Factors affecting mechanical (nociceptive) thresholds in piglets.

OBJECTIVE

To evaluate the stability and repeatability of measures of mechanical (nociceptive) thresholds in piglets and to examine potentially confounding factors when using a hand held algometer.

STUDY DESIGN

Descriptive, prospective cohort.

ANIMALS

Forty-four piglets from four litters, weighing 4.6 ± 1.0 kg (mean ± SD) at 2 weeks of age.

METHODS

Mechanical thresholds were measured twice on each of 2 days during the first and second week of life. Data were analyzed using a repeated measures design to test the effects of behavior prior to testing, sex, week, day within week, and repetition within day. The effect of body weight and the interaction between piglet weight and behaviour were also tested. Piglet was entered into the model as a random effect as an additional test of repeatability. The effect of repeated testing was used to test the stability of measures. Pearson correlations between repeated measures were used to test the repeatability of measures. Variance component analysis was used to describe the variability in the data.

RESULTS

Variance component analysis indicated that piglet explained only 17% of the variance in the data. All variables in the model (behaviour prior to testing, sex, week, day within week, repetition within day, body weight, the interaction between body weight and behaviour, piglet identity) except sex had a significant effect (p < 0.04 for all). Correlations between repeated measures increased from the first to the second week.

CONCLUSIONS AND CLINICAL RELEVANCE

Repeatability was acceptable only during the second week of testing and measures changed with repeated testing and increased with increasing piglet weight, indicating that time (age) and animal body weight should be taken into account when measuring mechanical (nociceptive) thresholds in piglets. Mechanical (nociceptive) thresholds can be used both for testing the efficacy of anaesthetics and analgesics, and for assessing hyperalgesia in chronic pain states in research and clinical settings.