Predictors of early hospital readmission after acute pulmonary embolism.

BACKGROUND: Risk factors for early mortality after pulmonary embolism (PE) are widely known. However, it is uncertain which factors are associated with early readmission after PE. We sought to identify predictors of readmission after an admission for PE. METHODS: We studied 14 426 patient discharges with a primary diagnosis of PE from 186 acute care hospitals in Pennsylvania from January 1, 2000, to November 30, 2002. The outcome was readmission within 30 days of presentation for PE. We used a discrete proportional odds model to study the association between time to readmission and patient factors (age, sex, race, insurance, discharge status, and severity of illness), thrombolysis, and hospital characteristics (region, teaching status, and number of beds). RESULTS: Overall, 2064 patient discharges (14.3%) resulted in a readmission within 30 days of presentation for PE. The most common reasons for readmission were venous thromboembolism (21.9%), cancer (10.8%), pneumonia (5.2%), and bleeding (5.0%). In multivariable analysis, African American race (odds ratio [OR], 1.19; 95% confidence interval [CI], 1.02-1.38), Medicaid insurance (OR, 1.54; 95% CI, 1.31-1.81), discharge home with supplemental care (OR, 1.40; 95% CI, 1.27-1.54), leaving the hospital against medical advice (OR, 2.84; 95% CI, 1.80-4.48), and severity of illness were independently associated with readmission; readmission also varied by hospital region. CONCLUSIONS: Early readmission after PE is common. African American race, Medicaid insurance, severity of illness, discharge status, and hospital region are significantly associated with readmission. The high readmission rates for venous thromboembolism and bleeding suggest that readmission may be linked to suboptimal quality of care in the management of PE.

Large-scale imatinib dose-concentration-effect study in CML patients under routine care conditions.

This observational study analyzed imatinib pharmacokinetics and response in 2478 chronic myeloid leukemia (CML) patients. Data were obtained through centralized therapeutic drug monitoring (TDM) at median treatment duration of ≥2 years. First, individual initial trough concentrations under 400mg/day imatinib starting dose were estimated. Second, their correlation (C^min(400mg)) with reported treatment response was verified. Low imatinib levels were predicted in young male patients and those receiving P-gp/CYP3A4 inducers. These patients had also lower response rates (7% lower 18-months MMR in male, 17% lower 1-year CCyR in young patients, Kaplan-Meier estimates). Time-point independent multivariate regression confirmed a correlation of individual C^min(400mg) with response and adverse events. Possibly due to confounding factors (e.g. dose modifications, patient selection bias), the relationship seemed however flatter than previously reported from prospective controlled studies. Nonetheless, these observational results strongly suggest that a subgroup of patients could benefit from early dosage optimization assisted by TDM, because of lower imatinib concentrations and lower response rates.

The application of chemometrics on Infrared and Raman spectra as a tool for the forensic analysis of paints

The aim of this work is to evaluate the capabilities and limitations of chemometric methods and other mathematical treatments applied on spectroscopic data and more specifically on paint samples. The uniqueness of the spectroscopic data comes from the fact that they are multivariate - a few thousands variables - and highly correlated. Statistical methods are used to study and discriminate samples. A collection of 34 red paint samples was measured by Infrared and Raman spectroscopy. Data pretreatment and variable selection demonstrated that the use of Standard Normal Variate (SNV), together with removal of the noisy variables by a selection of the wavelengths from 650 to 1830 cm−1 and 2730-3600 cm−1, provided the optimal results for infrared analysis. Principal component analysis (PCA) and hierarchical clusters analysis (HCA) were then used as exploratory techniques to provide evidence of structure in the data, cluster, or detect outliers. With the FTIR spectra, the Principal Components (PCs) correspond to binder types and the presence/absence of calcium carbonate. 83% of the total variance is explained by the four first PCs. As for the Raman spectra, we observe six different clusters corresponding to the different pigment compositions when plotting the first two PCs, which account for 37% and 20% respectively of the total variance. In conclusion, the use of chemometrics for the forensic analysis of paints provides a valuable tool for objective decision-making, a reduction of the possible classification errors, and a better efficiency, having robust results with time saving data treatments.

Adalimumab in acute sciatica reduces the long-term need for surgery: a 3-year follow-up of a randomised double-blind placebo-controlled trial.

