Methadone Destabilizes Cardiac Repolarization During Sleep.

Methadone, a widely prescribed medication for chronic pain and opioid addiction, is associated with respiratory depression and increased predisposition for torsades de pointes, a potentially fatal arrhythmia. Most methadone-related deaths occur during sleep. The objective of this study was to determine whether methadone's arrhythmogenic effects increase during sleep, with a focus on cardiac repolarization instability using QT variability index (QTVI), a measure shown to predict arrhythmias and mortality. Sleep study data of 24 patients on chronic methadone therapy referred to a tertiary clinic for overnight polysomnography were compared with two matched groups not on methadone: 24 patients referred for overnight polysomnography to the same clinic (clinic group), and 24 volunteers who had overnight polysomnography at home (community group). Despite similar values for heart rate, heart rate variability, corrected QT interval, QTVI, and oxygen saturation (SpO2 ) when awake, patients on methadone had larger QTVI (P = 0.015 vs. clinic, P < 0.001 vs. community) and lower SpO2 (P = 0.008 vs. clinic, P = 0.013 vs. community) during sleep, and the increase in their QTVI during sleep vs. wakefulness correlated with the decrease in SpO2 (r = -0.54, P = 0.013). QTVI positively correlated with methadone dose during sleep (r = 0.51, P = 0.012) and wakefulness (r = 0.73, P < 0.001). High-density ectopy (> 1,000 premature beats per median sleep period), a precursor for torsades de pointes, was uncommon but more frequent in patients on methadone (P = 0.039). This study demonstrates that chronic methadone use is associated with increased cardiac repolarization instability. Methadone's pro-arrhythmic impact may be mediated by sleep-related hypoxemia, which could explain the increased nocturnal mortality associated with this opioid.

A practical guide to big data.

Big Data is increasingly prevalent in science and data analysis. We provide a short tutorial for adapting to these changes and making the necessary adjustments to the academic culture to keep Biostatistics truly impactful in scientific research.

The Effects of the Yes You Can! Curriculum on the Sexual Knowledge and Intent of Middle School Students.

BACKGROUND: The purpose of the study was to examine the effects of the "Yes You Can!" (YYC) curriculum on sexual knowledge and behavioral intent of program participants. METHODS: Participants included students ages 10-14 from schools in a northeast US urban area. Yes You Can! program lessons were designed to support healthy relationships. The curriculum was taught by trained instructors. The testing instrument was a 30-item questionnaire, which included sexual knowledge and intent items. Students completed the questionnaire before program implementation, immediately following intervention, and a third time at follow-up. Data were analyzed using analysis of covariance. Pretest knowledge scores were used as the covariate for the knowledge analyses. Pretest intent scores were used as the covariate for the intent analyses. RESULTS: Results showed the intervention group had less intent to engage in sexual intercourse than the control group at post-test (p < .001) and at follow-up (p < .001). Similarly, the intervention group had higher knowledge scores than the control group at post-test (p < .001) and at follow-up (p < .001). CONCLUSIONS: Results indicate that the YYC program had a statistically significant, positive impact on knowledge and sexual intent. These variables are important precursors to actual behavior. Future research should examine the effects of the program on changes in sexual behavior.

Modelling subject-specific childhood growth using linear mixed-effect models with cubic regression splines.

BACKGROUND: Childhood growth is a cornerstone of pediatric research. Statistical models need to consider individual trajectories to adequately describe growth outcomes. Specifically, well-defined longitudinal models are essential to characterize both population and subject-specific growth. Linear mixed-effect models with cubic regression splines can account for the nonlinearity of growth curves and provide reasonable estimators of population and subject-specific growth, velocity and acceleration. METHODS: We provide a stepwise approach that builds from simple to complex models, and account for the intrinsic complexity of the data. We start with standard cubic splines regression models and build up to a model that includes subject-specific random intercepts and slopes and residual autocorrelation. We then compared cubic regression splines vis-à-vis linear piecewise splines, and with varying number of knots and positions. Statistical code is provided to ensure reproducibility and improve dissemination of methods. Models are applied to longitudinal height measurements in a cohort of 215 Peruvian children followed from birth until their fourth year of life. RESULTS: Unexplained variability, as measured by the variance of the regression model, was reduced from 7.34 when using ordinary least squares to 0.81 (p < 0.001) when using a linear mixed-effect models with random slopes and a first order continuous autoregressive error term. There was substantial heterogeneity in both the intercept (p < 0.001) and slopes (p < 0.001) of the individual growth trajectories. We also identified important serial correlation within the structure of the data (ρ = 0.66; 95 % CI 0.64 to 0.68; p < 0.001), which we modeled with a first order continuous autoregressive error term as evidenced by the variogram of the residuals and by a lack of association among residuals. The final model provides a parametric linear regression equation for both estimation and prediction of population- and individual-level growth in height. We show that cubic regression splines are superior to linear regression splines for the case of a small number of knots in both estimation and prediction with the full linear mixed effect model (AIC 19,352 vs. 19,598, respectively). While the regression parameters are more complex to interpret in the former, we argue that inference for any problem depends more on the estimated curve or differences in curves rather than the coefficients. Moreover, use of cubic regression splines provides biological meaningful growth velocity and acceleration curves despite increased complexity in coefficient interpretation. CONCLUSIONS: Through this stepwise approach, we provide a set of tools to model longitudinal childhood data for non-statisticians using linear mixed-effect models.

