Low-dose ketamine for children and adolescents with acute sickle cell disease related pain: A single center experience

Background: Opioids are the mainstay of therapy for painful vasoocclusive episodes (VOEs) in sickle cell disease (SCD). Based on limited studies, low-dose ketamine could be a useful adjuvant analgesic for refractory SCD pain, but its safety and efficacy has not been evaluated in pediatric SCD. Procedure: Using retrospective chart review we recorded and compared characteristics of hospitalizations of 33 children with SCD hospitalized with VOE who were treated with low-dose ketamine and opioid PCA vs. a paired hospitalization where the same patients received opioid PCA without ketamine. We seek to 1) describe a single center experience using adjuvant low-dose ketamine with opioid PCA for sickle cell related pain, 2) retrospectively explore the safety and efficacy of adjuvant low-dose ketamine for pain management, and 3) determine ketamine’s effect on opioid consumption in children and adolescents hospitalized with VOE. Results: During hospitalizations where patients received ketamine, pain scores and opioid use were higher (6.48 vs. 5.99; p=0.002 and 0.040 mg/kg/h vs. 0.032 mg/kg/h; p=0.004 respectively) compared to hospitalizations without ketamine. In 3 patients, ketamine was discontinued due to temporary and reversible psychotomimetic effects. There were no additional short term side effects of ketamine. Conclusions: Low-dose ketamine has an acceptable short-term safety profile for patients with SCD hospitalized for VOE. Lack of an opioid sparing effect of ketamine likely represents use of low-dose ketamine for patients presenting with more severe VOE pain. Prospective randomized studies of adjuvant low-dose ketamine for SCD pain are warranted to determine efficacy and long-term safety

Who Listens to Our Advice? A Secondary Analysis of Data From a Clinical Trial Testing an Intervention Designed to Decrease Delay in Seeking Treatment for Acute Coronary Syndrome

Objective Prolonged prehospital delay in persons experiencing acute coronary syndrome (ACS) remains a problem. Understanding which patients respond best to particular interventions designed to decrease delay time would provide mechanistic insights into the process by which interventions work. Methods In the PROMOTION trial, 3522 at-risk patients were enrolled from 5 sites in the United States (56.4%), Australia and New Zealand; 490 (N = 272 intervention, N = 218 control) had an acute event within 2 years. Focusing on these 490, we (1) identified predictors of a rapid response to symptoms, (2) identified intervention group subjects with a change in these predictors over 3 months of follow-up, and (3) compared intervention group participants with and without the favorable response pattern. Hypothesized predictors of rapid response were increased perceived control and decreased anxiety. Knowledge, attitudes, and beliefs were hypothesized to differ between responders and non-responders. Results Contrary to hypothesis, responders had low anxiety and low perceived control. Only 73 (26.8%) subjects showed this pattern 3 months following the intervention. No differences in ACS knowledge, attitudes, or beliefs were found. Conclusion The results of this study challenge existing beliefs. Practice implications New intervention approaches that focus on a realistic decrease in anxiety and perceived control are needed

True durability: HIV virologic suppression in an urban clinic and implications for timing of intensive adherence efforts and viral load monitoring

Although the majority of HIV-infected patients who begin potent antiretroviral therapy should expect long-term virologic suppression, the realities in practice are less certain. Durability of viral suppression was examined to define the best timing of targeted adherence strategies and intensive viral load monitoring in an urban clinic population with multiple challenges to ART adherence. We examined the risk of viral rebound for patients who achieved two consecutive viral loads lower than the lower limit of quantification (LLOQ) within 390 days. For 791 patients with two viral loads below the LLOQ, viral rebound \u3eLLOQ from the first viral load was 36.9 % (95 % CI 32.2–41.6) in the first year, 26.9 % (95 % CI 21.7–32.1) in the year following one year of viral suppression, and 24.6 % (95 % CI 18.4–30.9) in the year following 2 years of viral suppression. However, for patients with CD4 ≥300 cells/µl who had 3–6 years of virologic suppression, the risk of viral rebound was very low. At the population level, the risk of viral rebound in a complex urban clinic population is surprisingly high even out to 3 years. Intensified monitoring and adherence efforts should target this high risk period. Thereafter, confidence in truly durable virologic suppression is improved

True durability: HIV virologic suppression in an urban clinic and implications for timing of intensive adherence efforts and viral load monitoring.

