Abstract:This drug interaction modeling example is useful to explain combination therapy nuances and impacts on study design. Differences in effect between single drug therapy and combination therapy should be sought at lower doses and beyond the immediate postoperative period. Combination therapy may prolong the duration of analgesia. The maximum effect (E(MAX) ) limits the early additional analgesic gain from combination therapy beyond commonly used doses.
“…Hormones possibly have influence on the higher levels of pain and decreased pain threshold experienced by women because these differences are less Data taken from [69].…”
Section: Sexmentioning
confidence: 99%
“…A constant hazard with pain score as a time varying covariate was used. The hazard of dropping out was increased with increased pain score (hazard ratio of 1.35 per unit change in pain) [69].…”
Nonlinear mixed effects models help interpret analgesic data and their use is increasing. The PK is relatively well understood. The next investigative step will involve investigation into covariate effects for PD. Mathematical functions for both placebo models and dropout models are well described and should be incorporated into analgesic effectiveness studies that investigate a range of doses. Improvements in pain assessment tools and a greater understanding of pharmacogenomics factors will help individualize analgesic therapy.
“…Hormones possibly have influence on the higher levels of pain and decreased pain threshold experienced by women because these differences are less Data taken from [69].…”
Section: Sexmentioning
confidence: 99%
“…A constant hazard with pain score as a time varying covariate was used. The hazard of dropping out was increased with increased pain score (hazard ratio of 1.35 per unit change in pain) [69].…”
Nonlinear mixed effects models help interpret analgesic data and their use is increasing. The PK is relatively well understood. The next investigative step will involve investigation into covariate effects for PD. Mathematical functions for both placebo models and dropout models are well described and should be incorporated into analgesic effectiveness studies that investigate a range of doses. Improvements in pain assessment tools and a greater understanding of pharmacogenomics factors will help individualize analgesic therapy.
“…Steepness (γ) was a function of θ, as shown in Equation 8. In summary, the Minto model required 6 parameters (C 50alf , C 50mid , β 2 50 ,U , γ mid , γ alf , and β γ ).…”
The reduced Greco model had the lowest objective function value and AICc and thus the best fit. This model was reliable with acceptable predictive ability based on adequate clinical correlation. We suggest that this model has practical clinical value for patients undergoing procedures with varying degrees of stimulation.
“…A recent simulation study suggested a prolonged analgesic effect for the combination of acetaminophen and ibuprofen compared with either drug alone. 17 Those authors emphasized the importance of scheduling follow-up evaluations for combination therapy that extend beyond the immediate postoperative period. This may explain the finding of Viitanen et al that superiority of the combination was evident only following discharge from hospital 14 as well as our own result that a requirement for post-discharge rescue medication was eliminated for children receiving the combination.…”
Section: Limitationsmentioning
confidence: 99%
“…17 Larger doses (as used in this study) result in concentrations that correspond to the upper portion of the response curve, meaning that the maximal analgesic effect is approached for both drugs, and the difference between the single and combined therapies becomes less evident. This may explain the negative result in our comparison.…”
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