Mechanisms of antihypertensive effect of chlorthalidone in advanced chronic kidney disease-a causal mediation analysis.

BACKGROUND: Chlorthalidone in chronic kidney disease (CLICK) randomized trial demonstrated a robust reduction in systolic blood pressure (BP) in stage 4 chronic kidney disease (CKD). Here we explore the mechanisms underlying the antihypertensive effect of chlorthalidone. METHODS: In this prespecified analysis, we analyzed the contributions of baseline levels of 24-hour urinary sodium and aldosterone and the changes from baseline to 4 weeks in the multiple mediators reflecting volume status in a causal mediation analysis framework. Baseline levels of these mediators served as covariates. No power calculationfor this analysis was performed. RESULTS: Of the 160 patients randomized, 140 (87.5%) were included in this analysis. Compared to placebo, chlorthalidone within 4 weeks reduced weight -1.5 % (95% CI -2.2 to -0.7) and volume -1.4 % (95% CI -2.2 to -0.6), stimulated plasma renin 40.5% (95% CI 25.4 to 57.4%) and serum aldosterone 40.2% (95% CI 11.7% to 76%), and reduced plasma NT-pro BNP levels -19.4% (95% CI -33.8% to -1.9%). Mediation analysis revealed the following results: for weight change, the total effect on systolic BP was -10.8 mmHg (95% CI -16 to -5.7), of which weight change (indirect effect) accounted for -0.9 mmHg (95% CI -4.2 to 2.5) and BP change independent of weight (direct effect) accounted for -10 mmHg (-15.7 to - 4.2). Thus, the percent mediation was 8.1% (95% CI -22.4 to 38.5). Baseline excretion of 24-hour sodium or aldosterone or any of the changes in the above mediators examined accounted for <2 mmHg BP drop and were not significant for any of the mediators. CONCLUSION: Chlorthalidone improved BP control among patients with advanced CKD independently of baseline urinary sodium, aldosterone, weight loss, or changes in the renin-angiotensin system or NT-pro BNP. (Funded by the National Heart Lung and Blood Institute; CLICK ClinicalTrials.gov number, NCT02841280).

A flexible time-varying coefficient rate model for panel count data.

Panel count regression is often required in recurrent event studies, where the interest is to model the event rate. Existing rate models are unable to handle time-varying covariate effects due to theoretical and computational difficulties. Mean models provide a viable alternative but are subject to the constraints of the monotonicity assumption, which tends to be violated when covariates fluctuate over time. In this paper, we present a new semiparametric rate model for panel count data along with related theoretical results. For model fitting, we present an efficient EM algorithm with three different methods for variance estimation. The algorithm allows us to sidestep the challenges of numerical integration and difficulties with the iterative convex minorant algorithm. We showed that the estimators are consistent and asymptotically normally distributed. Simulation studies confirmed an excellent finite sample performance. To illustrate, we analyzed data from a real clinical study of behavioral risk factors for sexually transmitted infections.

TrialView: An AI-powered Visual Analytics System for Temporal Event Data in Clinical Trials.

Randomized controlled trials (RCT) are the gold standards for evaluating the efficacy and safety of therapeutic interventions in human subjects. In addition to the pre-specified endpoints, trial participants' experience reveals the time course of the intervention. Few analytical tools exist to summarize and visualize the individual experience of trial participants. Visual analytics allows integrative examination of temporal event patterns of patient experience, thus generating insights for better care decisions. Towards this end, we introduce TrialView, an information system that combines graph artificial intelligence (AI) and visual analytics to enhance the dissemination of trial data. TrialView offers four distinct yet interconnected views: Individual, Cohort, Progression, and Statistics, enabling an interactive exploration of individual and group-level data. The TrialView system is a general-purpose analytical tool for a broad class of clinical trials. The system is powered by graph AI, knowledge-guided clustering, explanatory modeling, and graph-based agglomeration algorithms. We demonstrate the system's effectiveness in analyzing temporal event data through a case study.

