Appropriateness of respiratory care: development of evidence-based guidelines in an acute care hospital

Background: Respiratory care is universally recognised as useful, but its indications and practice vary markedly. In order to improve appropriateness of respiratory care in our hospital, we developed evidence-based local guidelines in a collaborative effort involving physiotherapists, physicians, and health services researchers. Methods: Recommendations were developed using the standardised RAND appropriateness method. A literature search was performed for the period between 1995 and 2008 based on terms associated with guidelines and with respiratory care. Publications were assessed according to the Oxford classification of quality of evidence. A working group prepared proposals for recommendations which were then independently rated by a multidisciplinary expert panel. All recommendations were then discussed in common and indications for procedures were rated confidentially a second time by the experts. Each indication for respiratory care was classified as appropriate, uncertain, or inappropriate, based on the panel median rating and the degree of intra-panel agreement. Results: Recommendations were formulated for the following procedures: non-invasive ventilation, continuous positive airway pressure, intermittent positive pressure breathing, intrapulmonary percussive ventilation, mechanical insufflation-exsufflation, incentive spirometry, positive expiratory pressure, nasotracheal suctioning, noninstrumental airway clearance techniques. Each recommendation referred to a particular medical condition, and was assigned to a hierarchical category based on the quality of evidence from literature supporting the recommendation and on the consensus of experts. Conclusion: Despite a marked heterogeneity of scientific evidence, the method used allowed us to develop commonly agreed local guidelines for respiratory care. In addition, this work fostered a closer relationship between physiotherapists and physicians in our institution.

Conditioning of stochastic 3-D fracture networks to hydrological and geophysical data

The geometry and connectivity of fractures exert a strong influence on the flow and transport properties of fracture networks. We present a novel approach to stochastically generate three-dimensional discrete networks of connected fractures that are conditioned to hydrological and geophysical data. A hierarchical rejection sampling algorithm is used to draw realizations from the posterior probability density function at different conditioning levels. The method is applied to a well-studied granitic formation using data acquired within two boreholes located 6 m apart. The prior models include 27 fractures with their geometry (position and orientation) bounded by information derived from single-hole ground-penetrating radar (GPR) data acquired during saline tracer tests and optical televiewer logs. Eleven cross-hole hydraulic connections between fractures in neighboring boreholes and the order in which the tracer arrives at different fractures are used for conditioning. Furthermore, the networks are conditioned to the observed relative hydraulic importance of the different hydraulic connections by numerically simulating the flow response. Among the conditioning data considered, constraints on the relative flow contributions were the most effective in determining the variability among the network realizations. Nevertheless, we find that the posterior model space is strongly determined by the imposed prior bounds. Strong prior bounds were derived from GPR measurements and helped to make the approach computationally feasible. We analyze a set of 230 posterior realizations that reproduce all data given their uncertainties assuming the same uniform transmissivity in all fractures. The posterior models provide valuable statistics on length scales and density of connected fractures, as well as their connectivity. In an additional analysis, effective transmissivity estimates of the posterior realizations indicate a strong influence of the DFN structure, in that it induces large variations of equivalent transmissivities between realizations. The transmissivity estimates agree well with previous estimates at the site based on pumping, flowmeter and temperature data.

Cancer mortality inequalities in urban areas: a Bayesian small area analysis in Spanish cities

Background Intra-urban inequalities in mortality have been infrequently analysed in European contexts. The aim of the present study was to analyse patterns of cancer mortality and their relationship with socioeconomic deprivation in small areas in 11 Spanish cities. Methods It is a cross-sectional ecological design using mortality data (years 1996-2003). Units of analysis were the census tracts. A deprivation index was calculated for each census tract. In order to control the variability in estimating the risk of dying we used Bayesian models. We present the RR of the census tract with the highest deprivation vs. the census tract with the lowest deprivation. Results In the case of men, socioeconomic inequalities are observed in total cancer mortality in all cities, except in Castellon, Cordoba and Vigo, while Barcelona (RR = 1.53 95%CI 1.42-1.67), Madrid (RR = 1.57 95%CI 1.49-1.65) and Seville (RR = 1.53 95%CI 1.36-1.74) present the greatest inequalities. In general Barcelona and Madrid, present inequalities for most types of cancer. Among women for total cancer mortality, inequalities have only been found in Barcelona and Zaragoza. The excess number of cancer deaths due to socioeconomic deprivation was 16,413 for men and 1,142 for women. Conclusion This study has analysed inequalities in cancer mortality in small areas of cities in Spain, not only relating this mortality with socioeconomic deprivation, but also calculating the excess mortality which may be attributed to such deprivation. This knowledge is particularly useful to determine which geographical areas in each city need intersectorial policies in order to promote a healthy environment.

