A prospective randomised multi-centre controlled trial on tight glucose control by intensive insulin therapy in adult intensive care units: the Glucontrol study.

PURPOSE: An optimal target for glucose control in ICU patients remains unclear. This prospective randomized controlled trial compared the effects on ICU mortality of intensive insulin therapy (IIT) with an intermediate glucose control. METHODS: Adult patients admitted to the 21 participating medico-surgical ICUs were randomized to group 1 (target BG 7.8-10.0 mmol/L) or to group 2 (target BG 4.4-6.1 mmol/L). RESULTS: While the required sample size was 1,750 per group, the trial was stopped early due to a high rate of unintended protocol violations. From 1,101 admissions, the outcomes of 542 patients assigned to group 1 and 536 of group 2 were analysed. The groups were well balanced. BG levels averaged in group 1 8.0 mmol/L (IQR 7.1-9.0) (median of all values) and 7.7 mmol/L (IQR 6.7-8.8) (median of morning BG) versus 6.5 mmol/L (IQR 6.0-7.2) and 6.1 mmol/L (IQR 5.5-6.8) for group 2 (p < 0.0001 for both comparisons). The percentage of patients treated with insulin averaged 66.2 and 96.3%, respectively. Proportion of time spent in target BG was similar, averaging 39.5% and 45.1% (median (IQR) 34.3 (18.5-50.0) and 39.3 (26.2-53.6)%) in the groups 1 and 2, respectively. The rate of hypoglycaemia was higher in the group 2 (8.7%) than in group 1 (2.7%, p < 0.0001). ICU mortality was similar in the two groups (15.3 vs. 17.2%). CONCLUSIONS: In this prematurely stopped and therefore underpowered study, there was a lack of clinical benefit of intensive insulin therapy (target 4.4-6.1 mmol/L), associated with an increased incidence of hypoglycaemia, as compared to a 7.8-10.0 mmol/L target. (ClinicalTrials.gov # NCT00107601, EUDRA-CT Number: 200400391440).

The MIGCLIM R package - seamless integration of dispersal constraints into projections of species distribution models

The MIGCLIM R package is a function library for the open source R software that enables the implementation of species-specific dispersal constraints into projections of species distribution models under environmental change and/or landscape fragmentation scenarios. The model is based on a cellular automaton and the basic modeling unit is a cell that is inhabited or not. Model parameters include dispersal distance and kernel, long distance dispersal, barriers to dispersal, propagule production potential and habitat invasibility. The MIGCLIM R package has been designed to be highly flexible in the parameter values it accepts, and to offer good compatibility with existing species distribution modeling software. Possible applications include the projection of future species distributions under environmental change conditions and modeling the spread of invasive species.

Estimating attributable mortality due to nosocomial infections acquired in intensive care units.

BACKGROUND: The strength of the association between intensive care unit (ICU)-acquired nosocomial infections (NIs) and mortality might differ according to the methodological approach taken. OBJECTIVE: To assess the association between ICU-acquired NIs and mortality using the concept of population-attributable fraction (PAF) for patient deaths caused by ICU-acquired NIs in a large cohort of critically ill patients. SETTING: Eleven ICUs of a French university hospital. DESIGN: We analyzed surveillance data on ICU-acquired NIs collected prospectively during the period from 1995 through 2003. The primary outcome was mortality from ICU-acquired NI stratified by site of infection. A matched-pair, case-control study was performed. Each patient who died before ICU discharge was defined as a case patient, and each patient who survived to ICU discharge was defined as a control patient. The PAF was calculated after adjustment for confounders by use of conditional logistic regression analysis. RESULTS: Among 8,068 ICU patients, a total of 1,725 deceased patients were successfully matched with 1,725 control patients. The adjusted PAF due to ICU-acquired NI for patients who died before ICU discharge was 14.6% (95% confidence interval [CI], 14.4%-14.8%). Stratified by the type of infection, the PAF was 6.1% (95% CI, 5.7%-6.5%) for pulmonary infection, 3.2% (95% CI, 2.8%-3.5%) for central venous catheter infection, 1.7% (95% CI, 0.9%-2.5%) for bloodstream infection, and 0.0% (95% CI, -0.4% to 0.4%) for urinary tract infection. CONCLUSIONS: ICU-acquired NI had an important effect on mortality. However, the statistical association between ICU-acquired NI and mortality tended to be less pronounced in findings based on the PAF than in study findings based on estimates of relative risk. Therefore, the choice of methods does matter when the burden of NI needs to be assessed.

