Completion and Publication Rates of Randomized Controlled Trials in Surgery: An Empirical Study.

OBJECTIVE: To investigate the prevalence of discontinuation and nonpublication of surgical versus medical randomized controlled trials (RCTs) and to explore risk factors for discontinuation and nonpublication of surgical RCTs. BACKGROUND: Trial discontinuation has significant scientific, ethical, and economic implications. To date, the prevalence of discontinuation of surgical RCTs is unknown. METHODS: All RCT protocols approved between 2000 and 2003 by 6 ethics committees in Canada, Germany, and Switzerland were screened. Baseline characteristics were collected and, if published, full reports retrieved. Risk factors for early discontinuation for slow recruitment and nonpublication were explored using multivariable logistic regression analyses. RESULTS: In total, 863 RCT protocols involving adult patients were identified, 127 in surgery (15%) and 736 in medicine (85%). Surgical trials were discontinued for any reason more often than medical trials [43% vs 27%, risk difference 16% (95% confidence interval [CI]: 5%-26%); P = 0.001] and more often discontinued for slow recruitment [18% vs 11%, risk difference 8% (95% CI: 0.1%-16%); P = 0.020]. The percentage of trials not published as full journal article was similar in surgical and medical trials (44% vs 40%, risk difference 4% (95% CI: -5% to 14%); P = 0.373). Discontinuation of surgical trials was a strong risk factor for nonpublication (odds ratio = 4.18, 95% CI: 1.45-12.06; P = 0.008). CONCLUSIONS: Discontinuation and nonpublication rates were substantial in surgical RCTs and trial discontinuation was strongly associated with nonpublication. These findings need to be taken into account when interpreting surgical literature. Surgical trialists should consider feasibility studies before embarking on full-scale trials.

Is the Front Line Prepared for the Changing Faces of Patients? Predictors of Cross-Cultural Preparedness Among Clinical Nurses and Resident Physicians in Lausanne, Switzerland.

UNLABELLED: Phenomenon: Assuring quality medical care for all persons requires that healthcare providers understand how sociocultural factors affect a patient's health beliefs/behaviors. Switzerland's changing demographics highlight the importance of provider cross-cultural preparedness for all patients-especially those at risk for social/health precarity. We evaluated healthcare provider cross-cultural preparedness for commonly encountered vulnerable patient profiles. APPROACH: A survey on cross-cultural care was mailed to Lausanne University hospital's "front-line healthcare providers": clinical nurses and resident physicians at our institution. Preparedness items asked "How prepared do you feel to care for ... ?" (referring to example patient profiles) on an ascending 5-point Likert scale. We examined proportions of "4 - well/5 - very well prepared" and the mean composite score for preparedness. We used linear regression to examine the adjusted effect of demographics, work context, cultural-competence training, and cross-cultural care problem awareness, on preparedness. FINDINGS: Of 885 questionnaires, 368 (41.2%) were returned: 124 (33.6%) physicians and 244 (66.4%) nurses. Mean preparedness composite was 3.30 (SD = 0.70), with the lowest proportion of healthcare providers feeling prepared for patients "whose religious beliefs affect treatment" (22%). After adjustment, working in a sensitized department (β = 0.21, p = .01), training on the history/culture of a specific group (β = 0.25, p = .03), and awareness regarding (a) a lack of practical experience caring for diverse populations (β = 0.25, p = .004) and (b) inadequate cross-cultural training (β = 0.18, p = .04) were associated with higher preparedness. Speaking French as a dominant language and physician role (vs. nurse) were negatively associated with preparedness (β = -0.26, p = .01; β = -0.22, p = .01). Insights: The state of cross-cultural care preparedness among Lausanne's front-line healthcare providers leaves room for improvement. Our study points toward institutional strategies to improve preparedness: notably, making sure departments are sensitized to cross-cultural care resources and increasing provider diversity to reflect the changing Swiss demographic.

Radial dose function of a 90Sr 90Y seed in water and A150: Comment on Calibration and characterization of beta-particle sources for intravascular brachytherapy

Intravascular brachytherapy with beta sources has become a useful technique to prevent restenosis after cardiovascular intervention. In particular, the Beta-Cath high-dose-rate system, manufactured by Novoste Corporation, is a commercially available 90Sr 90Y source for intravascular brachytherapy that is achieving widespread use. Its dosimetric characterization has attracted considerable attention in recent years. Unfortunately, the short ranges of the emitted beta particles and the associated large dose gradients make experimental measurements particularly difficult. This circumstance has motivated the appearance of a number of papers addressing the characterization of this source by means of Monte Carlo simulation techniques.