Population pharmacokinetics and effects of efavirenz in patients with human immunodeficiency virus infection.

OBJECTIVE: The reverse transcriptase inhibitor efavirenz is currently used at a fixed dose of 600 mg/d. However, dosage individualization based on plasma concentration monitoring might be indicated. This study aimed to assess the efavirenz pharmacokinetic profile and interpatient versus intrapatient variability in patients who are positive for human immunodeficiency virus, to explore the relationship between drug exposure, efficacy, and central nervous system toxicity and to build up a Bayesian approach for dosage adaptation. METHODS: The population pharmacokinetic analysis was performed by use of NONMEM based on plasma samples from a cohort of unselected patients receiving efavirenz. With the use of a 1-compartment model with first-order absorption, the influence of demographic and clinical characteristics on oral clearance and oral volume of distribution was examined. The average drug exposure during 1 dosing interval was estimated for each patient and correlated with markers of efficacy and toxicity. The population kinetic parameters and the variabilities were integrated into a Bayesian equation for dosage adaptation based on a single plasma sample. RESULTS: Data from 235 patients with a total of 719 efavirenz concentrations were collected. Oral clearance was 9.4 L/h, oral volume of distribution was 252 L, and the absorption rate constant was 0.3 h(-1). Neither the demographic covariates evaluated nor the comedications showed a clinically significant influence on efavirenz pharmacokinetics. A large interpatient variability was found to affect efavirenz relative bioavailability (coefficient of variation, 54.6%), whereas the intrapatient variability was small (coefficient of variation, 26%). An inverse correlation between average drug exposure and viral load and a trend with central nervous system toxicity were detected. This enabled the derivation of a dosing adaptation strategy suitable to bring the average concentration into a therapeutic target from 1000 to 4000 microg/L to optimize viral load suppression and to minimize central nervous system toxicity. CONCLUSIONS: The high interpatient and low intrapatient variability values, as well as the potential relationship with markers of efficacy and toxicity, support the therapeutic drug monitoring of efavirenz. However, further evaluation is needed before individualization of an efavirenz dosage regimen based on routine drug level monitoring should be recommended for optimal patient management.

Modelling structural zeros in compositional data

This analysis was stimulated by the real data analysis problem of householdexpenditure data. The full dataset contains expenditure data for a sample of 1224 households. The expenditure is broken down at 2 hierarchical levels: 9 major levels (e.g. housing, food, utilities etc.) and 92 minor levels. There are also 5 factors and 5 covariates at the household level. Not surprisingly, there are a small number of zeros at the major level, but many zeros at the minor level. The question is how best to model the zeros. Clearly, models that tryto add a small amount to the zero terms are not appropriate in general as at least some of the zeros are clearly structural, e.g. alcohol/tobacco for households that are teetotal. The key question then is how to build suitable conditional models. For example, is the sub-composition of spendingexcluding alcohol/tobacco similar for teetotal and non-teetotal households?In other words, we are looking for sub-compositional independence. Also, what determines whether a household is teetotal? Can we assume that it is independent of the composition? In general, whether teetotal will clearly depend on the household level variables, so we need to be able to model this dependence. The other tricky question is that with zeros on more than onecomponent, we need to be able to model dependence and independence of zeros on the different components. Lastly, while some zeros are structural, others may not be, for example, for expenditure on durables, it may be chance as to whether a particular household spends money on durableswithin the sample period. This would clearly be distinguishable if we had longitudinal data, but may still be distinguishable by looking at the distribution, on the assumption that random zeros will usually be for situations where any non-zero expenditure is not small.While this analysis is based on around economic data, the ideas carry over tomany other situations, including geological data, where minerals may be missing for structural reasons (similar to alcohol), or missing because they occur only in random regions which may be missed in a sample (similar to the durables)