Food resources and kitchen skills plus aerobic training (FoRKS+) for black adults with hypertension: A pilot trial protocol.

BACKGROUND: Midlife hypertension is associated with cognitive decline and Alzheimer's disease and related dementia (ADRD), suggesting that blood pressure control may be a therapeutic target for dementia prevention. Given excess hypertension in non-Hispanic Black (NHB) adults, blood pressure control may also reduce ADRD disparities. We describe a pilot randomized controlled trial (RCT) to evaluate the feasibility and preliminary efficacy of a multicomponent lifestyle-based intervention versus enhanced usual care on cognition among middle-aged NHB adults. METHODS AND STUDY DESIGN: The Food Resources and Kitchen Skills plus Aerobic Training (FoRKS+) study is a 2-arm, single-blinded trial that compares those receiving the FoRKS+ program (target N = 64) versus those receiving enhanced usual care (target N = 64) in local federally-qualified health centers. Key eligibility criteria include self-identified NHB adults between ages 35-75 with a mean systolic blood pressure ≥ 130 mm/Hg obtained from 24-h ambulatory blood pressure monitoring. The FoRKS+ program includes 5 weeks of hypertension self-management courses, 11 weeks of nutrition courses, and 12 weeks of aerobic training in dietitian and health coach-led virtual groups. We will collect data on primary cognitive outcomes, feasibility, hypothesized intervention mediators and moderators, and demographic and health covariates at baseline, near intervention weeks 16-, and 28 (primary outcome assessment), and week 52 follow-up. We will use mixed-effects modeling to examine intervention effects on cognition. DISCUSSION: This pilot RCT will examine the feasibility and preliminary effects of a multicomponent lifestyle intervention on cognitive function in NHB adults, which may have implications for reducing health disparities in ADRD.

Who gets screened and who tests positive? Drug screening among justice-involved youth in a midwestern urban county.

BACKGROUND: Given high rates of substance use among justice-involved youth, justice systems have attempted to monitor use through drug screening (DS) procedures. However, there is discretion in deciding who is screened for substance use, as not every youth who encounters the system is screened. The aim of the current study was to examine factors associated with selection for and results of oral DS among justice-involved youth assigned to probation to better inform potential DS policy. Electronic court records from 4,668 youth with first-incident records assigned to probation in a midwestern urban county's juvenile justice system between 2011 and 2016 were included in the analytical sample. Race/ethnicity, gender, age, number of charges and charge type for the current incident were included as independent variables. RESULTS: Multivariable hierarchical logistic regression analyses indicated that males were more likely to be assigned to DS (aOR = 0.40, 95%CI [0.34, 0.46]), and more likely to test positive for use (aOR = 0.43, 95% CI [0.34, 0.54]) than females. As age increased, youth were less likely to be assigned to DS (aOR = 0.91, 95% CI [0.87, 0.94]), with non-significant differences in DS results. Greater number of charges were associated with a higher likelihood of being assigned to DS (aOR = 1.55, 95% CI [1.43, 1.68]). Youth with violent offenses were more likely to be assigned to DS than those with other offense types (property offenses, drug offenses, statutory offenses, disorderly conduct, and all other offenses), but less likely to test positive for use. CONCLUSIONS: Many factors were associated with differences in DS, but these factors were not always associated with differential DS results. Demographic or charge-based decisions may not be appropriate for DS assignment.

An additive-multiplicative model for longitudinal data with informative observation times.

Designed clinical studies often assess outcomes at pre-planned time points. In most situations, standard statistical models, such as generalized linear mixed models and generalized additive models, are sufficient to depict the temporal trends of the outcome and produce valid inference. Complicating factors, however, do exist in practical data analyses. One complication arises when the outcome and observational processes are interdependent, that is, the observational process is informative; another challenge is patient characteristics may influence the longitudinally observed outcomes in non-additive ways, for example, by multiplicative factors. In this research, we extend the standard longitudinal models to accommodate informative observation through a more flexible modeling structure-one with additive-multiplicative components that do not require explicit specification of the dependency structure between the outcome and observation processes. Along this vein, we provide the essential theory for inference in such models. Simulation studies showed the proposed method performs well for finite-sample scenarios, and the method was applied to analyze a motivating example from an alcohol-associated hepatitis observational study.

