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Since September 2010, more than 10,000 patients have undergone preemptive, panel-based pharmacogenomic testing through the Vanderbilt Pharmacogenomic Resource for Enhanced Decisions in Care and Treatment program. Analysis of the genetic data from the first 9,589 individuals reveals that the frequency of genetic variants is concordant with published allele frequencies. Based on five currently implemented drug-gene interactions, the multiplexed test identified one or more actionable variants in 91% of the genotyped patients and in 96% of African American patients. Using medication exposure data from electronic medical records, we compared a theoretical 'reactive,' prescription-triggered, serial single-gene testing strategy with our preemptive, multiplexed genotyping approach. Reactive genotyping would have generated 14,656 genetic tests. These data highlight three advantages of preemptive genotyping: (i) the vast majority of patients carry at least one pharmacogenetic variant; (ii) data are available at the point of care; and (iii) there is a substantial reduction in testing burden compared with a reactive strategy. [ABSTRACT FROM AUTHOR]

A typical longitudinal study prospectively collects both repeated measures of a health status outcome as well as covariates that are used either as the primary predictor of interest or as important adjustment factors. In many situations, all covariates are measured on the entire study cohort. However, in some scenarios the primary covariates are time dependent yet may be ascertained retrospectively after completion of the study. One common example would be covariate measurements based on stored biological specimens such as blood plasma. While authors have previously proposed generalizations of the standard case-control design in which the clustered outcome measurements are used to selectively ascertain covariates (Neuhaus and Jewell, 1990) and therefore provide resource efficient collection of information, these designs do not appear to be commonly used. One potential barrier to the use of longitudinal outcome-dependent sampling designs would be the lack of a flexible class of likelihood-based analysis methods. With the relatively recent development of flexible and practical methods such as generalized linear mixed models (Breslow and Clayton, 1993) and marginalized models for categorical longitudinal data (see Heagerty and Zeger, 2000, for an overview), the class of likelihood-based methods is now sufficiently well developed to capture the major forms of longitudinal correlation found in biomedical repeated measures data. Therefore, the goal of this manuscript is to promote the consideration of outcome-dependent longitudinal sampling designs and to both outline and evaluate the basic conditional likelihood analysis allowing for valid statistical inference. [ABSTRACT FROM AUTHOR]

Background Up to 38% of inpatient medication errors occur at the administration stage. Although they reduce prescribing errors, computerized provider order entry (CPOE) systems do not prevent administration errors or timing discrepancies. This study determined the degree to which CPOE medication orders matched actual dose administration times. METHODS At a 658-bed academic hospital with CPOE but lacking electronic medication administration charting, authors randomly selected adult patients with eligible medication orders from historical 1999-2003 CPOE log files. Retrospective manual chart audits compared expected (from CPOE) and actual timing of medication administrations. Outcomes included: dose omissions, median lag times between ordered and charted administrations, unauthorized doses, wrong dose errors, and the rate of nurses' medication schedule shifting. RESULTS Dose omissions occurred in 756 of 6019 (12.6%) audited administration opportunities; only 313 of the omissions (5.2% of opportunities) were unexplained. Wrong doses and unexpected doses occurred for 0.1% and 0.7% of opportunities, respectively. Median lag from expected first dose to actual charted administration time was 27 minutes (IQR 0-127). Nursing staff shifted from ordered to alternate administration schedules for 10.7% of regularly scheduled recurring medication orders. Chart review identified reasons for dose omissions, delays, and dose shifting. CONCLUSION Inpatient CPOE orders are legible and conveyed electronically to nurses and the pharmacy. Nonetheless, ward-based medication administrations do not consistently occur as ordered. Medication administration discrepancies are likely to persist even after implementing CPOE and bar-coded medication administration unless recommended interventions are made to address issues such as determining the true urgency of medication administration, avoiding overlapping duplicative medication orders, and developing a safe means for shifting dosing schedules. [ABSTRACT FROM AUTHOR]

Information concerning the impact of environmental factors on cystic fibrosis (CF) is limited. We conducted a cohort study to assess the impact of air pollutants in CF. The study included patients over the age of 6 years enrolled in the Cystic Fibrosis Foundation National Patient Registry in 1999 and 2000. Exposure was assessed by linking air pollution values from the Aerometric Information Retrieval System with the patients' home zip code. After adjusting for confounders, a 10 microg/m(3) rise in particulate matter (both with a median aerodynamic diameter of 10 microm (PM(10)) or less and with an aerodynamic diameter of 2.5 microm or less (PM(2.5)) was associated with an 8% (95% confidence interval [CI], 2-15%) and 21% (95% CI, 7-33%) increase in the odds of two or more exacerbations, respectively; a 10-ppb rise in ozone was associated with a 10% (95% CI, 3-17%) increase in odds of two or more exacerbations. For every increase in PM(2.5) of 10 microg/m(3), there was an associated fall in FEV(1) of 24 ml (7-40) (95% CI) after adjusting for confounders. PM(2.5)'s association with mortality did not achieve statistical significance (adjusted RR = 1.32 per 10 microg/m(3) 0.91-1.93; 95% CI). Annual average exposures to particulate air pollution was associated with an increased risk of pulmonary exacerbations and a decline in lung function, suggesting a role of environmental exposures on prognosis in CF. [ABSTRACT FROM AUTHOR]

Background: While several studies examine the relationship between screen time and dietary practices in children and teenagers, there is limited research in toddlers. This study evaluates the association between television (TV) exposure and dietary practices in 2-year-old children., Methods: We conducted a cross-sectional, secondary data analysis from the Greenlight Intervention Study. Toddlers' daily TV watching time, mealtime TV, and dietary practices were assessed by caregiver report at the 24-month well-child visit. Separate regression models were used and adjusted for sociodemographic/household characteristics and clinic site., Results: Five hundred and thirty-two toddlers were included (51% Latino; 30% non-Latino Black; 59% ≤$20,000 annual household income). Median daily TV watching time was 42 minutes (interquartile range: 25, 60); 25% reported the TV was "usually on" during mealtimes. After adjustment, toddlers who watched more TV daily had higher odds of consuming sugar-sweetened beverages, fast food, and more junk food; those watching less TV had higher odds of consuming more fruits/vegetables. Those with the TV "usually on" during mealtimes were more likely to consume sugar-sweetened beverages (aOR 3.72 [95% confidence interval {CI} 2.16-6.43]), fast food (aOR 2.83 [95%CI 1.54-5.20]), and more junk food (aOR 4.25 [95%CI 2.71-6.65])., Conclusions: Among toddlers from primarily minoritized populations and of lower socioeconomic status, those who watched more TV daily and usually had the TV on during meals had significantly less healthy dietary practices, even after adjusting for known covariates. This study supports the current American Academy of Pediatrics screen time guidelines and underscores the importance of early counseling on general and mealtime TV., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.)

Background: Adults hospitalized for cardiovascular events are at high risk for postdischarge mortality. Screening of psychosocial risk is prioritized by the Joint Commission. We tested whether key patient-reported psychosocial and behavioral measures could predict posthospitalization mortality in a cohort of adults hospitalized for a cardiovascular event., Methods: We conducted a prospective cohort study to test the prognostic utility of validated patient-reported measures, including health literacy, social support, health behaviors and disease management, and socioeconomic status. Cox survival analyses of mortality were conducted over a median of 3.5 years., Results: Among 2977 adults hospitalized for either acute coronary syndrome or acute decompensated heart failure, the mean age was 53 years, and 60% were male. After adjusting for demographic, clinical, and other psychosocial factors, mortality risk was greatest among patients who reported being unemployed (hazard ratio [HR]: 1.99, 95% confidence interval [CI]): 1.30-3.06), retired (HR: 2.14, 95% CI: 1.60-2.87), or unable to work due to disability (HR: 2.36, 95% CI: 1.73-3.21), as compared to those who were employed. Patient-reported perceived health competence (PHCS-2) and exercise frequency were also associated with mortality risk after adjusting for all other variables (HR: 0.86, 95% CI: 0.73-1.00 per four-point increase in PHCS-2; HR: 0.86, 95% CI: 0.77-0.96 per 3-day increase in exercise frequency, respectively)., Conclusions: Patient-reported measures of employment status, perceived health competence, and exercise frequency independently predict mortality after a cardiac hospitalization. Incorporating these brief, valid measures into hospital-based screening may help with prognostication and targeting patients for resources during post-discharge transitions of care., (© 2024 The Authors. Journal of Hospital Medicine published by Wiley Periodicals LLC on behalf of Society of Hospital Medicine.)

