests may underestimate the true average transmissibility, even when test specificity is high. Our finding of potential high variability (overdispersion) in transmissibility of infected individuals is consistent with characterizing SARS-CoV-2 transmission being largely driven by superspreading from a minority of infected individuals. Mitigation efforts targeting large households and other locations where many people congregate indoors might curb continued spread of the virus.

Introduction As short-term mortality declines for critically ill patients, a growing number of survivors face long-term physical, cognitive and/or mental health impairments. After hospital discharge, many critical illness survivors require an in-depth plan to address their healthcare needs. Early after hospital discharge, numerous survivors experience inadequate care or a mismatch between their healthcare needs and what is provided. Many patients are readmitted to the hospital, have substantial healthcare resource use and experience long-lasting morbidity. The objective of this study is to investigate the gap in healthcare needs occurring immediately after hospital discharge and its association with hospital readmissions or death for survivors of acute respiratory failure (ARF).Methods and analysis In this multicentre prospective cohort study, we will enrol 200 survivors of ARF in the intensive care unit (ICU) who are discharged directly home from their acute care hospital stay. Unmet healthcare needs, the primary exposure of interest, will be evaluated as soon as possible within 1 to 4 weeks after hospital discharge, via a standardised telephone assessment. The primary outcome, death or hospital readmission, will be measured at 3 months after discharge. Secondary outcomes (eg, quality of life, cognitive impairment, depression, anxiety and post-traumatic stress disorder) will be measured as part of 3-month and 6-month telephone-based follow-up assessments. Descriptive statistics will be reported for the exposure and outcome variables along with a propensity score analysis, using inverse probability weighting for the primary exposure, to evaluate the relationship between the primary exposure and outcome.Ethics and dissemination The study received ethics approval from Vanderbilt University Medical Center Institutional Review Board (IRB) and the University of Utah IRB (for the Veterans Affairs site). These results will inform both clinical practice and future interventional trials in the field. We plan to disseminate the results in peer-reviewed journals, and via national and international conferences.Trial registration details ClinicalTrials.gov (NCT03738774). Registered before enrollment of the first patient.

BackgroundDiarrhea is one of the leading causes of childhood morbidity and mortality in lower- and middle-income countries. In such settings, access to laboratory diagnostics are often limited, and decisions for use of antimicrobials often empiric. Clinical predictors are a potential non-laboratory method to more accurately assess diarrheal etiology, the knowledge of which could improve management of pediatric diarrhea.MethodsWe used clinical and quantitative molecular etiologic data from the Global Enteric Multicenter Study (GEMS), a prospective, case-control study, to develop predictive models for the etiology of diarrhea. Using random forests, we screened the available variables and then assessed the performance of predictions from random forest regression models and logistic regression models using 5-fold cross-validation.ResultsWe identified 1049 cases where a virus was the only etiology, and developed predictive models against 2317 cases where the etiology was known but non-viral (bacterial, protozoal, or mixed). Variables predictive of a viral etiology included lower age, a dry and cold season, increased height-for-age z-score (HAZ), lack of bloody diarrhea, and presence of vomiting. Cross-validation suggests an AUC of 0.825 can be achieved with a parsimonious model of 5 variables, achieving a specificity of 0.85, a sensitivity of 0.59, a NPV of 0.82 and a PPV of 0.64.ConclusionPredictors of the etiology of pediatric diarrhea can be used by providers in low-resource settings to inform clinical decision-making. The use of non-laboratory methods to diagnose viral causes of diarrhea could be a step towards reducing inappropriate antibiotic prescription worldwide.

Abstract Background Chronic spinal pain affects many in the United States and is associated with rising healthcare costs - but not improved outcomes. Education and self-care promotion are hallmarks of the recommended approach for this condition. Pain Neuroscience Education (PNE) is a method of educating patients about the neurophysiology of pain that aims to reconceptualize pain from an indicator of damage to an interpretation of input signals by the brain and nervous system. PNE has shown efficacy in controlled situations when delivered by experts, but its effectiveness has not been investigated among trained clinicians in a pragmatic setting. Methods A cluster randomized trial will randomly assign 16 clinic regions to either receive PNE training or continue with usual care. Patients with chronic neck or back pain will be enrolled to provide outcome data. Measures will be collected at baseline, 2 weeks, and 12 weeks. The primary outcome will be the Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function computer-adapted test (PF-CAT). Pre-specified statistical analyses will compare outcomes between clinic regions assigned to PNE treatment or usual care while using random effects to account for region-level clustering. Discussion Pain Neuroscience Education has been shown efficacious for a variety of patient-centered outcomes for those with chronic pain, but it has not yet been investigated outside of controlled settings. This trial has the potential to promote PNE as a low-cost intervention for chronic spinal pain and affect physical therapy education. Trial registration ClinicalTrials.gov identifier NCT03168165, registered May 30, 2017.

