Background Globally, reverse shoulder arthroplasty (RSA) has moved away from the Grammont design to modern prosthesis designs. The purpose of this study was to provide a focused, updated systematic review for each of the most common complications of RSA by limiting each search to publications after 2010. In this part II, the following were examined: (1) instability, (2) humerus/glenoid fracture, (3) acromial/scapular spine fractures (AF/SSF), and (4) problems/miscellaneous. Methods Four separate PubMed database searches were performed following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Overall, 137 studies for instability, 94 for humerus/glenoid fracture, 120 for AF/SSF, and 74 for problems/miscellaneous were included in each review, respectively. Univariate analysis was performed with chi-square and Fisher exact tests. Results The Grammont design had a higher instability rate vs. all other designs combined (4.0%, 1.3%; P < .001), and the onlay humerus design had a lower rate than the lateralized glenoid design (0.9%, 2.0%; P = .02). The rate for intraoperative humerus fracture was 1.8%; intraoperative glenoid fracture, 0.3%; postoperative humerus fracture, 1.2%; and postoperative glenoid fracture, 0.1%. The rate of AF/SSF was 2.6% (371/14235). The rate for complex regional pain syndrome was 0.4%; deltoid injury, 0.1%; hematoma, 0.3%; and heterotopic ossification, 0.8%. Conclusions Focused systematic reviews of recent literature with a large volume of shoulders demonstrate that using non-Grammont modern prosthesis designs, complications including instability, intraoperative humerus and glenoid fractures, and hematoma are significantly reduced compared with previous studies. As the indications continue to expand for RSA, it is imperative to accurately track the rate and types of complications in order to justify its cost and increased indications.
Background: Analyzing outcomes and the minimal clinically important difference (MCID) after anterior cruciate ligament reconstruction (ACLR) is of increased interest in the orthopaedic literature. The purposes of this study were to report outcomes after ACLR at medium to long-term follow-up, identify the threshold preoperative outcome values that would be predictive of achieving the MCID postoperatively, and analyze outcome maintenance at medium to long-term follow-up after ACLR.Methods: Active athletes who underwent ACLR were identified in an institutional ACL registry. Patient-reported outcome measures (PROMs) were administered preoperatively and at the 2-year and >5-year postoperative follow-up; measures included the International Knee Documentation Committee (IKDC) form, the 12-item Short Form Health Survey (SF-12) Physical Component Summary (PCS) and Mental Component Summary (MCS), and Lysholm scale. We calculated the MCID from baseline to each of the 2 follow-up periods (2-year and mean 7.7-year). Logistic regression was performed to investigate factors associated with achievement of the MCID.Results: A total of 142 patients (mean follow-up, 7.7 years [range, 6.6 to 9.1 years]) underwent ACLR. The mean age and body mass index at the time of surgery were 27.2 ± 13.0 years and 23.2 ± 3.0 kg/m 2 , respectively. Final postoperative outcome scores improved significantly from baseline for the IKDC (50.9 ± 14.7 to 87.9 ± 11.2), SF-12 PCS (41.6 ± 8.9 to 55.6 ± 3.2), and Lysholm scale (62.2 ± 17.6 to 90.5 ± 10.3) (p < 0.0001), while the SF-12 MCS did not improve significantly (54.2 ± 8.0 to 54.4 ± 6.0) (p = 0.763). Between 2-and >5-year follow-up, the SF-12 PCS showed significant improvement (54.6 ± 4.5 to 55.6 ± 3.2; p = 0.036), while no change was noted in the IKDC (87.6 ± 11.1 to 87.9 ± 11.2), SF-12 MCS (55.5 ± 5.3 to 54.4 ± 6.0), and Lysholm scale (89.8 ± 10.6 to 90.5 ± 10.3) (p ‡ 0.09). At the time of final follow-up, the MCID was achieved by 94.7% of patients for the IKDC, 80.8% for the Lysholm, 79.0% for the SF-12 PCS, and 28.2% for the SF-12 MCS. At 2-year follow-up, 95.3% of patients were either "very" or "somewhat" satisfied with their surgery, compared with 88.6% at the time of final follow-up. Conclusions:We found a high level of maintained function following ACLR. The IKDC, SF-12 PCS, and Lysholm scores improved significantly after ACLR at the time of final follow-up and were not significantly different between follow-up periods. Approximately 95% and 89% of patients reported being satisfied with the outcome of surgery at the 2-year and final follow-up, respectively.
