An Update on Drugs Used for Lumbosacral Epidural Anesthesia and Analgesia in Dogs

This review aims to report an update on drugs administered into the epidural space for anesthesia and analgesia in dogs, describing their potential advantages and disadvantages in the clinical setting. Databases searched include Pubmed, Google scholar, and CAB abstracts. Benefits of administering local anesthetics, opioids, and alpha2 agonists into the epidural space include the use of lower doses of general anesthetics (anesthetic “sparing” effect), perioperative analgesia, and reduced side effects associated with systemic administration of drugs. However, the potential for cardiorespiratory compromise, neurotoxicity, and other adverse effects should be considered when using the epidural route of administration. When these variables are considered, the epidural technique is useful as a complementary method of anesthesia for preventive and postoperative analgesia and/or as part of a balanced anesthesia technique

Comparison of Pharmacopuncture, Aquapuncture and Acepromazine for Sedation of Horses

Pharmacopuncture, the injection of subclinical doses of drugs into acupoints reduces drug undesirable side effects, residues in animal consumption products and treatment costs in large animals. Acepromazine (Acp) produces several undesirable effects, such as hypotension. Previous studies with the injection of 1/10 of Acp dose in dog acupoints showed its advantage for sedation, minimizing undesirable effects. Eight horses were randomly submitted to four different treatment protocols according to a Latin Square double-blind design: (i) 0.1 ml kg−1 of saline subcutaneously injected at the cervical region, (ii) 0.1 mg kg−1 of Acp injected subcutaneously at the cervical region, (iii) 0.01 ml kg−1 of saline injected into GV1 acupoint (aquapuncture) and (iv) 0.01 mg kg−1 of Acp injected into GV1 acupoint (pharmacopuncture). Heart rate, respiratory rate, head height and degree of sedation were measured before and at 30, 60 and 90 min after treatments. Signs of sedation were observed in all treated groups at 30 min and only in 1/10Acp-GV1 at 60 min after the treatments. Only the group treated with 0.1 mg kg−1 of Acp s.c. had significantly lower values of head height at 30 min. Respiratory rate tended to reduce in all groups but was significantly lower only in horses treated with 0.1 mg kg−1 of Acp s.c. Heart rate remained unchanged in all groups. Acp-pharmacopuncture on GV1 in horses produced a mild sedation when compared with the conventional dose of Acp. More investigations are necessary to determine the optimal dosage of Acp-pharmacopuncture for sedation in horses

Deep learning for video-based automated pain recognition in rabbits

Abstract 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

Reliability and Validity of UNESP-Botucatu Cattle Pain Scale and Cow Pain Scale in Bos taurus and Bos indicus Bulls to Assess Postoperative Pain of Surgical Orchiectomy

Pain assessment guides decision-making in pain management and improves animal welfare. We aimed to investigate the reliability and validity of the UNESP-Botucatu cattle pain scale (UCAPS) and the cow pain scale (CPS) for postoperative pain assessment in Bos taurus (Angus) and Bos indicus (Nelore) bulls after castration. Methods: Ten Nelore and nine Angus bulls were anaesthetised with xylazine–ketamine–diazepam–isoflurane–flunixin meglumine. Three-minute videos were recorded at -48 h, preoperative, after surgery, after rescue analgesia and at 24 h. Two evaluators assessed 95 randomised videos twice one month apart. Results: There were no significant differences in the pain scores between breeds. Intra and inter-rater reliability varied from good (>0.70) to very good (>0.81) for all scales. The criterion validity showed a strong correlation (0.76–0.78) between the numerical rating scale and VAS versus UCAPS and CPS, and between UCAPS and CPS (0.76). The UCAPS and CPS were responsive; all items and total scores increased after surgery. Both scales were specific (81–85%) and sensitive (82–87%). The cut-off point for rescue analgesia was >4 for UCAPS and >3 for CPS. Conclusions. The UCAPS and CPS are valid and reliable to assess postoperative pain in Bos taurus and Bos indicus bulls

Explainable automated pain recognition in cats

Abstract Manual tools for pain assessment from facial expressions have been suggested and validated for several animal species. However, facial expression analysis performed by humans is prone to subjectivity and bias, and in many cases also requires special expertise and training. This has led to an increasing body of work on automated pain recognition, which has been addressed for several species, including cats. Even for experts, cats are a notoriously challenging species for pain assessment. A previous study compared two approaches to automated ‘pain’/‘no pain’ classification from cat facial images: a deep learning approach, and an approach based on manually annotated geometric landmarks, reaching comparable accuracy results. However, the study included a very homogeneous dataset of cats and thus further research to study generalizability of pain recognition to more realistic settings is required. This study addresses the question of whether AI models can classify ‘pain’/‘no pain’ in cats in a more realistic (multi-breed, multi-sex) setting using a more heterogeneous and thus potentially ‘noisy’ dataset of 84 client-owned cats. Cats were a convenience sample presented to the Department of Small Animal Medicine and Surgery of the University of Veterinary Medicine Hannover and included individuals of different breeds, ages, sex, and with varying medical conditions/medical histories. Cats were scored by veterinary experts using the Glasgow composite measure pain scale in combination with the well-documented and comprehensive clinical history of those patients; the scoring was then used for training AI models using two different approaches. We show that in this context the landmark-based approach performs better, reaching accuracy above 77% in pain detection as opposed to only above 65% reached by the deep learning approach. Furthermore, we investigated the explainability of such machine recognition in terms of identifying facial features that are important for the machine, revealing that the region of nose and mouth seems more important for machine pain classification, while the region of ears is less important, with these findings being consistent across the models and techniques studied here