Background: Understanding how different populations respond to a childhood obesity intervention could help optimize personalized treatment strategies, especially with the goal to reduce disparities in obesity. Methods: We conducted a secondary analysis of the Greenlight Cluster Randomized Controlled Trial, a health communication focused pediatric obesity prevention trial, to evaluate for heterogeneity of treatment effect (HTE) by child biological sex, caregiver BMI, caregiver reported race and ethnicity, primary language, and health literacy. To examine HTE on BMI z-score from 2 to 24 months of age, we fit linear mixed effects models. Results: We analyzed 802 caregiver-child pairs, of which 52% of children were female, 58% of households reported annual family income of <$20,000, and 83% did not have a college degree. We observed evidence to suggest HTE by primary language ( p  = 0.047 for Spanish vs. English) and the combination of primary language and health literacy ( p  = 0.01). There was insufficient evidence to suggest that the Greenlight intervention effect differed by biological sex, caregiver BMI, or by race/ethnicity. Conclusions: This HTE analysis found that the Greenlight obesity prevention intervention had a more beneficial effect on child BMI z-score over 2 years for children of caregivers with limited health literacy and for caregivers for whom Spanish was the primary language.

Background and Objectives: The American Academy of Pediatrics designed The Injury Prevention Program (TIPP) in 1983 to help pediatricians prevent unintentional injuries, but TIPP's effectiveness has never been formally evaluated. We sought to evaluate the impact of TIPP on reported injuries in the first 2 years of life., Methods: We conducted a stratified, cluster-randomized trial at 4 academic medical centers: 2 centers trained their pediatric residents and implemented TIPP screening and counseling materials at all well-child checks (WCCs) for ages 2 to 24 months, and 2 centers implemented obesity prevention. At each WCC, parents reported the number of child injuries since the previous WCC. Proportional odds logistic regression analyses with generalized estimating equation examined the extent to which the number of injuries reported were reduced at TIPP intervention sites compared with control sites, adjusting for baseline child, parent, and household factors., Results: A total of 781 parent-infant dyads (349 TIPP; 432 control) were enrolled and had sufficient data to qualify for analyses: 51% Hispanic, 28% non-Hispanic Black, and 87% insured by Medicaid. Those at TIPP sites had significant reduction in the adjusted odds of reported injuries compared with non-TIPP sites throughout the follow-up (P = .005), with adjusted odds ratios (95% CI) of 0.77 (0.66-0.91), 0.60 (0.44-0.82), 0.32 (0.16-0.62), 0.26 (0.12-0.53), and 0.27 (0.14-0.52) at 4, 6, 12, 18, and 24 months, respectively., Conclusions: In this cluster-randomized trial with predominantly low-income, Hispanic, and non-Hispanic Black families, TIPP resulted in a significant reduction in parent-reported injuries. Our study provides evidence for implementing the American Academy of Pediatrics' TIPP in routine well-child care., (Copyright © 2024 by the American Academy of Pediatrics.)

Background: Hospital readmission is common among patients with heart failure. Vulnerability to decline in physical function may increase the risk of noncardiovascular readmission for these patients, but the association between vulnerability and the cause of unplanned readmission is poorly understood, inhibiting the development of effective interventions., Objectives: We examined the association of vulnerability with the cause of readmission (cardiovascular vs. noncardiovascular) among hospitalized patients with acute decompensated heart failure., Designs, Settings, and Participants: This prospective longitudinal study is part of the Vanderbilt Inpatient Cohort Study., Main Outcome and Measures: The primary outcome was the cause of unplanned readmission (cardiovascular vs. noncardiovascular). The primary independent variable was vulnerability, measured using the Vulnerable Elders Survey (VES-13)., Results: Among 804 hospitalized patients with acute decompensated heart failure, 315 (39.2%) experienced an unplanned readmission within 90 days of discharge. In a multinomial logistic model with no readmission as the reference category, higher vulnerability was associated with readmission for noncardiovascular causes (relative risk ratio [RRR] = 1.36, 95% confidence interval [CI]: 1.06-1.75) in the first 90 days after discharge. The VES-13 score was not associated with readmission for cardiovascular causes (RRR = 0.94, 95% CI: 0.75-1.17)., Conclusions: Vulnerability to functional decline predicted noncardiovascular readmission risk among hospitalized patients with heart failure. The VES-13 is a brief, validated, and freely available tool that should be considered in planning care transitions. Additional work is needed to examine the efficacy of interventions to monitor and mitigate noncardiovascular concerns among vulnerable patients with heart failure being discharged from the hospital., (© 2024 Society of Hospital Medicine.)

Objective: Infants with high birthweight have increased risk for adverse outcomes at birth and across childhood. Prenatal risks to healthy food access may increase odds of high birthweight. We tested whether having a poor neighborhood food environment and/or food insecurity had associations with high birthweight., Methods: We analyzed cross-sectional baseline data in Greenlight Plus, an obesity prevention trial across six US cities (n = 787), which included newborns with a gestational age greater than 34 weeks and a birthweight greater than 2500 g. We assessed neighborhood food environment using the Place-Based Survey and food insecurity using the US Household Food Security Module. We performed logistic regression analyses to assess the individual and additive effects of risk factors on high birthweight. We adjusted for potential confounders: infant sex, race, ethnicity, gestational age, birthing parent age, education, income, and study site., Results: Thirty-four percent of birthing parents reported poor neighborhood food environment and/or food insecurity. Compared to those without food insecurity, food insecure families had greater odds of delivering an infant with high birthweight (adjusted odds ratios [aOR] 1.96, 95% confidence intervals [CI]: 1.01, 3.82) after adjusting for poor neighborhood food environment, which was not associated with high birthweight (aOR 1.35, 95% CI: 0.78, 2.34). Each additional risk to healthy food access was associated with a 56% (95% CI: 4%-132%) increase in high birthweight odds., Conclusions: Prenatal risks to healthy food access may increase high infant birthweight odds. Future studies designed to measure neighborhood factors should examine infant birthweight outcomes in the context of prenatal social determinants of health., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.)

Researchers interested in understanding the relationship between a readily available longitudinal binary outcome and a novel biomarker exposure can be confronted with ascertainment costs that limit sample size. In such settings, two-phase studies can be cost-effective solutions that allow researchers to target informative individuals for exposure ascertainment and increase estimation precision for time-varying and/or time-fixed exposure coefficients. In this paper, we introduce a novel class of residual-dependent sampling (RDS) designs that select informative individuals using data available on the longitudinal outcome and inexpensive covariates. Together with the RDS designs, we propose a semiparametric analysis approach that efficiently uses all data to estimate the parameters. We describe a numerically stable and computationally efficient EM algorithm to maximize the semiparametric likelihood. We examine the finite sample operating characteristics of the proposed approaches through extensive simulation studies, and compare the efficiency of our designs and analysis approach with existing ones. We illustrate the usefulness of the proposed RDS designs and analysis method in practice by studying the association between a genetic marker and poor lung function among patients enrolled in the Lung Health Study (Connett et al, 1993)., (© The Author(s) 2024. Published by Oxford University Press on behalf of The International Biometric Society.)

