Histological validation of a type 1 diabetes clinical diagnostic model for classification of diabetes

AIMS

Misclassification of diabetes is common due to an overlap in the clinical features of type 1 and type 2 diabetes. Combined diagnostic models incorporating clinical and biomarker information have recently been developed that can aid classification, but they have not been validated using pancreatic pathology. We evaluated a clinical diagnostic model against histologically defined type 1 diabetes.

METHODS

We classified cases from the Network for Pancreatic Organ donors with Diabetes (nPOD) biobank as type 1 (n = 111) or non-type 1 (n = 42) diabetes using histopathology. Type 1 diabetes was defined by lobular loss of insulin-containing islets along with multiple insulin-deficient islets. We assessed the discriminative performance of previously described type 1 diabetes diagnostic models, based on clinical features (age at diagnosis, BMI) and biomarker data [autoantibodies, type 1 diabetes genetic risk score (T1D-GRS)], and singular features for identifying type 1 diabetes by the area under the curve of the receiver operator characteristic (AUC-ROC).

RESULTS

Diagnostic models validated well against histologically defined type 1 diabetes. The model combining clinical features, islet autoantibodies and T1D-GRS was strongly discriminative of type 1 diabetes, and performed better than clinical features alone (AUC-ROC 0.97 vs. 0.95; P = 0.03). Histological classification of type 1 diabetes was concordant with serum C-peptide [median < 17 pmol/l (limit of detection) vs. 1037 pmol/l in non-type 1 diabetes; P < 0.0001].

CONCLUSIONS

Our study provides robust histological evidence that a clinical diagnostic model, combining clinical features and biomarkers, could improve diabetes classification. Our study also provides reassurance that a C-peptide-based definition of type 1 diabetes is an appropriate surrogate outcome that can be used in large clinical studies where histological definition is impossible. Parts of this study were presented in abstract form at the Network for Pancreatic Organ Donors Conference, Florida, USA, 19-22 February 2019 and Diabetes UK Professional Conference, Liverpool, UK, 6-8 March 2019.

Participatory approach for the identification of dairy industry needs inthe design of research, development and extension actions: Australianand Brazilian case studies

In both Australia and Brazil there are rapid changes occurring in the macroenvironment of the dairy industry. These changes are sometimes not noticed in the microenvironment of the farm, due to the labour-intensive nature of family farms, and the traditionally weak links between production and marketing. Trends in the external environment need to be discussed in a cooperative framework, to plan integrated actions for the dairy community as a whole and to demand actions from research, development and extension (R, D & E). This paper reviews the evolution of R, D & E in terms of paradigms and approaches, the present strategies used to identify dairy industry needs in Australia and Brazil, and presents a participatory strategy to design R, D & E actions for both countries. The strategy incorporates an integration of the opinions of key industry actors (defined as members of the dairy and associated communities), especially farm suppliers (input market), farmers, R, D & E people, milk processors and credit providers. The strategy also uses case studies with farm stays, snowball interviewing techniques, semi-structured interviews, content analysis, focus group meetings, and feedback analysis, to refine the priorities for R, D & E actions in the region.

Ground-Based Monitoring: a Process of Learning by Doing

Rangeland monitoring using ground-based methods has been presented as a major instrument in the management of rangelands. Yet there are some doubts about its utility as a stand-alone tool in providing reliable, objective evidence on range trend. If the technology is to have relevance in rangeland management at the landholder level, stronger recognition and direction is required for other, potentially important roles, that contribute to the development of knowledge applied to management. This position recognises landholders' primary responsibility for day-to-day decisions in rangeland management. Decision-making, adult learning, action-research and ecosystem management principles are drawn on to propose and advocate two separate but complementary roles for ground-based monitoring. Firstly, in a learning role, landholders' capture and use of ground-based monitoring data can develop and enhance the managerial knowledge and skill applied to their decisions. Secondly, in a decision supporting role, there is the interpretation of range trend from ground-based range monitoring data and the incorporation of that information into management decisions at tactical and strategic levels. Using a collaborative approach to system development and support, this blend of 'soft' and 'hard' technologies can combine in a process of 'learning by doing' that will enhance the quality of management applied in the rangelands.

A survey of pet owner views of veterinarians in Brisbane environs - a behavioral approach

Three hundred and thirty-seven pet owners were interviewed by final-year veterinary students from the University of Queensland, using a questionnaire prepared by the authors. The survey area included Brisbane city and suburbs and was conducted in 1977. The majority of respondents (52.5%) reported that the pets were owned by the family, while 24.6% claimed that pets were owned by individual adults only. Dogs and cats were the most popular pets. Of the respondents sampled, 51% changed their veterinarian while 46% reported that they had not changed their veterinarian. Satisfaction with the service, nearness of the service and personal liking were the major reasons for continuing to use the same veterinary surgeon. Nearly 40% of respondents used the veterinary service on the basis of recommendation of friends, relatives and other people who owned similar types of pets. According to the respondents, major qualities for a good veterinarian are: competence and knowledge (86.9%), compassion for animals (61.7%), professional approach (which includes good listening and explanation, the instillation of confidence, integrity and appearance) (57.4%), regard for owners and their feelings (46.3%), good surgery conditions (14.2%) and reasonable fees (12.8%). While professional competence was reported as one of the important qualities of a good veterinary service, the majority (51%) of them disagreed with the statement that professional competence is the only thing that matters in the care of pets and many other social and interpersonal factors influenced their attitude towards the veterinary service. The application of behavioural sciences to the veterinary profession is discussed.