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Simple Summary: Facial expression (FE) has been used for pain diagnosis in horses. The current study aimed to identify pain in horses undergoing under-skin polylactide-based polymer implantation. Five statistical methods for analyzing FE were used, including conventional and new approaches. First, we scored the seven FEs separately. Subsequently, the scores of the seven FEs were added (SUM). Subsequently, principal component analysis (PCoA) was performed using the scores of the seven FEs obtained using the first method. Afterwards, weights were created for each FE based on each variable's contribution variability obtained from the PCoA (SUM.W). Finally, we applied a general score to the animal's face (GFS). The horses were filmed before and 24 and 48 h after implantation. The tissue sensitivity to mechanical stimulation and skin temperature of the horses were assessed at the same time points. The results show no changes in the FEs analyzed separately or jointly. The horses with incision and suture but no polymer implant displayed a higher pain-related FE 48 h after implantation, while the horses implanted with polymers displayed more apparent alterations in the mechanical skin sensitivity and temperature. Our findings show that the five statistical methods used to analyze the faces of the horses were not able to detect low-grade inflammatory pain. Facial-expression-based analysis has been widely applied as a pain coding system in horses. Herein, we aimed to identify pain in horses undergoing subcutaneously polylactide-based polymer implantation. The sham group was submitted only to surgical incision. The horses were filmed before and 24 and 48 h after implantation. Five statistical methods for evaluating their facial expressions (FEs) were tested. Primarily, three levels of scores (0, 1, and 2) were applied to the seven FEs (ear movements, eyebrow tension, orbicularis tension, dilated nostrils, eye opening, muzzle tension, and masticatory muscles tension). Subsequently, the scores of the seven FEs were added (SUM). Afterwards, principal component analysis (PCoA) was performed using the scores of the seven FEs obtained using the first method. Subsequently, weights were created for each FE, based on each variable's contribution variability obtained from the PCoA (SUM.W). Lastly, we applied a general score (GFS) to the animal's face (0 = without pain; 1 = moderate pain; 2 = severe pain). The mechanical nociceptive threshold (MNT) and cutaneous temperature (CT) values were collected at the same moments. The results show no intra- or intergroup differences, when evaluating each FE separately or in the GFS. In the intragroup comparison and 48 h after implantation, the control group showed higher values for SUM, PCoA, and SUM.W, although the horses implanted with polymers displayed more obvious alterations in the CT and MNT. Our findings show that the five statistical strategies used to analyze the faces of the horses were not able to detect low-grade inflammatory pain. [ABSTRACT FROM AUTHOR]

Background. Pain is the leading cause of animal suffering, hence the importance of validated tools to ensure its appropriate evaluation and treatment. We aimed to test the psychometric properties of the short form of the Unesp-Botucatu Feline Pain Scale (UFEPS-SF) in eight languages. Methods. The original scale was condensed from ten to four items. The content validation was performed by five specialists in veterinary anesthesia and analgesia. The English version of the scale was translated and back-translated into Chinese, French, German, Italian, Japanese, Portuguese and Spanish by fluent English and native speaker translators. Videos of the perioperative period of 30 cats submitted to ovariohysterectomy (preoperative, after surgery, after rescue analgesia and 24 h after surgery) were randomly evaluated twice (one-month interval) by one evaluator for each language unaware of the pain condition. After watching each video, the evaluators scored the unidimensional, UFEPS-SF and Glasgow composite multidimensional feline pain scales. Statistical analyses were carried out using R software for intra and interobserver reliability, principal component analysis, criteria concurrent and predictive validities, construct validity, item-total correlation, internal consistency, specificity, sensitivity, the definition of the intervention score for rescue analgesia and diagnostic uncertainty zone, according to the receiver operating characteristic (ROC) curve. Results. UFEPS-SF intra- and inter-observer reliability were -0.92 and 0.84, respectively, for all observers. According to the principal component analysis, UFEPS-SF is a unidimensional scale. Concurrent criterion validity was confirmed by the high correlation between UFEPS-SF and all other scales (-0.9). The total score and all items of UFEPS-SF increased after surgery (pain), decreased to baseline after analgesia and were intermediate at 24 h after surgery (moderate pain), confirming responsiveness and construct validity. Item total correlation of each item (0.68-0.83) confirmed that the items contributed homogeneously to the total score. Internal consistency was excellent (-0.9) for all items. Both specificity (baseline) and sensitivity (after surgery) based on the Youden index was 99% (97-100%). The suggestive cut-off score for the administration of analgesia according to the ROC curve was -4 out of 12. The diagnostic uncertainty zone ranged from 3 to 4. The area under the curve of 0.99 indicated excellent discriminatory capacity of UFEPS-SF. Conclusions. The UFEPS-SF and its items, assessed by experienced evaluators, demonstrated very good repeatability and reproducibility, content, criterion and construct validities, item-total correlation, internal consistency, excellent sensitivity and specificity and a cut-off point indicating the need for rescue analgesia in Chinese, French, English, German, Italian, Japanese, Portuguese and Spanish. [ABSTRACT FROM AUTHOR]