Background: Study protocols involving experimental animals often require the monitoring of different parameters not only in anesthetized, but also in free moving animals. Most animal research involves small rodents, in which continuously monitoring parameters such as temperature and heart rate is very stressful for the awake animals or simply not possible. Aim of the underlying study was to monitor heart rate, temperature and activity and to assess inflammation in the heart, lungs, liver and kidney in the early postoperative phase after experimental cardiopulmonary bypass involving 45 min of deep hypothermic circulatory arrest in rats. Besides continuous monitoring of heart rate, temperature and behavioural activity, the main focus was on avoiding uncontrolled death of an animal in the early postoperative phase in order to harvest relevant organs before autolysis would render them unsuitable for the assessment of inflammation.
Findings: We therefore set up a telemetry-based system (Data Science International, DSI™) that continuously monitored the rat's temperature, heart rate and activity in their cages. The data collection using telemetry was combined with an analysis software (Microsoft excel™), a webmail application (GMX) and a text message-service. Whenever an animal's heart rate dropped below the pre-defined threshold of 150 beats per minute (bpm), a notification in the form of a text message was automatically sent to the experimenter's mobile phone. With a positive predictive value of 93.1% and a negative predictive value of 90.5%, the designed surveillance and alarm system proved a reliable and inexpensive tool to avoid uncontrolled death in order to minimize suffering and harvest relevant organs before autolysis would set in.
Conclusions: This combination of a telemetry-based system and software tools provided us with a reliable notification system of imminent death. The system's high positive predictive value helped to avoid uncontrolled death and facilitated timely organ harvesting. Additionally we were able to markedly reduce the drop out rate of experimental animals, and therefore the total number of animals used in our study. This system can be easily adapted to different study designs and prove a helpful tool to relieve stress and more importantly help to reduce animal numbers.