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Cho CH, Bae KC, Kim DH. Patients who have undergone rotator cuff repair experience around 75% functional recovery at 6 months after surgery. Knee Surg Sports Traumatol Arthrosc 2021; 29:2220-7. [PMID: 32347347 DOI: 10.1007/s00167-020-06019-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/08/2019] [Accepted: 04/21/2020] [Indexed: 12/11/2022]
Abstract
PURPOSE The purposes of this study were to (1) evaluate changes in recovery patterns [i.e., clinical outcomes, range of motion (ROM)] in the first 12 months following surgery, (2) identify potential prognostic factors of early clinical outcomes after rotator cuff repair (RCR). METHODS The study cohort included 344 consecutive patients treated with RCR. Data were collected prospectively and included pre- and perioperative variables. Univariate and multivariate linear regression analyses for various parameters including demographics, pre- and perioperative variables were used to predict shoulder function at 12-month follow-up, as measured by clinical outcomes and ROM. RESULTS Significant improvement in all clinical scores and ROM were noted during serial follow-ups after RCR (all p < 0.001). Multivariate analysis revealed that female sex, older age, more anchors, diabetes mellitus, and preoperative stiffness were independently associated with worse shoulder function 3 months after RCR. Including the 3 months factors, heavy labor, use of the suture-bridge technique, and large tears were also independently associated with worse outcomes 6 months after surgery. Heavy labor, suture-bridge technique, diabetes mellitus, and preoperative stiffness were associated with significantly worse functional outcomes at 12 months after surgery (all p < 0.05). CONCLUSION Functional recovery based on clinical outcomes (i.e., UCLA, ASES scores) showed approximately 60% of ultimate recovery at 3 months and approximately 75% recovery at 6 months after RCR. Female sex, diabetes mellitus, preoperative stiffness, a larger number of anchors, suture bridge technique, heavy labor, old age and, larger tears were prognostic factors of poor clinical results or ROM in the short-term follow-up intervals. Knowledge of these prognostic factors may lead to improved insight for physicians to predict the pattern of the recovery and patient expectations accordingly. LEVEL OF EVIDENCE III, A cohort study.
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Abstract
Background Shoulder surgery results in several months of rehabilitation, which is often underestimated by patients preoperatively. Currently, there is little written about this process of recovery. Information on this would help patients to anticipate the trajectory of their recovery. This would also provide a reference point allowing surgeons to compare a patient's progress in their recovery. The purpose of our study was to analyze and document the expected rate of recovery for the most common shoulder operations. Methods A retrospective analysis of all patients who underwent total shoulder arthroplasty (TSA), reverse total shoulder arthroplasty (RTSA), arthroscopic rotator cuff repair (ARCR), and arthroscopic biceps tenodesis (BT) using prospectively collected data from the Surgical Outcomes System registry was performed. All patients included had a complete 2-year follow-up data set. The pain score (visual analog scale) was measured preoperatively at 2, 6, and 12 weeks and 6, 12, and 24 months. The American Shoulder and Elbow Surgeons (ASES) and Single Assessment Numeric Evaluation (SANE) score were recorded preoperatively and after 6, 12, and 24 months. The speed of recovery, defined as the percentage of total improvement, for each procedure was assessed as the primary outcome parameter at all time points. Results All shoulder interventions resulted in significant improvement of the pain, SANE, and ASES scores 2 years after shoulder surgery. The speed of recovery of all 3 scores was highest after TSA at all measured time points and slowest after ARCR and BT. Measured by the pain score, 90% and 82% of the total improvement after TSA and RTSA was completed after 6 weeks compared to 58% and 59% after ARCR and BT, respectively. Six months postoperatively the ASES recovery rate was significantly higher after arthroplasty (TSA 96% and RTSA 85%) compared to ARCR and BT (76% and 77%, respectively). The SANE score recovery rate was between 82% and 92% (TSA 92%, RTSA 89%, ARCR 87%, BT 82%) 6 months after surgery. After 1 year all patient groups reached 89% or more of the total improvement in all scores, except for the pain after ARCR (89%). Conclusion The improvement in pain is fastest after TSA and slowest after ARCR and BT. After TSA and RTSA, >80% of the total pain reduction is achieved 6 weeks postoperatively, whereas after ARCR and BT, >80% of the pain reduction is achieved only 6 months postoperatively. At 12 months postoperatively, the differences in recovery curves were not significant.