Refinement criteria for global illumination using convex funcions

In several computer graphics areas, a refinement criterion is often needed to decide whether to goon or to stop sampling a signal. When the sampled values are homogeneous enough, we assume thatthey represent the signal fairly well and we do not need further refinement, otherwise more samples arerequired, possibly with adaptive subdivision of the domain. For this purpose, a criterion which is verysensitive to variability is necessary. In this paper, we present a family of discrimination measures, thef-divergences, meeting this requirement. These convex functions have been well studied and successfullyapplied to image processing and several areas of engineering. Two applications to global illuminationare shown: oracles for hierarchical radiosity and criteria for adaptive refinement in ray-tracing. Weobtain significantly better results than with classic criteria, showing that f-divergences are worth furtherinvestigation in computer graphics. Also a discrimination measure based on entropy of the samples forrefinement in ray-tracing is introduced. The recursive decomposition of entropy provides us with a naturalmethod to deal with the adaptive subdivision of the sampling region

On AUV control architecture

This paper surveys control architectures proposed in the literature and describes a control architecture that is being developed for a semi-autonomous underwater vehicle for intervention missions (SAUVIM) at the University of Hawaii. Conceived as hybrid, this architecture has been organized in three layers: planning, control and execution. The mission is planned with a sequence of subgoals. Each subgoal has a related task supervisor responsible for arranging a set of pre-programmed task modules in order to achieve the subgoal. Task modules are the key concept of the architecture. They are the main building blocks and can be dynamically re-arranged by the task supervisor. In our architecture, deliberation takes place at the planning layer while reaction is dealt through the parallel execution of the task modules. Hence, the system presents both a hierarchical and an heterarchical decomposition, being able to show a predictable response while keeping rapid reactivity to the dynamic environment

Speculative parallelization of multipath radiosity algorithm

In computer graphics, global illumination algorithms take into account not only the light that comes directly from the sources, but also the light interreflections. This kind of algorithms produce very realistic images, but at a high computational cost, especially when dealing with complex environments. Parallel computation has been successfully applied to such algorithms in order to make it possible to compute highly-realistic images in a reasonable time. We introduce here a speculation-based parallel solution for a global illumination algorithm in the context of radiosity, in which we have taken advantage of the hierarchical nature of such an algorithm

Municipal distribution of bladder cancer mortality in Spain: Possible role of mining and industry

BACKGROUND Spain shows the highest bladder cancer incidence rates in men among European countries. The most important risk factors are tobacco smoking and occupational exposure to a range of different chemical substances, such as aromatic amines. METHODS This paper describes the municipal distribution of bladder cancer mortality and attempts to "adjust" this spatial pattern for the prevalence of smokers, using the autoregressive spatial model proposed by Besag, York and Molliè, with relative risk of lung cancer mortality as a surrogate. RESULTS It has been possible to compile and ascertain the posterior distribution of relative risk for bladder cancer adjusted for lung cancer mortality, on the basis of a single Bayesian spatial model covering all of Spain's 8077 towns. Maps were plotted depicting smoothed relative risk (RR) estimates, and the distribution of the posterior probability of RR>1 by sex. Towns that registered the highest relative risks for both sexes were mostly located in the Provinces of Cadiz, Seville, Huelva, Barcelona and Almería. The highest-risk area in Barcelona Province corresponded to very specific municipal areas in the Bages district, e.g., Suría, Sallent, Balsareny, Manresa and Cardona. CONCLUSION Mining/industrial pollution and the risk entailed in certain occupational exposures could in part be dictating the pattern of municipal bladder cancer mortality in Spain. Population exposure to arsenic is a matter that calls for attention. It would be of great interest if the relationship between the chemical quality of drinking water and the frequency of bladder cancer could be studied.

