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Simple Summary: Pain in animals is assessed by behavioral alterations presented on scales. We aimed to validate the CMPS-SF according to the COSMIN and GRADE guidelines, used to assess the validity and reliability of health instruments. Four trained evaluators assessed 208 videos in four periods (pre-operative, peak of pain, 1 h after peak of pain and analgesia, and 24 h after surgery) of 52 dogs, divided into negative control (animals without pain), soft tissue surgeries, and orthopedic surgeries. The videos were evaluated in two stages, with intervals of 21 days. The CMPS-SF is a unidimensional scale with good reliability both intra-observer and between different observers, and it showed a strong correlation with other scales. Pain scores were higher after than before surgery, reduced after analgesia, and reduced even further after 24 h, which demonstrates its responsiveness. Postoperative pain scores were higher in dogs undergoing surgery versus controls. The scale is homogeneous, and there is a good interrelationship between its items. The detection values for dogs truly with and without pain were 74–83% and 78–87%, respectively. The score for indicating analgesia was ≥5 and the GRADE classification was high, confirming the validity of the scale. We aimed to validate the CMPS-SF according to COSMIN and GRADE guidelines. Four trained evaluators assessed 208 videos (pre-operative-M1, peak of pain-M2, 1 h after the peak of pain and analgesia (rescue)-M3, and 24 h post-extubation-M4) of 52 dogs, divided into negative controls (n = 10), soft tissue surgeries (n = 22), and orthopedic surgeries (n = 20). The videos were randomized and blinded as to when they were filmed, and were evaluated in two stages, 21 days apart. According to confirmatory analysis, the CMPS-SF is a unidimensional scale. Intra-observer reliability was between 0.80 and 0.99 and inter-observer reliability between 0.73 and 0.86. Criterion validity was confirmed by the correlation between the CMPS-SF and other unidimensional scales (≥0.7). The differences between the scores were M2 ≥ M3 > M4 > M1 (responsiveness), and the scale presented construct validity (higher postoperative pain scores in dogs undergoing surgery versus control). Internal consistency was 0.7 (Cronbach's α) and 0.77 (McDonald's ω), and the item-total correlation was between 0.3 and 0.7, except for "A(ii)—Attention to wound". Specificity and sensitivity were 78–87% and 74–83%, respectively. The cut-off point for rescue analgesia was ≥5 or ≥4 excluding item B(iii) mobility, and the GRADE classification was high, confirming the validity of the scale. [ABSTRACT FROM AUTHOR]

Despite the wide range of uses of rabbits (Oryctolagus cuniculus) as experimental models for pain, as well as their increasing popularity as pets, pain assessment in rabbits is understudied. This study is the first to address automated detection of acute postoperative pain in rabbits. Using a dataset of video footage of n = 28 rabbits before (no pain) and after surgery (pain), we present an AI model for pain recognition using both the facial area and the body posture and reaching accuracy of above 87%. We apply a combination of 1 sec interval sampling with the Grayscale Short-Term stacking (GrayST) to incorporate temporal information for video classification at frame level and a frame selection technique to better exploit the availability of video data. [ABSTRACT FROM AUTHOR]