Abstract Background Low back pain is a common and costly condition. Spinal manipulative therapy (SMT) is a treatment supported in some guidelines, although most clinical trials examining SMT report small effect sizes. Enhancing the effects of SMT requires an understanding of underlying mechanisms and a systematic approach to leverage understanding of mechanisms to create more effective treatment protocols that are scalable in clinical practice. Prior work has identified effects on spinal stiffness and lumbar multifidus activation as possible mechanisms. This project represents a refinement phase study within the context of a multi-phase optimization strategy (MOST) framework. Our goal is to identify an optimized SMT treatment protocol by examining the impact of using co-intervention exercise strategies that are proposed to accentuate SMT mechanisms. The optimized protocol can then be evaluated in confirmation phase clinical trials and implementation studies. Methods A phased, factorial randomized trial design will be used to evaluate the effects of three intervention components provided in eight combinations on mechanistic (spinal stiffness and multifidus muscle activation) and patient-reported outcomes (pain and disability). All participants will receive two sessions then will be randomly assigned to receive six additional sessions (or no additional treatment) over the next three weeks with factorial combinations of additional SMT and exercise co-interventions (spine mobilizing and multifidus activating). Outcome assessments occur at baseline, and one week, four weeks, and three months after enrollment. Pre-specified analyses will evaluate main effects for treatment components as well as interaction effects. Discussion Building on preliminary findings identifying possible mechanisms of effects for SMT, this trial represents the next phase in a multiphase strategy towards the ultimate goal of developing an optimized protocol for providing SMT to patients with LBP. If successful, the results of this trial can be tested in future clinical trials in an effort to produce larger treatment benefits and improve patient-centered outcomes for individuals with LBP. Trial registration ClinicalTrials.gov, NCT02868034. Registered on 16 August 2016.

Abstract Background This study evaluated the responsiveness of several PROMIS patient-reported outcome measures in patients with hand and upper extremity disorders and provided comparisons with the qDASH instrument. Methods The PROMIS Upper Extremity computer adaptive test (UE CAT) v1.2, the PROMIS Physical Function (PF) CAT v1.2, the PROMIS Pain Interference (PI) CAT v1.1 and the qDASH were administered to patients presenting to an orthopaedic hand clinic during the years 2014–2016, along with anchor questions. The responsiveness of these instruments was assessed using anchor based methods. Changes in functional outcomes were evaluated by paired-sample t-test, effect size, and standardized response mean. Results There were a total of 255 patients (131 females and 124 males) with an average age of 50.75 years (SD = 15.84) included in our study. Based on the change and no change scores, there were three instances (PI at 3 months, PI >3 months, and qDASH >3 months follow-ups) where scores differed between those experiencing clinically meaningful change versus no clinically meaningful change. Effect sizes for the responsiveness of all instruments were large and ranged from 0.80–1.48. All four instruments demonstrated high responsiveness, with a standardized response mean ranging from 1.05 to 1.63. Conclusion The PROMIS UE CAT, PF CAT, PI CAT, and qDASH are responsive to patient-reported functional change in the hand and upper extremity patient population.

The associations of dietary protein and/or energy intakes with protein or energy wasting in patients on maintenance hemodialysis are controversial. We examined these in the Hemodialysis (HEMO) Study. Methods: In 1487 participants in the HEMO Study, baseline dietary protein intake (grams per kilogram per day) and dietary energy intake (kilocalories per kilograms per day) were related to the presence of the protein-energy wasting (PEW) syndrome at month 12 (defined as the presence of at least 1 criteria in 2 of the 3 categories of low serum chemistry, low body mass, and low muscle mass) in logistic regression models. In additional separate models, protein intake estimated from equilibrated normalized protein catabolic rate (enPCR) was also related to the PEW syndrome. Results: Compared with the lowest quartile, the highest quartile of baseline dietary protein intake was paradoxically associated with increased risk of the PEW syndrome at month 12 (odds ratio [OR]: 4.11; 95% confidence interval [CI]: 2.79–6.05). This relationship was completely attenuated (OR: 1.35; 95% CI: 0.88–2.06) with adjustment for baseline body weight, which suggested mathematical coupling. Results were similar for dietary energy intake. Compared with the lowest quartile of baseline enPCR, the highest quartile was not associated with the PEW syndrome at 12 months (OR: 0.78; 95% CI: 0.54–1.12). Discussion: These data do not support the use of dietary protein intake or dietary energy intake criteria in the definition of the PEW syndrome in patients on maintenance hemodialysis.