Inflammatory Markers and Incident Heart Failure Risk in Older Adults: The Health, Aging, and Body Composition Study

Background: Inflammation is associated with heart failure (HF) risk factors and also directly affects myocardial function. However, the association between inflammation and HF risk in older adults has not been adequately evaluated. Methods: The association of baseline serum concentrations of interleukin-6 (IL-6), tumor necrosis factor alpha (TNF- ), and C-reactive protein (CRP) with incident HF was assessed with Cox proportional hazards models among 2610 older persons without prevalent HF enrolled in the Health, Aging, and Body Composition (Health ABC) Study (age, 73.6±2.9 years; 48.3% men; 59.6% white). Results: Median (interquartile range) baseline concentrations of IL-6, TNF- , and CRP were 1.80 (1.23, 2.76) pg/mL, 3.14 (2.41, 4.06) pg/mL, and 1.64 (0.99, 3.04) µg/mL, respectively. On follow-up (median, 9.4 years), 311 participants (11.9%) developed HF. In models controlling for clinical predictors of HF and incident coronary heart disease, doubling of IL-6, TNF- , and CRP concentrations was associated with 34% (95% CI, 18 -52%; P<.001), 33% (95% CI, 9 - 63%; P=.006), and 13% (95% CI, 3-24%; P=.01) increase in HF risk, respectively. In models including all 3 markers, IL-6 and TNF- , but not CRP, remained significant. Findings were similar across sex and race. Post-HF ejection fraction (EF) was available in 239 (76.8%) cases. When only cases with preserved EF were considered (n=105), IL-6 (HR per doubling, 1.57; 95% CI, 1.28 -1.94; P<.001), TNF- (HR per doubling, 1.59; 95% CI, 1.12-2.26; P=.01), and CRP (HR per doubling, 1.23; 95% CI, 1.05-1.44; P=.01) were all associated with HF risk in adjusted models. In contrast, when only cases with reduced EF (n=134) were considered, only IL-6 attained marginal significance in adjusted models (HR per doubling, 1.20; 95% CI, 0.99 -1.46; P=.06). Participants with 2 or 3 markers above median had pronounced HF risk in adjusted models (HR, 1.66; 95% CI, 1.12-2.46; P=.01; and HR, 1.76; 95% CI, 1.16 -2.65; P=.007, respectively). Addition of IL-6 to the clinical Health ABC HF model improved discrimination (C index from 0.717 to 0.734; P=.001) and fit (decreased Bayes information criterion by 17.8; P<.001). Conclusions: Inflammatory markers are associated with HF risk among older adults and may improve HF risk stratification.

Compositional analysis of bivariate discrete probabilities

A joint distribution of two discrete random variables with finite support can be displayed as a two way table of probabilities adding to one. Assume that this table hasn rows and m columns and all probabilities are non-null. This kind of table can beseen as an element in the simplex of n · m parts. In this context, the marginals areidentified as compositional amalgams, conditionals (rows or columns) as subcompositions. Also, simplicial perturbation appears as Bayes theorem. However, the Euclideanelements of the Aitchison geometry of the simplex can also be translated into the tableof probabilities: subspaces, orthogonal projections, distances.Two important questions are addressed: a) given a table of probabilities, which isthe nearest independent table to the initial one? b) which is the largest orthogonalprojection of a row onto a column? or, equivalently, which is the information in arow explained by a column, thus explaining the interaction? To answer these questionsthree orthogonal decompositions are presented: (1) by columns and a row-wise geometric marginal, (2) by rows and a columnwise geometric marginal, (3) by independenttwo-way tables and fully dependent tables representing row-column interaction. Animportant result is that the nearest independent table is the product of the two (rowand column)-wise geometric marginal tables. A corollary is that, in an independenttable, the geometric marginals conform with the traditional (arithmetic) marginals.These decompositions can be compared with standard log-linear models.Key words: balance, compositional data, simplex, Aitchison geometry, composition,orthonormal basis, arithmetic and geometric marginals, amalgam, dependence measure,contingency table