Continuous response data are regularly transformed to meet regression modeling assumptions. However, approaches taken to identify the appropriate transformation can be ad hoc and can increase model uncertainty. Further, the resulting transformations often vary across studies leading to difficulties with synthesizing and interpreting results. When a continuous response variable is measured repeatedly within individuals or when continuous responses arise from clusters, analyses have the additional challenge caused by within-individual or within-cluster correlations. We extend a widely used ordinal regression model, the cumulative probability model (CPM), to fit clustered, continuous response data using generalized estimating equations for ordinal responses. With the proposed approach, estimates of marginal model parameters, cumulative distribution functions , expectations, and quantiles conditional on covariates can be obtained without pretransformation of the response data. While computational challenges arise with large numbers of distinct values of the continuous response variable, we propose feasible and computationally efficient approaches to fit CPMs under commonly used working correlation structures. We study finite sample operating characteristics of the estimators via simulation and illustrate their implementation with two data examples. One studies predictors of CD4:CD8 ratios in a cohort living with HIV, and the other investigates the association of a single nucleotide polymorphism and lung function decline in a cohort with early chronic obstructive pulmonary disease., (© 2023 The International Biometric Society.)

Objective: To assess if 100% fruit juice intake prior to 6 months is associated with juice and sugar-sweetened beverage (SSB) intake at 24 months and whether this differs by sociodemographic factors., Methods: We used longitudinal data from infants enrolled in the control (no obesity intervention) arm of Greenlight, a cluster randomized trial to prevent childhood obesity which included parent-reported child 100% fruit juice intake at all well child checks between 2 and 24 months. We studied the relationship between the age of juice introduction (before vs after 6 months) and juice and SSB intake at 24 months using negative binomial regression while controlling for baseline sociodemographic factors., Results: We report results for 187 participants (43% Hispanic, 39% non-Hispanic Black), more than half (54%) of whom had reported 100% fruit juice intake before 6 months. Average 100% fruit juice intake at 24 months was greater than the recommended amount (of 4 oz) and was 8.2 oz and 5.3 oz for those who had and had not, respectively, been introduced to juice before 6 months. In adjusted models, early introduction of juice was associated with a 43% (95% confidence interval: 5%-96%) increase in juice intake at 24 months., Conclusions: 100% fruit juice intake exceeding recommended levels at 6 and 24 months in this diverse cohort was prevalent. Introducing 100% fruit juice prior to 6 months may put children at greater risk for more juice intake as they age. Further research is necessary to determine if early guidance can reduce juice intake., (Copyright © 2023 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.)

Two-phase studies are crucial when outcome and covariate data are available in a first-phase sample (e.g., a cohort study), but costs associated with retrospective ascertainment of a novel exposure limit the size of the second-phase sample, in whom the exposure is collected. For longitudinal outcomes, one class of two-phase studies stratifies subjects based on an outcome vector summary (e.g., an average or a slope over time) and oversamples subjects in the extreme value strata while undersampling subjects in the medium-value stratum. Based on the choice of the summary, two-phase studies for longitudinal data can increase efficiency of time-varying and/or time-fixed exposure parameter estimates. In this manuscript, we extend efficient, two-phase study designs to multivariate longitudinal continuous outcomes, and we detail two analysis approaches. The first approach is a multiple imputation analysis that combines complete data from subjects selected for phase two with the incomplete data from those not selected. The second approach is a conditional maximum likelihood analysis that is intended for applications where only data from subjects selected for phase two are available. Importantly, we show that both approaches can be applied to secondary analyses of previously conducted two-phase studies. We examine finite sample operating characteristics of the two approaches and use the Lung Health Study (Connett et al. (1993), Controlled Clinical Trials, 14, 3S-19S) to examine genetic associations with lung function decline over time., (© 2022 The International Biometric Society.)

Background: The cost-effectiveness of screening the U.S. population for Centers for Disease Control and Prevention (CDC) Tier 1 genomic conditions is unknown., Objective: To estimate the cost-effectiveness of simultaneous genomic screening for Lynch syndrome (LS), hereditary breast and ovarian cancer syndrome (HBOC), and familial hypercholesterolemia (FH)., Design: Decision analytic Markov model., Data Sources: Published literature., Target Population: Separate age-based cohorts (ages 20 to 60 years at time of screening) of racially and ethnically representative U.S. adults., Time Horizon: Lifetime., Perspective: U.S. health care payer., Intervention: Population genomic screening using clinical sequencing with a restricted panel of high-evidence genes, cascade testing of first-degree relatives, and recommended preventive interventions for identified probands., Outcome Measures: Incident breast, ovarian, and colorectal cancer cases; incident cardiovascular events; quality-adjusted survival; and costs., Results of Base-Case Analysis: Screening 100 000 unselected 30-year-olds resulted in 101 (95% uncertainty interval [UI], 77 to 127) fewer overall cancer cases and 15 (95% UI, 4 to 28) fewer cardiovascular events and an increase of 495 quality-adjusted life-years (QALYs) (95% UI, 401 to 757) at an incremental cost of $33.9 million (95% UI, $27.0 million to $41.1 million). The incremental cost-effectiveness ratio was $68 600 per QALY gained (95% UI, $41 800 to $88 900)., Results of Sensitivity Analysis: Screening 30-, 40-, and 50-year-old cohorts was cost-effective in 99%, 88%, and 19% of probabilistic simulations, respectively, at a $100 000-per-QALY threshold. The test costs at which screening 30-, 40-, and 50-year-olds reached the $100 000-per-QALY threshold were $413, $290, and $166, respectively. Variant prevalence and adherence to preventive interventions were also highly influential parameters., Limitations: Population averages for model inputs, which were derived predominantly from European populations, vary across ancestries and health care environments., Conclusion: Population genomic screening with a restricted panel of high-evidence genes associated with 3 CDC Tier 1 conditions is likely to be cost-effective in U.S. adults younger than 40 years if the testing cost is relatively low and probands have access to preventive interventions., Primary Funding Source: National Human Genome Research Institute., Competing Interests: Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M22-0846.

Outcome-dependent sampling (ODS) is a commonly used class of sampling designs to increase estimation efficiency in settings where response information (and possibly adjuster covariates) is available, but the exposure is expensive and/or cumbersome to collect. We focus on ODS within the context of a two-phase study, where in Phase One the response and adjuster covariate information is collected on a large cohort that is representative of the target population, but the expensive exposure variable is not yet measured. In Phase Two, using response information from Phase One, we selectively oversample a subset of informative subjects in whom we collect expensive exposure information. Importantly, the Phase Two sample is no longer representative, and we must use ascertainment-correcting analysis procedures for valid inferences. In this paper, we focus on likelihood-based analysis procedures, particularly a conditional-likelihood approach and a full-likelihood approach. Whereas the full-likelihood retains incomplete Phase One data for subjects not selected into Phase Two, the conditional-likelihood explicitly conditions on Phase Two sample selection (ie, it is a "complete case" analysis procedure). These designs and analysis procedures are typically implemented assuming a known, parametric model for the response distribution. However, in this paper, we approach analyses implementing a novel semi-parametric extension to generalized linear models (SPGLM) to develop likelihood-based procedures with improved robustness to misspecification of distributional assumptions. We specifically focus on the common setting where standard GLM distributional assumptions are not satisfied (eg, misspecified mean/variance relationship). We aim to provide practical design guidance and flexible tools for practitioners in these settings., (© 2023 John Wiley & Sons, Ltd.)

