Association Between Stimulant Treatment and Substance Use Through Adolescence Into Early Adulthood.

Importance: Possible associations between stimulant treatment of attention-deficit/hyperactivity disorder (ADHD) and subsequent substance use remain debated and clinically relevant. Objective: To assess the association of stimulant treatment of ADHD with subsequent substance use using the Multimodal Treatment Study of ADHD (MTA), which provides a unique opportunity to test this association while addressing methodologic complexities (principally, multiple dynamic confounding variables). Design, Setting, and Participants: MTA was a multisite study initiated at 6 sites in the US and 1 in Canada as a 14-month randomized clinical trial of medication and behavior therapy for ADHD but transitioned to a longitudinal observational study. Participants were recruited between 1994 and 1996. Multi-informant assessments included comprehensively assessed demographic, clinical (including substance use), and treatment (including stimulant treatment) variables. Children aged 7 to 9 years with rigorously diagnosed DSM-IV combined-type ADHD were repeatedly assessed until a mean age of 25 years. Analysis took place between April 2018 and February 2023. Exposure: Stimulant treatment of ADHD was measured prospectively from baseline for 16 years (10 assessments) initially using parent report followed by young adult report. Main Outcomes and Measures: Frequency of heavy drinking, marijuana use, daily cigarette smoking, and other substance use were confidentially self-reported with a standardized substance use questionnaire. Results: A total of 579 children (mean [SD] age at baseline, 8.5 [0.8] years; 465 [80%] male) were analyzed. Generalized multilevel linear models showed no evidence that current (B [SE] range, -0.62 [0.55] to 0.34 [0.47]) or prior stimulant treatment (B [SE] range, -0.06 [0.26] to 0.70 [0.37]) or their interaction (B [SE] range, -0.49 [0.70] to 0.86 [0.68]) were associated with substance use after adjusting for developmental trends in substance use and age. Marginal structural models adjusting for dynamic confounding by demographic, clinical, and familial factors revealed no evidence that more years of stimulant treatment (B [SE] range, -0.003 [0.01] to 0.04 [0.02]) or continuous, uninterrupted stimulant treatment (B [SE] range, -0.25 [0.33] to -0.03 [0.10]) were associated with adulthood substance use. Findings were the same for substance use disorder as outcome. Conclusions and Relevance: This study found no evidence that stimulant treatment was associated with increased or decreased risk for later frequent use of alcohol, marijuana, cigarette smoking, or other substances used for adolescents and young adults with childhood ADHD. These findings do not appear to result from other factors that might drive treatment over time and findings held even after considering opposing age-related trends in stimulant treatment and substance use.

Prediction using a randomized evaluation of data collection integrated through connected technologies (PREDICT): Design and rationale of a randomized trial of patients discharged from the hospital to home.

BACKGROUND: Hospital readmission prediction models often perform poorly. A critical limitation is that they use data collected up until the time of discharge but do not leverage information on patient behaviors at home after discharge. METHODS: PREDICT is a two-arm, randomized trial comparing ways to use remotely-monitored patient activity levels after hospital discharge to improve hospital readmission prediction models. Patients are randomly assigned to use a wearable device or smartphone application to track physical activity data. The study collects also validated assessments on patient characteristics as well as disparate data on credit scores and medication adherence. Patients are followed for 6 months. We evaluate whether these data sources can improve prediction compared to standard modelling approaches. CONCLUSION: The PREDICT Trial tests a novel method of remotely-monitoring patient behaviors after hospital discharge. Findings from the trial could inform new ways to improve the identification of patients at high-risk for hospital readmission. TRIAL REGISTRATION: Clinicaltrials.gov Identifier: NCT02983812.

Despite variation in volume, Veterans Affairs hospitals show consistent outcomes among patients with non-postoperative mechanical ventilation.

OBJECTIVE: To assess the relationship between volume of nonoperative mechanically ventilated patients receiving care in a specific Veterans Health Administration hospital and their mortality. DESIGN: Retrospective cohort study. SETTING: One-hundred nineteen Veterans Health Administration medical centers. PATIENTS: We identified 5,131 hospitalizations involving mechanically ventilated patients in an intensive care unit during 2009, who did not receive surgery. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We extracted demographic and clinical data from the VA Inpatient Evaluation Center. For each hospital, we defined volume as the total number of nonsurgical admissions receiving mechanical ventilation in an intensive care unit during 2009. We examined the hospital contribution to 30-day mortality using multilevel logistic regression models with a random intercept for each hospital. We quantified the extent of interhospital variation in 30-day mortality using the intraclass correlation coefficient and median odds ratio. We used generalized estimating equations to examine the relationship between volume and 30-day mortality and risk-adjusted all models using a patient-level prognostic score derived from clinical data representing the risk of death conditional on treatment at a high-volume hospital. Mean age for the sample was 65 (SD 11) yrs, 97% were men, and 60% were white. The median VA hospital cared for 40 (interquartile range 19-62) mechanically ventilated patients in 2009. Crude 30-day mortality for these patients was 36.9%. After reliability and risk adjustment to the median patient, adjusted hospital-level mortality varied from 33.5% to 40.6%. The intraclass correlation coefficient for the hospital-level variation was 0.6% (95% confidence interval 0.1, 3.4%), with a median odds ratio of 1.15 (95% confidence interval 1.06, 1.38). The relationship between hospital volume of mechanically ventilated and 30-day mortality was not statistically significant: each 50-patient increase in volume was associated with a nonsignificant 2% decrease in the odds of death within 30 days (odds ratio 0.98, 95% confidence interval 0.87-1.10). CONCLUSIONS: Veterans Health Administration hospitals caring for lower volumes of mechanically ventilated patients do not have worse mortality. Mechanisms underlying this finding are unclear, but, if elucidated, may offer other integrated health systems ways to overcome the disadvantages of small-volume centers in achieving good outcomes.