Abdelrahman, A., Kumstel, S., Zhang, X. et al. 2019. A novel multi-parametric analysis of non-invasive methods to assess animal distress during chronic pancreatitis. Scientific Reports 9, 14084.

Ethical responsibility, legal requirements and the need to improve the quality of research create a growing interest in the welfare of laboratory animals. Judging the welfare of animals requires readout parameters, which are valid and sensitive as well as specific to assess distress after different interventions. In the present study, we evaluated the sensitivity and specificity of different non-invasive parameters (body weight change, faecal corticosterone metabolites concentration, burrowing and nesting activity) by receiver operating characteristic curves and judged the merit of a multi-parametric analysis by logistic regression. Chronic pancreatitis as well as laparotomy caused significant changes in all parameters. However, the accuracy of these parameters was different between the two animal models. In both animal models, the multi-parametric analysis relying on all the readout parameters had the highest accuracy when predicting distress. This multi-parametric analysis revealed that C57BL/6 mice during the course of chronic pancreatitis often experienced less distress than mice after laparotomy. Interestingly these data also suggest that distress does not steadily increase during chronic pancreatitis. In conclusion, combining these non-invasive methods for severity assessment represents a reliable approach to evaluate animal distress in models such as chronic pancreatitis.