INTRODUCTION: Two subcutaneous injections of adalimumab in severe acute sciatica significantly reduced the number of back operations in a short-term randomised controlled clinical trial. OBJECTIVE: To determine in a 3-year follow-up study whether the short-term benefit of adalimumab in sciatica is sustained over a longer period of time. METHODS: The primary outcome of this analysis was incident discectomy. Three years after randomisation, information on surgery could be retrieved in 56/61 patients (92%).A multivariate Cox proportional hazard models, adjusted for potential confounders, was used to determine factors predisposing to surgery. RESULTS: Twenty-three (41%) patients had back surgery within 3 years, 8/29 (28%) in the adalimumab group and 15/27 (56%) in the placebo group, p=0.04. Adalimumab injections reduced the need for back surgery by 61% (HR)=0.39 (95% CI 0.17 to 0.92). In a multivariate model, treatment with a tumour necrosis factor-α antagonist remained the strongest protective factor (HR=0.17, p=0.002). Other significant predictors of surgery were a good correlation between symptoms and MRI findings (HR=11.6, p=0.04), baseline intensity of leg pain (HR=1.3, p=0.06), intensity of back pain (HR=1.4, p=0.03) and duration of sickness leave (HR=1.01 per day, p=0.03). CONCLUSION: A short course of adalimumab in patients with severe acute sciatica significantly reduces the need for back surgery.

Modelling dependence in a ratemaking procedure with multivariate Poisson regression models

When actuaries face with the problem of pricing an insurance contract that contains different types of coverage, such as a motor insurance or homeowner's insurance policy, they usually assume that types of claim are independent. However, this assumption may not be realistic: several studies have shown that there is a positive correlation between types of claim. Here we introduce different regression models in order to relax the independence assumption, including zero-inflated models to account for excess of zeros and overdispersion. These models have been largely ignored to multivariate Poisson date, mainly because of their computational di±culties. Bayesian inference based on MCMC helps to solve this problem (and also lets us derive, for several quantities of interest, posterior summaries to account for uncertainty). Finally, these models are applied to an automobile insurance claims database with three different types of claims. We analyse the consequences for pure and loaded premiums when the independence assumption is relaxed by using different multivariate Poisson regression models and their zero-inflated versions.

Looming signals reveal synergistic principles of multisensory integration.

Multisensory interactions are a fundamental feature of brain organization. Principles governing multisensory processing have been established by varying stimulus location, timing and efficacy independently. Determining whether and how such principles operate when stimuli vary dynamically in their perceived distance (as when looming/receding) provides an assay for synergy among the above principles and also means for linking multisensory interactions between rudimentary stimuli with higher-order signals used for communication and motor planning. Human participants indicated movement of looming or receding versus static stimuli that were visual, auditory, or multisensory combinations while 160-channel EEG was recorded. Multivariate EEG analyses and distributed source estimations were performed. Nonlinear interactions between looming signals were observed at early poststimulus latencies (∼75 ms) in analyses of voltage waveforms, global field power, and source estimations. These looming-specific interactions positively correlated with reaction time facilitation, providing direct links between neural and performance metrics of multisensory integration. Statistical analyses of source estimations identified looming-specific interactions within the right claustrum/insula extending inferiorly into the amygdala and also within the bilateral cuneus extending into the inferior and lateral occipital cortices. Multisensory effects common to all conditions, regardless of perceived distance and congruity, followed (∼115 ms) and manifested as faster transition between temporally stable brain networks (vs summed responses to unisensory conditions). We demonstrate the early-latency, synergistic interplay between existing principles of multisensory interactions. Such findings change the manner in which to model multisensory interactions at neural and behavioral/perceptual levels. We also provide neurophysiologic backing for the notion that looming signals receive preferential treatment during perception.

Updated response assessment criteria for high-grade gliomas: response assessment in neuro-oncology working group.

Currently, the most widely used criteria for assessing response to therapy in high-grade gliomas are based on two-dimensional tumor measurements on computed tomography (CT) or magnetic resonance imaging (MRI), in conjunction with clinical assessment and corticosteroid dose (the Macdonald Criteria). It is increasingly apparent that there are significant limitations to these criteria, which only address the contrast-enhancing component of the tumor. For example, chemoradiotherapy for newly diagnosed glioblastomas results in transient increase in tumor enhancement (pseudoprogression) in 20% to 30% of patients, which is difficult to differentiate from true tumor progression. Antiangiogenic agents produce high radiographic response rates, as defined by a rapid decrease in contrast enhancement on CT/MRI that occurs within days of initiation of treatment and that is partly a result of reduced vascular permeability to contrast agents rather than a true antitumor effect. In addition, a subset of patients treated with antiangiogenic agents develop tumor recurrence characterized by an increase in the nonenhancing component depicted on T2-weighted/fluid-attenuated inversion recovery sequences. The recognition that contrast enhancement is nonspecific and may not always be a true surrogate of tumor response and the need to account for the nonenhancing component of the tumor mandate that new criteria be developed and validated to permit accurate assessment of the efficacy of novel therapies. The Response Assessment in Neuro-Oncology Working Group is an international effort to develop new standardized response criteria for clinical trials in brain tumors. In this proposal, we present the recommendations for updated response criteria for high-grade gliomas.

