Identifying recovery trajectories following primary total shoulder arthroplasty: a cohort study of 3,358 patients from the Dutch Arthroplasty Register
DOI:
https://doi.org/10.2340/17453674.2025.43085Keywords:
Arthroplasty, ShoulderAbstract
Background and purpose: Some patients do not improve after total shoulder arthroplasty (TSA), indicating different recovery trajectories. We aimed to identify recovery trajectories after TSA based on the Oxford Shoulder Score (OSS). Second, we investigated whether recovery trajectories were associated with patient or procedure characteristics.
Methods: We included primary anatomical and reversed TSAs (ATSAs/RTSAs) for osteoarthritis (OA) or cuff arthropathy/rupture with preoperative, 3-month, and/or 12-month postoperative OSS, registered between 2016 and 2022 in the Dutch Arthroplasty Register (n = 3,358). We used latent class growth modeling (LCGM) to identify recovery patterns, and multinomial logistic regression analyses to investigate associations between potential risk factors and class membership (odds ratio [OR], 95% confidence interval [CI]).
Results: We identified 3 recovery patterns: “Fast responders” (59%), “Steady responders” (27%), and “Poor responders” (14%). Factors associated with “Steady responders” vs “Fast responders” were female vs male sex (OR 2.0, CI 1.5–2.7), ASA III–IV vs ASA I (OR 1.9, CI 1.2–3.1), Walch A1 vs B2 (OR 1.6, CI 1.1–2.5), and most vs medium socioeconomic deprivation (OR 1.4, CI 1.1–1.9). Factors associated with “Poor responders” vs “Fast responders” were ASA II vs ASA I (OR 2.0, CI 1.1–3.6), ASA III–IV vs ASA I (OR 3.0, CI 1.6–5.5), Walch A1 vs B2 (OR 2.1, CI 1.3–3.3), previous shoulder surgeries (OR 1.8, CI 1.3–2.4), most vs medium socioeconomic deprivation (OR 1.5, CI 1.2–2.0), RTSA for OA vs ATSA for OA (OR 1.8, CI 1.2–2.7), and RTSA for cuff arthropathy or rupture vs ATSA for OA (OR 2.3, CI 1.5–3.4).
Conclusion: 3 recovery trajectories were identified following TSA, which we labelled as “Fast responders,” “Steady responders,” and “Poor responders.” “Steady responders” and “Poor responders” were more likely to have higher ASA scores, a Walch A1 vs B2 classification, and greater vs medium socioeconomic deprivation than “Fast responders.” Moreover, “Steady responders” were more likely to be female, while “Poor responders” were more likely to have previous shoulder surgeries and RTSA for OA or for cuff arthropathy or rupture than “Fast responders.”
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Carter M J, Mikuls T R, Nayak S, Fehringer E V, Michaud K. Impact of total shoulder arthroplasty on generic and shoulder-specific health-related quality-of-life measures: a systematic literature review and meta-analysis. J Bone Joint Surg Am 2012; 94(17): e127. doi: 10.2106/JBJS.K.00204. DOI: https://doi.org/10.2106/JBJS.K.00204
Roberson T A, Bentley J C, Griscom J T, Kissenberth M J, Tolan S J, Hawkins R J, et al. Outcomes of total shoulder arthroplasty in patients younger than 65 years: a systematic review. J Shoulder Elbow Surg 2017; 26(7): 1298-306. doi: 10.1016/j.jse.2016.12.069. DOI: https://doi.org/10.1016/j.jse.2016.12.069
Bjornholdt K T, Brandsborg B, Soballe K, Nikolajsen L. Persistent pain is common 1–2 years after shoulder replacement. Acta Orthop 2015; 86(1): 71-7. doi: 10.3109/17453674.2014.987065. DOI: https://doi.org/10.3109/17453674.2014.987065
Auer C J, Glombiewski J A, Doering B K, Winkler A, Laferton J A, Broadbent E, et al. Patients’ expectations predict surgery outcomes: a meta-analysis. Int J Behav Med 2016; 23(1): 49-62. doi: 10.1007/s12529-015-9500-4. DOI: https://doi.org/10.1007/s12529-015-9500-4