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Affiliation(s)
- Florian Grubhofer
- Massachusetts General Hospital, Department of Orthopedic Surgery, Harvard Medical School, Boston, MA, USA
- Corresponding author: Florian Grubhofer, MD, Department of Orthopedic Surgery, Harvard Medical School, Fruit Street 55, Boston, MA 02114, USA.
| | - Andres R. Muniz Martinez
- Massachusetts General Hospital, Department of Orthopedic Surgery, Harvard Medical School, Boston, MA, USA
| | - Lukas Ernstbrunner
- Balgrist University Hospital, Department of Orthopedic Surgery, University of Zürich, Zürich, Switzerland
| | - Jillian Haberli
- Massachusetts General Hospital, Department of Orthopedic Surgery, Harvard Medical School, Boston, MA, USA
| | - Megan E. Selig
- Massachusetts General Hospital, Department of Orthopedic Surgery, Harvard Medical School, Boston, MA, USA
| | - Karen Yi
- Massachusetts General Hospital, Department of Orthopedic Surgery, Harvard Medical School, Boston, MA, USA
| | - Jon J.P. Warner
- Massachusetts General Hospital, Department of Orthopedic Surgery, Harvard Medical School, Boston, MA, USA
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Kuranova A, Booij SH, Menne-Lothmann C, Decoster J, van Winkel R, Delespaul P, De Hert M, Derom C, Thiery E, Rutten BPF, Jacobs N, van Os J, Wigman JTW, Wichers M. Measuring resilience prospectively as the speed of affect recovery in daily life: a complex systems perspective on mental health. BMC Med 2020; 18:36. [PMID: 32066437 PMCID: PMC7027206 DOI: 10.1186/s12916-020-1500-9] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2019] [Accepted: 01/21/2020] [Indexed: 11/10/2022] Open
Abstract
INTRODUCTION There is growing evidence that mental disorders behave like complex dynamic systems. Complex dynamic systems theory states that a slower recovery from small perturbations indicates a loss of resilience of a system. This study is the first to test whether the speed of recovery of affect states from small daily life perturbations predicts changes in psychopathological symptoms over 1 year in a group of adolescents at increased risk for mental disorders. METHODS We used data from 157 adolescents from the TWINSSCAN study. Course of psychopathology was operationalized as the 1-year change in the Symptom Checklist-90 sum score. Two groups were defined: one with stable and one with increasing symptom levels. Time-series data on momentary daily affect and daily unpleasant events were collected 10 times a day for 6 days at baseline. We modeled the time-lagged effect of daily unpleasant events on negative and positive affect after each unpleasant event experienced, to examine at which time point the impact of the events is no longer detectable. RESULTS There was a significant difference between groups in the effect of unpleasant events on negative affect 90 min after the events were reported. Stratified by group, in the Increase group, the effect of unpleasant events on both negative (B = 0.05, p < 0.01) and positive affect (B = - 0. 08, p < 0.01) was still detectable 90 min after the events, whereas in the Stable group this was not the case. CONCLUSION Findings cautiously suggest that adolescents who develop more symptoms in the following year may display a slower affect recovery from daily perturbations at baseline. This supports the notion that mental health may behave according to the laws of a complex dynamic system. Future research needs to examine whether these dynamic indicators of system resilience may prove valuable for personalized risk assessment in this field.
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Affiliation(s)
- Anna Kuranova
- University of Groningen, University Medical Center Groningen, University Center Psychiatry (UCP) Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Groningen, The Netherlands.