Early-onset ventilator-associated pneumonia incidence in intensive care units: a surveillance-based study.

ABSTRACT: BACKGROUND: The incidence of ventilator-associated pneumonia (VAP) within the first 48 hours of intensive care unit (ICU) stay has been poorly investigated. The objective was to estimate early-onset VAP occurrence in ICUs within 48 hours after admission. METHODS: We analyzed data from prospective surveillance between 01/01/2001 and 31/12/2009 in 11 ICUs of Lyon hospitals (France). The inclusion criteria were: first ICU admission, not hospitalized before admission, invasive mechanical ventilation during first ICU day, free of antibiotics at admission, and ICU stay >=48 hours. VAP was defined according to a national protocol. Its incidence was the number of events per 1,000 invasive mechanical ventilation-days. The Poisson regression model was fitted from day 2 (D2) to D8 to incident VAP to estimate the expected VAP incidence from D0 to D1 of ICU stay. RESULTS: Totally, 367 (10.8%) of 3,387 patients in 45,760 patient-days developed VAP within the first 9 days. The predicted cumulative VAP incidence at D0 and D1 was 5.3 (2.6-9.8) and 8.3 (6.1-11.1), respectively. The predicted cumulative VAP incidence was 23.0 (20.8-25.3) at D8. The proportion of missed VAP within 48 hours from admission was 11% (9%-17%). CONCLUSIONS: Our study indicates underestimation of early-onset VAP incidence in ICUs, if only VAP occurring [greater than or equal to]48 hours is considered to be hospital-acquired. Clinicians should be encouraged to develop a strategy for early detection after ICU admission.

Real-life versus package insert: a post-marketing study on adverse-event rates of the virosomal hepatitis A vaccine Epaxal® in healthy travellers.

There are various methods to collect adverse events (AEs) in clinical trials. The methods how AEs are collected in vaccine trials is of special interest: solicited reporting can lead to over-reporting events that have little or no biological relationship to the vaccine. We assessed the rate of AEs listed in the package insert for the virosomal hepatitis A vaccine Epaxal(®), comparing data collected by solicited or unsolicited self-reporting. In an open, multi-centre post-marketing study, 2675 healthy travellers received single doses of vaccine administered intramuscularly. AEs were recorded based on solicited and unsolicited questioning during a four-day period after vaccination. A total of 2541 questionnaires could be evaluated (95.0% return rate). Solicited self-reporting resulted in significantly higher (p<0.0001) rates of subjects with AEs than unsolicited reporting, both at baseline (18.9% solicited versus 2.1% unsolicited systemic AEs) and following immunization (29.6% versus 19.3% local AEs; 33.8% versus 18.2% systemic AEs). This could indicate that actual reporting rates of AEs with Epaxal(®) may be substantially lower than described in the package insert. The distribution of AEs differed significantly between the applied methods of collecting AEs. The most common AEs listed in the package insert were reported almost exclusively with solicited questioning. The reporting of local AEs was more likely than that of systemic AEs to be influenced by subjects' sex, age and study centre. Women reported higher rates of AEs than men. The results highlight the need for detailing the methods how vaccine tolerability was reported and assessed.

Characteristics and determinants of outcome of hospital-acquired bloodstream infections in intensive care units: the EUROBACT International Cohort Study.

