A stitch in time saves nine: perceptions about colorectal cancer screening after a non-cancer colonoscopy result. Qualitative study

Objectives To explore perceptions of colorectal cancer (CRC) screening among participants who have experienced a 'false alarm' for CRC, and to explore perceptions about the relevance of screening for themselves or others. Methods Semi-structured interviews with screening participants who had participated in the Danish CRC screening program and experienced a 'false alarm' for colorectal cancer. A thematic analysis was performed, based on an interpretive tradition of ethnography. Results Perceptions about CRC screening after a non-cancer colonoscopy result were characterized by trust in the colonoscopy result showing no CRC, and satisfaction with the screening offer despite the risk for 'false alarm'. The patient-involving behavior of the healthcare professionals during the examination was for most participants a cornerstone for trusting the validity of the colonoscopy result showing no CRC. Strong notions about perceived obligation to participate in screening were common. Conclusions Prominent themes were trust in the result, satisfaction with the procedure, and moral obligations to participate both for themselves and for others. Practice implications Information to future invitees after a 'false alarm' experience could build on peoples' trust in the validity of a previous non-cancer result and should underscore the importance of subsequent screening even after a 'false alarm' for cancer

Effect of transportation and social isolation on facial expressions of healthy horses

Horses have the ability to generate a remarkable repertoire of facial expressions, some of which have been linked to the affective component of pain. This study describes the facial expressions in healthy horses free of pain before and during transportation and social isolation, which are putatively stressful but ordinary management procedures. Transportation was performed in 28 horses by subjecting them to short-term road transport in a horse trailer. A subgroup (n = 10) of these horses was also subjected to short-term social isolation. During all procedures, a body-mounted, remote-controlled heart rate monitor provided continuous heart rate measurements. The horses' heads were video-recorded during the interventions. An exhaustive dataset was generated from the selected video clips of all possible facial action units and action descriptors, time of emergency, duration, and frequency according to the Equine Facial Action Coding System (EquiFACS). Heart rate increased during both interventions (p<0.01), confirming that they caused disruption in sympato-vagal balance. Using the current method for ascribing certain action units (AUs) to specific emotional states in humans and a novel data-driven co-occurrence method, the following facial traits were observed during both interventions: eye white increase (p<0.001), nostril dilator (p<0.001), upper eyelid raiser (p<0.001), inner brow raiser (p = 0.042), tongue show (p<0.001). Increases in 'ear flicker' (p<0.001) and blink frequency (p<0.001) were also seen. These facial actions were used to train a machine-learning classifier to discriminate between the high-arousal interventions and calm horses, which achieved at most 79% accuracy. Most facial features identified correspond well with previous findings on behaviors of stressed horses, for example flared nostrils, repetitive mouth behaviors, increased eye white, tongue show, and ear movements. Several features identified in this study of pain-free horses, such as dilated nostrils, eye white increase, and inner brow raiser, are used as indicators of pain in some face-based pain assessment tools. In order to increase performance parameters in pain assessment tools, the relations between facial expressions of stress and pain should be studied further

Predictive Modeling of Equine Activity Budgets Using a 3D Skeleton Reconstructed from Surveillance Recordings

In this work, we present a pipeline to reconstruct the 3D pose of a horse from 4 simultaneous surveillance camera recordings. Our environment poses interesting challenges to tackle, such as limited field view of the cameras and a relatively closed and small environment. The pipeline consists of training a 2D markerless pose estimation model to work on every viewpoint, then applying it to the videos and performing triangulation. We present numerical evaluation of the results (error analysis), as well as show the utility of the achieved poses in downstream tasks of selected behavioral predictions. Our analysis of the predictive model for equine behavior showed a bias towards pain-induced horses, which aligns with our understanding of how behavior varies across painful and healthy subjects.Comment: 3rd Workshop on CV4Animals: Computer Vision for Animal Behavior Tracking and Modeling (in conjunction with CVPR 2023) [POSTER

Changes in the equine facial repertoire during different orthopedic pain intensities

A number of facial expressions are associated with pain in horses, however, the entire display of facial activities during orthopedic pain have yet to be described. The aim of the present study was to exhaustively map changes in facial activities in eight resting horses during a progression from sound to mild and moderate degree of orthopedic pain, induced by lipopolysaccharides (LPS) administered in the tarsocrural joint. Lameness progression and regression was measured by objective gait analysis during movement, and facial activities were described by EquiFACS in video sequences (n = 348, total length 892.5 min) of the horses obtained when resting in their box stalls. Predictive modeling identified 16 action units and action descriptors, related to ears, eyes, and lower face. Lower lip depressor (AU16), lips part (AU25), half blink (AU47), single ear forward (SEAD101) and single ear rotator (SEAD104) were selected as co-occurring significantly more in horses with pain than in horses without pain. The major change in co-occurring facial activities occurred in the transition from no pain to mild pain. In conclusion, resting horses with induced orthopedic pain showed a dynamic upper and lower facial repertoire and the relationship between level of pain intensity and facial activity appears complex

In vivo joint synovial fluid disposition of a novel sustained-release formulation of diclofenac and hyaluronic acid in horses

Intra-articular administration of sustained-release anti-inflammatory drugs is indicated in horses suffering from joint inflammation, but no such drugs are labelled for veterinary use. To obtain initial data on synovial disposition and safety of a new sustained-release formulation of diclofenac (SYN321) in the joints of horses, an experimental interventional study of elimination and side effects of intra-articular administration of SYN321 was conducted. Nine clinically sound horses were included in the study, and SYN321 was administered by the intra-articular route. Dose ranges and sampling intervals were established in a pilot study with two horses, and then applied in a main study involving seven horses treated in the fetlock joint. Diclofenac was detected above lower limit of quantification (LOQ: 0.5 ng/ml) in synovial fluid throughout the study period (14 days), and below LOQ (0.1 ng/ml) in plasma after 4 days and in urine after 14 days. No obvious clinical side effects were detected. Clinical examination and objective lameness evaluation suggested that SYN321 has potential as a local joint NSAID treatment with sustained release in horses, but further studies on synovial fluid exposure, safety and clinical efficacy are warranted

Dynamics are Important for the Recognition of Equine Pain in Video

A prerequisite to successfully alleviate pain in animals is to recognize it, which is a great challenge in non-verbal species. Furthermore, prey animals such as horses tend to hide their pain. In this study, we propose a deep recurrent two-stream architecture for the task of distinguishing pain from non-pain in videos of horses. Different models are evaluated on a unique dataset showing horses under controlled trials with moderate pain induction, which has been presented in earlier work. Sequential models are experimentally compared to single-frame models, showing the importance of the temporal dimension of the data, and are benchmarked against a veterinary expert classification of the data. We additionally perform baseline comparisons with generalized versions of state-of-the-art human pain recognition methods. While equine pain detection in machine learning is a novel field, our results surpass veterinary expert performance and outperform pain detection results reported for other larger non-human species.Comment: CVPR 2019: IEEE Conference on Computer Vision and Pattern Recognitio