Background: The number of patients requiring reoperation has increased as the volume of hip arthroscopy for femoroacetabular impingement syndrome (FAIS) has increased. The factors most important in determining patients who are likely to require reoperation remain elusive. Purpose: To leverage machine learning to better characterize the complex relationship across various preoperative factors (patient characteristics, radiographic parameters, patient-reported outcome measures [PROMs]) for patients undergoing primary hip arthroscopy for FAIS to determine which features predict the need for future ipsilateral hip reoperation, namely, revision hip arthroscopy, total hip arthroplasty (THA), hip resurfacing arthroplasty (HRA), or periacetabular osteotomy (PAO). Study Design: Cohort study; Level of evidence, 3. Methods: A cohort of 3147 patients undergoing 3748 primary hip arthroscopy procedures were included from an institutional hip preservation registry. Preoperative computed tomography of the hip was obtained for each patient, from which the following parameters were calculated: the alpha angle; the coronal center-edge angle; the neck-shaft angle; the acetabular version angle at 1, 2, and 3 o’clock; and the femoral version angle. Preoperative PROMs included the modified Harris Hip Score (mHHS), the Hip Outcome Score (HOS)–Activities of Daily Living subscale (HOS-ADL) and the Sport Specific subscale, and the international Hip Outcome Tool (iHOT-33). Random forest models were created for revision hip arthroscopy, the THA, the HRA, and the PAO. Area under the curve (AUC) for the receiver operating characteristic curve and accuracy were calculated to evaluate each model. Results: A total of 171 patients (4.6%) underwent subsequent hip surgery after primary hip arthroscopy for FAIS. The AUC and accuracy, respectively, were 0.77 (fair) and 76% for revision hip arthroscopy (mean, 26.4-month follow-up); 0.80 (good) and 81% for THA (mean, 32.5-month follow-up); 0.62 (poor) and 69% for HRA (mean, 45.4-month follow-up); and 0.76 (fair) and 74% for PAO (mean, 30.4-month follow-up). The most important factors in predicting reoperation after primary hip arthroscopy were higher body mass index (BMI) and lower preoperative HOS-ADL for revision hip arthroscopy, greater age and lower preoperative iHOT-33 for THA, increased BMI for HRA, and larger neck-shaft angle and lower preoperative mHHS for PAO. Conclusion: Despite the low failure rate of hip arthroscopy for FAIS, our study demonstrated that machine learning has the capability to identify key preoperative risk factors that may predict subsequent ipsilateral hip surgery before the index hip arthroscopy. Knowledge of these demographic, radiographic, and patient-reported outcome data may aid in preoperative counseling and expectation management to better optimize hip preservation.
Background: The relationship between the preoperative radiographic indices for femoroacetabular impingement syndrome (FAIS) and postoperative patient-reported outcome measure (PROM) scores continues to be under investigation, with inconsistent findings reported. Purpose: To apply a machine learning model to determine which preoperative radiographic indices, if any, among patients indicated for the arthroscopic correction of FAIS predict whether a patient will achieve the minimal clinically important difference (MCID) for 1- and 2-year PROM scores. Study Design: Cohort study; Level of evidence, 3. Methods: A total of 1735 consecutive patients undergoing primary hip arthroscopic surgery for FAIS were included from an institutional hip preservation registry. Patients underwent preoperative computed tomography of the hip, from which the following radiographic indices were calculated by a musculoskeletal radiologist: alpha angle, beta angle, sagittal center-edge angle, coronal center-edge angle, neck shaft angle, acetabular version angle, and femoral version angle. PROM scores were collected preoperatively, at 1 year postoperatively, and at 2 years postoperatively for the modified Harris Hip Score (mHHS), the Hip Outcome Score (HOS)–Activities of Daily Living (HOS-ADL) and –Sport Specific (HOS-SS), and the International Hip Outcome Tool (iHOT-33). Random forest models were created for each PROM at 1 and 2 years’ follow-up, with each PROM’s MCID used to establish clinical meaningfulness. Data inputted into the models included ethnicity, laterality, sex, age, body mass index, and radiographic indices. Comprehensive and separate models were built specifically to assess the association of the alpha angle, femoral version angle, coronal center-edge angle, McKibbin index, and hip impingement index with respect to each PROM. Results: As evidenced by poor area under the curves and P values >.05 for each model created, no combination of radiographic indices or isolated index (alpha angle, coronal center-edge angle, femoral version angle, McKibbin index, hip impingement index) was a significant predictor of a clinically meaningful improvement in scores on the mHHS, HOS-ADL, HOS-SS, or iHOT-33. The mean difference between 1- and 2-year PROM scores compared with preoperative values exceeded the respective MCIDs for the cohort. Conclusion: In patients appropriately indicated for FAIS corrective surgery, clinical improvements can be achieved, regardless of preoperative radiographic indices, such as the femoral version angle, coronal center-edge angle, and alpha angle. No specific radiographic parameter or combination of indices was found to be predictive of reaching the MCID for any of the 4 studied hip-specific PROMs at either 1 or 2 years’ follow-up.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.