Nagin D S, Odgers C L. Group-based trajectory modeling in clinical research. Annu Rev Clin Psychol 2010; 6: 109-38. doi: 10.1146/annurev.clinpsy.121208.131413. DOI: https://doi.org/10.1146/annurev.clinpsy.121208.131413
Hesseling B, Mathijssen N M C, van Steenbergen L N, Melles M, Vehmeijer S B W, Porsius J T. Fast starters, slow starters, and late dippers: trajectories of patient-reported outcomes after total hip arthroplasty: results from a Dutch nationwide database. J Bone Joint Surg Am 2019; 101(24): 2175-86. doi: 10.2106/JBJS.19.00234. DOI: https://doi.org/10.2106/JBJS.19.00234
van Egmond J C, Hesseling B, Melles M, Vehmeijer S B W, van Steenbergen L N, Mathijssen N M C, et al. Three distinct recovery patterns following primary total knee arthroplasty: Dutch arthroplasty register study of 809 patients. Knee Surg Sports Traumatol Arthrosc 2021; 29(2): 529-39. doi: 10.1007/s00167-020-05969-8. DOI: https://doi.org/10.1007/s00167-020-05969-8
Kuijpers M F L, Van Steenbergen L N, Schreurs B W, Hannink G. Patient-reported outcome of 95% of young patients improves after primary total hip arthroplasty: identification of 3 recovery trajectories in 3,207 patients younger than 55 years from the Dutch Arthroplasty Register. Acta Orthop 2022; 93: 560-7. doi: 10.2340/17453674.2022.3140. DOI: https://doi.org/10.2340/17453674.2022.3140
Rubenstein W J, Warwick H S L, Aung M S, Zhang A L, Feeley B T, Ma C B, et al. Defining recovery trajectories after shoulder arthroplasty: a latent class analysis of patient-reported outcomes. J Shoulder Elbow Surg 2021; 30(10): 2375-85. doi: 10.1016/j.jse.2021.02.024. DOI: https://doi.org/10.1016/j.jse.2021.02.024
LROI. Annual report 2024. Landelijke Registratie Orthopedische Interventies; 2024. Available from: https://www.lroi.nl/media/prqogokg/pdf-lroi-report-2024.pdf
Resnik L, Borgia M, Silver B, Cancio J. Systematic review of measures of impairment and activity limitation for persons with upper limb trauma and amputation. Arch Phys Med Rehabil 2017; 98(9): 1863-92 e14. doi: 10.1016/j.apmr.2017.01.015. DOI: https://doi.org/10.1016/j.apmr.2017.01.015
Ram N, Grimm K J. Growth mixture modeling: a method for identifying differences in longitudinal change among unobserved groups. Int J Behav Dev 2009; 33(6): 565-76. doi: 10.1177/0165025409343765. DOI: https://doi.org/10.1177/0165025409343765
Proust-Lima C, Saulnier T, Philipps V, Traon A P, Peran P, Rascol O, et al. Describing complex disease progression using joint latent class models for multivariate longitudinal markers and clinical endpoints. Stat Med 2023; 42(22): 3996-4014. doi: 10.1002/sim.9844. DOI: https://doi.org/10.1002/sim.9844
Bonsel J M, Reijman M, Verhaar J A N, van Steenbergen L N, Janssen M F, Bonsel G J. Socioeconomic inequalities in patient-reported outcome measures of Dutch primary hip and knee arthroplasty patients for osteoarthritis. Osteoarthritis Cartilage 2024; 32(2): 200-9. doi: 10.1016/j.joca.2023.07.004. DOI: https://doi.org/10.1016/j.joca.2023.07.004
Sahoo S, Entezari V, Ho J C, Jun B J, Cleveland Clinic Shoulder G, Jin Y, et al. Disease diagnosis and arthroplasty type are strongly associated with short-term postoperative patient-reported outcomes in patients undergoing primary total shoulder arthroplasty. J Shoulder Elbow Surg 2024; 33(6): e308-e21. doi: 10.1016/j.jse.2024.01.028. DOI: https://doi.org/10.1016/j.jse.2024.01.028
Ling D I, Schneider B, Ode G, Lai E Y, Gulotta L V. The impact of Charlson and Elixhauser comorbidities on patient outcomes following shoulder arthroplasty. Bone Joint J 2021; 103-B(5): 964-70. doi: 10.1302/0301-620X.103B5.BJJ-2020-1503.R1. DOI: https://doi.org/10.1302/0301-620X.103B5.BJJ-2020-1503.R1
