23 research outputs found
Prevalence of and Comorbid Health Conditions Associated With Pediatric Prescription Opioid Use in the US
<p>Prescription opioids are among the most effective analgesics to treat moderate to severe pain; however, little is known about the use of prescription opioids in children, particularly those receiving an extended-release formulation for the treatment of chronic pain. In this retrospective study, the authors determined the prevalence of prescription opioid use among 7–17-year-old children and associated comorbid health conditions from 2010 to 2013 using Truven Health MarketScan (MarketScan) and Optum Clinformatics DataMart (Optum). The primary end points were prevalence of using any prescription opioids, using only prescription short-acting opioids (SAOs), and at least one prescription of a long-acting opioid (LAO). The prevalence of prescription opioid use among children is non-negligible and has been trending downwards: 6.90% in 2010 and 5.93% in 2013 using MarketScan and a similar trend using Optum: 5.47% in 2010 and 4.51% in 2013. Very few children had claims for LAOs, with only 0.04% (4979 children) in MarketScan and 0.03% (1117 children) in Optum. Given the very small number of children, primarily in the 12–17 age group, who are prescribed LAOs, there is a need to focus on a better understanding of the patterns of SAO use in children.</p
Observed, population predicted, and individual predicted ivermectin concentrations of individual subjects following ivermectin alone (No AZ) and after co-administration with azithromycin (AZ) for Subpopulation B, where increased bioavailability is observed in the interaction period.
<p>The solid line represents the fit predicted by the typical pharmacokinetic mixture model parameters. The dashed line shows the fit of the post hoc estimates of the population model. Circles represent the observed concentrations.</p
Cumulative incidence of discontinuation among newly anticoagulated non-valvular atrial fibrillation patients.
<p>(Upper panel) Cumulative incidence of discontinuation during the follow-up period. The unadjusted cumulative incidence of discontinuation was lower among patients initiated on apixaban compared to patients inititated on other oral anticoagulants. (Lower panel) The number of patients at risk for discontinuation at varying points during the follow-up.</p
Upper panel: Observed maximum ivermectin concentration data in baseline and interaction arms from all subjects (open boxes) and from subpopulations A and B (shaded and hatched boxes).
<p>Lower panel: Maximum concentration data from 1000 simulation replicates using the non-mixture model in all subjects (open boxes) and from the mixture model in subpopulations A and B (shaded and hatched boxes). The line in the interior of the box denotes the median, the bottom and top edges denote the first and third quartiles, respectively. The lines from the top and bottom edges extend to 1.5 times the interquartile range. Values exceeding the interquartile range are plotted as individual points.</p
Final Non-Mixture Model Parameter Estimates and Their Variabilities.
<p>Point Estimate = Final Parameter Estimates for <i>θ</i>s, ω<i>s</i>, and σs; SEE = standard error of estimates; %RSE = relative standard error (100<sup>*</sup>(SEE/Estimate));</p><p>IIV(%CV) = interpatient variability (100<sup>*</sup>sqrt(Estimate for <i>ω<sup>2</sup></i>)); <i>ω<sup>2</sup></i>: random effect parameter that represents inter-patient variance; σ<sup>2:</sup> random effect parameter that represents residual variance.</p
Ivermectin AUC ratio (AUC in interaction phase/AUC in baseline phase) versus azithromycin AUC in interaction phase.
<p>Solid line serves as a reference point of no change of ivermectin bioavailability; dotted line is Loess fit (local regression fit) to indicate lack of linear relationship. Circles are the observed individual values.</p
Observed data plotted as individual points.
<p>The solid center lines represent the median values of the 1000 simulated data sets, whereas the upper and lower lines represent the 97.5th and 2.5th quantiles of the simulated data, respectively.</p
Two-compartment pharmacokinetic structural model for ivermectin.
<p>The best fit was obtained by models for two subpopulation (A and B), characterized by different F values, relative to the baseline model that included all subjects. Parameters: central and peripheral compartment volumes, total body clearance (CL), inter-compartmental clearance (Q), rate of absorption, and relative bioavailability (F). Note that albendazole was administered in both baseline and interaction phases.</p
Baseline patient characteristics and treatment follow-up period.
<p>Baseline patient characteristics and treatment follow-up period.</p