METHODS: The intrasubject coefficient of variation was estimated from the residual mean square error obtained from analysis of variance of the parameters AUC0-infinity, Cmax and Cmax/AUC0-infinity after logarithmic transformation. The test power in the analyses of the above parameters was subsequently estimated using nomograms provided by Diletti et al. [1991].
RESULTS AND CONCLUSION: Thirty products covering 16 drugs were studied in which 22 were immediate-release (including one dispersible tablet) and 8 were sustained-release formulations. The intrasubject coefficient of variation for the parameter AUC0-infinity was smaller than Cmax, and hence considerably more studies were able to attain a power of greater than 80% using 12 volunteers for the AUC0-infinity, compared to the Cmax. However, the variability in the Cmax could be reduced by using the parameter Cmax/ AUC0-infinity, and thus, provide a more realistic estimation of sample size, since the latter reflects only the rate of absorption and not both the rate and extent as in the case of Cmax [Endrenyi et al. 1991].
METHODS: The model-based method uses a single-compartment lung model (SCM) to simulate the resultant tidal volume of patient pairs at a set ventilation setting. If both patients meet specified safe ventilation criteria under similar ventilation settings, the actual mechanical ventilator settings for Co-MV are determined via simulation using a double-compartment lung model (DCM). This method allows clinicians to analyse Co-MV in silico, before clinical implementation.
RESULTS: The proposed method demonstrates successful patient matching and MV setting in a model-based simulation as well as good discrimination to avoid mismatched patient pairs. The pairing process is based on model-based, patient-specific respiratory mechanics identified from measured data to provide useful information for guiding care. Specifically, the matching is performed via estimation of MV delivered tidal volume (mL/kg) based on patient-specific respiratory mechanics. This information can provide insights for the clinicians to evaluate the subsequent effects of Co-MV. In addition, it was also found that Co-MV patients with highly restrictive respiratory mechanics and obese patients must be performed with extra care.
CONCLUSION: This approach allows clinicians to analyse patient matching in a virtual environment without patient risk. The approach is tested in simulation, but the results justify the necessary clinical validation in human trials.
METHODS: Patients aged 18 years old or above and who were scheduled for gynecology surgery were selected. Three different models with a combination of latent factors were based on a priori hypotheses from previous studies. The root-mean-squared error of approximation, comparative fit index, Tucker-Lewis Index, Chi-squared test, and change in Chi-squared statistic given a change in degrees of freedom between models were used to assess the model fit to the present data.
RESULTS: A total of 302 patients completed the questionnaire. The five-factor model which was based on Gordon's study has an acceptable fit for the data and was superior when compared to the one-factor baseline model. Although the four-factor model, which originated from Botti's study, also demonstrates a good model fit, the "perception of care" construct was excluded in this model. The "perception of care" construct is conceptually important as patient-centered care has become the focus of quality improvement of pain service.
CONCLUSIONS: The APS-POQ-R is easy to administer and is useful for quality evaluation in postoperative pain management. The present study demonstrates that a five-factor structure of the APS-POQ-R is the best fitting model in our patient sample. The results of this study provide further evidence to support the use of APS-POQ-R as a measurement tool for pain management evaluation in acute postoperative patients with a multi-cultural background.