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- Morris, A, et al.
(författare)
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The Development of a Multidisciplinary System to Understand Causal Factors in Road Crashes
- 2006
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Ingår i: 42nd Annual Human Factors and Ergonomics Society of Australia Conference 2006, HFESA 2006. - 9781622769599 ; , s. 31-38
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- The persistent lack of crash causation data to help inform and monitor road and vehicle safety policy is a major obstacle. Data are needed to assess the performance of road and vehicle safety stakeholders and is needed to support the development of further actions. A recent analysis conducted by the European Transport Safety Council identified that there was no single system in place that could meet all of the needs and that there were major gaps including in-depth crash causation information. This paper describes the process of developing a data collection and analysis system designed to fill these gaps. A project team with members from 7 countries was set up to devise appropriate variable lists to collect crash causation information under the following topic levels: accident, road environment, vehicle, and road user, using two quite different sets of resources: retrospective detailed police reports (n=1300) and prospective, independent, on-scene accident research investigations (n=1000). Data categorisation and human factors analysis methods based on Cognitive Reliability and Error Analysis Method (Hollnagel, 1998) were developed to enable the causal factors to be recorded, linked and understood. A harmonised, prospective "on-scene" method for recording the root causes and critical events of road crashes was developed. Where appropriate, this includes interviewing road users in collaboration with more routine accident investigation techniques. The typical level of detail recorded is a minimum of 150 variables for each accident. The project will enable multidisciplinary information on the circumstances of crashes to be interpreted to provide information on the causal factors. This has major applications in the areas of active safety systems, infrastructure and road safety, as well as for tailoring behavioural interventions. There is no direct model available internationally that uses such a systems based approach.
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- Fagerlind, Helen, 1975, et al.
(författare)
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Development of an In-depth European Accident Causation Database and the Driving Reliability and Error Analysis Method, DREAM 3.0
- 2008
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Ingår i: 3rd International Conference ESAR (Expert Symposium on Accident Research). - Hannover, Tyskland.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- The SafetyNet project was formulated in part to address the need for safety oriented European road accident data. One of the main tasks included within the project was the development of a methodology for better understanding of accident causation together with the development of an associated database involving data obtained from on-scene or “nearly on-scene” accident investigations. Information from these investigations was complemented by data from follow-up interviews with crash participants to determine critical events and contributory factors to the accident occurrence. A method for classification of accident contributing factors, known as DREAM 3.0, was developed and tested in conjunction with the SafetyNet activities. Collection of data and case analysis for some 1 000 individual crashes have recently been completed and inserted into the database and therefore aggregation analyses of the data are now being undertaken. This paper describes the methodology development, an overview of the database and the initial aggregation analyses.
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- Haas, Jan, et al.
(författare)
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Atlas of the clinical genetics of human dilated cardiomyopathy
- 2015
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Ingår i: European Heart Journal. - : Oxford University Press. - 0195-668X .- 1522-9645. ; 36:18, s. 1123-U43
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Tidskriftsartikel (refereegranskat)abstract
- Aim: We were able to show that targeted Next-Generation Sequencing is well suited to be applied in clinical routine diagnostics, substantiating the ongoing paradigm shift from low- to high-throughput genomics in medicine. By means of our atlas of the genetics of human DCM, we aspire to soon be able to apply our findings to the individual patient with cardiomyopathy in daily clinical practice. Numerous genes are known to cause dilated cardiomyopathy (DCM). However, until now technological limitations have hindered elucidation of the contribution of all clinically relevant disease genes to DCM phenotypes in larger cohorts. We now utilized next-generation sequencing to overcome these limitations and screened all DCM disease genes in a large cohort. Methods and results: In this multi-centre, multi-national study, we have enrolled 639 patients with sporadic or familial DCM. To all samples, we applied a standardized protocol for ultra-high coverage next-generation sequencing of 84 genes, leading to 99.1% coverage of the target region with at least 50-fold and a mean read depth of 2415. In this well characterized cohort, we find the highest number of known cardiomyopathy mutations in plakophilin-2, myosin-binding protein C-3, and desmoplakin. When we include yet unknown but predicted disease variants, we find titin, plakophilin-2, myosin-binding protein-C 3, desmoplakin, ryanodine receptor 2, desmocollin-2, desmoglein-2, and SCN5A variants among the most commonly mutated genes. The overlap between DCM, hypertrophic cardiomyopathy (HCM), and channelopathy causing mutations is considerably high. Of note, we find that >38% of patients have compound or combined mutations and 12.8% have three or even more mutations. When comparing patients recruited in the eight participating European countries we find remarkably little differences in mutation frequencies and affected genes. Conclusion: This is to our knowledge, the first study that comprehensively investigated the genetics of DCM in a large-scale cohort and across a broad gene panel of the known DCM genes. Our results underline the high analytical quality and feasibility of Next-Generation Sequencing in clinical genetic diagnostics and provide a sound database of the genetic causes of DCM.
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