| Publication type: | Article in scientific journal |
| Type of review: | Peer review (publication) |
| Title: | Prediction of shoulder stiffness after arthroscopic rotator cuff repair |
| Authors: | Audigé, Laurent Aghlmandi, Soheila Grobet, Cécile Stojanov, Thomas Müller, Andreas M. Felsch, Quinten Gleich, Johannes Flury, Matthias Scheibel, Markus |
| et. al: | No |
| DOI: | 10.1177/03635465211028980 |
| Published in: | The American Journal of Sports Medicine |
| Volume(Issue): | 49 |
| Issue: | 11 |
| Page(s): | 3030 |
| Pages to: | 3039 |
| Issue Date: | 2021 |
| Publisher / Ed. Institution: | Sage |
| ISSN: | 0363-5465 1552-3365 |
| Language: | English |
| Subjects: | Capsulitis; Arthroscopy; Case-Control study; Retrospective study; Rotator cuff tear; Surgery; Complication; Shoulder stiffness; Frozen shoulder; Risk factor; Prediction; Discrimination; Registry Database |
| Subject (DDC): | 617.5: Orthopaedic surgery |
| Abstract: | Background: Postoperative shoulder stiffness (POSS) is a prevalent adverse event after arthroscopic rotator cuff repair (ARCR) that is associated with major limitations in everyday activities and prolonged rehabilitation. Purpose/Hypothesis: The purpose was to develop a predictive model for determining the risk of POSS within 6 months after primary ARCR. We hypothesized that sufficient discrimination ability of such a model could be achieved using a local institutional database. Study Design: Case-control study; Level of evidence, 3. Methods: Consecutive primary ARCRs documented in a local clinical registry between 2013 and 2017 were included, and patients who experienced POSS before the final clinical 6-month follow-up were identified. A total of 29 prognostic factor candidates were considered, including patient-related factors (n = 7), disease-related factors (n = 9), rotator cuff integrity factors (n = 6), and operative details (n = 7). We used imputed data for the primary analysis, and a sensitivity analysis was conducted using complete case data. Logistic regression was applied to develop a model based on clinical relevance and statistical criteria. To avoid overfitting in the multivariable model, highly correlated predictors were not included together in any model. A final prognostic model with a maximum of 8 prognostic factors was considered. The model’s predictive accuracy was assessed by the area under the receiver operating characteristic curve (AUC). Internal validation was performed using bootstrapping. Results: Of 1330 ARCR cases (N = 1330 patients), 112 (8.4%) patients had POSS. Our final model had a moderate predictive ability with an AUC of 0.67. The predicted risks of POSS ranged from 2.3% to 38.9% and were significantly higher in women; patients with partial tears, low baseline passive shoulder abduction, and lack of tendon degeneration; and when no acromioplasty was performed. Conclusion: A prognostic model for POSS was developed for patients with ARCR, offering a personalized risk evaluation to support the future decision process for surgery and rehabilitation. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/24239 |
| Fulltext version: | Published version |
| License (according to publishing contract): | Licence according to publishing contract |
| Departement: | School of Management and Law |
| Organisational Unit: | Winterthur Institute of Health Economics (WIG) |
| Appears in collections: | Publikationen School of Management and Law |
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