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1.  Evidence and consensus-based German guidelines for the management of analgesia, sedation and delirium in intensive care – short version 
Targeted monitoring of analgesia, sedation and delirium, as well as their appropriate management in critically ill patients is a standard of care in intensive care medicine. With the undisputed advantages of goal-oriented therapy established, there was a need to develop our own guidelines on analgesia and sedation in intensive care in Germany and these were published as 2nd Generation Guidelines in 2005. Through the dissemination of these guidelines in 2006, use of monitoring was shown to have improved from 8 to 51% and the use of protocol-based approaches increased to 46% (from 21%).
Between 2006–2009, the existing guidelines from the DGAI (Deutsche Gesellschaft für Anästhesiologie und Intensivmedizin) and DIVI (Deutsche Interdisziplinäre Vereinigung für Intensiv- und Notfallmedizin) were developed into 3rd Generation Guidelines for the securing and optimization of quality of analgesia, sedation and delirium management in the intensive care unit (ICU). In collaboration with another 10 professional societies, the literature has been reviewed using the criteria of the Oxford Center of Evidence Based Medicine. Using data from 671 reference works, text, diagrams and recommendations were drawn up. In the recommendations, Grade “A” (very strong recommendation), Grade “B” (strong recommendation) and Grade “0” (open recommendation) were agreed.
As a result of this process we now have an interdisciplinary and consensus-based set of 3rd Generation Guidelines that take into account all critically illness patient populations.
The use of protocols for analgesia, sedation and treatment of delirium are repeatedly demonstrated. These guidelines offer treatment recommendations for the ICU team. The implementation of scores and protocols into routine ICU practice is necessary for their success.
PMCID: PMC2830566  PMID: 20200655
guideline; evidence; analgesia; sedation; delirium; monitoring; treatment; intensive care
2.  SiPaGene: A new repository for instant online retrieval, sharing and meta-analyses of GeneChip® expression data 
BMC Genomics  2009;10:98.
Microarray expression profiling is becoming a routine technology for medical research and generates enormous amounts of data. However, reanalysis of public data and comparison with own results is laborious. Although many different tools exist, there is a need for more convenience and online analysis with restriction of access and user specific sharing options. Furthermore, most of the currently existing tools do not use the whole range of statistical power provided by the MAS5.0/GCOS algorithms.
With a current focus on immunology, infection, inflammation, tissue regeneration and cancer we developed a database platform that can load preprocessed Affymetrix GeneChip expression data for immediate access. Group or subgroup comparisons can be calculated online, retrieved for candidate genes, transcriptional activity in various biological conditions and compared with different experiments. The system is based on Oracle 9i with algorithms in java and graphical user interfaces implemented as java servlets. Signals, detection calls, signal log ratios, change calls and corresponding p-values were calculated with MAS5.0/GCOS algorithms. MIAME information and gene annotations are provided via links to GEO and EntrezGene. Users access via https protocol their own, shared or public data. Sharing is comparison- and user-specific with different levels of rights. Arrays for group comparisons can be selected individually. Twenty-two different group comparison parameters can be applied in user-defined combinations on single or multiple group comparisons. Identified genes can be reviewed online or downloaded. Optimized selection criteria were developed and reliability was demonstrated with the "Latin Square" data set. Currently more than 1,000 arrays, 10,000 pairwise comparisons and 500 group comparisons are presented with public or restricted access by different research networks or individual users.
SiPaGene is a repository and a high quality tool for primary analysis of GeneChips. It exploits the MAS5.0/GCOS pairwise comparison algorithm, enables restricted access and user specific sharing. It does not aim for a complete representation of all public arrays but for high quality analysis with stepwise integration of reference signatures for detailed meta-analyses. Development of additional tools like functional annotation networks based on expression information will be future steps towards a systematic biological analysis of expression profiles.
PMCID: PMC2657156  PMID: 19265543

Results 1-2 (2)