Anesthetic efficacy of anterior middle superior alveolar injection in single-visit endodontic therapy: an in vivo study

Clinical Oral Investigations - To evaluate and compare the anesthetic efficacy of anterior middle superior alveolar (AMSA) injection in single-visit endodontic therapy, an in vivo study. Teeth in...     

Release modulating hydrophilic matrix systems of losartan potassium: optimization of formulation using statistical experimental design.

The aim of the present research work was to systemically device a model of factors that would yield an optimized sustained release dosage form of an anti-hypertensive agent, losartan potassium, using response surface methodology by employing a 3-factor, 3-level Box-Behnken statistical design. Independent variables studied were the amount of the release retardant polymers - HPMC K15M (X(1)), HPMC K100M (X(2)) and sodium carboxymethyl cellulose (X(3)). The dependent variables were the burst release in 15 min (Y(1)), cumulative percentage release of drug after 60 min (Y(2)) and hardness (Y(3)) of the tablets with constraints on the Y(2)=31-35%. Statistical validity of the polynomials was established. In vitro release and swelling studies were carried out for the optimized formulation and the data were fitted to kinetic equations. The polynomial mathematical relationship obtained Y(2)=32.91-2.30X(1)-5.69X(2)-0.97X(3)-0.41X(1)X(2)+0.21X(1)X(3)-0.92X(1)(2)-1.89X(2)(2) (r(2)=0.9944) explained the main and quadratic effects, and the interactions of factors influencing the drug release from matrix tablets. The adjusted (0.9842) and predicted values (0.9893) of r(2) for Y(2) were in close agreement. Validation of the optimization study indicated high degree of prognostic ability of response surface methodology. Tablets showed an initial burst release preceding a more gradual sustained release phase following a non-fickian diffusion process. The Box-Behnken experimental design facilitated the formulation and optimization of sustained release hydrophilic matrix systems of losartan potassium.     

Using OrgAhead, a computational modeling program, to improve patient care unit safety and quality outcomes

As part of ongoing research to investigate the impact of patient characteristics, organization characteristics and patient unit characteristics on safety and quality outcomes, we used a computational modeling program, OrgAhead, to model patient care units' achievement of patient safety (medication errors and falls) and quality outcomes. We tuned OrgAhead using data we collected from 32 units in 12 hospitals in Arizona. Validation studies demonstrated acceptable levels of correspondence between actual and virtual patient units. In this paper, we report how we used OrgAhead to develop testable hypotheses about the kinds of innovations that nurse managers might realistically implement on their patient care units to improve quality and safety outcomes. Our focus was on unit-level innovations that are likely to be easier for managers to implement. For all but the highest performing unit (for which we encountered a ceiling effect), we were able to generate practical strategies that improved performance of the virtual units that could be implemented by actual units to improve safety and quality outcomes. Nurse managers have responded enthusiastically to the additional decision support for quality improvement.