Caffeine consumption attenuates neurochemical modifications in the hippocampus of streptozotocin-induced diabetic rats.

Type 1 diabetes can affect hippocampal function triggering cognitive impairment through unknown mechanisms. Caffeine consumption prevents hippocampal degeneration and memory dysfunction upon different insults and is also known to affect peripheral glucose metabolism. Thus we now characterized glucose transport and the neurochemical profile in the hippocampus of streptozotocin-induced diabetic rats using in vivo(1)H NMR spectroscopy and tested the effect of caffeine consumption thereupon. We found that hippocampal glucose content and transport were unaltered in diabetic rats, irrespective of caffeine consumption. However diabetic rats displayed alterations in their hippocampal neurochemical profile, which were normalized upon restoration of normoglycaemia, with the exception of myo-inositol that remained increased (36 +/- 5%, p < 0.01 compared to controls) likely reflecting osmolarity deregulation. Compared to controls, caffeine-consuming diabetic rats displayed increased hippocampal levels of myo-inositol (15 +/- 5%, p < 0.05) and taurine (23 +/- 4%, p < 0.01), supporting the ability of caffeine to control osmoregulation. Compared to controls, the hippocampus of diabetic rats displayed a reduced density of synaptic proteins syntaxin, synaptophysin and synaptosome-associated protein of 25 kDa (in average 18 +/- 1%, p < 0.05) as well increased glial fibrillary acidic protein (20 +/- 5%, p < 0.05), suggesting synaptic degeneration and astrogliosis, which were prevented by caffeine consumption. In conclusion, neurochemical alterations in the hippocampus of diabetic rats are not related to defects of glucose transport but likely reflect osmoregulatory adaptations caused by hyperglycemia. Furthermore, caffeine consumption affected this neurochemical adaptation to high glucose levels, which may contribute to its potential neuroprotective effects, namely preventing synaptic degeneration and astrogliosis.

Gambling among youths in Switzerland and its association with other addictive behaviours: a population-based study.

OBJECTIVE: To assess the prevalence of problem gambling in a population of youths in Switzerland and to determine its association with other potentially addictive behaviours. METHODS: Cross-sectional survey including 1,102 participants in the first and second year of post-compulsory education, reporting gambling, socio-demographics, internet use and substance use. For three categories of gambling (nongambler; nonproblem gambler and at-risk/problem gambler). socio-demographic and addiction data were compared using a bivariate analysis. All significant variables were included in a multinominal logistic regression using nongamblers as the reference category. RESULTS: The prevalence of gamblers was 37.48% (n = 413), with nonproblem gamblers being 31.94% (n = 352) and at-risk/problem gamblers 5.54% (n = 61). At the bivariate level, severity of gambling increased among adults (over 18 years) and among males, vocational students, participants not living with both parents and youths having a low socio-economic status. Gambling was also associated to the four addictive behaviours studied. At the multivariate level, risk of nonproblem gambling was increased in males, older youths, vocational students, participants of Swiss origin and alcohol misusers. Risk of at-risk/problem gambling was higher for males, older youths, alcohol misusers, participants not living with both parents and problem internet users. CONCLUSIONS: One-third of youths in our sample had gambled in the previous year and gambling is associated with other addictive behaviours. Clinicians should screen their adolescent patients for gambling habits, especially if other addictive behaviours are present. Additionally, gambling should be included in prevention campaigns together with other addictive behaviours.

Quality of life depends on the drinking pattern in alcohol-dependent patients.