It is unknown whether the criteria used to define protein−energy wasting (PEW) syndrome in dialysis patients reflect protein or energy wasting in the general and moderate CKD populations. Methods: In 11,834 participants in the 1999 to 2004 National Health and Nutrition Examination Survey, individual PEW syndrome criteria and the number of PEW syndrome categories were related to lean body and fat masses (measured by dual-energy absorptiometry) using linear regression in the entire cohort and CKD subpopulation. Results: Serum chemistry, body mass, and muscle mass PEW criteria tended to be associated with lower lean body and fat masses, but the low dietary protein and energy intake criteria were associated with significantly higher protein and energy stores. When the number of PEW syndrome categories was defined by nondietary categories alone, there was a monotonic inverse relationship with lean body and fat masses and a strong positive relationship with mortality. In contrast, when dietary category alone was present, mean body mass index was in the obesity range; the additional presence of 2 nondietary categories was associated with lower body mass index and lower lean body and fat masses. Thus, the association of a dietary category plus 2 additional nondietary categories with lower protein or energy stores was driven by the presence of the 2 nondietary categories. Results were similar in CKD subgroup. Discussion: Hence, a definition of PEW syndrome without dietary variables has face validity and reflects protein or energy wasting.

Background Intensive systolic blood pressure (SBP) lowering significantly reduced cardiovascular disease (CVD) events in SPRINT (Systolic Blood Pressure Intervention Trial) but not in ACCORD BP (Action to Control Cardiovascular Risk in Diabetes Blood Pressure). Methods and Results SPRINT tested the effects of intensive (

Background: In observational studies, higher uric acid levels are associated with metabolic syndrome, diabetes, and kidney disease. Objective: The objective of this study is to examine whether reduction of plasma uric acid with febuxostat, a xanthine oxido reductase inhibitor, impacts adipose tissue oxidative stress, adipokines, and markers of systemic inflammation or kidney fibrosis. Design: This was a double-blinded randomized controlled trial. Setting: Academic university setting was used. Patients: Overweight or obese adults with hyperuricemia and type 2 diabetic nephropathy were included. Measurements: Adipose tissue thiobarbituric acid reducing substances (TBARS) and adiponectin concentrations and urinary transforming growth factor–β (TGF-β) were primary endpoints. Plasma C-reactive protein, high molecular weight–adiponectin, interleukin–6, tumor necrosis factor–α, and TBARS and albuminuria were among predefined secondary endpoints. Methods: Participants were randomly assigned to febuxostat (n = 40) or matching placebo (n = 40) and followed for 24 weeks. Results: Baseline plasma uric acid levels were 426 ± 83 µmol/L; 95% completed the study. Estimated glomerular filtration rate (eGFR) declined from 54 ± 17 mL/min/1.73 m 2 at baseline to 51 ± 17 mL/min/1.73 m 2 at 24 weeks ( P = .05). In separate mixed-effects models, compared with placebo, febuxostat reduced uric acid by 50% ( P < .001) but had no significant effects on subcutaneous adipose tissue TBARS (−7.4%, 95% confidence interval [CI], 57.4%-101.4%) or adiponectin (6.7%, 95% CI, 26.0%-53.8%) levels or urinary TGF-β/creatinine ratio (18.0%, 95% CI, 10.0%-54.8%) or secondary endpoints. Limitations: Relatively modest sample size and short duration of follow-up. Conclusions: In this population with progressive diabetic nephropathy, febuxostat effectively reduced plasma uric acid. However, no detectable effects were observed for the prespecified primary or secondary endpoints. Trial Registration: The study was registered in clinicaltrials.gov (NCT01350388).

