Drug utilisation in a neonatal intensive care unit of a swiss university hospital

Introduction Medication errors in hospitalsmay occur at any step of the medication process including prescription, transcription, preparation and administration, and may originate with any of the actors involved. Neonatal intensive care units (NICU) take care of extremely frail patients in whom errors could have dramatic consequences. Our objective was to assess the frequency and nature of medication errors in the NICU of a university hospital in order to propose measures for improvement.Materials & Methods The design was that of an observational prospective study over 4 consecutivemonths. All patients receiving C 3drugs were included. For each patient, observations during the different stages were compiled in a computer formulary and compared with the litterature. Setting: The 11-bed NICU of our university hospital.Main outcome measures:(a) Frequency and nature of medication errors in prescription,transcription, preparation and administration.(b) Drugs affected by errors.Results 83 patients were included. 505 prescriptions and transcriptions, 447 preparations and 464 administrations were analyzed. 220 medications errors were observed: 102 (46.4%) at prescription, 25 (11.4%) at transcription, 19 (8.6%) at preparation and 73 (33.2%) at administration. Uncomplete/ambiguous orders (24; 23.5%) were the most common errors observed at prescription, followed by wrong name (21; 20.6%), wrong dose (17; 16.7%) and omission (15; 14.7%). Wrong time (33; 45.2%) and wrong administration technique (31; 42.5%) were the most important medication errors during administration. According to the ATC classification, systemic antibacterials (53; 24.1%) were the most implicated, followed by perfusion solutions (40; 18.2%), respiratory system products (30; 13.6%), and mineral supplements and antithrombotic agents (20; 9.1%).Discussions, Conclusion Proposed recommendations: ? Better teaching of neonatal prescription to medical interns;? Improved prescription form to avoid omissions and ambiguities;? Development of a neonatal drug formulary, including prescription,preparation and administration modalities to reduce errors at different stages;? Presence of a clinical pharmacist in the NICU.Disclosure of Interest None Declared

Mixed spectral-structural classification of very high resolution images with summation kernels

In this paper, mixed spectral-structural kernel machines are proposed for the classification of very-high resolution images. The simultaneous use of multispectral and structural features (computed using morphological filters) allows a significant increase in classification accuracy of remote sensing images. Subsequently, weighted summation kernel support vector machines are proposed and applied in order to take into account the multiscale nature of the scene considered. Such classifiers use the Mercer property of kernel matrices to compute a new kernel matrix accounting simultaneously for two scale parameters. Tests on a Zurich QuickBird image show the relevance of the proposed method : using the mixed spectral-structural features, the classification accuracy increases of about 5%, achieving a Kappa index of 0.97. The multikernel approach proposed provide an overall accuracy of 98.90% with related Kappa index of 0.985.

Facilitatory and interfering effects of neighbourhood density on speech production: Evidence from aphasic errors.

In a system where tens of thousands of words are made up of a limited number of phonemes, many words are bound to sound alike. This similarity of the words in the lexicon as characterized by phonological neighbourhood density (PhND) has been shown to affect speed and accuracy of word comprehension and production. Whereas there is a consensus about the interfering nature of neighbourhood effects in comprehension, the language production literature offers a more contradictory picture with mainly facilitatory but also interfering effects reported on word production. Here we report both of these two types of effects in the same study. Multiple regression mixed models analyses were conducted on PhND effects on errors produced in a naming task by a group of 21 participants with aphasia. These participants produced more formal errors (interfering effect) for words in dense phonological neighbourhoods, but produced fewer nonwords and semantic errors (a facilitatory effect) with increasing density. In order to investigate the nature of these opposite effects of PhND, we further analysed a subset of formal errors and nonword errors by distinguishing errors differing on a single phoneme from the target (corresponding to the definition of phonological neighbours) from those differing on two or more phonemes. This analysis confirmed that only formal errors that were phonological neighbours of the target increased in dense neighbourhoods, while all other errors decreased. Based on additional observations favouring a lexical origin of these formal errors (they exceeded the probability of producing a real-word error by chance, were of a higher frequency, and preserved the grammatical category of the targets), we suggest that the interfering effect of PhND is due to competition between lexical neighbours and target words in dense neighbourhoods.