Importance: Preclinical models suggest dysregulation of the renin-angiotensin system (RAS) caused by SARS-CoV-2 infection may increase the relative activity of angiotensin II compared with angiotensin (1-7) and may be an important contributor to COVID-19 pathophysiology., Objective: To evaluate the efficacy and safety of RAS modulation using 2 investigational RAS agents, TXA-127 (synthetic angiotensin [1-7]) and TRV-027 (an angiotensin II type 1 receptor-biased ligand), that are hypothesized to potentiate the action of angiotensin (1-7) and mitigate the action of the angiotensin II., Design, Setting, and Participants: Two randomized clinical trials including adults hospitalized with acute COVID-19 and new-onset hypoxemia were conducted at 35 sites in the US between July 22, 2021, and April 20, 2022; last follow-up visit: July 26, 2022., Interventions: A 0.5-mg/kg intravenous infusion of TXA-127 once daily for 5 days or placebo. A 12-mg/h continuous intravenous infusion of TRV-027 for 5 days or placebo., Main Outcomes and Measures: The primary outcome was oxygen-free days, an ordinal outcome that classifies a patient's status at day 28 based on mortality and duration of supplemental oxygen use; an adjusted odds ratio (OR) greater than 1.0 indicated superiority of the RAS agent vs placebo. A key secondary outcome was 28-day all-cause mortality. Safety outcomes included allergic reaction, new kidney replacement therapy, and hypotension., Results: Both trials met prespecified early stopping criteria for a low probability of efficacy. Of 343 patients in the TXA-127 trial (226 [65.9%] aged 31-64 years, 200 [58.3%] men, 225 [65.6%] White, and 274 [79.9%] not Hispanic), 170 received TXA-127 and 173 received placebo. Of 290 patients in the TRV-027 trial (199 [68.6%] aged 31-64 years, 168 [57.9%] men, 195 [67.2%] White, and 225 [77.6%] not Hispanic), 145 received TRV-027 and 145 received placebo. Compared with placebo, both TXA-127 (unadjusted mean difference, -2.3 [95% CrI, -4.8 to 0.2]; adjusted OR, 0.88 [95% CrI, 0.59 to 1.30]) and TRV-027 (unadjusted mean difference, -2.4 [95% CrI, -5.1 to 0.3]; adjusted OR, 0.74 [95% CrI, 0.48 to 1.13]) resulted in no difference in oxygen-free days. In the TXA-127 trial, 28-day all-cause mortality occurred in 22 of 163 patients (13.5%) in the TXA-127 group vs 22 of 166 patients (13.3%) in the placebo group (adjusted OR, 0.83 [95% CrI, 0.41 to 1.66]). In the TRV-027 trial, 28-day all-cause mortality occurred in 29 of 141 patients (20.6%) in the TRV-027 group vs 18 of 140 patients (12.9%) in the placebo group (adjusted OR, 1.52 [95% CrI, 0.75 to 3.08]). The frequency of the safety outcomes was similar with either TXA-127 or TRV-027 vs placebo., Conclusions and Relevance: In adults with severe COVID-19, RAS modulation (TXA-127 or TRV-027) did not improve oxygen-free days vs placebo. These results do not support the hypotheses that pharmacological interventions that selectively block the angiotensin II type 1 receptor or increase angiotensin (1-7) improve outcomes for patients with severe COVID-19., Trial Registration: ClinicalTrials.gov Identifier: NCT04924660.

A generalized case-control (GCC) study, like the standard case-control study, leverages outcome-dependent sampling (ODS) to extend to nonbinary responses. We develop a novel, unifying approach for analyzing GCC study data using the recently developed semiparametric extension of the generalized linear model (GLM), which is substantially more robust to model misspecification than existing approaches based on parametric GLMs. For valid estimation and inference, we use a conditional likelihood to account for the biased sampling design. We describe analysis procedures for estimation and inference for the semiparametric GLM under a conditional likelihood, and we discuss problems with estimation and inference under a conditional likelihood when the response distribution is misspecified. We demonstrate the flexibility of our approach over existing ones through extensive simulation studies, and we apply the methodology to an analysis of the Asset and Health Dynamics Among the Oldest Old study, which motives our research. The proposed approach yields a simple yet versatile solution for handling ODS in a wide variety of possible response distributions and sampling schemes encountered in practice., (© 2021 The International Biometric Society.)

Introduction: Social support is a modifiable social determinant of health that shapes breastfeeding outcomes and may contribute to racial and ethnic breastfeeding disparities. This study characterizes the relationship between social support and early breastfeeding., Methods: This is a cross-sectional analysis of baseline data collected in 2019-2021 for an RCT. Social support was measured using the Enhancing Recovery in Coronary Heart Disease Social Support Instrument. Outcomes, collected by self-report, included (1) early breastfeeding within the first 21 days of life, (2) planned breastfeeding duration, and (3) confidence in meeting breastfeeding goals. Each outcome was modeled using proportional odds regression, adjusting for covariates. Analysis was conducted in 2021-2022., Results: Self-reported race and ethnicity among 883 mothers were 50% Hispanic, 17% Black, 23% White, and 10% other. A large proportion (88%) of mothers were breastfeeding. Most breastfeeding mothers (82%) planned to breastfeed for at least 6 months, with more than half (58%) planning to continue for 12 months or more. Most women (65%) were confident or very confident in meeting their breastfeeding duration goal. In adjusted models, perceived social support was associated with planned breastfeeding duration (p=0.042) but not with early breastfeeding (p=0.873) or confidence in meeting breastfeeding goals (p=0.427). Among the covariates, maternal depressive symptoms were associated with lower breastfeeding confidence (p<0.001)., Conclusions: The associations between perceived social support and breastfeeding outcomes are nuanced. In this sample of racially and ethnically diverse mothers, social support was associated with longer planned breastfeeding duration but not with early breastfeeding or breastfeeding confidence., (Copyright © 2022 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.)

Background: The first 1000 days of a child's life are increasingly recognized as a critical window for establishing a healthy growth trajectory to prevent childhood obesity and its associated long-term comorbidities. The purpose of this manuscript is to detail the methods for a multi-site, comparative effectiveness trial designed to prevent childhood overweight and obesity from birth to age 2 years., Methods: This study is a multi-site, individually randomized trial testing the comparative effectiveness of two active intervention arms: 1) the Greenlight intervention; and 2) the Greenlight Plus intervention. The Greenlight intervention is administered by trained pediatric healthcare providers at each well-child visit from 0 to 18 months and consists of a low health literacy toolkit used during clinic visits to promote shared goal setting. Families randomized to Greenlight Plus receive the Greenlight intervention plus a health information technology intervention, which includes: 1) personalized, automated text-messages that facilitate caregiver self-monitoring of tailored and age-appropriate child heath behavior goals; and 2) a web-based, personalized dashboard that tracks child weight status, progress on goals, and electronic Greenlight content access. We randomized 900 parent-infant dyads, recruited from primary care clinics across six academic medical centers. The study's primary outcome is weight for length trajectory from birth through 24 months., Conclusions: By delivering a personalized and tailored health information technology intervention that is asynchronous to pediatric primary care visits, we aim to achieve improvements in child growth trajectory through two years of age among a sample of geographically, socioeconomically, racially, and ethnically diverse parent-child dyads., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Healthy individuals in the United States identified as having Black race have lower neutrophil counts, on average, than individuals identified as having White race, which could result in more negative diagnostic evaluations for neutropenia. To test this hypothesis, the proportion of evaluations where the final diagnosis was clinically insignificant neutropenia for Black and White individuals who underwent an evaluation by a haematologist that included a bone marrow (BM) biopsy to investigate neutropenia was assessed. 172 individuals without prior haematological diagnoses who underwent a haematological evaluation to investigate neutropenia. Individuals diagnosed with clinically insignificant neutropenia between Black and White individuals were compared using a propensity-score-adjusted logistic regression. Of 172 individuals, 42 (24%) were classified as Black race, 86 (50%) were males, and the 79 (46%) were over 18 years old. A BM biopsy did not identify pathology in 95% (40 of 42) of Black individuals and 68% (89 of 130) of White Individuals. Black individuals (25 of 42 [60%]) received a final diagnosis of clinically insignificant neutropenia, compared to White individuals (12 of 130 [9%]) (adjusted odds ratio =7.9, 95% CI: 3.1 - 21.1). We conclude that black individuals were more likely to receive a diagnosis of clinically insignificant neutropenia after haematological assessment., (© 2022 The Authors. Journal of Cellular and Molecular Medicine published by Foundation for Cellular and Molecular Medicine and John Wiley & Sons Ltd.)