PURPOSE: The recent increase in drug-resistant micro-organisms complicates the management of hospital-acquired bloodstream infections (HA-BSIs). We investigated the epidemiology of HA-BSI and evaluated the impact of drug resistance on outcomes of critically ill patients, controlling for patient characteristics and infection management. METHODS: A prospective, multicentre non-representative cohort study was conducted in 162 intensive care units (ICUs) in 24 countries. RESULTS: We included 1,156 patients [mean ± standard deviation (SD) age, 59.5 ± 17.7 years; 65 % males; mean ± SD Simplified Acute Physiology Score (SAPS) II score, 50 ± 17] with HA-BSIs, of which 76 % were ICU-acquired. Median time to diagnosis was 14 [interquartile range (IQR), 7-26] days after hospital admission. Polymicrobial infections accounted for 12 % of cases. Among monomicrobial infections, 58.3 % were gram-negative, 32.8 % gram-positive, 7.8 % fungal and 1.2 % due to strict anaerobes. Overall, 629 (47.8 %) isolates were multidrug-resistant (MDR), including 270 (20.5 %) extensively resistant (XDR), and 5 (0.4 %) pan-drug-resistant (PDR). Micro-organism distribution and MDR occurrence varied significantly (p < 0.001) by country. The 28-day all-cause fatality rate was 36 %. In the multivariable model including micro-organism, patient and centre variables, independent predictors of 28-day mortality included MDR isolate [odds ratio (OR), 1.49; 95 % confidence interval (95 %CI), 1.07-2.06], uncontrolled infection source (OR, 5.86; 95 %CI, 2.5-13.9) and timing to adequate treatment (before day 6 since blood culture collection versus never, OR, 0.38; 95 %CI, 0.23-0.63; since day 6 versus never, OR, 0.20; 95 %CI, 0.08-0.47). CONCLUSIONS: MDR and XDR bacteria (especially gram-negative) are common in HA-BSIs in critically ill patients and are associated with increased 28-day mortality. Intensified efforts to prevent HA-BSIs and to optimize their management through adequate source control and antibiotic therapy are needed to improve outcomes.

Cross-species and cross-platform gene expression studies with the Bioconductor-compliant R package 'annotationTools'.

Background: The variety of DNA microarray formats and datasets presently available offers an unprecedented opportunity to perform insightful comparisons of heterogeneous data. Cross-species studies, in particular, have the power of identifying conserved, functionally important molecular processes. Validation of discoveries can now often be performed in readily available public data which frequently requires cross-platform studies.Cross-platform and cross-species analyses require matching probes on different microarray formats. This can be achieved using the information in microarray annotations and additional molecular biology databases, such as orthology databases. Although annotations and other biological information are stored using modern database models ( e. g. relational), they are very often distributed and shared as tables in text files, i.e. flat file databases. This common flat database format thus provides a simple and robust solution to flexibly integrate various sources of information and a basis for the combined analysis of heterogeneous gene expression profiles.Results: We provide annotationTools, a Bioconductor-compliant R package to annotate microarray experiments and integrate heterogeneous gene expression profiles using annotation and other molecular biology information available as flat file databases. First, annotationTools contains a specialized set of functions for mining this widely used database format in a systematic manner. It thus offers a straightforward solution for annotating microarray experiments. Second, building on these basic functions and relying on the combination of information from several databases, it provides tools to easily perform cross-species analyses of gene expression data.Here, we present two example applications of annotationTools that are of direct relevance for the analysis of heterogeneous gene expression profiles, namely a cross-platform mapping of probes and a cross-species mapping of orthologous probes using different orthology databases. We also show how to perform an explorative comparison of disease-related transcriptional changes in human patients and in a genetic mouse model.Conclusion: The R package annotationTools provides a simple solution to handle microarray annotation and orthology tables, as well as other flat molecular biology databases. Thereby, it allows easy integration and analysis of heterogeneous microarray experiments across different technological platforms or species.