Randomized trial of anakinra plus zinc vs. prednisone for severe alcohol-associated hepatitis.

BACKGROUND & AIMS: Severe alcohol-associated hepatitis (SAH) is associated with high 90-day mortality. Glucocorticoid therapy for 28 days improves 30- but not 90-day survival. We assessed the efficacy and safety of a combination of anakinra, an IL-1 antagonist, plus zinc (A+Z) compared to prednisone using the Day-7 Lille score as a stopping rule in patients with SAH. METHODS: In this phase IIb double-blind randomized trial in adults with SAH and MELD scores of 20-35, participants were randomized to receive either daily anakinra 100 mg subcutaneously for 14 days plus daily zinc sulfate 220 mg orally for 90 days, or daily prednisone 40 mg orally for 30 days. Prednisone or prednisone placebo was stopped if Day-7 Lille score was >0.45. All study drugs were stopped for uncontrolled infection or ≥5 point increase in MELD score. The primary endpoint was overall survival at 90 days. RESULTS: Seventy-three participants were randomized to prednisone and 74 to A+Z. The trial was stopped early after a prespecified interim analysis showed prednisone was associated with higher 90-day overall survival (90% vs. 70%; hazard ratio for death = 0.34, 95% CI 0.14-0.83, p = 0.018) and transplant-free survival (88% vs. 64%; hazard ratio for transplant or death = 0.30, 95% CI 0.13-0.69, p = 0.004) than A+Z. Acute kidney injury was more frequent with A+Z (45%) than prednisone (22%) (p = 0.001), but rates of infection were similar (31% in A+Z vs. 27% in prednisone, p = 0.389). CONCLUSIONS: Participants with SAH treated with prednisone using the Day-7 Lille score as a stopping rule had significantly higher overall and transplant-free 90-day survival and lower incidence of acute kidney injury than those treated with A+Z. IMPACT AND IMPLICATIONS: There is no approved treatment for severe alcohol-associated hepatitis (SAH). In this double-blind randomized trial, patients with SAH treated with prednisone using the Lille stopping rule on Day 7 had higher 90-day overall and transplant-free survival and lower rates of acute kidney injury compared to patients treated with a combination of anakinra and zinc. The data support continued use of glucocorticoids for patients with SAH, with treatment discontinuation for those with a Lille score >0.45 on Day 7. TRIAL REGISTRATION: NCT04072822.

Development and evaluation of objective trial performance metrics for multisite clinical studies: Experience from the AlcHep Network.

BACKGROUND: Recruitment and retention are critical in clinical studies but there are limited objective metrics of trial performance. We tested if development of trial performance metrics will allow for objective evaluation of study quality. Performance metrics were developed using data from the observational cohort (OBS) and randomized clinical trial (RCT) arms of the prospective Alcoholic Hepatitis Network. METHODS: Yield-rate (%YR; eligible/screened), recruitment index (RI; mean recruitment time/patient), completion index (CI; average number of days to complete the follow-up/patient), and protocol adherence index (AI; average number of deviations/subject recruited) were determined. RESULTS: 2250 patients (1168 for OBS; 1082 for RCT) were screened across 8 sites. Recruitment in the RCT (57% target) was similar to that in the OBS (59% target). Of those screened, 743 (63.6%) subjects in the OBS and 147 (13.6%) subjects in the RCT were enrolled in the study. In OBS study, 253 (34.1%) subjects, and in the RCT, 68 (46.3%) subjects, completed the study or reached a censoring event. Across all sites (range), YR for OBS was 63.6% (41.3-98.3%) and for RCT was 13.6% (5.5-92.6%); RI for OBS was 1.66 (8.79-19.85) and for RCT was 4.05 (19.76-36.43); CI for OBS was 4.87 (22.6-118.3) and for RCT was 8.75 (27.27-161.5); and AR for OBS was 0.56 (0.08-1.04) and for RCT was 1.55 (0.39-3.21. Factors related to participants, research design, study team, and research sponsors contributed to lower performance metrics. CONCLUSIONS: Objective measures of clinical trial performance allow for strategies to enhance study quality and development of site-specific improvement plans. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov NCT4072822 NCT03850899.