Studies of critically ill, hospitalized patients often follow participants and characterize daily health status using an ordinal outcome variable. Statistically, longitudinal proportional odds models are a natural choice in these settings since such models can parsimoniously summarize differences across patient groups and over time. However, when one or more of the outcome states is absorbing, the proportional odds assumption for the follow-up time parameter will likely be violated, and more flexible longitudinal models are needed. Motivated by the VIOLET Study (Ginde et al), a parallel-arm, randomized clinical trial of Vitamin D 3 in critically ill patients, we discuss and contrast several treatment effect estimands based on time-dependent odds ratio parameters, and we detail contemporary modeling approaches. In VIOLET, the outcome is a four-level ordinal variable where the lowest "not alive" state is absorbing and the highest "at-home" state is nearly absorbing. We discuss flexible extensions of the proportional odds model for longitudinal data that can be used for either model-based inference, where the odds ratio estimator is taken directly from the model fit, or for model-assisted inferences, where heterogeneity across cumulative log odds dichotomizations is modeled and results are summarized to obtain an overall odds ratio estimator. We focus on direct estimation of cumulative probability model (CPM) parameters using likelihood-based analysis procedures that naturally handle absorbing states. We illustrate the modeling procedures, the relative precision of model-based and model-assisted estimators, and the possible differences in the values for which the estimators are consistent through simulations and analysis of the VIOLET Study data., (© 2022 John Wiley & Sons Ltd.)

Background: Continuous peripheral nerve catheters (PNCs) have been shown to provide superior postoperative analgesia, decrease opioid consumption, and improve patient satisfaction compared with single injection techniques. In order to achieve success and reliability, accurate catheter positioning is an essential element of PNC placement. An agitated solution of normal saline, D5W, or a local anesthetic solution can be produced by the introduction of air to the injectate, creating air bubbles that can enhance ultrasonographic visualization and possibly improve block success., Methods: Eighty-three patients were enrolled. Ultrasound-guided continuous popliteal sciatic nerve blocks were performed by positioning the tip of a Tuohy needle between the tibial and common peroneal branches of the sciatic nerve and threading a catheter. An agitated local anesthetic solution was injected through the catheter, viewed with color Doppler ultrasound and video recorded. A peripheral block score (lower score = greater blockade, range 0-14) was calculated based upon the motor and sensory testing at 10, 20, and 30 min after block completion. The color Doppler agitation coverage pattern for the branches of the sciatic nerve was graded as follows: complete (> 50%), partial (> 0%, ≤ 50%), or none (0%)., Results: The degree of nerve blockade at 30 min as judged by median (10th, 90th percentile) peripheral block score was significant for partial or complete color Doppler coverage of the sciatic nerve injectate compared to no coverage [3 (0, 7) vs 8 (4, 14); p < 0.01] and block onset was faster (p = 0.03). The block success was higher in groups with partial or complete coverage of the branches of the sciatic nerve vs no coverage (96% vs 70%; p = 0.02)., Conclusions: Injection of an agitated solution through a popliteal sciatic perineural catheter is predictive of accurate catheter placement when partial or complete coverage of the sciatic nerve branches is visualized with color Doppler ultrasound., Trial Registration: NCT01591603., (© 2021. The Author(s).)

Importance: Up to two-thirds of African American individuals carry the benign rs2814778-CC genotype that lowers total white blood cell (WBC) count., Objective: To examine whether the rs2814778-CC genotype is associated with an increased likelihood of receiving a bone marrow biopsy (BMB) for an isolated low WBC count., Design, Setting, and Participants: This retrospective genetic association study assessed African American patients younger than 90 years who underwent a BMB at Vanderbilt University Medical Center, Mount Sinai Health System, or Children's Hospital of Philadelphia from January 1, 1998, to December 31, 2020., Exposure: The rs2814778-CC genotype., Main Outcomes and Measures: The proportion of individuals with the CC genotype who underwent BMB for an isolated low WBC count and had a normal biopsy result compared with the proportion of individuals with the CC genotype who underwent BMB for other indications and had a normal biopsy result., Results: Among 399 individuals who underwent a BMB (mean [SD] age, 41.8 [22.5] years, 234 [59%] female), 277 (69%) had the CC genotype. A total of 35 patients (9%) had clinical histories of isolated low WBC counts, and 364 (91%) had other histories. Of those with a clinical history of isolated low WBC count, 34 of 35 (97%) had the CC genotype vs 243 of 364 (67%) of those without a low WBC count history. Among those with the CC genotype, 33 of 34 (97%) had normal results for biopsies performed for isolated low WBC counts compared with 134 of 243 individuals (55%) with biopsies performed for other histories (P < .001)., Conclusions and Relevance: In this genetic association study, among patients of African American race who had a BMB with a clinical history of isolated low WBC counts, the rs2814778-CC genotype was highly prevalent, and 97% of these BMBs identified no hematologic abnormality. Accounting for the rs2814778-CC genotype in clinical decision-making could avoid unnecessary BMB procedures.

Objective: This study examines the development of active television (TV) watching behaviors across the first 2 years of life in a racially and ethnically diverse, low-income cohort and identifies caregiver and child predictors of early TV watching., Methods: We used longitudinal data from infants enrolled in the active control group (N = 235; 39% Latino; 29% Black; 15% White) of Greenlight, a cluster randomized multisite trial to prevent childhood obesity. At preventive health visits from 2 months to 2 years, caregivers were asked: "How much time does [child's first name] spend watching television each day?" Proportional odds models and linear regression analyses were used to assess associations among TV introduction age, active TV watching amount at 2 years, and sociodemographic factors., Results: Sixty-eight percent of children watched TV by 6 months, and 88% by 2 years. Age of TV introduction predicted amount of daily active TV watching at 2 years, with a mean time of 93 minutes if starting at 2 months; 64 minutes if starting at 4 or 6 months; and 42 minutes if starting after 6 months. Factors predicting earlier introduction included lower income, fewer children in household, care away from home, male sex, and non-Latino ethnicity of child., Conclusions: Many caregivers report that their infants actively watch TV in the first 6 months of life. Earlier TV watching is related to sociodemographic factors yet predicts more daily TV watching at 2 years even controlling those factors. Interventions to limit early TV watching should be initiated in infancy., (Copyright © 2020 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.)

Background: A large multi-center survey was conducted to understand patients' perspectives on biobank study participation with particular focus on racial and ethnic minorities. In order to enrich the study sample with racial and ethnic minorities, disproportionate stratified sampling was implemented with strata defined by electronic health records (EHR) that are known to be inaccurate. We investigate the effect of sampling strata misclassification in complex survey design., Methods: Under non-differential and differential misclassification in the sampling strata, we compare the validity and precision of three simple and common analysis approaches for settings in which the primary exposure is used to define the sampling strata. We also compare the precision gains/losses observed from using a disproportionate stratified sampling scheme compared to using a simple random sample under varying degrees of strata misclassification., Results: Disproportionate stratified sampling can result in more efficient parameter estimates of the rare subgroups (race/ethnic minorities) in the sampling strata compared to simple random sampling. When sampling strata misclassification is non-differential with respect to the outcome, a design-agnostic analysis was preferred over model-based and design-based analyses. All methods yielded unbiased parameter estimates but standard error estimates were lowest from the design-agnostic analysis. However, when misclassification is differential, only the design-based method produced valid parameter estimates of the variables included in the sampling strata., Conclusions: In complex survey design, when the interest is in making inference on rare subgroups, we recommend implementing disproportionate stratified sampling over simple random sampling even if the sampling strata are misclassified. If the misclassification is non-differential, we recommend a design-agnostic analysis. However, if the misclassification is differential, we recommend using design-based analyses., (© 2021. The Author(s).)

