DESIGN: This was a single-center prospective observational study that compared resting energy expenditure estimated by 15 commonly used predictive equations against resting energy expenditure measured by indirect calorimetry at different phases. Degree of agreement between resting energy expenditure calculated by predictive equations and resting energy expenditure measured by indirect calorimetry was analyzed using intraclass correlation coefficient and Bland-Altman analyses. Resting energy expenditure values calculated from predictive equations differing by ± 10% from resting energy expenditure measured by indirect calorimetry was used to assess accuracy. A score ranking method was developed to determine the best predictive equations.
SETTING: General Intensive Care Unit, University of Malaya Medical Centre.
PATIENTS: Mechanically ventilated critically ill patients.
INTERVENTIONS: None.
MEASUREMENTS AND MAIN RESULTS: Indirect calorimetry was measured thrice during acute, late, and chronic phases among 305, 180, and 91 ICU patients, respectively. There were significant differences (F= 3.447; p = 0.034) in mean resting energy expenditure measured by indirect calorimetry among the three phases. Pairwise comparison showed mean resting energy expenditure measured by indirect calorimetry in late phase (1,878 ± 517 kcal) was significantly higher than during acute phase (1,765 ± 456 kcal) (p = 0.037). The predictive equations with the best agreement and accuracy for acute phase was Swinamer (1990), for late phase was Brandi (1999) and Swinamer (1990), and for chronic phase was Swinamer (1990). None of the resting energy expenditure calculated from predictive equations showed very good agreement or accuracy.
CONCLUSIONS: Predictive equations tend to either over- or underestimate resting energy expenditure at different phases. Predictive equations with "dynamic" variables and respiratory data had better agreement with resting energy expenditure measured by indirect calorimetry compared with predictive equations developed for healthy adults or predictive equations based on "static" variables. Although none of the resting energy expenditure calculated from predictive equations had very good agreement, Swinamer (1990) appears to provide relatively good agreement across three phases and could be used to predict resting energy expenditure when indirect calorimetry is not available.
METHODS: The complex has been characterized for its apparent solubility and in vitro dissolution. The solid state characterization has been carried out using Fourier Transform Infra-Red (FTIR) Spectroscopy, Elemental Analysis, X-Ray Powder Diffraction (XRD), Differential Scanning Calorimetry (DSC) analysis, Thermal Gravimetric Analysis (TGA) and Scanning Electron Microscopy (SEM).
RESULTS: Simvastatin-Arginine (SMV-ARG) complex exhibited massive solubility enhancement by 12,000 fold and significant improvement in both acidic and alkaline dissolution media. A conversion of coherent crystalline to non-coherent pattern, and certain extent of amorphization in SMV-ARG complex, fully justifies the enhanced solubility, and hence the dissolution profile.
CONCLUSION: The present study provides a significant evidence that ARG molecules are capable to form a complex with small molecules and increase their aqueous solubility which prove to be beneficial in drug formulation and development.
METHODS: Semi-crystalline nanoparticles (NPs) of 90-110 nm diameter for APSP and 65-75 nm diameter for EPN were prepared and then characterized using differential scanning calorimetry (DSC) and X-ray powder diffractometry (XRD). Thereafter, drug content solubility and dissolution studies were undertaken. Berberine and its NPs were evaluated for their antibacterial activity.
RESULTS: The results indicate that the NPs have significantly increased solubility and dissolution rate due to conversion of the crystalline structure to a semi-crystalline form.
CONCLUSION: Berberine NPs produced by both APSP and EPN methods have shown promising activities against Gram-positive and Gram-negative bacteria, and yeasts, with NPs prepared through the EPN method showing superior results compared to those made with the APSP method and the unprocessed drug.