Statistical tools to improve assessing agreement between several observers

In the context of assessing the impact of management and environmental factors on animal health, behaviour or performance it has become increasingly important to conduct (epidemiological) studies in the field. Hence, the number of investigated farms per study is considerably high so that numerous observers are needed for investigation. In order to maintain the quality and validity of study results calibration meetings where observers are trained and the current level of agreement is assessed have to be conducted to minimise the observer effect. When study animals were rated independently by the same observers by a categorical variable the exclusion test can be performed to identify disagreeing observers. This statistical test compares for each variable and each observer the observer-specific agreement with the overall agreement among all observers based on kappa coefficients. It accounts for two major challenges, namely the absence of a gold-standard observer and different data type comprising ordinal, nominal and binary data. The presented methods are applied on a reliability study to assess the agreement among eight observers rating welfare parameters of laying hens. The degree to which the observers agreed depended on the investigated item (global weighted kappa coefficients: 0.37 to 0.94). The proposed method and graphical description served to assess the direction and degree to which an observer deviates from the others. It is suggested to further improve studies with numerous observers by conducting calibration meetings and accounting for observer bias

Diabetic retinopathy and diabetic kidney disease, either isolated or associated, impact on the 10-year risk of cardiovascular disease: are we dealing with similar conditions?

Abstract Objective: To evaluate the association between diabetic retinopathy, diabetic kidney disease, and the 10-year risk of atherosclerotic cardiovascular disease in patients with diabetes. Subjects and methods: A cross-sectional study was performed involving patients diagnosed with either type 1 or type 2 diabetes mellitus. Participants were classified into four groups: DM (patients without diabetes-related complications), DR (patients with diabetic retinopathy only), DKD (patients with diabetic kidney disease only), and DR + DKD (patients with both diabetic retinopathy and diabetic kidney disease). The primary outcome was the 10-year risk assessment for cardiovascular events, calculated using the American Heart Association’s atherosclerotic cardiovascular disease score. Results: A total of 571 patients were selected including 128 with type 1 diabetes (average age of 39.4 ± 15.1 years; 48.4% female) and 443 with type 2 diabetes (average age of 59.5 ± 11.9 years; 66.4% female). Among the participants with type 2 diabetes, the cardiovascular risk was 15.2 ± 14.6% for the DM group, 15.7 ± 10.7% for the DR group, 22.5 ± 16.7% for the DKD group, and 21.5 ± 15.1% for the DR + DKD group, reflecting a significantly higher cardiovascular risk in the groups with renal involvement (P <0.001). For those with type 1 diabetes, the DM group had a risk of 6.1 ± 8.9%, the DR group 8.9 ±11.8%, the DKD group 5.4 ± 8.8%, and the DR + DKD group 6.1 ± 9.5%. The mean difference in risk between the groups was not statistically significant. Conclusion: In patients with type 2 diabetes, those with diabetic kidney disease appeared to have a higher theoretical risk of cardiovascular disease compared to those with only diabetic retinopathy