The value of utilizing a multigene pharmacogenetic panel to tailor pharmacotherapy is contingent on the prevalence of prescribed medications with an actionable pharmacogenetic association. The Clinical Pharmacogenetics Implementation Consortium (CPIC) has categorized over 35 gene-drug pairs as "level A," for which there is sufficiently strong evidence to recommend that genetic information be used to guide drug prescribing. The opportunity to use genetic information to tailor pharmacotherapy among adult patients was determined by elucidating the exposure to CPIC level A drugs among 11 Implementing Genomics In Practice Network (IGNITE)-affiliated health systems across the US. Inpatient and/or outpatient electronic-prescribing data were collected between January 1, 2011 and December 31, 2016 for patients ≥ 18 years of age who had at least one medical encounter that was eligible for drug prescribing in a calendar year. A median of ~ 7.2 million adult patients was available for assessment of drug prescribing per year. From 2011 to 2016, the annual estimated prevalence of exposure to at least one CPIC level A drug prescribed to unique patients ranged between 15,719 (95% confidence interval (CI): 15,658-15,781) in 2011 to 17,335 (CI: 17,283-17,386) in 2016 per 100,000 patients. The estimated annual exposure to at least 2 drugs was above 7,200 per 100,000 patients in most years of the study, reaching an apex of 7,660 (CI: 7,632-7,687) per 100,000 patients in 2014. An estimated 4,748 per 100,000 prescribing events were potentially eligible for a genotype-guided intervention. Results from this study show that a significant portion of adults treated at medical institutions across the United States is exposed to medications for which genetic information, if available, should be used to guide prescribing., (© 2021 The Authors. Clinical Pharmacology & Therapeutics © 2021 American Society for Clinical Pharmacology and Therapeutics.)

Background and Objectives: Children who become overweight by age 2 have greater risk of long-term obesity and health problems. The study aim was to assess the effectiveness of a primary care-based intervention on the prevalence of overweight at age 24 months., Methods: In a cluster-randomized trial, sites were randomly assigned to the Greenlight intervention or an attention-control arm. Across 4 pediatric residency clinics, we enrolled infant-caregiver dyads at the 2-month well-child visit. Inclusion criteria included parent English- or Spanish-speaking and birth weight ≥1500 g. Designed with health-literacy principles, the intervention included a parent toolkit at each well-child visit, augmented by provider training in clear-health communication. The primary outcome was proportion of children overweight (BMI ≥85th percentile) at age 24 months. Secondary outcomes included weight status (BMI z score)., Results: A total of 459 intervention and 406 control dyads were enrolled. In total, 49% of all children were overweight at 24 months. Adjusted odds for overweight at 24 months (treatment versus control) was 1.02 (95% confidence interval [CI]: 0.63 to 1.64). Adjusted mean BMI z score differences (treatment minus control) were -0.04 (95% CI: -0.07 to -0.01), -0.09 (95% CI: -0.14 to -0.03), -0.19 (-0.33 to -0.05), -0.20 (-0.36 to -0.03), -0.16 (95% CI: -0.34 to 0.01), and 0.00 (95% CI -0.21 to 0.21) at 4, 6, 12, 15, 18, and 24 months, respectively., Conclusions: The intervention resulted in less weight gain through age 18 months, which was not sustained through 24 months. Clinic-based interventions may be beneficial for early weight gain, but greater intervention intensity may be needed to maintain positive effects., Competing Interests: POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose., (Copyright © 2021 by the American Academy of Pediatrics.)

We discuss tradeoffs and errors associated with approaches to modeling health economic decisions. Through an application in pharmacogenomic (PGx) testing to guide drug selection for individuals with a genetic variant, we assessed model accuracy, optimal decisions, and computation time for an identical decision scenario modeled 4 ways: using 1) coupled-time differential equations (DEQ), 2) a cohort-based discrete-time state transition model (MARKOV), 3) an individual discrete-time state transition microsimulation model (MICROSIM), and 4) discrete event simulation (DES). Relative to DEQ, the net monetary benefit for PGx testing (v. a reference strategy of no testing) based on MARKOV with rate-to-probability conversions using commonly used formulas resulted in different optimal decisions. MARKOV was nearly identical to DEQ when transition probabilities were embedded using a transition intensity matrix. Among stochastic models, DES model outputs converged to DEQ with substantially fewer simulated patients (1 million) v. MICROSIM (1 billion). Overall, properly embedded Markov models provided the most favorable mix of accuracy and runtime but introduced additional complexity for calculating cost and quality-adjusted life year outcomes due to the inclusion of "jumpover" states after proper embedding of transition probabilities. Among stochastic models, DES offered the most favorable mix of accuracy, reliability, and speed.

Two-phase outcome-dependent sampling (ODS) designs are useful when resource constraints prohibit expensive exposure ascertainment on all study subjects. One class of ODS designs for longitudinal binary data stratifies subjects into three strata according to those who experience the event at none, some, or all follow-up times. For time-varying covariate effects, exclusively selecting subjects with response variation can yield highly efficient estimates. However, if interest lies in the association of a time-invariant covariate, or the joint associations of time-varying and time-invariant covariates with the outcome, then the optimal design is unknown. Therefore, we propose a class of two-wave two-phase ODS designs for longitudinal binary data. We split the second-phase sample selection into two waves, between which an interim design evaluation analysis is conducted. The interim design evaluation analysis uses first-wave data to conduct a simulation-based search for the optimal second-wave design that will improve the likelihood of study success. Although we focus on longitudinal binary response data, the proposed design is general and can be applied to other response distributions. We believe that the proposed designs can be useful in settings where (1) the expected second-phase sample size is fixed and one must tailor stratum-specific sampling probabilities to maximize estimation efficiency, or (2) relative sampling probabilities are fixed across sampling strata and one must tailor sample size to achieve a desired precision. We describe the class of designs, examine finite sampling operating characteristics, and apply the designs to an exemplar longitudinal cohort study, the Lung Health Study., (© 2021 John Wiley & Sons, Ltd.)

Objectives: To compare patient-reported social determinants of health (SDOH) to the Brokamp Area Deprivation Index (ADI), and evaluate the association of patient-reported SDOH and ADI with mortality in patients with cardiovascular disease (CVD)., Design: Prospective cohort., Setting: Academic medical center., Participants: Adults with acute coronary syndrome (ACS) and/or acute exacerbation of heart failure (HF) hospitalized between 2011 and 2015., Methods: Patient-reported SDOH included: income range, education, health insurance, and household size. ADI was calculated using census tract level variables of poverty, median income, high school completion, lack of health insurance, assisted income, and vacant housing., Primary Outcome: All-cause mortality, up to 5 years follow-up., Results: The sample was 60% male, 84% White, and 93% insured; mean patient-reported household income was $48,000 (SD $34,000). ADI components were significantly associated with corresponding patient-reported variables. In age, sex, and race adjusted Cox regression models, ADI was associated with mortality for ACS (HR 1.23, 95% CI 1.06, 1.42), but not HF (HR 1.09, 95% CI .99, 1.21). Mortality models for ACS improved with consideration of social determinants data (C-statistics: base demographic model=.612; ADI added=.644; patient-reported SDOH added=.675; both ADI and patient-reported SDOH added=.689). HF mortality models improved only slightly (C-statistics: .600, .602, .617, .620, respectively)., Conclusions: The Brokamp ADI is associated with mortality in hospitalized patients with CVD. In the absence of available patient-reported data, hospitals could implement the Brokamp ADI as an approximation for patient-reported data to enhance risk stratification of patients with CVD., Competing Interests: Competing Interests: None declared., (Copyright © 2021, Ethnicity & Disease, Inc.)

