Faculty Bibliography

Our aim was to investigate whether four treatment features (i.e., the inclusion of parental involvement, goal-setting strategies, maintenance/relapse prevention sessions, the addition of booster sessions) were associated with posttreatment and follow-up effect size of youth cognitive behavioral therapies (yCBTs) for anxiety, depression, posttraumatic stress disorder, and obsessive-compulsive disorder in age groups spanning young children to adolescents. We conducted a random-effects meta-analysis of 106 yCBTs tested in 76 randomized clinical trials from the PracticeWise Database to examine average effects of yCBTs posttreatment and at a later follow-up assessment. We coded the use of parental involvement, goal setting, booster sessions, and maintenance/relapse prevention in each yCBT and conducted random-effects meta-regression analyses to investigate whether these treatment features were associated with yCBT effects at posttreatment as well as at follow-up. Overall, yCBTs produced large pre- to posttreatment effects (d = 1.05), 95% confidence interval [0.94, 1.15], and larger pre- to follow-up effects (d = 1.29), 95% confidence interval [1.18, 1.40]. Metaregression results indicated that parental involvement was significantly associated with larger pre- to posttreatment effect sizes as well as pre- to follow-up effect sizes. Booster sessions, goal setting, and maintenance/relapse prevention were not significantly related to effect sizes at posttreatment or follow-up. Parental involvement may be helpful for maximizing long-term effectiveness of yCBT. Future studies should investigate for whom and under what conditions inclusion of yCBT treatment features is related to the durability of treatment gains.

OBJECTIVE:This study provides evidence of disordered RSFC of cerebellar output nuclei to the striatum and neocortex at the early stage of schizophrenia. Furthermore, dysfunctional cerebellar influences on fronto-parietal areas that are independent of striatal dysfunction in patients with FEP were observed. The results suggest that cortico-striatal abnormalities in patients with FEP are produced by abnormal cerebellar influences.

Understanding of early brain changes has the potential to investigate imaging biomarkers for pre-symptomatic diagnosis and thus opportunity for optimal therapeutic intervention, for example in early diagnosis of infants at risk to autism or altered development of infants to drug exposure. In this paper, we propose a framework to analyze longitudinal changes of structural connectivity in the early developing infant brain by exploring underlying network components of brain structural connectivity and its changes with age. Structural connectivity is a non-negative sparse network. Projective non-negative matrix factorization (PNMF) offers benefits in sparsity and learning fewer parameters for non-negative sparse data. The number of matrix subcomponents was estimated by automatic relevance determination PNMF (ARDPNMF) for brain connectivity networks for the given data. We apply linear mixed effect modeling on the resulting loadings from ARDPNMF to model longitudinal network component changes over time. The proposed framework was validated on a synthetic example generated by known linear mixed effects on loadings of the known number of bases with different levels of additive noises. Feasibility of the framework on real data has been demonstrated by analysis of structural connectivity networks of high angular resonance diffusion imaging (HARDI) data from an ongoing neuroimaging study of autism. A total of 139 image data sets from high-risk and low-risk subjects acquired at multiple time points have been processed. Results demonstrate the feasibility of the framework to analyze connectivity network properties as a function of age and the potential to eventually explore differences associated with risk status

Background: In ED patients who present with acute drug overdose, severe QTc prolongation (>500 ms) has been shown to be a predictor of adverse cardiovascular events (ACVE). However, it is unclear what clinical factors are associated with delayed severe QTc prolongation (dsQTp), and it is unknown whether dsQTp can predict ACVE. This study aims to: (1) Define clinical factors associated with dsQTp, and (2) test whether dsQTp is an independent predictor for ACVE.
Method(s): This was a prospective cohort study at 2 urban tertiary care EDs. Data was collected by trained research assistants, and included demographics, drug exposure, medication administration, initial and repeat ECG data, lab data, and outcome measures. dsQTp was defined as presence of initial QTc 499. The primary study outcome was the composite of ACVE defined as in-hospital occurrence of any of the following: MI, shock, ventricular dysrhythmia, and cardiac arrest. Univariate statistics and multivariable logistic regression calculations were made using SPSS version 24. With a fixed sample size of 1670, we calculated that we would have 99% power to show a 3-fold increase in risk with 0.05 alpha.
Result(s): Out of 2311 patients screened, 641 were excluded (age 500) leaving 1670 patients for analysis. The dsQTp group (N = 27) was found to be older than the control group (N = 1643)(40.1 vs 51.6, P
Conclusion(s): This cohort study reveals a subset of ED patients who are at greater risk of overdose-related ACVE but not immediately apparent by the initial ECG. Further study is needed to identify which patients are at risk for dsQTp, as they may require prolonged observation and repeated ECGs. Limitations include missing repeat QTc measurements, and inability to control for overdose severity as a surrogate for repeat ECGs. Future study is warranted to further characterize patients at risk for dsQTp to evaluate other exposure-related factors as yet undiscovered