Although the majority of HIV-infected patients who begin potent antiretroviral therapy should expect long-term virologic suppression, the realities in practice are less certain. Durability of viral suppression was examined to define the best timing of targeted adherence strategies and intensive viral load monitoring in an urban clinic population with multiple challenges to ART adherence. We examined the risk of viral rebound for patients who achieved two consecutive viral loads lower than the lower limit of quantification (LLOQ) within 390 days. For 791 patients with two viral loads below the LLOQ, viral rebound \u3eLLOQ from the first viral load was 36.9 % (95 % CI 32.2-41.6) in the first year, 26.9 % (95 % CI 21.7-32.1) in the year following one year of viral suppression, and 24.6 % (95 % CI 18.4-30.9) in the year following 2 years of viral suppression. However, for patients with CD4 ≥300 cells/µl who had 3-6 years of virologic suppression, the risk of viral rebound was very low. At the population level, the risk of viral rebound in a complex urban clinic population is surprisingly high even out to 3 years. Intensified monitoring and adherence efforts should target this high risk period. Thereafter, confidence in truly durable virologic suppression is improved

Curve registration in functional data analysis with informatively censored event-times

Curve Registration is a technique for aligning a set of curves whose time scale is observed subject to random error. In this dissertation, a general approach to Curve Registration for longitudinal and functional data, in the possible presence of informative dropout and time-varying treatments, is developed. A new method is developed for fitting the Semiparametric Nonlinear Mixed Effects Model (SNMM) where a B-spline basis expansion is used to estimate the common shape function. By using a smoothing spline to estimate the common shape function, the existing approaches to estimation and inference in this framework do not estimate the model parameters from a unified likelihood-based optimization criterion and instead use a backfitting approach that iterates between two mixed effects models. Such an iterative algorithm will not be guaranteed to converge, and because the variability in each of the two models is not properly accounted for, statistical inferences based on this approach may not be valid. Instead, a B-spline basis expansion is used in place of the smoothing spline which unifies estimation of all parameters within the same likelihood. Convergence is guaranteed, and likelihood-based statistical inferences and model selection will be valid. Computationally, the algorithm is simplified in comparison to the smoothing spline approach because the dimension of integration needed to compute the log-likelihood is typically small. Therefore, a more accurate numerical integration scheme based on Adaptive Gaussian Quadrature is implemented. The SNMM is extended to the shared parameter framework to enable joint modeling of the longitudinal trajectories and informatively censored event-times. Time-varying treatments are also accommodated through another extension to the branching curve problem. The methods developed in this dissertation are applied to a Women\u27s Health study involving women attempting a vaginal birth after cesarean (VBAC). The results of fitting the SNMM and its extensions are used to characterize the average progression of labor, to determine whether cases of uterine rupture tended to have longer delivery times, on average, than healthy controls, to model the effect of oxytocin, a labor inducing agent, on the average labor progressions

The estimation of branching curves in the presence of subject-specific random effects

Branching curves are a technique for modeling curves that change trajectory at a change (branching) point. Currently, the estimation framework is limited to independent data, and smoothing splines are used for estimation. This article aims to extend the branching curve framework to the longitudinal data setting where the branching point varies by subject. If the branching point is modeled as a random effect, then the longitudinal branching curve framework is a Semiparametric Nonlinear Mixed Effects Model. Given existing issues with using random effects within a smoothing spline, we express the model as a B-spline Based Semiparametric Nonlinear Mixed Effects Model. Simple, clever smoothness constraints are enforced on the B-splines at the change point. The method is applied to Women’s Health data where we model the shape of the labor curve (cervical dilation measured longitudinally) before and after treatment with oxytocin (a labor stimulant)

Evaluating methods for utilizing time loss data in sports settings using a sample of U.S. collegiate soccer-related injury observations

Background: Time loss has featured heavily in assessments of sports-related injury severity. Typically, it is measured as a count of days lost to injury and analyzed using ordinal cut points. We argue that a refinement of methods for the analysis of time loss which acknowledges the role of severity, is advantageous. We propose to instead model time loss with count or survival regression and adopt the view that it is a manifestation of injury severity, which is a latent variable. Inclusion of a random intercept in the model enables representation of latent injury severity as an unobservable predictor of time loss and admits an interesting, clinically relevant interpretation of observable covariate effects as being ‘severity-adjusted.’ Methods: Using a sample of U.S. collegiate soccer-related injury observations, we fit random effects Poisson and Weibull Regression models to perform ‘severity-adjusted’ evaluations of time loss. Results: Injury site, injury mechanism and injury history emerged as the strongest predictors in our sample. In comparing random effects and fixed effects models, we noted that the incorporation of the random effect attenuated associations between most observed covariates and time loss, and model fit statistics revealed that the random effects models improved model fit over the fixed effects models