Predicting successful long-term weight loss from short-term weight-loss outcomes: new insights from a dynamic energy balance model (the POUNDS Lost study).

BACKGROUND: Currently, early weight-loss predictions of long-term weight-loss success rely on fixed percent-weight-loss thresholds. OBJECTIVE: The objective was to develop thresholds during the first 3 mo of intervention that include the influence of age, sex, baseline weight, percent weight loss, and deviations from expected weight to predict whether a participant is likely to lose 5% or more body weight by year 1. DESIGN: Data consisting of month 1, 2, 3, and 12 treatment weights were obtained from the 2-y Preventing Obesity Using Novel Dietary Strategies (POUNDS Lost) intervention. Logistic regression models that included covariates of age, height, sex, baseline weight, target energy intake, percent weight loss, and deviation of actual weight from expected were developed for months 1, 2, and 3 that predicted the probability of losing <5% of body weight in 1 y. Receiver operating characteristic (ROC) curves, area under the curve (AUC), and thresholds were calculated for each model. The AUC statistic quantified the ROC curve's capacity to classify participants likely to lose <5% of their body weight at the end of 1 y. The models yielding the highest AUC were retained as optimal. For comparison with current practice, ROC curves relying solely on percent weight loss were also calculated. RESULTS: Optimal models for months 1, 2, and 3 yielded ROC curves with AUCs of 0.68 (95% CI: 0.63, 0.74), 0.75 (95% CI: 0.71, 0.81), and 0.79 (95% CI: 0.74, 0.84), respectively. Percent weight loss alone was not better at identifying true positives than random chance (AUC ≤0.50). CONCLUSIONS: The newly derived models provide a personalized prediction of long-term success from early weight-loss variables. The predictions improve on existing fixed percent-weight-loss thresholds. Future research is needed to explore model application for informing treatment approaches during early intervention.

Quality of life and BMI changes in youth participating in an integrated pediatric obesity treatment program.

BACKGROUND: Changes in Quality of Life (QOL) measures over time with treatment of obesity have not previously been described for youth. We describe the changes from baseline through two follow up visits in youth QOL (assessed by the Pediatric Quality Life Inventory, PedsQL4.0), teen depression (assessed by the Patient Health Questionnaire, PHQ9A), Body Mass Index (BMI) and BMI z-score. We also report caregiver proxy ratings of youth QOL. METHODS: A sample of 267 pairs of youth and caregiver participants were recruited at their first visit to an outpatient weight-treatment clinic that provides care integrated between a physician, dietician, and mental health provider; of the 267, 113 attended a visit two (V2) follow-up appointment, and 48 attended visit three (V3). We investigated multiple factors longitudinally experienced by youth who are overweight and their caregivers across up to three different integrated care visits. We determined relationships at baseline in QOL, PHQ9A, and BMI z-score, as well as changes in variables over time using linear mixed models with time as a covariate. RESULTS: Overall across three visits the results indicate that youth had slight declines in relative BMI, significant increases in their QOL and improvements in depression. CONCLUSIONS: We encourage clinicians and researchers to track youth longitudinally throughout treatment to investigate not only youth's BMI changes, but also psychosocial changes including QOL.

Brief report: parental child-directed speech as a predictor of receptive language in children with autism symptomatology.

Facilitative linguistic input directly connected to children's interest and focus of attention has become a recommended component of interventions for young children with autism spectrum disorder (ASD). This longitudinal correlational study used two assessment time points and examined the association between parental undemanding topic-continuing talk related to the child's attentional focus (i.e., follow-in comments) and later receptive language for 37 parent-child dyads with their young (mean = 21 months, range 15-24 months) children with autism symptomology. The frequency of parental follow-in comments positively predicted later receptive language after considering children's joint attention skills and previous receptive language abilities.

Feasibility of interdisciplinary community-based fall risk screening.

OBJECTIVE: This pilot study examined the feasibility of (1) conducting interdisciplinary fall risk screens at a communitywide adult fall prevention event and (2) collecting preliminary follow-up data from people screened at the event about balance confidence and home and activity modifications made after receiving educational information at the event. METHOD: We conducted a pilot study with pre- and posttesting (4-mo follow-up) with 35 community-dwelling adults ≥55 yr old. RESULTS: Approximately half the participants were at risk for falls. Most participants who anticipated making environmental or activity changes to reduce fall risk initiated changes (n = 8/11; 72.7%) during the 4-mo follow-up period. We found no significant difference in participants' balance confidence between baseline (median = 62.81) and follow-up (median = 64.06) as measured by the Activities-specific Balance Confidence scale. CONCLUSION: Conducting interdisciplinary fall risk screens at an adult fall prevention event is feasible and can facilitate environmental and behavior changes to reduce fall risk.