Accelerated Microstructure Imaging via Convex Optimization (AMICO) in crossing fibers

Mapping the microstructure properties of the local tissues in the brain is crucial to understand any pathological condition from a biological perspective. Most of the existing techniques to estimate the microstructure of the white matter assume a single axon orientation whereas numerous regions of the brain actually present a fiber-crossing configuration. The purpose of the present study is to extend a recent convex optimization framework to recover microstructure parameters in regions with multiple fibers.

A comprehensive model for quantum noise characterization in digital mammography.

NlmCategory="UNASSIGNED">A version of cascaded systems analysis was developed specifically with the aim of studying quantum noise propagation in x-ray detectors. Signal and quantum noise propagation was then modelled in four types of x-ray detectors used for digital mammography: four flat panel systems, one computed radiography and one slot-scan silicon wafer based photon counting device. As required inputs to the model, the two dimensional (2D) modulation transfer function (MTF), noise power spectra (NPS) and detective quantum efficiency (DQE) were measured for six mammography systems that utilized these different detectors. A new method to reconstruct anisotropic 2D presampling MTF matrices from 1D radial MTFs measured along different angular directions across the detector is described; an image of a sharp, circular disc was used for this purpose. The effective pixel fill factor for the FP systems was determined from the axial 1D presampling MTFs measured with a square sharp edge along the two orthogonal directions of the pixel lattice. Expectation MTFs were then calculated by averaging the radial MTFs over all possible phases and the 2D EMTF formed with the same reconstruction technique used for the 2D presampling MTF. The quantum NPS was then established by noise decomposition from homogenous images acquired as a function of detector air kerma. This was further decomposed into the correlated and uncorrelated quantum components by fitting the radially averaged quantum NPS with the radially averaged EMTF(2). This whole procedure allowed a detailed analysis of the influence of aliasing, signal and noise decorrelation, x-ray capture efficiency and global secondary gain on NPS and detector DQE. The influence of noise statistics, pixel fill factor and additional electronic and fixed pattern noises on the DQE was also studied. The 2D cascaded model and decompositions performed on the acquired images also enlightened the observed quantum NPS and DQE anisotropy.

Microcalcification evaluation in computer assisted diagnosis for digital mammography

In order to develop applications for z;isual interpretation of medical images, the early detection and evaluation of microcalcifications in digital mammograms is verg important since their presence is oftenassociated with a high incidence of breast cancers. Accurate classification into benign and malignant groups would help improve diagnostic sensitivity as well as reduce the number of unnecessa y biopsies. The challenge here is the selection of the useful features to distinguish benign from malignant micro calcifications. Our purpose in this work is to analyse a microcalcification evaluation method based on a set of shapebased features extracted from the digitised mammography. The segmentation of the microcalcificationsis performed using a fixed-tolerance region growing method to extract boundaries of calcifications with manually selected seed pixels. Taking into account that shapes and sizes of clustered microcalcificationshave been associated with a high risk of carcinoma based on digerent subjective measures, such as whether or not the calcifications are irregular, linear, vermiform, branched, rounded or ring like, our efforts were addressed to obtain a feature set related to the shape. The identification of the pammeters concerning the malignant character of the microcalcifications was performed on a set of 146 mammograms with their real diagnosis known in advance from biopsies. This allowed identifying the following shape-based parameters as the relevant ones: Number of clusters, Number of holes, Area, Feret elongation, Roughness, and Elongation. Further experiments on a set of 70 new mammogmms showed that the performance of the classification scheme is close to the mean performance of three expert radiologists, which allows to consider the proposed method for assisting the diagnosis and encourages to continue the investigation in the senseof adding new features not only related to the shape

Modeling and Classifying Breast Tissue Density in Mammograms

We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsupervised manner, and second, we will use this tissue distribution to perform the classification. We achieve this using a classifier based on local descriptors and probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature. We studied the influence of different descriptors like texture and SIFT features at the classification stage showing that textons outperform SIFT in all cases. Moreover we demonstrate that pLSA automatically extracts meaningful latent aspects generating a compact tissue representation based on their densities, useful for discriminating on mammogram classification. We show the results of tissue classification over the MIAS and DDSM datasets. We compare our method with approaches that classified these same datasets showing a better performance of our proposal

Type II aromatic polyketide biosynthetic tailoring enzymes: diversity and adaptation in Streptomyces secondary metabolism.

