Elbow injuries constitute a sizeable percentage of tennis injuries. A basic understanding of biomechanics of tennis and analysis of the forces, loads and motions of the elbow during tennis will improve the understanding of the pathophysiology of these injuries. All different strokes in tennis have a different repetitive biomechanical nature that can result in tennis-related injuries. In this article, a biomechanically-based evaluation of tennis strokes is presented. This overview includes all tennis-related pathologies of the elbow joint, whereby the possible relation of biomechanics to pathology is analysed, followed by treatment recommendations.

BackgroundKnee osteoarthritis (KOA) is a heterogenous disease, meaning individuals can present with various signs and symptoms related to different biopsychosocial (BPS) factors[1,2]. Several phenotypes can as such be expected. Phenotyping KOA patients, specifically those awaiting total knee arthroplasty (TKA), could be relevant, because a substantial part of patients (20%) reports chronic post-TKA pain[3]. Various preoperative phenotypic factors related to domains of the BPS model have been described, but consensus and a classification of patients based on these factors is still lacking[4–7].ObjectivesThe aim of this exploratory study is to identify phenotypes based on BPS related factors in KOA patients awaiting TKA.MethodsParticipants were included if they were diagnosed with KOA and waiting for TKA surgery in one of the four participating hospitals in Belgium and the Netherlands. A cross-sectional latent profile analysis was conducted in MPlus[8]containing the grade of KOA before TKA surgery (structural variable); body mass index and glycated hemoglobin value (metabolic variables); isometric strength of m. Quadriceps and m. Hamstrings of the affected leg, proprioceptive accuracy of the affected leg, and physical function (functional variables); pain intensity scores and symptoms related to altered somatosensory processing (pain-related variables); pain catastrophizing, depression, anxiety symptoms, expectations and satisfaction (psychological variables); and work and education level (social variables). Data were checked for multicollinearity and multivariate outliers. The ideal model was chosen based on qualitative evaluation, goodness of fit and classification uncertainty.Results224 participants were included of which 109 women (65.19 +/- 8.18 years old) and 108 men (66.92 +/- 7.18 years old). A model with 2 phenotypes was found to be most appropriate. Both phenotypes differed in 13 out of 19 continuous variables. Phenotype 1 (72% of all participants) was characterized by scoring better on at least one of all metabolic, functional, psychological and pain-related continuous variables compared to phenotype 2 (28% of all participants), except for glycated hemoglobin value, proprioception, expectations, and widespread temporal summation and conditioned pain modulation (part of somatosensory processing variables). Concerning categorical variables, phenotype 1 (72%) was characterized by having a lower probability to have a Kellgren & Lawrence (K&L) scale 2 compared with patients in phenotype 2 (28%). The probabilities of the other categorical variables did not differ between the two phenotypes.ConclusionA model with 2 phenotypes in KOA patients awaiting TKA appeared the most appropriate, which confirmed the existence of a group that experiences disturbed somatosensory processing signs in combination with worse results on psychological (pain catastrophizing, fear and depression), functional (strength and physical function), structural (higher possibility to have a K&L grade 2 compared to the other phenotype) and metabolic factors (body mass index), and a group that does not present this disruption in combination with better results on the aforementioned BPS factors. Further research is necessary and should also investigate if different phenotypes react differently regarding treatment outcome after TKA.References[1]Dell’Isola, A. et al. PLoS One 13, e0191045 (2018)[2]Bierma-Zeinstra, S. M. A. et al. Arthritis Res. Ther. 13, 213 (2011)[3]Sayah, S. M. et al. J. Arthroplasty 36, 3993-4002.e37 (2021)[4]Baert, I. A. et al. Osteoarthritis Cartilage 24, 213–23 (2016)[5]Wylde, V. et al. BMJ Open 7, e018105 (2017)[6]Petersen, K. K.-S. Scand. J. Pain (2022)[7]Laferton, J. A. C. et al. Health Psychol. Rev. 16, 50–66 (2022)[8]Muthén, L. K., et al. (2017)Figure 1.Acknowledgements:NIL.Disclosure of InterestsSophie Vervullens: None declared, Lotte Meert: None declared, Gavin Van der Nest: None declared, Jonas Verbrugghe: None declared, Peter Verdonk: None declared, Frank Rahussen: None declared, Rob Smeets Grant/research support from: Global Awards for Advancing Chronic Pain Research (ADVANCE) 2021 ID#70107413 --> However not used for this study., Mira Meeus: None declared.