Shirin Modarresi1, Nina Suh2, David M Walton3, Joy C MacDermid4. 1. Health & Rehabilitation Science, Western University, London, ON, Canada. Electronic address: smodarre@uwo.ca. 2. Roth|McFarlane Hand and Upper Limb Centre, St Joseph's Health Care, London, ON, Canada; Department of Orthopedic Surgery, Western University, London, ON, Canada. 3. School of Physical Therapy, Western University, London, ON, Canada. 4. Roth|McFarlane Hand and Upper Limb Centre, St Joseph's Health Care, London, ON, Canada; Department of Orthopedic Surgery, Western University, London, ON, Canada; School of Physical Therapy, Western University, London, ON, Canada; School of Rehabilitation Sciences, McMaster University, Hamilton, ON, Canada.
Abstract
BACKGROUND: Distal radius fractures (DRFs) are common and can lead to substantial pain and disability. Most people recover in six months, but some experience persistent pain and disability for one year or longer after injury. Therefore, it is important to understand the factors that can help predict poor recovery. OBJECTIVE: To identify recovery trajectories in DRF patients and to determine the factors that can help predict poor recovery. METHODS: Recovery was assessed in 318 patients using the Patient-Rated Wrist Evaluation scale at baseline, three, six, and 12 months. Demographic information was collected in addition to the Self-Administered Comorbidity Questionnaire, from which data regarding depression were extracted. Latent growth curve analysis (LGCA) was used to identify the recovery trajectories. Comparisons of proportion between the emergent classes were then conducted using chi-square and Kruskal-Wallis tests. RESULTS: The LGCA revealed three distinct trajectories (rapid-recovery: (69%), slow-recovery: (23%), and non-recovery: (8%) as the best fit to the data. The proportion of people with depression was significantly greater in the non-recovery class (24%) compared to the slow (16%, p = 0.04) and rapid-recovery (8%, p = 0.03) classes. Additionally, the proportion of females were significantly lower in the non-recovery (64%, p = 0.03) compared to the slow (85%, p = 0.03) and the rapid-recovery classes (81%, p = 0.048). CONCLUSION: Recovery from DRF was best described using three different trajectories. Greater self-reported depression and a lower proportion of females in the non-recovery class were distinguishing factors between the classes. Patients who appear to be in slow-recovery or non-recovery classes may be followed more closely.
BACKGROUND: Distal radius fractures (DRFs) are common and can lead to substantial pain and disability. Most people recover in six months, but some experience persistent pain and disability for one year or longer after injury. Therefore, it is important to understand the factors that can help predict poor recovery. OBJECTIVE: To identify recovery trajectories in DRF patients and to determine the factors that can help predict poor recovery. METHODS: Recovery was assessed in 318 patients using the Patient-Rated Wrist Evaluation scale at baseline, three, six, and 12 months. Demographic information was collected in addition to the Self-Administered Comorbidity Questionnaire, from which data regarding depression were extracted. Latent growth curve analysis (LGCA) was used to identify the recovery trajectories. Comparisons of proportion between the emergent classes were then conducted using chi-square and Kruskal-Wallis tests. RESULTS: The LGCA revealed three distinct trajectories (rapid-recovery: (69%), slow-recovery: (23%), and non-recovery: (8%) as the best fit to the data. The proportion of people with depression was significantly greater in the non-recovery class (24%) compared to the slow (16%, p = 0.04) and rapid-recovery (8%, p = 0.03) classes. Additionally, the proportion of females were significantly lower in the non-recovery (64%, p = 0.03) compared to the slow (85%, p = 0.03) and the rapid-recovery classes (81%, p = 0.048). CONCLUSION: Recovery from DRF was best described using three different trajectories. Greater self-reported depression and a lower proportion of females in the non-recovery class were distinguishing factors between the classes. Patients who appear to be in slow-recovery or non-recovery classes may be followed more closely.
Authors: O O Babatunde; M Bucknall; C Burton; J J Forsyth; N Corp; S Gwilym; Z Paskins; D A van der Windt Journal: Osteoporos Int Date: 2021-11-11 Impact factor: 4.507
Authors: Shirin Modarresi; Joy C MacDermid; Nina Suh; James M Elliott; David M Walton Journal: Clin Orthop Relat Res Date: 2022-02-01 Impact factor: 4.755
Authors: Othman Alkassabi; Lennard Voogt; Pamela Andrews; Ahmad Alhowimel; Jo Nijs; Hana Alsobayel Journal: Int J Environ Res Public Health Date: 2022-07-29 Impact factor: 4.614