Members of the bacterial genus Streptomyces are well known for their ability to produce an exceptionally wide selection of diverse secondary metabolites. These include natural bioactive chemical compounds which have potential applications in medicine, agriculture and other fields of commerce. The outstanding biosynthetic capacity derives from the characteristic genetic flexibility of Streptomyces secondary metabolism pathways: i) Clustering of the biosynthetic genes in chromosome regions redundant for vital primary functions, and ii) the presence of numerous genetic elements within these regions which facilitate DNA rearrangement and transfer between non-progeny species. Decades of intensive genetic research on the organization and function of the biosynthetic routes has led to a variety of molecular biology applications, which can be used to expand the diversity of compounds synthesized. These include techniques which, for example, allow modification and artificial construction of novel pathways, and enable gene-level detection of silent secondary metabolite clusters. Over the years the research has expanded to cover molecular-level analysis of the enzymes responsible for the individual catalytic reactions. In vitro studies of the enzymes provide a detailed insight into their catalytic functions, mechanisms, substrate specificities, interactions and stereochemical determinants. These are factors that are essential for the thorough understanding and rational design of novel biosynthetic routes. The current study is a part of a more extensive research project (Antibiotic Biosynthetic Enzymes; www.sci.utu.fi/projects/biokemia/abe), which focuses on the post-PKS tailoring enzymes involved in various type II aromatic polyketide biosynthetic pathways in Streptomyces bacteria. The initiative here was to investigate specific catalytic steps in anthracycline and angucycline biosynthesis through in vitro biochemical enzyme characterization and structural enzymology. The objectives were to elucidate detailed mechanisms and enzyme-level interactions which cannot be resolved by in vivo genetic studies alone. The first part of the experimental work concerns the homologous polyketide cyclases SnoaL and AknH. These catalyze the closure of the last carbon ring of the tetracyclic carbon frame common to all anthracycline-type compounds. The second part of the study primarily deals with tailoring enzymes PgaE (and its homolog CabE) and PgaM, which are responsible for a cascade of sequential modification reactions in angucycline biosynthesis. The results complemented earlier in vivo findings and confirmed the enzyme functions in vitro. Importantly, we were able to identify the amino acid -level determinants that influence AknH and SnoaL stereoselectivity and to determine the complex biosynthetic steps of the angucycline oxygenation cascade of PgaE and PgaM. In addition, the findings revealed interesting cases of enzyme-level adaptation, as some of the catalytic mechanisms did not coincide with those described for characterised homologs or enzymes of known function. Specifically, SnoaL and AknH were shown to employ a novel acid-base mechanism for aldol condenzation, whereas the hydroxylation reaction catalysed by PgaM involved unexpected oxygen chemistry. Owing to a gene-level fusion of two ancestral reading frames, PgaM was also shown to adopt an unusual quaternary sturucture, a non-covalent fusion complex of two alternative forms of the protein. Furthermore, the work highlighted some common themes encountered in polyketide biosynthetic pathways such as enzyme substrate specificity and intermediate reactivity. These are discussed in the final chapters of the work.

Adherence and perceptions regarding simulation training in undergraduate health Sciences

