Streamlining the medication process improves safety in the intensive care unit.

BACKGROUND: Multiple interventions were made to optimize the medication process in our intensive care unit (ICU). 1 Transcriptions from the medical order form to the administration plan were eliminated by merging both into a single document; 2 the new form was built in a logical sequence and was highly structured to promote completeness and standardization of information; 3 frequently used drug names, approved units, and fixed routes were pre-printed; 4 physicians and nurses were trained with regard to the correct use of the new form. This study was aimed at evaluating the impact of these interventions on clinically significant types of medication errors. METHODS: Eight types of medication errors were measured by a prospective chart review before and after the interventions in the ICU of a public tertiary care hospital. We used an interrupted time-series design to control the secular trends. RESULTS: Over 85 days, 9298 lines of drug prescription and/or administration to 294 patients, corresponding to 754 patient-days were collected and analysed for the three series before and three series following the intervention. Global error rate decreased from 4.95 to 2.14% (-56.8%, P < 0.001). CONCLUSIONS: The safety of the medication process in our ICU was improved by simple and inexpensive interventions. In addition to the optimization of the prescription writing process, the documentation of intravenous preparation, and the scheduling of administration, the elimination of the transcription in combination with the training of users contributed to reducing errors and carried an interesting potential to increase safety.

Experimental american trypanomiasis in rats: sympathetic denervation, parasitism and inflammatory process

Tissue parasitism, inflammatory process (histologic methods) and sympathetic denervation (glyoxylic acid-induced histofluorescence for demonstration of catecholamines) were studied in the heart (atrium and verntricle) and the submandibular gland of rats infected with the Y strain of Trypanosoma cruzi. In the heart paralleling intense parasitism and inflammatory process, the sympathetic denervation started at day 6 of infection and at the end of the acute phase (day 20) practically no varicose nerve terminals were found in both myocardium and vessels. In the submandibular gland, in spite of the rarity of anastigote pseudocysts and the scarcity of inflammatory foci, slight to moderate (days 13-15 of infection) or moderate to severe denervation (day 20) was found. At day 120 of infection both organs exhibited normal pattern of sympathetic innervation and only the heart showed some inflammatory foci and rare psudocysts (ventricle). Our data suggest the involvement of circulating factors in the sympathetic denervation phenomena but indicate that local inflammatory process is, at least, an aggravating factor.

Bayesian Inference in the Time Varying Cointegration Model

There are both theoretical and empirical reasons for believing that the parameters of macroeconomic models may vary over time. However, work with time-varying parameter models has largely involved Vector autoregressions (VARs), ignoring cointegration. This is despite the fact that cointegration plays an important role in informing macroeconomists on a range of issues. In this paper we develop time varying parameter models which permit cointegration. Time-varying parameter VARs (TVP-VARs) typically use state space representations to model the evolution of parameters. In this paper, we show that it is not sensible to use straightforward extensions of TVP-VARs when allowing for cointegration. Instead we develop a specification which allows for the cointegrating space to evolve over time in a manner comparable to the random walk variation used with TVP-VARs. The properties of our approach are investigated before developing a method of posterior simulation. We use our methods in an empirical investigation involving a permanent/transitory variance decomposition for inflation.

New perspectives in the use of ink evidence in forensic science: Part I. Development of a quality assurance process for forensic ink analysis by HPTLC

The level of information provided by ink evidence to the criminal and civil justice system is limited. The limitations arise from the weakness of the interpretative framework currently used, as proposed in the ASTM 1422-05 and 1789-04 on ink analysis. It is proposed to use the likelihood ratio from the Bayes theorem to interpret ink evidence. Unfortunately, when considering the analytical practices, as defined in the ASTM standards on ink analysis, it appears that current ink analytical practices do not allow for the level of reproducibility and accuracy required by a probabilistic framework. Such framework relies on the evaluation of the statistics of the ink characteristics using an ink reference database and the objective measurement of similarities between ink samples. A complete research programme was designed to (a) develop a standard methodology for analysing ink samples in a more reproducible way, (b) comparing automatically and objectively ink samples and (c) evaluate the proposed methodology in a forensic context. This report focuses on the first of the three stages. A calibration process, based on a standard dye ladder, is proposed to improve the reproducibility of ink analysis by HPTLC, when these inks are analysed at different times and/or by different examiners. The impact of this process on the variability between the repetitive analyses of ink samples in various conditions is studied. The results show significant improvements in the reproducibility of ink analysis compared to traditional calibration methods.

Evaluating sampling strategies and logistic regression methods for modelling complex land cover changes

The role of land cover change as a significant component of global change has become increasingly recognized in recent decades. Large databases measuring land cover change, and the data which can potentially be used to explain the observed changes, are also becoming more commonly available. When developing statistical models to investigate observed changes, it is important to be aware that the chosen sampling strategy and modelling techniques can influence results. We present a comparison of three sampling strategies and two forms of grouped logistic regression models (multinomial and ordinal) in the investigation of patterns of successional change after agricultural land abandonment in Switzerland. Results indicated that both ordinal and nominal transitional change occurs in the landscape and that the use of different sampling regimes and modelling techniques as investigative tools yield different results. Synthesis and applications. Our multimodel inference identified successfully a set of consistently selected indicators of land cover change, which can be used to predict further change, including annual average temperature, the number of already overgrown neighbouring areas of land and distance to historically destructive avalanche sites. This allows for more reliable decision making and planning with respect to landscape management. Although both model approaches gave similar results, ordinal regression yielded more parsimonious models that identified the important predictors of land cover change more efficiently. Thus, this approach is favourable where land cover change pattern can be interpreted as an ordinal process. Otherwise, multinomial logistic regression is a viable alternative.