ARDaC Common Data Model Facilitates Data Dissemination and Enables Data Commons for Modern Clinical Studies.

Modern clinical studies collect longitudinal and multimodal data about participants, treatments and responses, biospecimens, and molecular and multiomics data. Such rich and complex data requires new common data models (CDM) to support data dissemination and research collaboration. We have developed the ARDaC CDM for the Alcoholic Hepatitis Network (AlcHepNet) Research Data Commons (ARDaC) to support clinical studies and translational research in the national AlcHepNet consortium. The ARDaC CDM bridges the gap between the data models used by the AlcHepNet electronic data capture platform (REDCap) and the Genomic Data Commons (GDC) data model used by the Gen3 data commons framework. It extends the GDC data model for clinical studies; facilitates the harmonization of research data across consortia and programs; and supports the development of the ARDaC. ARDaC CDM is designed as a general and extensible CDM for addressing the needs of modern clinical studies. The ARDaC CDM is available at https://dev.ardac.org/DD.

An Improved Statistical Modeling Approach to Individual Anticholinergic Drug Use Trend Analysis.

Anticholinergic (AC) drugs are commonly prescribed to older adults for treating diseases and chronic conditions, such as chronic obstructive pulmonary disease, urinary incontinence, gastrointestinal disorder, or simply pain and allergy. The high prevalence of AC drug use can have a detrimental effect on the mental health of older adults. We aim to improve the prediction of future trends of AC drug use at the individual level, with pharmacy refill data. The individual drug use data presents challenges in the modeling, such as data being discrete-valued with excess zeros and having significant unobserved heterogeneity in the trend pattern. To address these challenges, we propose a statistical model of hierarchical structure and an EM scheme for the model parameter estimation. We evaluate the proposed modeling approach through a numerical study with synthetic data and a case study with real-world pharmacy refill data. The simulation study show that our analysis method outperforms the existing ones (e.g., reducing MSE significantly), particularly in terms of accurately predicting the trend pattern. The real-world case study further verifies the out-performance and demonstrate the advantageous features of our method. We expect the prediction tool developed based on our study can assist pharmacists' decision on initiating or strengthening behavioral interventions with the hope of discontinuing AC drug misuse.

Impact of Finerenone-Induced Albuminuria Reduction on Chronic Kidney Disease Outcomes in Type 2 Diabetes : A Mediation Analysis.

BACKGROUND: In patients with chronic kidney disease (CKD) and type 2 diabetes (T2D), finerenone, a nonsteroidal mineralocorticoid receptor antagonist, reduces cardiovascular and kidney failure outcomes. Finerenone also lowers the urine albumin-to-creatinine ratio (UACR). Whether finerenone-induced change in UACR mediates cardiovascular and kidney failure outcomes is unknown. OBJECTIVE: To quantify the proportion of kidney and cardiovascular risk reductions seen over a 4-year period mediated by a change in kidney injury, as measured by the change in log UACR between baseline and month 4. DESIGN: Post hoc mediation analysis using pooled data from 2 phase 3, double-blind trials of finerenone. (ClinicalTrials.gov: NCT02540993 and NCT02545049). SETTING: Several clinical sites in 48 countries. PATIENTS: 12 512 patients with CKD and T2D. INTERVENTION: Finerenone and placebo (1:1). MEASUREMENTS: Separate mediation analyses were done for the composite kidney (kidney failure, sustained ≥57% decrease in estimated glomerular filtration rate from baseline [approximately a doubling of serum creatinine], or kidney disease death) and cardiovascular (cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure) outcomes. RESULTS: At baseline, median UACR was 514 mg/g. A 30% or greater reduction in UACR was seen in 3338 (53.2%) patients in the finerenone group and 1684 (27.0%) patients in the placebo group. Reduction in UACR (analyzed as a continuous variable) mediated 84% and 37% of the treatment effect on the kidney and cardiovascular outcomes, respectively. When change in UACR was analyzed as a binary variable (that is, whether the guideline-recommended 30% reduction threshold was met), the proportions mediated for each outcome were 64% and 26%, respectively. LIMITATION: The current findings are not readily extendable to other drugs. CONCLUSION: In patients with CKD and T2D, early albuminuria reduction accounted for a large proportion of the treatment effect against CKD progression and a modest proportion of the effect against cardiovascular outcomes. PRIMARY FUNDING SOURCE: Bayer AG.

