Prognostic factors for the occurrence of post-operative shoulder stiffness after arthroscopic rotator cuff repair: a systematic review

Incidence and risk factors for shoulder stiffness after open and arthroscopic rotator cuff repair

INTRODUCTION

The aim of this study was to estimate the incidence of stiffness during the first 6 months after rotator cuff repair and to evaluate postoperative stiffness with respect to its risk factors and its influence on the outcome at 6 months postoperatively.

METHODS

In a prospective cohort of 117 patients (69 women, 48 men; average age 59) from our institutional rotator cuff registry, who underwent either arthroscopic (n = 77) or open (n = 40) rotator cuff repair, we measured shoulder range of motion (ROM) at 3 and 6 months post-surgery. We evaluated the incidence of stiffness and analyzed functional outcomes, comparing various preoperative and intraoperative factors in patients with stiffness to those without at the 6-month mark.

RESULTS

Shoulder stiffness was observed in 31% of patients (36/117) at 3 months postoperatively, decreasing to 20% (23/117) at 6 months. No significant link was found between stiffness at 6 months and demographic factors, preoperative stiffness, tear characteristics, or the type of repair. Notably, patients undergoing arthroscopic repair exhibited a 4.3-fold higher risk (OR 4.3; 95% CI 1.2-15.6, p = 0.02) of developing stiffness at 6 months compared to those with mini-open repair. Despite these differences in stiffness rates, no significant variation was seen in the American Shoulder and Elbow Surgeons (ASES) score, Single Assessment Numeric Evaluation (SANE) score, or Visual Analog Scale (VAS) scores at 6 months between the groups.

CONCLUSION

The incidence of postoperative shoulder stiffness following rotator cuff repair was substantial at 31% at 3 months, reducing to 20% by 6 months. Mini-open repair was associated with a lower 6-month stiffness incidence than arthroscopic repair, likely due to variations in rehabilitation protocols. However, the presence of stiffness at 6 months post-surgery did not significantly affect functional outcomes or pain levels.

Effectiveness of nursing intervention in the operating room to prevent wound infections in patients undergoing orthopaedic surgery: A meta-analysis

Surgical site wound infection is one of the most common postoperative complications in orthopaedic clinical practice. This study employed a meta-analysis approach to comprehensively evaluate the effect of operating room nursing interventions on the prevention of surgical site wound infections in orthopaedic surgical patients. A computer search was conducted using PubMed, EMBASE, Cochrane Library, China National Knowledge Infrastructure (CNKI), Chinese Biomedical Literature Database (CBM), VIP, and Wanfang databases from the inception of each database until May 2023 for randomised controlled trials (RCTs) that investigated the application of operating room nursing interventions in orthopaedic surgery. Two reviewers independently screened the literature, extracted data, and assessed study quality. The meta-analysis was conducted using Stata 17.0. A total of 29 studies involving 3567 patients were included, with 1784 patients in the intervention group, and 1783 patients in the control group. The results of the meta-analysis showed that compared with the control group, the use of operating room nursing interventions significantly reduced the incidence of surgical site wound infection after orthopaedic surgery (2.85% vs. 13.24%; odds ratio: 0.18, 95% confidence interval: 0.14-0.25; p < 0.001). Current evidence suggests that operating room nursing interventions reduce the incidence of surgical site wound infections. However, owing to the limited number and low quality of the studies, more high-quality, large-sample RCTs are needed to further verify these findings.

Development and internal validation of a model predicting patient-reported shoulder function after arthroscopic rotator cuff repair in a Swiss setting

BACKGROUND

Prediction models for outcomes after orthopedic surgery provide patients with evidence-based postoperative outcome expectations. Our objectives were (1) to identify prognostic factors associated with the postoperative shoulder function outcome (the Oxford Shoulder Score (OSS)) and (2) to develop and validate a prediction model for postoperative OSS.

METHODS

Patients undergoing arthroscopic rotator cuff repair (ARCR) were prospectively documented at a Swiss orthopedic tertiary care center. The first primary ARCR in adult patients with a partial or complete rotator cuff tear were included between October 2013 and June 2021. Thirty-two potential prognostic factors were used for prediction model development. Two sets of factors identified using the knowledge from three experienced surgeons (Set 1) and Bayesian projection predictive variable selection (Set 2) were compared in terms of model performance using R squared and root-mean-squared error (RMSE) across 45 multiple imputed data sets using chained equations and complete case data.

RESULTS

Multiple imputation using data from 1510 patients was performed. Set 2 retained the following factors: American Society of Anesthesiologists (ASA) classification, baseline level of depression and anxiety, baseline OSS, operation duration, tear severity, and biceps status and treatment. Apparent model performance was R-squared = 0.174 and RMSE = 7.514, dropping to R-squared = 0.156, and RMSE = 7.603 after correction for optimism.

CONCLUSION

A prediction model for patients undergoing ARCR was developed using solely baseline and operative data in order to provide patients and surgeons with individualized expectations for postoperative shoulder function outcomes. Yet, model performance should be improved before being used in clinical routine.