OBJECTIVES/SPECIFIC AIMS: The objective of this research is to determine under what conditions endpoints based on estimated glomerular filtration rate (eGFR) slope or on relatively small declines in eGFR provide valid and useful surrogate endpoints for pivotal clinical trials in chronic kidney disease (CKD) patients. METHODS/STUDY POPULATION: We consider 2 classes of surrogate endpoints. The first class includes endpoints defined by the average rate of change in eGFR during defined portions of the follow-up period of the trial, following initiation of the randomized treatment interventions. The second class includes composite endpoints defined by the time from randomization until the occurrence of a designated decline in eGFR or kidney failure. The true clinical endpoint is considered to be the time from randomization until kidney failure, irrespective of the trajectory in eGFR measurements prior to kidney failure. We apply statistical simulation to determine conditions under which alternative endpoints within the 2 classes are (1) valid surrogate endpoints, in the sense of preserving a low probability of rejecting the null hypothesis of no treatment effect on the surrogate endpoint when there is no treatment effect on the clinical endpoints and are also (2) useful surrogate endpoints, in the sense of providing increased statistical power that allows significant reductions in sample size and/or duration of follow-up. Input parameters for the simulations include (a) characteristics of the joint distribution of the longitudinal eGFR measurements and the time to occurrence of renal failure, (b) characteristics of the short-term and long-term effects of the treatment, and (c) design parameters, including the duration of accrual and follow-up and the spacing of eGFR measurements during the follow-up period. We use joint analyses of 19 treatment comparisons across 13 previous clinical trials of CKD patients to guide the selection of input parameters for the simulations. We apply longitudinal mixed effects models for analysis of endpoints based on eGFR slope, and Cox regression for analyses of the composite time-to-event endpoints. RESULTS/ANTICIPATED RESULTS: We have previously shown that surrogate endpoints defined by eGFR declines of 30% or 40% can provide valid and useful alternative endpoints in CKD clinical trials for interventions that do not produce short-term effects on eGFR which differ from the longer-term effects of the interventions. Other factors influencing the validity and utility of these endpoints include the average baseline eGFR, the mean rate of change in eGFR, and the extent to which the size of the treatment effect depends on the patient’s underling rate of eGFR decline. We will extend these results by presenting preliminary results describing conditions under which outcomes based on eGFR slope provide valid and useful alternatives to the clinical endpoint of time until occurrence of kidney failure. DISCUSSION/SIGNIFICANCE OF IMPACT: The statistical simulation strategy described in this research can be used during the design of clinical trials of chronic kidney disease to assist in the selection of endpoints that maximize savings in sample size and duration of follow-up while retaining a low risk of producing a false positive conclusion in the absence of a true effect of the treatment on the time until kidney failure.

OBJECTIVES/SPECIFIC AIMS: In this study, we propose to investigate effectiveness of 2 core services provided by the Center for Clinical and Translational Science (CCTS), home for CTSA program in the School of Medicine at the University of Utah. METHODS/STUDY POPULATION: We will apply a longitudinal database of research and tenure track faculty (n>600) in the School of Medicine at the University of Utah from 2006 to 2016 to estimate the effect of initial usage of the biostatistics and clinical services cores of the University of Utah CCTS on the probability of (a) ≥1 peer reviewed publication, (b) external grant funding, and (c) academic promotion within 1, 2, and 3 years after the initial contact. We will apply a “new users” design (Hernan et al., Epidemiology, 2008; 19: 766–779) to compare the outcomes of faculty initiating use of the 2 CCTS cores Versus faculty without prior use of these cores in a series of cohorts defined by the calendar year of initial contract with the 2 cores, with covariate adjustment performed within each cohort to account for measured confounders. Separate outcome models will be specified for each cohort, but the statistical models will be fit to stacked augmented data sets which include the data from each cohort. Using the stacked data set, results will be pooled across each of the cohorts to increase statistical power. Robust sandwich estimates of standard errors will be used to account for the inclusion of multiple assessments for each faculty member. RESULTS/ANTICIPATED RESULTS: Estimates of the effect of initiation of new CTSA usage on academic productivity outcomes will be obtained, and provided in conjunction with sensitivity analyses to address the potential impact of uncontrolled confounding. DISCUSSION/SIGNIFICANCE OF IMPACT: The proposed evaluation strategy should overcome some of the biases inherent in typical metrics for effectiveness of CTSA programs, and will be applied to evaluate success of future initiatives.

Pulse pressure (PP), a marker of arterial system properties, has been linked to cardiovascular (CV) complications. We examined (a) association between unit changes of PP and (i) composite CV outcomes and (ii) development of left-ventricular hypertrophy (LVH) and (b) effect of mean arterial pressure (MAP) control on rate of change in PP. We studied 1094 nondiabetics with nephrosclerosis in the African American Study of Kidney Disease and Hypertension. Subjects were randomly assigned to usual MAP goal (102–107 mmHg) or a lower MAP goal (≤92 mmHg) and randomized to beta-blocker, angiotensin converting enzyme inhibitor, or calcium channel blocker. After covariate adjustment, a higher PP was associated with increased risk of CV outcome (RR = 1.28, CI = 1.11–1.47, P