Predictors and outcome impact of perioperative serum sodium changes in a high-risk population.

BACKGROUND: The perioperative period may be associated with a marked neurohumoral stress response, significant fluid losses, and varied fluid replacement regimes. Acute changes in serum sodium concentration are therefore common, but predictors and outcomes of these changes have not been investigated in a large surgical population. METHODS: We carried out a retrospective cohort analysis of 27 068 in-patient non-cardiac surgical procedures in a tertiary teaching hospital setting. Data on preoperative conditions, perioperative events, hospital length of stay, and mortality were collected, along with preoperative and postoperative serum sodium measurements up to 7 days after surgery. Logistic regression was used to investigate the association between sodium changes and mortality, and to identify clinical characteristics associated with a deviation from baseline sodium >5 mmol litre(-1). RESULTS: Changes in sodium concentration >5 mmol litre(-1) were associated with increased mortality risk (adjusted odds ratio 1.49 for a decrease, 3.02 for an increase). Factors independently associated with a perioperative decrease in serum sodium concentration >5 mmol litre(-1) included age >60, diabetes mellitus, and the use of patient-controlled opioid analgesia. Factors associated with a similar increase were preoperative oxygen dependency, mechanical ventilation, central nervous system depression, non-elective surgery, and major operative haemorrhage. CONCLUSIONS: Maximum deviation from preoperative serum sodium value is associated with increased hospital mortality in patients undergoing in-patient non-cardiac surgery. Specific preoperative and perioperative factors are associated with significant serum sodium changes.This work was supported by the Cambridge University Division of Anaesthesia.This is the author accepted manuscript. The final version is available from Oxford University Press via http://dx.doi.org/10.1093/bja/aeu40

e-MIR2: a public online inventory of medical informatics resources

Background. Over the last years, the number of available informatics resources in medicine has grown exponentially. While specific inventories of such resources have already begun to be developed for Bioinformatics (BI), comparable inventories are as yet not available for Medical Informatics (MI) field, so that locating and accessing them currently remains a hard and time-consuming task. Description. We have created a repository of MI resources from the scientific literature, providing free access to its contents through a web-based service. Relevant information describing the resources is automatically extracted from manuscripts published in top-ranked MI journals. We used a pattern matching approach to detect the resources? names and their main features. Detected resources are classified according to three different criteria: functionality, resource type and domain. To facilitate these tasks, we have built three different taxonomies by following a novel approach based on folksonomies and social tagging. We adopted the terminology most frequently used by MI researchers in their publications to create the concepts and hierarchical relationships belonging to the taxonomies. The classification algorithm identifies the categories associated to resources and annotates them accordingly. The database is then populated with this data after manual curation and validation. Conclusions. We have created an online repository of MI resources to assist researchers in locating and accessing the most suitable resources to perform specific tasks. The database contained 282 resources at the time of writing. We are continuing to expand the number of available resources by taking into account further publications as well as suggestions from users and resource developers

Survival dimensionality reduction (SDR): development and clinical application of an innovative approach to detect epistasis in presence of right-censored data

Contains fulltext : 89126.pdf (publisher's version ) (Open Access)BACKGROUND: Epistasis is recognized as a fundamental part of the genetic architecture of individuals. Several computational approaches have been developed to model gene-gene interactions in case-control studies, however, none of them is suitable for time-dependent analysis. Herein we introduce the Survival Dimensionality Reduction (SDR) algorithm, a non-parametric method specifically designed to detect epistasis in lifetime datasets. RESULTS: The algorithm requires neither specification about the underlying survival distribution nor about the underlying interaction model and proved satisfactorily powerful to detect a set of causative genes in synthetic epistatic lifetime datasets with a limited number of samples and high degree of right-censorship (up to 70%). The SDR method was then applied to a series of 386 Dutch patients with active rheumatoid arthritis that were treated with anti-TNF biological agents. Among a set of 39 candidate genes, none of which showed a detectable marginal effect on anti-TNF responses, the SDR algorithm did find that the rs1801274 SNP in the Fc gamma RIIa gene and the rs10954213 SNP in the IRF5 gene non-linearly interact to predict clinical remission after anti-TNF biologicals. CONCLUSIONS: Simulation studies and application in a real-world setting support the capability of the SDR algorithm to model epistatic interactions in candidate-genes studies in presence of right-censored data. Availability: http://sourceforge.net/projects/sdrproject/

Applying science in practice: the optimization of biological therapy in rheumatoid arthritis

Most authorities recommend starting biological agents upon failure of at least one disease-modifying agent in patients with rheumatoid arthritis. However, owing to the absence of head-to-head studies, there is little guidance about which biological to select. Still, the practicing clinician has to decide. This review explores the application of published evidence to practice, discussing the goals of treatment, the (in) ability to predict individual responses to therapy, and the potential value of indirect comparisons. We suggest that cycling of biological agents, until remission is achieved or until the most effective agent for that individual patient is determined, deserves consideration in the current stage of knowledge

Genome-wide Association Study of Response to Methotrexate in Early Rheumatoid Arthritis Patients

Methotrexate (MTX) monotherapy is a common first treatment for rheumatoid arthritis (RA), but many patients do not respond adequately. In order to identify genetic predictors of response, we have combined data from two consortia to carry out a genome-wide study of response to MTX in 1424 early RA patients of European ancestry. Clinical endpoints were change from baseline to 6 months after starting treatment in swollen 28-joint count, tender 28-joint count, C-reactive protein and the overall 3-component disease activity score (DAS28). No single nucleotide polymorphism (SNP) reached genome-wide statistical significance for any outcome measure. The strongest evidence for association was with rs168201 in NRG3 (p = 10‾⁷ for change in DAS28). Some support was also seen for association with ZMIZ1, previously highlighted in a study of response to MTX in juvenile idiopathic arthritis. Follow-up in two smaller cohorts of 429 and 177 RA patients did not support these findings, although these cohorts were more heterogeneous

Analysis of unresolved thermometric groups of rotational lines of the OH UV spectrum in the wavelength range 310-378 NM

International audiencePrevious experimental and theoretical studies [1, 2, 3] of the UV spectrum of the OH radical (band head at 306.357 nm, transition Α2Σ,v=0→Χ2Π,v′=0), easily observed in hot gases containing oxygen and hydrogen (flames, plasma chemistry), have showed the existence of three groups of unresolved rotational lines which evolution against the rotational temperature is sensitive and monotonous. From a numerical simulation of the UV OH spectrum obtained with the experimental data of Diecke et Crosswhite [4], the variations of the amplitude of these unresolved groups of lines were calibrated as a function of the temperature and of the optical apparatus function. Since the 3 groups of unresolved rotational lines may be perturbed by atomic lines coming from electrode materials in plasma processes (it is the case for neutral aluminium lines at the wavelength 308.2 nm and 309.2 nm), the previous studies have been extended to other groups of unresolved lines in the wavelength range 310−318 nm. Experiments using an oxyacetylene flame clearly demonstrate that the new groups of unresolved lines give a too high rotational temperature value. This effect can be explained with an analysis of the different rotational components that constitute these unresolved groups of lines

Gene profiling predicts rheumatoid arthritis responsiveness to IL-1Ra (anakinra)

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