AIMS: In patients with alcohol dependence, health-related quality of life (QOL) is reduced compared with that of a normal healthy population. The objective of the current analysis was to describe the evolution of health-related QOL in adults with alcohol dependence during a 24-month period after initial assessment for alcohol-related treatment in a routine practice setting, and its relation to drinking pattern which was evaluated across clusters based on the predominant pattern of alcohol use, set against the influence of baseline variables METHODS: The Medical Outcomes Study 36-Item Short-Form Survey (MOS-SF-36) was used to measure QOL at baseline and quarterly for 2 years among participants in CONTROL, a prospective observational study of patients initiating treatment for alcohol dependence. The sample consisted of 160 adults with alcohol dependence (65.6% males) with a mean (SD) age of 45.6 (12.0) years. Alcohol use data were collected using TimeLine Follow-Back. Based on the participant's reported alcohol use, three clusters were identified: 52 (32.5%) mostly abstainers, 64 (40.0%) mostly moderate drinkers and 44 (27.5%) mostly heavy drinkers. Mixed-effect linear regression analysis was used to identify factors that were potentially associated with the mental and physical summary MOS-SF-36 scores at each time point. RESULTS: The mean (SD) MOS-SF-36 mental component summary score (range 0-100, norm 50) was 35.7 (13.6) at baseline [mostly abstainers: 40.4 (14.6); mostly moderate drinkers 35.6 (12.4); mostly heavy drinkers 30.1 (12.1)]. The score improved to 43.1 (13.4) at 3 months [mostly abstainers: 47.4 (12.3); mostly moderate drinkers 44.2 (12.7); mostly heavy drinkers 35.1 (12.9)], to 47.3 (11.4) at 12 months [mostly abstainers: 51.7 (9.7); mostly moderate drinkers 44.8 (11.9); mostly heavy drinkers 44.1 (11.3)], and to 46.6 (11.1) at 24 months [mostly abstainers: 49.2 (11.6); mostly moderate drinkers 45.7 (11.9); mostly heavy drinkers 43.7 (8.8)]. Mixed-effect linear regression multivariate analyses indicated that there was a significant association between a lower 2-year follow-up MOS-SF-36 mental score and being a mostly heavy drinker (-6.97, P < 0.001) or mostly moderate drinker (-3.34 points, P = 0.018) [compared to mostly abstainers], being female (-3.73, P = 0.004), and having a Beck Inventory scale score ≥8 (-6.54, P < 0.001), at baseline. The mean (SD) MOS-SF-36 physical component summary score was 48.8 (10.6) at baseline, remained stable over the follow-up and did not differ across the three clusters. Mixed-effect linear regression univariate analyses found that the average 2-year follow-up MOS-SF-36 physical score was increased (compared with mostly abstainers) in mostly heavy drinkers (+4.44, P = 0.007); no other variables tested influenced the MOS-SF-36 physical score. CONCLUSION: Among individuals with alcohol dependence, a rapid improvement was seen in the mental dimension of QOL following treatment initiation, which was maintained during 24 months. Improvement was associated with the pattern of alcohol use, becoming close to the general population norm in patients classified as mostly abstainers, improving substantially in mostly moderate drinkers and improving only slightly in mostly heavy drinkers. The physical dimension of QOL was generally in the normal range but was not associated with drinking patterns.

Multivariate contemporaneous-threshold autoregressive models

This paper proposes a contemporaneous-threshold multivariate smooth transition autoregressive (C-MSTAR) model in which the regime weights depend on the ex ante probabilities that latent regime-specific variables exceed certain threshold values. A key feature of the model is that the transition function depends on all the parameters of the model as well as on the data. Since the mixing weights are also a function of the regime-specific innovation covariance matrix, the model can account for contemporaneous regime-specific co-movements of the variables. The stability and distributional properties of the proposed model are discussed, as well as issues of estimation, testing and forecasting. The practical usefulness of the C-MSTAR model is illustrated by examining the relationship between US stock prices and interest rates.

Alteration of brain glycogen turnover in the conscious rat after 5h of prolonged wakefulness.

Although glycogen (Glyc) is the main carbohydrate storage component, the role of Glyc in the brain during prolonged wakefulness is not clear. The aim of this study was to determine brain Glyc concentration ([]) and turnover time (tau) in euglycemic conscious and undisturbed rats, compared to rats maintained awake for 5h. To measure the metabolism of [1-(13)C]-labeled Glc into Glyc, 23 rats received a [1-(13)C]-labeled Glc solution as drink (10% weight per volume in tap water) ad libitum as their sole source of exogenous carbon for a "labeling period" of either 5h (n=13), 24h (n=5) or 48 h (n=5). Six of the rats labeled for 5h were continuously maintained awake by acoustic, tactile and olfactory stimuli during the labeling period, which resulted in slightly elevated corticosterone levels. Brain [Glyc] measured biochemically after focused microwave fixation in the rats maintained awake (3.9+/-0.2 micromol/g, n=6) was not significantly different from that of the control group (4.0+/-0.1 micromol/g, n=7; t-test, P>0.5). To account for potential variations in plasma Glc isotopic enrichment (IE), Glyc IE was normalized by N-acetyl-aspartate (NAA) IE. A simple mathematical model was developed to derive brain Glyc turnover time as 5.3h with a fit error of 3.2h and NAA turnover time as 15.6h with a fit error of 6.5h, in the control rats. A faster tau(Glyc) (2.9h with a fit error of 1.2h) was estimated in the rats maintained awake for 5h. In conclusion, 5h of prolonged wakefulness mainly activates glycogen metabolism, but has minimal effect on brain [Glyc].