Broekman M M, Brinkman N, Swanson D, Ring D, van den Bekerom M, Jawa A. Variations in 1-year trajectories of levels of pain and capability after shoulder arthroplasty are associated with baseline mental health. Clin Orthop Relat Res 2024; 482(3): 514-22. doi: 10.1097/CORR.0000000000002821. DOI: https://doi.org/10.1097/CORR.0000000000002821
Parsons M, Routman H D, Roche CP, Friedman R J. Patient-reported outcomes of reverse total shoulder arthroplasty: a comparative risk factor analysis of improved versus unimproved cases. JSES Open Access 2019; 3(3): 174-8. doi: 10.1016/j.jses.2019.07.004. DOI: https://doi.org/10.1016/j.jses.2019.07.004
Mahony G T, Werner B C, Chang B, Grawe B M, Taylor S A, Craig E V, et al. Risk factors for failing to achieve improvement after anatomic total shoulder arthroplasty for glenohumeral osteoarthritis. J Shoulder Elbow Surg 2018; 27(6): 968-75. doi: 10.1016/j.jse.2017.12.018. DOI: https://doi.org/10.1016/j.jse.2017.12.018
Friedman R J, Eichinger J, Schoch B, Wright T, Zuckerman J, Flurin P H, et al. Preoperative parameters that predict postoperative patient-reported outcome measures and range of motion with anatomic and reverse total shoulder arthroplasty. JSES Open Access 2019; 3(4): 266-72. doi: 10.1016/j.jses.2019.09.010. DOI: https://doi.org/10.1016/j.jses.2019.09.010
Baram A, Ammitzboell M, Brorson S, Olsen B S, Amundsen A, Rasmussen J V. What factors are associated with revision or worse patient-reported outcome after reverse shoulder arthroplasty for cuff-tear arthropathy? As from the Danish Shoulder Arthroplasty Registry. Clin Orthop Relat Res 2020; 478(5): 1089-97. doi: 10.1097/CORR.0000000000001114. DOI: https://doi.org/10.1097/CORR.0000000000001114
Waheed I, Ediripolage F, Alvi I, Haider J M. Preoperative risk factors for pain after reverse total shoulder arthroplasty: a systematic review. Cureus 2024; 16(5): e60041. doi: 10.7759/cureus.60041. DOI: https://doi.org/10.7759/cureus.60041
Rolfson O, Bohm E, Franklin P, Lyman S, Denissen G, Dawson J, et al. Patient-reported outcome measures in arthroplasty registries: Report of the Patient-Reported Outcome Measures Working Group of the International Society of Arthroplasty Registries Part II. Recommendations for selection, administration, and analysis. Acta Orthop 2016; 87 Suppl 1(Suppl 1): 9-23. doi: 10.1080/17453674.2016.1181816. DOI: https://doi.org/10.1080/17453674.2016.1181816
Harris I A, Peng Y, Cashman K, Ackerman I, Heath E, Rowden N, et al. Association between patient factors and hospital completeness of a patient-reported outcome measures program in joint arthroplasty, a cohort study. J Patient Rep Outcomes 2022; 6(1): 32. doi: 10.1186/s41687-022-00441-2. DOI: https://doi.org/10.1186/s41687-022-00441-2
Pines Y, Gordon D, Alben M, Kwon Y W, Zuckerman J D, Virk M S. Performance and responsiveness to change of PROMIS UE in patients undergoing total shoulder arthroplasty. J Orthop Res 2022; 40(10): 2457-64. doi: 10.1002/jor.25263. DOI: https://doi.org/10.1002/jor.25263
Terwee C B, Bot S D, de Boer M R, van der Windt D A, Knol D L, Dekker J, et al. Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol 2007; 60(1): 34-42. doi: 10.1016/j.jclinepi.2006.03.012. DOI: https://doi.org/10.1016/j.jclinepi.2006.03.012
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Copyright (c) 2025 Mirthe H W van Veghel, Liza N van Steenbergen, Cornelis P J Visser, B Willem Schreurs, Gerjon Hannink

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