Cluster-based active learning for compact image classification

In this paper, we consider active sampling to label pixels grouped with hierarchical clustering. The objective of the method is to match the data relationships discovered by the clustering algorithm with the user's desired class semantics. The first is represented as a complete tree to be pruned and the second is iteratively provided by the user. The active learning algorithm proposed searches the pruning of the tree that best matches the labels of the sampled points. By choosing the part of the tree to sample from according to current pruning's uncertainty, sampling is focused on most uncertain clusters. This way, large clusters for which the class membership is already fixed are no longer queried and sampling is focused on division of clusters showing mixed labels. The model is tested on a VHR image in a multiclass classification setting. The method clearly outperforms random sampling in a transductive setting, but cannot generalize to unseen data, since it aims at optimizing the classification of a given cluster structure.

Current Issues in the Diagnosis and Classification of Peripheral T-Cell Lymphomas

Mature T-cell and T/NK-cell neoplasms are both uncommon and heterogeneous, among the broad category of non-Hodgkin's lymphomas. Due to the lack of specific genetic alterations in the vast majority of cases, most currently defined entities show overlapping morphologic and immunophenotypic features and therefore pose a challenge to the diagnostic pathologist. The goal of the symposium is to address current criteria for the recognition of specific subtypes of T-cell lymphoma, and to highlight new data regarding emerging immunophenotypic or molecular markers. This activity has been designed to meet the needs of practicing pathologists, and residents and fellows enrolled in training programs in anatomic and clinical pathology. It should be a particular benefit to those with an interest in hematopathology. Upon completion of this activity, participants should be better able to: -To be able to state the basis for the classification of mature T-cell malignancies involving nodal and extranodal sites. -To recognize and accurately diagnose the various subtypes of nodal and extranodal peripheral T-cell lymphomas. -To utilize immunohistochemical and molecular tests to characterize atypical T-cell proliferations. -To recognize and accurately diagnose T-cell lymphoproliferative lesions involving the skin and gastrointestinal tract, and be able to provide guidance regarding their clinical aggressiveness and management -To be able to utilize flow cytometric data to identify diverse functional T-cell subsets.

The Effect of Tax Revenue Budgeting Errors on Fiscal Balance : Evidence from Swiss cantons

This study is an empirical analysis of the impact of direct tax revenue budgeting errors on fiscal deficits. Using panel data from 26 Swiss cantons between 1980 and 2002, we estimate a single equation model on the fiscal balance, as well as a simultaneous equation model on revenue and expenditure. We use new data on budgeted and actual tax revenue to show that underestimating tax revenue significantly reduces fiscal deficits. Furthermore, we show that this effect is channeled through decreased expenditure. The effects of over and underestimation turn out to be symmetric.

Evidence-based provisional clinical classification criteria for autoinflammatory periodic fevers.

The objective of this work was to develop and validate a set of clinical criteria for the classification of patients affected by periodic fevers. Patients with inherited periodic fevers (familial Mediterranean fever (FMF); mevalonate kinase deficiency (MKD); tumour necrosis factor receptor-associated periodic fever syndrome (TRAPS); cryopyrin-associated periodic syndromes (CAPS)) enrolled in the Eurofever Registry up until March 2013 were evaluated. Patients with periodic fever, aphthosis, pharyngitis and adenitis (PFAPA) syndrome were used as negative controls. For each genetic disease, patients were considered to be 'gold standard' on the basis of the presence of a confirmatory genetic analysis. Clinical criteria were formulated on the basis of univariate and multivariate analysis in an initial group of patients (training set) and validated in an independent set of patients (validation set). A total of 1215 consecutive patients with periodic fevers were identified, and 518 gold standard patients (291 FMF, 74 MKD, 86 TRAPS, 67 CAPS) and 199 patients with PFAPA as disease controls were evaluated. The univariate and multivariate analyses identified a number of clinical variables that correlated independently with each disease, and four provisional classification scores were created. Cut-off values of the classification scores were chosen using receiver operating characteristic curve analysis as those giving the highest sensitivity and specificity. The classification scores were then tested in an independent set of patients (validation set) with an area under the curve of 0.98 for FMF, 0.95 for TRAPS, 0.96 for MKD, and 0.99 for CAPS. In conclusion, evidence-based provisional clinical criteria with high sensitivity and specificity for the clinical classification of patients with inherited periodic fevers have been developed.