Impact of Antibiotic Use on Carbapenem Resistance in Pseudomonas aeruginosa: Is There a Role for Antibiotic Diversity?

In this study, we aimed to evaluate the relationship between the rates of resistance of Pseudomonas aeruginosa to carbapenems and the levels and diversity of antibiotic consumption. Data were retrospectively collected from 20 acute care hospitals across 3 regions of Switzerland between 2006 and 2010. The main outcome of the present study was the rate of resistance to carbapenems among P. aeruginosa. Putative predictors included the total antibiotic consumption and carbapenem consumption in defined daily doses per 100 bed days, the proportion of very broad-spectrum antibiotics used, and the Peterson index. The present study confirmed a correlation between carbapenem use and carbapenem resistance rates at the hospital and regional levels. The impact of diversifying the range of antibiotics used against P. aeruginosa resistance was suggested by (i) a positive correlation in multivariate analysis between the above-mentioned resistance and the proportion of consumed antibiotics having a very broad spectrum of activity (coefficient = 1.77; 95% confidence interval, 0.58 to 2.96; P < 0.01) and (ii) a negative correlation between the resistance and diversity of antibiotic use as measured by the Peterson homogeneity index (coefficient = -0.52; P < 0.05). We conclude that promoting heterogeneity plus parsimony in the use of antibiotics appears to be a valuable strategy for minimizing the spread of carbapenem resistance in P. aeruginosa in hospitals.

Coronary heart disease in primary care: accuracy of medical history and physical findings in patients with chest pain - a study protocol for a systematic review with individual patient data.

BACKGROUND: Chest pain is a common complaint in primary care, with coronary heart disease (CHD) being the most concerning of many potential causes. Systematic reviews on the sensitivity and specificity of symptoms and signs summarize the evidence about which of them are most useful in making a diagnosis. Previous meta-analyses are dominated by studies of patients referred to specialists. Moreover, as the analysis is typically based on study-level data, the statistical analyses in these reviews are limited while meta-analyses based on individual patient data can provide additional information. Our patient-level meta-analysis has three unique aims. First, we strive to determine the diagnostic accuracy of symptoms and signs for myocardial ischemia in primary care. Second, we investigate associations between study- or patient-level characteristics and measures of diagnostic accuracy. Third, we aim to validate existing clinical prediction rules for diagnosing myocardial ischemia in primary care. This article describes the methods of our study and six prospective studies of primary care patients with chest pain. Later articles will describe the main results. METHODS/DESIGN: We will conduct a systematic review and IPD meta-analysis of studies evaluating the diagnostic accuracy of symptoms and signs for diagnosing coronary heart disease in primary care. We will perform bivariate analyses to determine the sensitivity, specificity and likelihood ratios of individual symptoms and signs and multivariate analyses to explore the diagnostic value of an optimal combination of all symptoms and signs based on all data of all studies. We will validate existing clinical prediction rules from each of the included studies by calculating measures of diagnostic accuracy separately by study. DISCUSSION: Our study will face several methodological challenges. First, the number of studies will be limited. Second, the investigators of original studies defined some outcomes and predictors differently. Third, the studies did not collect the same standard clinical data set. Fourth, missing data, varying from partly missing to fully missing, will have to be dealt with.Despite these limitations, we aim to summarize the available evidence regarding the diagnostic accuracy of symptoms and signs for diagnosing CHD in patients presenting with chest pain in primary care. REVIEW REGISTRATION: Centre for Reviews and Dissemination (University of York): CRD42011001170.

Bayesian classification criterion for forensic multivariate data

This study presents a classification criteria for two-class Cannabis seedlings. As the cultivation of drug type cannabis is forbidden in Switzerland, law enforcement authorities regularly ask laboratories to determine cannabis plant's chemotype from seized material in order to ascertain that the plantation is legal or not. In this study, the classification analysis is based on data obtained from the relative proportion of three major leaf compounds measured by gas-chromatography interfaced with mass spectrometry (GC-MS). The aim is to discriminate between drug type (illegal) and fiber type (legal) cannabis at an early stage of the growth. A Bayesian procedure is proposed: a Bayes factor is computed and classification is performed on the basis of the decision maker specifications (i.e. prior probability distributions on cannabis type and consequences of classification measured by losses). Classification rates are computed with two statistical models and results are compared. Sensitivity analysis is then performed to analyze the robustness of classification criteria.