Robust Estimation of Heterogeneous Treatment Effects: An Algorithm-based Approach.

Heterogeneous treatment effect estimation is an essential element in the practice of tailoring treatment to suit the characteristics of individual patients. Most existing methods are not sufficiently robust against data irregularities. To enhance the robustness of the existing methods, we recently put forward a general estimating equation that unifies many existing learners. But the performance of model-based learners depends heavily on the correctness of the underlying treatment effect model. This paper addresses this vulnerability by converting the treatment effect estimation to a weighted supervised learning problem. We combine the general estimating equation with supervised learning algorithms, such as the gradient boosting machine, random forest, and artificial neural network, with appropriate modifications. This extension retains the estimators' robustness while enhancing their flexibility and scalability. Simulation shows that the algorithm-based estimation methods outperform their model-based counterparts in the presence of nonlinearity and non-additivity. We developed an R package, RCATE, for public access to the proposed methods. To illustrate the methods, we present a real data example to compare the blood pressure-lowering effects of two classes of antihypertensive agents.

The influence of social and environmental determinants of health on hospitalizations for pediatric asthma.

BACKGROUND: Asthma is the most common chronic disease of childhood, and has several social, environmental, and demographic factors potentially influential to its disease burden. This study sought to determine the influence of these factors on hospital admissions and readmissions for pediatric asthma. METHODS: This was a retrospective cohort study using data from the Indiana Network for Patient Care, a state-wide health information exchange in the United States. Study participants were children 2-18 years old admitted to the hospital with a respiratory diagnostic code between 2010 and 2021. Clinical variables were obtained from electronic health record data, and social and environmental determinants of health data were obtained from the Indiana Social Assets and Vulnerabilities Indicators using geocoding systems. Negative binomial models were used to examine community level social and environmental risk factors modifying the relationship between patient characteristics and the risk of asthma-related hospitalizations and 30-day readmissions. RESULTS: The study sample included 25,063 patients with an average follow-up of 9 (SD = 5) years. Of these, there were 17,816 asthma-related admissions. There were a total of 1,037 asthma-related 30-day readmissions, with an incidence rate of readmissions relative to total visits of 0.028 per person-year. A high social vulnerability index (SVI) was associated with an increased rate of hospital admissions (Proportion attributable ratio: 1.09, 95%CI (1.03,1.15), p < 0.05). No environmental determinants of health were significantly associated with hospitalization rate. CONCLUSION: High SVI was significantly associated with increased risk of total hospital admissions for pediatric asthma.

clusterMLD: An Efficient Hierarchical Clustering Method for Multivariate Longitudinal Data.