Laboratory-based animal research has revealed a number of exposures with multigenerational effects-ones that affect the children and grandchildren of those directly exposed. An important task for epidemiology is to investigate these relationships in human populations. Without the relative control achieved in laboratory settings, however, population-based studies of multigenerational associations have had to use a broader range of study designs. Current strategies to obtain multigenerational data include exploiting birth registries and existing cohort studies, ascertaining exposures within them, and measuring outcomes across multiple generations. In this paper, we describe the methodological challenges inherent to multigenerational studies in human populations. After outlining standard taxonomy to facilitate discussion of study designs and target exposure associations, we highlight the methodological issues, focusing on the interplay between study design, analysis strategy, and the fact that outcomes may be related to family size. In a simulation study, we show that different multigenerational designs lead to estimates of different exposure associations with distinct scientific interpretations. Nevertheless, target associations can be recovered by incorporating (possibly) auxiliary information, and we provide insights into choosing an appropriate target association. Finally, we identify areas requiring further methodological development., (Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2020. This work is written by (a) US Government employee(s) and is in the public domain in the US.)

Importance: Genotype-guided prescribing in pediatrics could prevent adverse drug reactions and improve therapeutic response. Clinical pharmacogenetic implementation guidelines are available for many medications commonly prescribed to children. Frequencies of medication prescription and actionable genotypes (genotypes where a prescribing change may be indicated) inform the potential value of pharmacogenetic implementation., Objective: To assess potential opportunities for genotype-guided prescribing in pediatric populations among multiple health systems by examining the prevalence of prescriptions for each drug with the highest level of evidence (Clinical Pharmacogenetics Implementation Consortium level A) and estimating the prevalence of potential actionable prescribing decisions., Design, Setting, and Participants: This serial cross-sectional study of prescribing prevalences in 16 health systems included electronic health records data from pediatric inpatient and outpatient encounters from January 1, 2011, to December 31, 2017. The health systems included academic medical centers with free-standing children's hospitals and community hospitals that were part of an adult health care system. Participants included approximately 2.9 million patients younger than 21 years observed per year. Data were analyzed from June 5, 2018, to April 14, 2020., Exposures: Prescription of 38 level A medications based on electronic health records., Main Outcomes and Measures: Annual prevalence of level A medication prescribing and estimated actionable exposures, calculated by combining estimated site-year prevalences across sites with each site weighted equally., Results: Data from approximately 2.9 million pediatric patients (median age, 8 [interquartile range, 2-16] years; 50.7% female, 62.3% White) were analyzed for a typical calendar year. The annual prescribing prevalence of at least 1 level A drug ranged from 7987 to 10 629 per 100 000 patients with increasing trends from 2011 to 2014. The most prescribed level A drug was the antiemetic ondansetron (annual prevalence of exposure, 8107 [95% CI, 8077-8137] per 100 000 children). Among commonly prescribed opioids, annual prevalence per 100 000 patients was 295 (95% CI, 273-317) for tramadol, 571 (95% CI, 557-586) for codeine, and 2116 (95% CI, 2097-2135) for oxycodone. The antidepressants citalopram, escitalopram, and amitriptyline were also commonly prescribed (annual prevalence, approximately 250 per 100 000 patients for each). Estimated prevalences of actionable exposures were highest for oxycodone and ondansetron (>300 per 100 000 patients annually). CYP2D6 and CYP2C19 substrates were more frequently prescribed than medications influenced by other genes., Conclusions and Relevance: These findings suggest that opportunities for pharmacogenetic implementation among pediatric patients in the US are abundant. As expected, the greatest opportunity exists with implementing CYP2D6 and CYP2C19 pharmacogenetic guidance for commonly prescribed antiemetics, analgesics, and antidepressants.

Background: Effective type 2 diabetes care remains a challenge for patients including those receiving primary care in safety net settings., Objective: The Partnership to Improve Diabetes Education (PRIDE) trial team and leaders from a regional department of health evaluated approaches to improve care for vulnerable patients., Design: Cluster randomized controlled trial., Patients: Adults with uncontrolled type 2 diabetes seeking care across 10 unblinded, randomly assigned safety net clinics in Middle TN., Interventions: A literacy-sensitive, provider-focused, health communication intervention (PRIDE; 5 clinics) vs. standard diabetes education (5 clinics)., Main Measures: Participant-level primary outcome was glycemic control [A1c] at 12 months. Secondary outcomes included select health behaviors and psychosocial aspects of care at 12 and 24 months. Adjusted mixed effects regression models were used to examine the comparative effectiveness of each approach to care., Key Results: Of 410 patients enrolled, 364 (89%) were included in analyses. Median age was 51 years; Black and Hispanic patients represented 18% and 25%; 96% were uninsured, and 82% had low annual income level (< $20,000); adequate health literacy was seen in 83%, but numeracy deficits were common. At 12 months, significant within-group treatment effects occurred from baseline for both PRIDE and control sites: adjusted A1c (- 0.76 [95% CI, - 1.08 to - 0.44]; P < .001 vs - 0.54 [95% CI, - 0.86 to - 0.21]; P = .001), odds of poor eating (0.53 [95% CI, 0.33-0.83]; P = .01 vs 0.42 [95% CI, 0.26-0.68]; P < .001), treatment satisfaction (3.93 [95% CI, 2.48-6.21]; P < .001 vs 3.04 [95% CI, 1.93-4.77]; P < .001), and self-efficacy (2.97 [95% CI, 1.89-4.67]; P < .001 vs 1.81 [95% CI, 1.1-2.84]; P = .01). No significant difference was observed between study arms in adjusted analyses., Conclusions: Both interventions improved the participant's A1c and behavioral outcomes. PRIDE was not more effective than standard education. Further research may elucidate the added value of a focused health communication program in this setting.

We propose a general class of 2-phase epidemiologic study designs for quantitative, longitudinal data that are useful when phase 1 longitudinal outcome and covariate data are available but data on the exposure (e.g., a biomarker) can only be collected on a subset of subjects during phase 2. To conduct a study using a design in the class, one first summarizes the longitudinal outcomes by fitting a simple linear regression of the response on a time-varying covariate for each subject. Sampling strata are defined by splitting the estimated regression intercept or slope distributions into distinct (low, medium, and high) regions. Stratified sampling is then conducted from strata defined by the intercepts, by the slopes, or from a mixture. In general, samples selected with extreme intercept values will yield low variances for associations of time-fixed exposures with the outcome and samples enriched with extreme slope values will yield low variances for associations of time-varying exposures with the outcome (including interactions with time-varying exposures). We describe ascertainment-corrected maximum likelihood and multiple-imputation estimation procedures that permit valid and efficient inferences. We embed all methodological developments within the framework of conducting a substudy that seeks to examine genetic associations with lung function among continuous smokers in the Lung Health Study (United States and Canada, 1986-1994)., (Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2019.)

We strive to understand care coordination structures of multidisciplinary teams and to evaluate their effect on post-surgical length of stay (PSLOS) in the Neonatal Intensive Care Unit (NICU). Electronic health record (EHR) data were extracted for 18 neonates, who underwent gastrostomy tube placement surgery at the Vanderbilt University Medical Center NICU. Based on providers' interactions with the EHR (e.g. viewing, documenting, ordering), provider-provider relations were learned and used to build patient-specific provider networks representing the care coordination structure. We quantified the networks using standard network analysis metrics (e.g., in-degree, out-degree, betweenness centrality, and closeness centrality). Coordination structure effectiveness was measured as the association between the network metrics and PSLOS, as modeled by a proportional-odds, logistical regression model. The 18 provider networks exhibited various team compositions and various levels of structural complexity. Providers, whose patients had lower PSLOS, tended to disperse patient-related information to more colleagues within their network than those, who treated higher PSLOS patients (P = 0.0294). In the NICU, improved dissemination of information may be linked to reduced PSLOS. EHR data provides an efficient, accessible, and resource-friendly way to study care coordination using network analysis tools. This novel methodology offers an objective way to identify key performance and safety indicators of care coordination and to study dissemination of patient-related information within care provider networks and its effect on care. Findings should guide improvements in the EHR system design to facilitate effective clinical communications among providers.

