K E M Harmelink1,2, R Dandis3, P J der Van der Wees Pj4, A V C M Zeegers5, M W Nijhuis-van der Sanden4, J B Staal4,6. 1. Radboud university medical center, Radboud Institute for Health Sciences, IQ healthcare, Geert Grooteplein Zuid 21, 6525, EZ, Nijmegen, the Netherlands. k.harmelink@flex-s.nl. 2. FysioHolland Twente, Geessinkbrink 7, 7544, CW, Enschede, the Netherlands. k.harmelink@flex-s.nl. 3. Department for Health Evidence, Section Biostatistics, Radboud university medical center, Radboud Institute for Health Sciences, Geert Grooteplein Zuid 21, 6525, EZ, Nijmegen, the Netherlands. 4. Radboud university medical center, Radboud Institute for Health Sciences, IQ healthcare, Geert Grooteplein Zuid 21, 6525, EZ, Nijmegen, the Netherlands. 5. Medisch Spectrum Twente (MST), Department of Orthopedic surgery, Koningsplein 1, 7512, KZ, Enschede, the Netherlands. 6. HAN University of Applied Sciences, Musculoskeletal Rehabilitation Research Group, Kapittelweg 33, 6525, EJ, Nijmegen, the Netherlands.
Abstract
BACKGROUND: Recovery trajectories differ between individual patients and it is hypothesizes that they can be used to predict if an individual patient is likely to recover earlier or later. Primary aim of this study was to determine if it is possible to identify recovery trajectories for physical functioning and pain during the first six weeks in patients after TKA. Secondary aim was to explore the association of these trajectories with one-year outcomes. METHODS: Prospective cohort study of 218 patients with the following measurement time points: preoperative, and at three days, two weeks, six weeks, and one year post-surgery (no missings). Outcome measures were performance-based physical functioning (Timed Up and Go [TUG]), self-reported physical functioning (Knee injury and Osteoarthritis Outcome Score-Activities of Daily Living [KOOS-ADL]), and pain (Visual Analogue Scale [VAS]). Latent Class Analysis was used to distinguish classes based on recovery trajectories over the first six weeks postoperatively. Multivariable regression analyses were used to identify associations between classes and one year outcomes. RESULTS: TUG showed three classes: "gain group" (n = 203), "moderate gain group" (n = 8) and "slow gain group" (n = 7), KOOS showed two classes: "gain group" (n = 86) and "moderate gain group" (n = 132), and VAS-pain three classes: "no/very little pain" (n = 151), "normal decrease of pain" (n = 48) and "sustained pain" (n = 19). The" low gain group" scored 3.31 [95% CI 1.52, 5.09] seconds less on the TUG than the "moderate gain group" and the KOOS "gain group" scored 11.97 [95% CI 8.62, 15.33] points better than the "moderate gain group" after one year. Patients who had an early trajectory of "sustained pain" had less chance to become free of pain at one year than those who reported "no or little pain" (odds ratio 0.11 [95% CI 0.03,0.42]. CONCLUSION: The findings of this study indicate that different recovery trajectories can be detected. These recovery trajectories can distinguish outcome after one year.
BACKGROUND: Recovery trajectories differ between individual patients and it is hypothesizes that they can be used to predict if an individual patient is likely to recover earlier or later. Primary aim of this study was to determine if it is possible to identify recovery trajectories for physical functioning and pain during the first six weeks in patients after TKA. Secondary aim was to explore the association of these trajectories with one-year outcomes. METHODS: Prospective cohort study of 218 patients with the following measurement time points: preoperative, and at three days, two weeks, six weeks, and one year post-surgery (no missings). Outcome measures were performance-based physical functioning (Timed Up and Go [TUG]), self-reported physical functioning (Knee injury and Osteoarthritis Outcome Score-Activities of Daily Living [KOOS-ADL]), and pain (Visual Analogue Scale [VAS]). Latent Class Analysis was used to distinguish classes based on recovery trajectories over the first six weeks postoperatively. Multivariable regression analyses were used to identify associations between classes and one year outcomes. RESULTS: TUG showed three classes: "gain group" (n = 203), "moderate gain group" (n = 8) and "slow gain group" (n = 7), KOOS showed two classes: "gain group" (n = 86) and "moderate gain group" (n = 132), and VAS-pain three classes: "no/very little pain" (n = 151), "normal decrease of pain" (n = 48) and "sustained pain" (n = 19). The" low gain group" scored 3.31 [95% CI 1.52, 5.09] seconds less on the TUG than the "moderate gain group" and the KOOS "gain group" scored 11.97 [95% CI 8.62, 15.33] points better than the "moderate gain group" after one year. Patients who had an early trajectory of "sustained pain" had less chance to become free of pain at one year than those who reported "no or little pain" (odds ratio 0.11 [95% CI 0.03,0.42]. CONCLUSION: The findings of this study indicate that different recovery trajectories can be detected. These recovery trajectories can distinguish outcome after one year.
Entities:
Keywords:
Latent class analysis; Physiotherapy program; Recovery; Total knee Arthroplasty
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