Drugs Associated with Hepatotoxicity and their Reporting Frequency of Liver Adverse Events in VigiBase (TM) Unified List Based on International Collaborative Work

BACKGROUND Challenges exist in the clinical diagnosis of drug-induced liver injury (DILI) and in obtaining information on hepatotoxicity in humans. OBJECTIVE (i) To develop a unified list that combines drugs incriminated in well vetted or adjudicated DILI cases from many recognized sources and drugs that have been subjected to serious regulatory actions due to hepatotoxicity; and (ii) to supplement the drug list with data on reporting frequencies of liver events in the WHO individual case safety report database (VigiBase). DATA SOURCES AND EXTRACTION (i) Drugs identified as causes of DILI at three major DILI registries; (ii) drugs identified as causes of drug-induced acute liver failure (ALF) in six different data sources, including major ALF registries and previously published ALF studies; and (iii) drugs identified as being subjected to serious governmental regulatory actions due to their hepatotoxicity in Europe or the US were collected. The reporting frequency of adverse events was determined using VigiBase, computed as Empirical Bayes Geometric Mean (EBGM) with 90% confidence interval for two customized terms, 'overall liver injury' and 'ALF'. EBGM of >or=2 was considered a disproportional increase in reporting frequency. The identified drugs were then characterized in terms of regional divergence, published case reports, serious regulatory actions, and reporting frequency of 'overall liver injury' and 'ALF' calculated from VigiBase. DATA SYNTHESIS After excluding herbs, supplements and alternative medicines, a total of 385 individual drugs were identified; 319 drugs were identified in the three DILI registries, 107 from the six ALF registries (or studies) and 47 drugs that were subjected to suspension or withdrawal in the US or Europe due to their hepatotoxicity. The identified drugs varied significantly between Spain, the US and Sweden. Of the 319 drugs identified in the DILI registries of adjudicated cases, 93.4% were found in published case reports, 1.9% were suspended or withdrawn due to hepatotoxicity and 25.7% were also identified in the ALF registries/studies. In VigiBase, 30.4% of the 319 drugs were associated with disproportionally higher reporting frequency of 'overall liver injury' and 83.1% were associated with at least one reported case of ALF. CONCLUSIONS This newly developed list of drugs associated with hepatotoxicity and the multifaceted analysis on hepatotoxicity will aid in causality assessment and clinical diagnosis of DILI and will provide a basis for further characterization of hepatotoxicity.

Clinical audit of COPD patients requiring hospital admissions in Spain: AUDIPOC study.

BACKGROUNDS AUDIPOC is a nationwide clinical audit that describes the characteristics, interventions and outcomes of patients admitted to Spanish hospitals because of an exacerbation of chronic obstructive pulmonary disease (ECOPD), assessing the compliance of these parameters with current international guidelines. The present study describes hospital resources, hospital factors related to case recruitment variability, patients' characteristics, and adherence to guidelines. METHODOLOGY/PRINCIPAL FINDINGS An organisational database was completed by all participant hospitals recording resources and organisation. Over an 8-week period 11,564 consecutive ECOPD admissions to 129 Spanish hospitals covering 70% of the Spanish population were prospectively identified. At hospital discharge, 5,178 patients (45% of eligible) were finally included, and thus constituted the audited population. Audited patients were reassessed 90 days after admission for survival and readmission rates. A wide variability was observed in relation to most variables, hospital adherence to guidelines, and readmissions and death. Median inpatient mortality was 5% (across-hospital range 0-35%). Among discharged patients, 37% required readmission (0-62%) and 6.5% died (0-35%). The overall mortality rate was 11.6% (0-50%). Hospital size and complexity and aspects related to hospital COPD awareness were significantly associated with case recruitment. Clinical management most often complied with diagnosis and treatment recommendations but rarely (<50%) addressed guidance on healthy life-styles. CONCLUSIONS/SIGNIFICANCE The AUDIPOC study highlights the large across-hospital variability in resources and organization of hospitals, patient characteristics, process of care, and outcomes. The study also identifies resources and organizational characteristics associated with the admission of COPD cases, as well as aspects of daily clinical care amenable to improvement.