| | - Sanne H Booij
- University of Groningen, University Medical Center Groningen, University Center Psychiatry (UCP) Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Groningen, The Netherlands
- Department of Research and Education, Friesland Mental Health Care Services, Leeuwarden, The Netherlands
- Center for Integrative Psychiatry, Lentis, Groningen, The Netherlands
| | - Claudia Menne-Lothmann
- Department of Psychiatry and Neuropsychology, School of mental health and neuroscience (MHeNS), Maastricht University, Maastricht, The Netherlands
| | - Jeroen Decoster
- University Psychiatric Centre Sint-Kamillus, Bierbeek, Belgium
| | - Ruud van Winkel
- KU Leuven, Department of Neurosciences, Center for Public Health Psychiatry, UPC KU Leuven, Leuven, Belgium
- KU Leuven, Department of Neurosciences, Center for Clinical Psychiatry, UPC KU Leuven, Leuven, Belgium
| | - Philippe Delespaul
- Department of Psychiatry and Neuropsychology, School of mental health and neuroscience (MHeNS), Maastricht University, Maastricht, The Netherlands
- Mondriaan Mental Health Care, Heerlen, The Netherlands
| | - Marc De Hert
- KU Leuven, Department of Neurosciences, Center for Public Health Psychiatry, UPC KU Leuven, Leuven, Belgium
- KU Leuven, Department of Neurosciences, Center for Clinical Psychiatry, UPC KU Leuven, Leuven, Belgium
- Antwerp Health Law and Ethics Chair - AHLEC University Antwerpen, Antwerp, Belgium
| | - Catherine Derom
- Centre of Human Genetics, University Hospital Leuven, KU Leuven, Leuven, Belgium
- Department of Obstetrics and Gynecology, Ghent University Hospital, Ghent University, Ghent, Belgium
| | - Evert Thiery
- Department of Neurology, Ghent University Hospital, Ghent University, Ghent, Belgium
| | - Bart P F Rutten
- Department of Psychiatry and Neuropsychology, School of mental health and neuroscience (MHeNS), Maastricht University, Maastricht, The Netherlands
| | - Nele Jacobs
- Department of Psychiatry and Neuropsychology, School of mental health and neuroscience (MHeNS), Maastricht University, Maastricht, The Netherlands
- Faculty of Psychology and Educational Sciences, Open University of the Netherlands, Heerlen, Netherlands
| | - Jim van Os
- Department of Psychiatry and Neuropsychology, School of mental health and neuroscience (MHeNS), Maastricht University, Maastricht, The Netherlands
- Department of Psychosis Studies, Institute of Psychiatry, King's Health Partners, King's College London, London, UK
- Department Psychiatry, Brain Center Rudolf Magnus, Utrecht University Medical Centre, Utrecht, The Netherlands
| | - Johanna T W Wigman
- University of Groningen, University Medical Center Groningen, University Center Psychiatry (UCP) Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Groningen, The Netherlands
- Department of Research and Education, Friesland Mental Health Care Services, Leeuwarden, The Netherlands
| | - Marieke Wichers
- University of Groningen, University Medical Center Groningen, University Center Psychiatry (UCP) Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Groningen, The Netherlands
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Abstract
Background Comorbidities have been shown to affect rotator cuff healing and postoperative outcomes. The purpose of this study was to analyze the effect of comorbidities on speed of recovery (SOR) and overall outcomes after arthroscopic rotator cuff repair (RCR). Methods We identified 627 patients who underwent primary arthroscopic RCR from 2006 to 2015. Measured motion and patient-reported outcome measures for pain and function were analyzed for preoperative, 3-month, 6-month, and 1-year intervals. Subgroup analysis of overall outcome and plateau in maximum improvement was performed for diabetes, smoking, obesity, hypercholesterolemia, and age. Results Diabetic patients had worse pain (visual analog scale for pain) and functional outcome (American Shoulder and Elbow Surgeons function, Simple Shoulder Test, visual analog scale for function, and elevation) scores at 6 months and 1 year (P < .05), with an earlier plateau in recovery (6 months) for nearly all variables. Smoking had no impact on postoperative outcome scores; however, plateaus occurred earlier in smokers (6 months). Obese patients had worse American Shoulder and Elbow Surgeons function score and external rotation at 1 year (P < .05) with similar plateau points. No significant differences were observed in outcomes for patients with hypercholesterolemia; however, plateaus for Single Assessment Numeric Evaluation and motion occurred earlier (6 months). Outcome scores for patients older than 65 years were not significantly different from those for younger patients. Conclusion After arthroscopic RCR, SOR for pain outpaced that for function and motion. Diabetic patients had worse outcomes and earlier plateau points. Earlier plateaus were seen for smokers and for motion in patients with obesity or hypercholesterolemia. Obese patients showed lower functional scores and external rotation. Age did not significantly influence SOR.
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Affiliation(s)
| | - Jennifer Kurowicki
- Holy Cross Orthopedic Institute, Fort Lauderdale, FL, USA.,Seton Hall University, School of Health and Medical Sciences, Department of Orthopaedics, South Orange, NJ, USA
| | | | - Brandon Horn
- Holy Cross Orthopedic Institute, Fort Lauderdale, FL, USA.,Witham Orthopaedic Associates, Lebanon, IN, USA
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