Longitudinal data clustering is challenging because the grouping has to account for the similarity of individual trajectories in the presence of sparse and irregular times of observation. This paper puts forward a hierarchical agglomerative clustering method based on a dissimilarity metric that quantifies the cost of merging two distinct groups of curves, which are depicted by B-splines for the repeatedly measured data. Extensive simulations show that the proposed method has superior performance in determining the number of clusters, classifying individuals into the correct clusters, and in computational efficiency. Importantly, the method is not only suitable for clustering multivariate longitudinal data with sparse and irregular measurements but also for intensely measured functional data. Towards this end, we provide an R package for the implementation of such analyses. To illustrate the use of the proposed clustering method, two large clinical data sets from real-world clinical studies are analyzed.

High flow nasal cannula use is associated with increased hospital length of stay for pediatric asthma.

BACKGROUND: High flow nasal cannula (HFNC) is a respiratory device increasingly used to treat asthma. Recent mechanistic studies have shown that nebulized medications may have reduced delivery with HFNC, which may impair asthma treatment. This study evaluated the association between HFNC use for pediatric asthma and hospital length of stay (LOS). METHODS: This was a retrospective matched cohort study. Cases included patients aged 2-18 years hospitalized between January 2010 and December 2021 with asthma and received HFNC treatment. Controls were selected using logistic regression propensity score matching based on demographics, vital signs, medications, imaging, and social and environmental determinants of health. The primary outcome was hospital LOS. RESULTS: A total of 23,659 encounters met eligibility criteria, and of these 1766 cases included HFNC treatment with a suitable matched control. Cases were well-matched in demographics, social and environmental determinants of health, and clinical characteristics including use of adjunctive asthma therapies. The median hospital LOS for study cases was significantly higher at 87 h (interquartile range [IQR]: 61-145) compared to 66 h (IQR: 43-105) in the matched controls (p < 0.01). There was no significant difference in the rate of intubation and mechanical ventilation (8.9% vs. 7.6%, p = .18); however, the use of NIV was significantly higher in the cases than the control group (21.3% vs. 6.7%, p < .01). CONCLUSION: In this study of children hospitalized for asthma, HFNC use was associated with increased hospital LOS compared to matched controls. Further research using more granular data and additional relevant variables is needed to validate these findings.

The Role of Partner Gender in Bisexual Men's Stigma-Related Experiences and Mental Health: Results From a Probability-Based Sample in the United States.

Bisexual men are disproportionately affected by negative mental health outcomes compared to heterosexual and gay men. These disparities are related to the unique stressors that they experience, and emerging evidence suggests that their experiences of these stressors can be different depending on the gender of their partner. However, previous studies have largely focused on bisexual women and little is known about the role of partner gender in bisexual men's experiences and mental health. We examined the associations between relationship type and outness, stigma-related experiences, and mental health using data from Wave 1 of the National Study of Stigma and Sexual Health, a probability-based sample of 502 gay and bisexual men in the U.S. Analyses focused on the subset of 128 men who identified as bisexual (44.53% in relationships with women, 14.84% in relationships with men, 40.63% not in relationships). Bisexual men in relationships with men reported being more out than those in relationships with women and those who were not in relationships; furthermore, bisexual men in relationships with men reported more discrimination and family stress than those in relationships with women. Bisexual men who were not in relationships reported more anticipated and internalized stigma than those in relationships with men; additionally, bisexual men who were not in relationships reported more anticipated stigma and depression than those in relationships with women. Partner gender plays a role in bisexual men's stigma-related experiences and mental health, and efforts to improve bisexual men's health should attend to sexual orientation, relationship status, and partner gender.

Using Palliative Leaders in Facilities to Transform Care for People with Alzheimer's Disease (UPLIFT-AD): protocol of a palliative care clinical trial in nursing homes.