BACKGROUND: Simulation techniques are spreading rapidly in medicine. Suc h resources are increasingly concentrated in Simulation Laboratories. The MSRP-USP is structuring such a laboratory and is interested in the prevalence of individual initiatives that could be centralized there. The MSRP-USP currently has five full-curriculum courses in the health sciences: Medicine, Speech Therapy, Physical Therapy, Nutrition, and Occupational Therapy, all consisting of core disciplines. GOAL: To determine the prevalence of simulation techniques in the regular courses at MSRP-USP. METHODS: Coordinators of disciplines in the various courses were interviewed using a specifically designed semi-structured questionnaire, and all the collected data were stored in a dedicated database. The disciplines were grouped according to whether they used (GI) or did not use (GII) simulation resources. RESULTS AND DISCUSSION: 256 disciplines were analyzed, of which only 18.3% used simulation techniques, varying according to course: Medicine (24.7.3%), Occupational Therapy (23.0%), Nutrition (15.9%), Physical Therapy (9.8%), and Speech Therapy (9.1%). Computer simulation programs predominated (42.5%) in all five courses. The resources were provided mainly by MSRP-USP (56.3%), with additional funding coming from other sources based on individual initiatives. The same pattern was observed for maintenance. There was great interest in centralizing the resources in the new Simulation Laboratory in order to facilitate maintenance, but there was concern about training and access to the material. CONCLUSIONS: 1) The MSRP-USP simulation resources show low complexity and are mainly limited to computer programs; 2) Use of simulation varies according to course, and is most prevalent in Medicine; 3) Resources are scattered across several locations, and their acquisition and maintenance depend on individual initiatives rather than central coordination or curricular guidelines

Fuzzy expert system in the prediction of neonatal resuscitation

In view of the importance of anticipating the occurrence of critical situations in medicine, we propose the use of a fuzzy expert system to predict the need for advanced neonatal resuscitation efforts in the delivery room. This system relates the maternal medical, obstetric and neonatal characteristics to the clinical conditions of the newborn, providing a risk measurement of need of advanced neonatal resuscitation measures. It is structured as a fuzzy composition developed on the basis of the subjective perception of danger of nine neonatologists facing 61 antenatal and intrapartum clinical situations which provide a degree of association with the risk of occurrence of perinatal asphyxia. The resulting relational matrix describes the association between clinical factors and risk of perinatal asphyxia. Analyzing the inputs of the presence or absence of all 61 clinical factors, the system returns the rate of risk of perinatal asphyxia as output. A prospectively collected series of 304 cases of perinatal care was analyzed to ascertain system performance. The fuzzy expert system presented a sensitivity of 76.5% and specificity of 94.8% in the identification of the need for advanced neonatal resuscitation measures, considering a cut-off value of 5 on a scale ranging from 0 to 10. The area under the receiver operating characteristic curve was 0.93. The identification of risk situations plays an important role in the planning of health care. These preliminary results encourage us to develop further studies and to refine this model, which is intended to implement an auxiliary system able to help health care staff to make decisions in perinatal care.

Nanotoxicité des points quantiques : étude in vitro chez les cellules épithéliales alvéolaires humaines A549

Les nanoparticules (NPs) sont définies comme des particules ayant au moins une dimension comprise entre 1 à 100 nanomètres. Plusieurs études in vitro et in vivo indiquent que les NPs pourraient constituer un risque potentiel pour la santé des personnes les synthétisant ou les manipulant lors de leur incorporation dans d’autres matériaux. La nanotoxicologie est un domaine de recherche émergeant. Les propriétés physico-chimiques particulières des NPs sont responsables d’interférences non spécifiques entre les nanomatériaux et certains des composants des essais in vitro pouvant mener à de faux résultats. L’inhalation a été identifiée comme une voie d’exposition présentant un risque important de toxicité. Dans le cadre de ce projet, nous avons utilisé la lignée de cellules épithéliales alvéolaires humaines, A549. Nous avons étudié chez cette lignée les conséquences de l’exposition aux points quantiques (PQs), NPs d’intérêt pour leurs applications potentielles en médecine (nanovecteur ou nanosonde). La mise au point des conditions expérimentales (interférence entre l’essai LDH et le milieu de culture) a permis de valider les essais de cytotoxicité MTS et LDH en présence des PQs. Nous avons montré que les PQs présentaient une cytotoxicité à court et long terme, et nous avons par la suite étudié un des mécanismes de toxicité potentielle, la mesure du cadmium (Cd2+) libéré des PQs. Nous avons déterminé que la mesure du Cd2+ comportait plusieurs interférences qui invalident cet essai. En conclusion, notre étude a permis d’identifier des interférences qui remettent en question plusieurs conclusions d’études publiées qui n’ont pas vérifié l’existence de telles interférences.