Factors Affecting Postoperative Rehabilitation Therapy Utilization After Arthroscopic Rotator Cuff Repair: An Epidemiological Analysis

Background and objective Rotator cuff tear (RCT) is an orthopedic shoulder pathology commonly managed via arthroscopic rotator cuff repair (ARCR) after the failure of conservative treatment options. Physical therapy (PT) after ARCR is an important component of patient recovery. Postoperative complications, such as postoperative shoulder stiffness (POSS), are frequent among these patients and place a significant burden on patients and clinicians. The purpose of this study is to analyze temporal PT utilization among patients after ARCR and its potential to improve patient outcomes and examine possible factors affecting postoperative complication rates. Methods An epidemiological study was performed by using a large de-identified national health research network (TriNetX) within the United States to search for patients with a diagnosis of partial or complete RCT and subsequent ARCR. Data were collected on patient demographics, number of postoperative PT visits, and PT visits distribution in the early postoperative period. Statistical analysis was performed to analyze factors that impacted the utilization of postoperative PT after ARCR. Results A total of 21,540 patients underwent ARCR with 11,312 receiving ARCR for partial RCT and 10,228 for complete RCT. Of all ARCR patients, 6,923 (32.1%) received postoperative PT within one year of ARCR. Patients with partial RCT had a greater number of PT visits (mean ±SD: 3.85 ± 8.33; min-max: 0-110; t = 15.2) compared to patients with complete RCT (2.90 ± 7.97; min-max: 0-125) after ARCR (p<0.001). Patients with ARCR for partial RCT also had more visits within the first 12 weeks after ARCR as compared to patients with ARCR for complete RCT (p<0.001). Female patients had more visits than male patients after ARCR, regardless of the RCT extent (p<0.001). Conclusion Partial RCT and female sex are associated with increased postoperative PT usage after ARCR. Postoperative PT utilization has high variability after ARCR, regardless of the RCT extent. More research is needed to further explore the impact of PT utilization on postoperative complications after ARCR.

Machine learning model successfully identifies important clinical features for predicting outpatients with rotator cuff tears

PURPOSE

The aim of this study is to develop a machine learning model to identify important clinical features related to rotator cuff tears (RCTs) using explainable artificial intelligence (XAI) for efficiently predicting outpatients with RCTs.

METHODS

A retrospective review of a local clinical registry dataset was performed to include patients with shoulder pain and dysfunction who underwent questionnaires and physical examinations between 2019 and 2022. RCTs were diagnosed by shoulder arthroscopy. Six machine-learning algorithms (Stacking, Gradient Boosting Machine, Bagging, Random Forest, Extreme Gradient Boost (XGBoost), and Adaptive Boosting) were developed for the prediction. The performance of the models was assessed by the area under the receiver operating characteristic curve (AUC), Brier scores, and Decision curve. The interpretability of the predicted outcomes was evaluated using Shapley additive explanation (SHAP) values.

RESULTS

A total of 1684 patients who completed questionnaires and clinical tests were included, and 417 patients with RCTs underwent shoulder arthroscopy. In six machining learning algorithms for predicting RCTs, the accuracy, AUC values, and Brier scores were in the range of 0.81-0.86, 0.75-0.92, and 0.15-0.19, respectively. The XGBoost model showed superior performance with accuracy, AUC, and Brier scores of 0.85(95% confidence interval, 0.82-0.87), 0.92 (95% confidence interval,0.90-0.94), and 0.15 (95% confidence interval,0.14-0.16), respectively. The Shapley plot showed the impact of the clinical features on predicting RCTs. The most important variables were Jobe test, Bear hug test, and age for prediction, with mean SHAP values of 1.458, 0.950, and 0.790, respectively.

CONCLUSION

The machine learning model successfully identified important clinical variables for predicting patients with RCTs. In addition, the best algorithm was also integrated into a digital application to provide predictions in outpatient settings. This tool may assist patients in reducing their pain experience and providing prompt treatments.

LEVEL OF EVIDENCE

Level III.

Prognostic factors for improvement of shoulder function after arthroscopic rotator cuff repair: a systematic review

Background

The identification of factors that specify prognostic models for postoperative results should be based on the best scientific evidence and expert assessment. We aimed to identify, map, and evaluate potential prognostic factors for the improvement of shoulder function in patients undergoing arthroscopic rotator cuff repair.

Methods

Longitudinal primary studies of arthroscopic rotator cuff repair reporting any multivariable factor analyses for shoulder function improvement with an endpoint assessment of at least 6 months were included. We systematically searched EMBASE, Medline, and Scopus for articles published between January 2014 and June 2021. The risk of bias of included studies and the quality of evidence were assessed using the Quality in Prognosis Studies tool and an adapted Grading of Recommendations, Assessment, Development, and Evaluations framework.

Results

Overall, 24 studies including 73 outcome analyses were included. We classified younger age and smaller tear size as probably prognostic for a greater improvement in objective outcomes. Shorter symptom duration, absence of a worker compensation claim, low preoperative level of functional status, and high preoperative pain level were classified as probably prognostic for greater improvement in patient-reported outcome measures. The quality of the synthesized evidence was low. Twenty-one studies had an overall high risk of bias.

Conclusion

Six potential prognostic factors for shoulder function after arthroscopic rotator cuff repair were identified. Along with ongoing expert opinion assessments, they will feed into a prognostic model-building process.