Polymorphisms in DNA-Repair Genes in a Cohort of Prostate Cancer Patients from Different Areas in Spain: Heterogeneity between Populations as a Confounding Factor in Association Studies.

BACKGROUND Differences in the distribution of genotypes between individuals of the same ethnicity are an important confounder factor commonly undervalued in typical association studies conducted in radiogenomics. OBJECTIVE To evaluate the genotypic distribution of SNPs in a wide set of Spanish prostate cancer patients for determine the homogeneity of the population and to disclose potential bias. DESIGN SETTING AND PARTICIPANTS A total of 601 prostate cancer patients from Andalusia, Basque Country, Canary and Catalonia were genotyped for 10 SNPs located in 6 different genes associated to DNA repair: XRCC1 (rs25487, rs25489, rs1799782), ERCC2 (rs13181), ERCC1 (rs11615), LIG4 (rs1805388, rs1805386), ATM (rs17503908, rs1800057) and P53 (rs1042522). The SNP genotyping was made in a Biotrove OpenArray® NT Cycler. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Comparisons of genotypic and allelic frequencies among populations, as well as haplotype analyses were determined using the web-based environment SNPator. Principal component analysis was made using the SnpMatrix and XSnpMatrix classes and methods implemented as an R package. Non-supervised hierarchical cluster of SNP was made using MultiExperiment Viewer. RESULTS AND LIMITATIONS We observed that genotype distribution of 4 out 10 SNPs was statistically different among the studied populations, showing the greatest differences between Andalusia and Catalonia. These observations were confirmed in cluster analysis, principal component analysis and in the differential distribution of haplotypes among the populations. Because tumor characteristics have not been taken into account, it is possible that some polymorphisms may influence tumor characteristics in the same way that it may pose a risk factor for other disease characteristics. CONCLUSION Differences in distribution of genotypes within different populations of the same ethnicity could be an important confounding factor responsible for the lack of validation of SNPs associated with radiation-induced toxicity, especially when extensive meta-analysis with subjects from different countries are carried out.

Inference about the number of contributors to a DNA mixture: Comparative analyses of a Bayesian network approach and the maximum allele count method.

In the forensic examination of DNA mixtures, the question of how to set the total number of contributors (N) presents a topic of ongoing interest. Part of the discussion gravitates around issues of bias, in particular when assessments of the number of contributors are not made prior to considering the genotypic configuration of potential donors. Further complication may stem from the observation that, in some cases, there may be numbers of contributors that are incompatible with the set of alleles seen in the profile of a mixed crime stain, given the genotype of a potential contributor. In such situations, procedures that take a single and fixed number contributors as their output can lead to inferential impasses. Assessing the number of contributors within a probabilistic framework can help avoiding such complication. Using elements of decision theory, this paper analyses two strategies for inference on the number of contributors. One procedure is deterministic and focuses on the minimum number of contributors required to 'explain' an observed set of alleles. The other procedure is probabilistic using Bayes' theorem and provides a probability distribution for a set of numbers of contributors, based on the set of observed alleles as well as their respective rates of occurrence. The discussion concentrates on mixed stains of varying quality (i.e., different numbers of loci for which genotyping information is available). A so-called qualitative interpretation is pursued since quantitative information such as peak area and height data are not taken into account. The competing procedures are compared using a standard scoring rule that penalizes the degree of divergence between a given agreed value for N, that is the number of contributors, and the actual value taken by N. Using only modest assumptions and a discussion with reference to a casework example, this paper reports on analyses using simulation techniques and graphical models (i.e., Bayesian networks) to point out that setting the number of contributors to a mixed crime stain in probabilistic terms is, for the conditions assumed in this study, preferable to a decision policy that uses categoric assumptions about N.