Liquid Chromatography-Electrospray Linear Ion Trap Mass Spectrometry Analysis of Targeted Neuropeptides in Tac1-/- Mouse Spinal Cords Reveal Significant Lower Concentration of Opioid Peptides.

Tachykinin and opioid peptides play a central role in pain transmission, modulation and inhibition. The treatment of pain is very important in medicine and many studies using NK1 receptor antagonists failed to show significant analgesic effects in humans. Recent investigations suggest that both pronociceptive tachykinins and the analgesic opioid systems are important for normal pain sensation. The analysis of opioid peptides in Tac1-/- spinal cord tissues offers a great opportunity to verify the influence of the tachykinin system on specific opioid peptides. The objectives of this study were to develop a HPLC–MS/MRM assay to quantify targeted peptides in spinal cord tissues. Secondly, we wanted to verify if the Tac1-/- mouse endogenous opioid system is hampered and therefore affect significantly the pain modulatory pathways. Targeted neuropeptides were analyzed by high performance liquid chromatography linear ion trap mass spectrometry. Our results reveal that EM-2, Leu-Enk and Dyn A were down-regulated in Tac1-/- spinal cord tissues. Interestingly, Dyn A was almost 3 fold down-regulated (p < 0.0001). No significant concentration differences were observed in mouse Tac1-/- spinal cords for Met-Enk and CGRP. The analysis of Tac1-/- mouse spinal cords revealed noteworthy decreases of EM-2, Leu-Enk and Dyn A concentrations which strongly suggest a significant impact on the endogenous pain-relieving mechanisms. These observations may have insightful impact on future analgesic drug developments and therapeutic strategies.

In Vitro Ketamine CYP3A Mediated Metabolism Study using Mammalian Liver S9 Fractions, cDNA Expressed Enzymes and Liquid Chromatography Tandem Mass Spectrometry

Ketamine is widely used in medicine in combination with several benzodiazepines including midazolam. The objectives of this study were to develop a novel HPLC-MS/SRM method capable of quantifying ketamine and norketamine using an isotopic dilution strategy in biological matrices and study the formation of norketamine, the principal metabolite of ketamine with and without the presence of midazolam, a well-known CYP3A substrate. The chromatographic separation was achieved using a Thermo Betasil Phenyl 100 x 2 mm column combined with an isocratic mobile phase composed of acetonitrile, methanol, water and formic acid (60:20:20:0.4) at a flow rate of 300 μL/min. The mass spectrometer was operating in selected reaction monitoring mode and the analytical range was set at 0.05–50 μM. The precision (%CV) and accuracy (%NOM) observed were ranging from 3.9–7.8 and 95.9.2–111.1% respectively. The initial rate of formation of norketamine was determined using various ketamine concentration and Km values of 18.4 μM, 13.8 μM and 30.8 μM for rat, dog and human liver S9 fractions were observed respectively. The metabolic stability of ketamine on liver S9 fractions was significantly higher in human (T1/2 = 159.4 min) compared with rat (T1/2 = 12.6 min) and dog (T1/2 = 7.3 min) liver S9 fractions. Moreover significantly lower IC50 and Ki values observed in human compared with rat and dog liver S9 fractions. Experiments with cDNA expressed CYP3A enzymes showed the formation of norketamine is mediated by CYP3A but results suggest an important contribution from others isoenzymes, most likely CYP2C particularly in rat.

A New Fast Fractal Modeling Approach for the Detection of Microcalcifications in Mammograms

In this paper, a novel fast method for modeling mammograms by deterministic fractal coding approach to detect the presence of microcalcifications, which are early signs of breast cancer, is presented. The modeled mammogram obtained using fractal encoding method is visually similar to the original image containing microcalcifications, and therefore, when it is taken out from the original mammogram, the presence of microcalcifications can be enhanced. The limitation of fractal image modeling is the tremendous time required for encoding. In the present work, instead of searching for a matching domain in the entire domain pool of the image, three methods based on mean and variance, dynamic range of the image blocks, and mass center features are used. This reduced the encoding time by a factor of 3, 89, and 13, respectively, in the three methods with respect to the conventional fractal image coding method with quad tree partitioning. The mammograms obtained from The Mammographic Image Analysis Society database (ground truth available) gave a total detection score of 87.6%, 87.6%, 90.5%, and 87.6%, for the conventional and the proposed three methods, respectively.