A Comparison Of Forecasting Procedures For Macroeconomic Series: The Contribution Of Structural Break Models

This paper compares the forecasting performance of different models which have been proposed for forecasting in the presence of structural breaks. These models differ in their treatment of the break process, the parameters defining the model which applies in each regime and the out-of-sample probability of a break occurring. In an extensive empirical evaluation involving many important macroeconomic time series, we demonstrate the presence of structural breaks and their importance for forecasting in the vast majority of cases. However, we find no single forecasting model consistently works best in the presence of structural breaks. In many cases, the formal modeling of the break process is important in achieving good forecast performance. However, there are also many cases where simple, rolling OLS forecasts perform well.

A Comparison Of Forecasting Procedures For Macroeconomic Series: The Contribution Of Structural Break Models

This paper compares the forecasting performance of different models which have been proposed for forecasting in the presence of structural breaks. These models differ in their treatment of the break process, the parameters defining the model which applies in each regime and the out-of-sample probability of a break occurring. In an extensive empirical evaluation involving many important macroeconomic time series, we demonstrate the presence of structural breaks and their importance for forecasting in the vast majority of cases. However, we find no single forecasting model consistently works best in the presence of structural breaks. In many cases, the formal modeling of the break process is important in achieving good forecast performance. However, there are also many cases where simple, rolling OLS forecasts perform well.

Estimating United States Phillips Curves With Expectations Consistent With The Statistical Process Of Inflation

‘Modern’ Phillips curve theories predict inflation is an integrated, or near integrated, process. However, inflation appears bounded above and below in developed economies and so cannot be ‘truly’ integrated and more likely stationary around a shifting mean. If agents believe inflation is integrated as in the ‘modern’ theories then they are making systematic errors concerning the statistical process of inflation. An alternative theory of the Phillips curve is developed that is consistent with the ‘true’ statistical process of inflation. It is demonstrated that United States inflation data is consistent with the alternative theory but not with the existing ‘modern’ theories.

Cerebrospinal fluid antimicroglial antibodies in Alzheimer disease: a putative marker of an ongoing inflammatory process.

Immunocompetent microglia play an important role in the pathogenesis of Alzheimer's disease (AD). Antimicroglial antibodies in the cerebrospinal fluid (CSF) in clinically diagnosed AD patients have been previously recorded. Here, we report the results of the analysis of the CSF from 38 autopsy cases: 7 with definite AD; 14 with mild and 10 with moderate Alzheimer's type pathology; and 7 controls. Antimicroglial antibodies were identified in 70% of patients with definite AD, in 80% of patients with moderate and in 28% of patients with mild Alzheimer's type pathology. CSF antimicroglial antibodies were not observed in any of the control cases. The results show that CSF antimicroglial antibodies are present in the majority of patients with definite AD and also in cases with moderate Alzheimer's type changes. They may also indicate dysregulation of microglial function. Together with previous observations, these findings indicate that compromised immune defense mechanisms play an important role in the pathogenesis of AD.

The Monetary policy rules and the inflation process in open emerging

This paper has three objectives. First, it aims at revealing the logic of interest rate setting pursued by monetary authorities of 12 new EU members. Using estimation of an augmented Taylor rule, we find that this setting was not always consistent with the official monetary policy. Second, we seek to shed light on the inflation process of these countries. To this end, we carry out an estimation of an open economy Philips curve (PC). Our main finding is that inflation rates were not only driven by backward persistency but also held a forward-looking component. Finally, we assess the viability of existing monetary arrangements for price stability. The analysis of the conditional inflation variance obtained from GARCH estimation of PC is used for this purpose. We conclude that inflation targeting is preferable to an exchange rate peg because it allowed decreasing the inflation rate and anchored its volatility.

'Modern' Phillips Curves and the Implications For The Statistical Process of Inflation

'Modern' theories of the Phillips curve imply that inflation is an integrated, or near integrated process. This paper explains this implication and why these 'modern' theories are logically inconsistent with what is commonly known about the statistical process of inflation.

Reforms of the pre-graduate curriculum for medical students: the Bologna process and beyond.

For several years, all five medical faculties of Switzerland have embarked on a reform of their training curricula for two reasons: first, according to a new federal act issued in 2006 by the administration of the confederation, faculties needed to meet international standards in terms of content and pedagogic approaches; second, all Swiss universities and thus all medical faculties had to adapt the structure of their curriculum to the frame and principles which govern the Bologna process. This process is the result of the Bologna Declaration of June 1999 which proposes and requires a series of reforms to make European Higher Education more compatible and comparable, more competitive and more attractive for Europeans students. The present paper reviews some of the results achieved in the field, focusing on several issues such as the shortage of physicians and primary care practitioners, the importance of public health, community medicine and medical humanities, and the implementation of new training approaches including e-learning and simulation. In the future, faculties should work on several specific challenges such as: students' mobility, the improvement of students' autonomy and critical thinking as well as their generic and specific skills and finally a reflection on how to improve the attractiveness of the academic career, for physicians of both sexes.