2 resultados para Master data
em Université de Lausanne, Switzerland
Resumo:
Efficient priming of adaptive immunity depends on danger signals provided by innate immune pathways. As an example, inflammasome-mediated activation of caspase-1 and IL-1beta is crucial for the development of reactive T cells targeting sensitizers like dinitrofluorobenzene (DNFB). Surprisingly, DNFB and dinitrothiocyanobenzene provide cross-reactive Ags yet drive opposing, sensitizing vs tolerizing, T cell responses. In this study, we show that, in mice, inflammasome-signaling levels can be modulated to turn dinitrothiocyanobenzene into a sensitizer and DNFB into a tolerizer, and that it correlates with the IL-6 and IL-12 secretion levels, affecting Th1, Th17, and regulatory T cell development. Hence, our data provide the first evidence that the inflammasome can define the type of adaptive immune response elicited by an Ag, and hint at new strategies to modulate T cell responses in vivo.
Resumo:
Objective: The Agency for Healthcare Research and Quality (AHRQ) developed Patient Safety Indicators (PSIs) for use with ICD-9-CM data. Many countries have adopted ICD-10 for coding hospital diagnoses. We conducted this study to develop an internationally harmonized ICD-10 coding algorithm for the AHRQ PSIs. Methods: The AHRQ PSI Version 2.1 has been translated into ICD-10-AM (Australian Modification), and PSI Version 3.0a has been independently translated into ICD-10-GM (German Modification). We converted these two country-specific coding algorithms into ICD-10-WHO (World Health Organization version) and combined them to form one master list. Members of an international expert panel-including physicians, professional medical coders, disease classification specialists, health services researchers, epidemiologists, and users of the PSI-independently evaluated this master list and rated each code as either "include," "exclude," or "uncertain," following the AHRQ PSI definitions. After summarizing the independent rating results, we held a face-to-face meeting to discuss codes for which there was no unanimous consensus and newly proposed codes. A modified Delphi method was employed to generate a final ICD-10 WHO coding list. Results: Of 20 PSIs, 15 that were based mainly on diagnosis codes were selected for translation. At the meeting, panelists discussed 794 codes for which consensus had not been achieved and 2,541 additional codes that were proposed by individual panelists for consideration prior to the meeting. Three documents were generated: a PSI ICD-10-WHO version-coding list, a list of issues for consideration on certain AHRQ PSIs and ICD-9-CM codes, and a recommendation to WHO to improve specification of some disease classifications. Conclusion: An ICD-10-WHO PSI coding list has been developed and structured in a manner similar to the AHRQ manual. Although face validity of the list has been ensured through a rigorous expert panel assessment, its true validity and applicability should be assessed internationally.