BACKGROUND: Palliative care is an effective model of care focused on maximizing quality of life and relieving the suffering of people with serious illnesses, including dementia. Evidence shows that many people receiving care in nursing homes are eligible for and would benefit from palliative care services. Yet, palliative care is not consistently available in nursing home settings. There is a need to test pragmatic strategies to implement palliative care programs in nursing homes. METHODS/DESIGN: The UPLIFT-AD (Utilizing Palliative Leaders in Facilities to Transform care for people with Alzheimer's Disease) study is a pragmatic stepped wedge trial in 16 nursing homes in Maryland and Indiana, testing the effectiveness of the intervention while assessing its implementation. The proposed intervention is a palliative care program, including 1) training at least two facility staff as Palliative Care Leads, 2) training for all staff in general principles of palliative care, 3) structured screening for palliative care needs, and 4) on-site specialty palliative care consultations for a one-year intervention period. All residents with at least moderate cognitive impairment, present in the facility for at least 30 days, and not on hospice at baseline are considered eligible. Opt-out consent is obtained from legal decision-makers. Outcome assessments measuring symptoms and quality of care are obtained from staff and family proxy respondents at four time points: pre-implementation (baseline), six months after implementation, at 12 months (conclusion of implementation), and six months after the end of implementation. Palliative care attitudes and practices are assessed through surveys of frontline nursing home staff both pre- and post-implementation. Qualitative and quantitative implementation data, including fidelity assessments and interviews with Palliative Care Leads, are also collected. The study will follow the Declaration of Helsinki. DISCUSSION: This trial assesses the implementation and effectiveness of a robust palliative care intervention for residents with moderate-to-advanced cognitive impairment in 16 diverse nursing homes. The intervention represents an innovative, pragmatic approach that includes both internal capacity-building of frontline nursing home staff, and support from external palliative care specialty consultants. TRIAL REGISTRATION: The project is registered on ClinicalTrials.gov: NCT04520698.

Delivering Food Resources and Kitchen Skills (FoRKS) to Adults with Food Insecurity and Hypertension: A Pilot Study.

Food insecurity affects nearly 50 million Americans and is linked to cardiovascular disease risk factors and health disparities. The purpose of this single-arm pilot study was to determine the feasibility of a 16-week dietitian-led lifestyle intervention to concurrently address food access, nutrition literacy, cooking skills, and hypertension among safety-net primary care adult patients. The Food Resources and Kitchen Skills (FoRKS) intervention provided nutrition education and support for hypertension self-management, group kitchen skills and cooking classes from a health center teaching kitchen, medically tailored home-delivered meals and meal kits, and a kitchen toolkit. Feasibility and process measures included class attendance rates and satisfaction and social support and self-efficacy toward healthy food behaviors. Outcome measures included food security, blood pressure, diet quality, and weight. Participants (n = 13) were on average {mean (SD)} aged 58.9 ± 4.5 years, 10 were female, and 12 were Black or African American. Attendance averaged 19 of 22 (87.1%) classes and satisfaction was rated as high. Food self-efficacy and food security improved, and blood pressure and weight declined. FoRKS is a promising intervention that warrants further evaluation for its potential to reduce cardiovascular disease risk factors among adults with food insecurity and hypertension.

Associations between outpatient treatment and the use of intensive psychiatric healthcare services.

The current manuscript examines concurrent and longitudinal associations between the utilization of outpatient and intensive psychiatric services among Medicaid-enrolled youth. Using an administrative dataset of Medicaid claims from 2007 to 2017, youth were included if they were between the ages of 10-18 (M = 13.4, SD = 2.6) and had a psychiatric Medicaid claim (N = 33,590). Psychiatric services were coded as outpatient, emergency department (ED), inpatient, or residential based on Medicaid codes. Logistic regression analyses indicated that the receipt of even one outpatient visit significantly reduced the odds of having an ED, inpatient, and residential visit within 60-, 90-, and 120-day windows. Survival analyses indicated most youth did not have any ED, inpatient, or residential visit following their first outpatient visit. For remaining youth, having an outpatient visit significantly increased the risk of having an ED, inpatient, and residential visit following their initial appointment, which may suggest these youth are being triaged to a more appropriate level of care. Classification accuracy analyses indicated a cutoff of 2 outpatient visits yielded maximum accuracy in determining youth with ED, inpatient, and residential visits. Findings highlight use of outpatient-level services in reducing risk of more intensive service utilization.