Objective: Depression is common in patients with type 2 diabetes and associated with poor diabetes-related outcomes. We evaluated the factors associated with antidepressant use in a low-income, racially and ethnically diverse sample of patients with type 2 diabetes., Research Design and Methods: We performed a cross-sectional study of baseline data from participants in a cluster randomized trial evaluating a health literacy intervention for diabetes care in safety net clinics. Depressive symptoms were measured by the Center for Epidemiological Studies Depression Scale (CES-D); antidepressant use was abstracted from medication lists. Multivariable mixed effects logistic regression was used to evaluate the relationship between antidepressant use and race/ethnicity adjusting for depressive symptoms, age, gender, income, and health literacy., Results: Of 403 participants, 58% were non-Hispanic White, 18% were non-Hispanic Black, and 24% were Hispanic. Median age was 51 years old; 60% were female, 52% of participants had a positive screen for depression, and 18% were on antidepressants. Black and Hispanic participants were significantly less likely to be on an antidepressant compared with white participants, adjusted odds ratios 0.31(95% CI: 0.12 to 0.80) and 0.26 (95% CI: 0.10 to 0.74), respectively., Conclusions: In this vulnerable population with type 2 diabetes, we found a high prevalence of depressive symptoms, and a small proportion of participants were on an antidepressant. Black and Hispanic participants were significantly less likely to be treated with an antidepressant. Our findings suggest depression may be inadequately treated in low-income, uninsured patients with type 2 diabetes, especially racial and ethnic minorities., (Copyright © 2019 Elsevier Inc. All rights reserved.)

We discuss a decision-theoretic approach to building a panel-based, preemptive genotyping program. The method is based on findings that a large percentage of patients are prescribed medications that are known to have pharmacogenetic associations, and over time, a substantial proportion are prescribed additional such medication. Preemptive genotyping facilitates genotype-guided therapy at the time medications are prescribed; panel-based testing allows providers to reuse previously collected genetic data when a new indication arises. Because it is cost-prohibitive to conduct panel-based genotyping on all patients, we describe a three-step approach to identify patients with the highest anticipated benefit. First, we construct prediction models to estimate the risk of being prescribed one of the target medications using readily available clinical data. Second, we use literature-based estimates of adverse event rates, variant allele frequencies, secular death rates, and costs to construct a discrete event simulation that estimates the expected benefit of having an individual's genetic data in the electronic health record after an indication has occurred. Finally, we combine medication prescription risk with expected benefit of genotyping once a medication is indicated to calculate the expected benefit of preemptive genotyping. For each patient-clinic visit, we calculate this expected benefit across a range of medications and select patients with the highest expected benefit overall. We build a proof of concept implementation using a cohort of patients from a single academic medical center observed from July 2010 through December 2012. We then apply the results of our modeling strategy to show the extent to which we can improve clinical and economic outcomes in a cohort observed from January 2013 through December 2015.

Objectives: We aimed to investigate the role of genetics in the respiratory response of asthmatic children to air pollution, with a genome-wide level analysis of gene by nitrogen dioxide (NO 2 ) and carbon monoxide (CO) interaction on lung function and to identify biological pathways involved., Methods: We used a two-step method for fast linear mixed model computations for genome-wide association studies, exploring whether variants modify the longitudinal relationship between 4-month average pollution and post-bronchodilator FEV 1 in 522 Caucasian and 88 African-American asthmatic children. Top hits were confirmed with classic linear mixed-effect models. We used the improved gene set enrichment analysis for GWAS (i-GSEA4GWAS) to identify plausible pathways., Results: Two SNPs near the EPHA3 (rs13090972 and rs958144) and one in TXNDC8 (rs7041938) showed significant interactions with NO 2 in Caucasians but we did not replicate this locus in African-Americans. SNP-CO interactions did not reach genome-wide significance. The i-GSEA4GWAS showed a pathway linked to the HO-1/CO system to be associated with CO-related FEV 1 changes. For NO 2 -related FEV 1 responses, we identified pathways involved in cellular adhesion, oxidative stress, inflammation, and metabolic responses., Conclusion: The host lung function response to long-term exposure to pollution is linked to genes involved in cellular adhesion, oxidative stress, inflammatory, and metabolic pathways.

Objective: We describe a stratified sampling design that combines electronic health records (EHRs) and United States Census (USC) data to construct the sampling frame and an algorithm to enrich the sample with individuals belonging to rarer strata., Materials and Methods: This design was developed for a multi-site survey that sought to examine patient concerns about and barriers to participating in research studies, especially among under-studied populations (eg, minorities, low educational attainment). We defined sampling strata by cross-tabulating several socio-demographic variables obtained from EHR and augmented with census-block-level USC data. We oversampled rarer and historically underrepresented subpopulations., Results: The sampling strategy, which included USC-supplemented EHR data, led to a far more diverse sample than would have been expected under random sampling (eg, 3-, 8-, 7-, and 12-fold increase in African Americans, Asians, Hispanics and those with less than a high school degree, respectively). We observed that our EHR data tended to misclassify minority races more often than majority races, and that non-majority races, Latino ethnicity, younger adult age, lower education, and urban/suburban living were each associated with lower response rates to the mailed surveys., Discussion: We observed substantial enrichment from rarer subpopulations. The magnitude of the enrichment depends on the accuracy of the variables that define the sampling strata and the overall response rate., Conclusion: EHR and USC data may be used to define sampling strata that in turn may be used to enrich the final study sample. This design may be of particular interest for studies of rarer and understudied populations.

Objective: To test theorized patient-level mediators in the causal pathway between health literacy (HL) and 1-year mortality in adults with cardiovascular disease (CVD)., Patients and Methods: A total of 3000 adults treated at Vanderbilt University Hospital from October 11, 2011, through December 18, 2015, for acute coronary syndrome or acute decompensated heart failure (ADHF) participated in the Vanderbilt Inpatient Cohort Study. Participants completed a bedside-administered survey and consented to health record review and longitudinal follow-up. Multivariable mediation models examined the direct and indirect effects of HL (a latent variable with 4 indicators) with 1-year mortality after discharge (dichotomous). Hypothesized mediators included social support, health competence, health behavior, comorbidity index, type of CVD diagnosis, and previous-year hospitalizations., Results: Of the 2977 patients discharged from the hospital (60% male; mean age, 61 years; 83% non-Hispanic white, 37% admitted for ADHF), 17% to 23% had inadequate HL depending on the measure, and 10% (n=304) died within 1 year. The total effect of lower HL on 1-year mortality (adjusted odds ratio [AOR]=1.31; 95% CI, 1.01-1.69) was decomposed into an indirect effect (AOR=1.50; 95% CI, 1.35-1.67) via the mediators and a nonsignificant direct effect (AOR=0.87; 95% CI, 0.66-1.14). Each SD decrease in HL was associated with an absolute 3.2 percentage point increase in the probability of 1-year mortality via mediators admitted for ADHF, comorbidities, health behavior, health competence, and previous-year hospitalizations (listed by contribution to indirect effect)., Conclusion: Patient-level factors link low HL and mortality. Health competence and health behavior are modifiable mediators that could be targeted by interventions post hospitalization for CVD., (Copyright © 2018 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.)