Clinical outcomes following reverse shoulder arthroplasty-allograft composite for revision of failed arthroplasty associated with proximal humeral bone deficiency: 2- to 15-year follow-up.

BACKGROUND: Patients with pain and disability due to a prior failed shoulder arthroplasty with associated proximal humeral bone loss have limited reconstruction options. Our purpose was to report the results of a large cohort of patients treated with a reverse shoulder allograft-prosthetic composite (APC). METHODS: Between 2002 and 2012, a total of 73 patients were treated with a reverse shoulder APC and had adequate follow-up. Clinical outcome scores, range of motion, and radiographic evidence of failure were assessed. The minimum follow-up period was 2 years, with an average of 67.9 months (range, 21-157 months). Of the patients, 43 had more than 5 years' follow-up and 12 had more than 10 years' follow-up. RESULTS: The total American Shoulder and Elbow Surgeons score improved from 33.8 to 51.4 (P < .0001), and the Simple Shoulder Test score improved from 1.3 to 3.5 (P < .0001). Good to excellent results were reported in 42 of 60 patients (70%), 10 patients (17%) reported satisfactory results, and 8 patients (13%) were unsatisfied. Range of motion improved in forward flexion (49° to 75°, P < .001) and abduction (45° to 72°, P < .001). Revision was required in 14 patients (19%) for periprosthetic fracture (n = 6), instability (n = 2), glenosphere dissociation (n = 2), humeral loosening (n = 2), and infection (n = 2) at a mean of 38 months postoperatively. The reoperation-free survival rate of all reconstructions was 88% (30 of 34) at 5 years, 78% (21 of 27) at 10 years, and 67% (8 of 12) beyond 10 years. Ten patients had radiographic evidence of humeral loosening at final follow-up, and 2 required revision. CONCLUSIONS: The use of a reverse total shoulder APC provides reliable pain relief and improved range of motion, with an acceptable rate of complications. Although ultimate function achieved is limited, patient satisfaction remains high.

Is there a relationship between preoperative diagnosis and clinical outcomes in reverse shoulder arthroplasty? An experience in 699 shoulders.

BACKGROUND: The influence of diagnosis on outcomes after reverse shoulder arthroplasty (RSA) is not completely understood. The purpose of this study was to compare clinical outcomes of different pathologies. METHODS: A total of 699 RSAs were performed for the following diagnoses: (1) rotator cuff tear arthropathy (RCA), (2) massive cuff tear (MCT) with osteoarthritis (OA), (3) MCT without OA, (4) OA, (5) acute proximal humeral fracture, (6) malunion, (7) nonunion, and (8) inflammatory arthropathy. All patients had minimum 2-year clinical follow-up (mean, 47 months; range, 24-155 months). Range of motion, Simple Shoulder Test scores, American Shoulder and Elbow Surgeons scores, visual analog scale scores for function, and health-related quality-of-life measures were obtained preoperatively and postoperatively. RESULTS: The RCA, MCT-with-OA, MCT-without-OA, and OA groups all exhibited significant improvements in all outcome scores and in all planes of motion from preoperatively until a minimum of 2 years postoperatively. The malunion, nonunion, and inflammatory arthropathy groups showed improvements in American Shoulder and Elbow Surgeons scores, Simple Shoulder Test scores, forward flexion, and abduction. The average changes for all other outcomes and planes of motions were also positive but did not reach statistical significance. After adjustment for age and compared with RCA, female patients with malunion had significantly poorer forward flexion (P < .05), those with OA had significantly better abduction (P < .05), and those with fractures had significantly worse patient satisfaction (P < .05). Among male patients, those with MCTs without OA had significantly worse satisfaction (P < .05). CONCLUSION: RSA reliably provides improvement regardless of preoperative diagnosis. Although subtle differences exist between male and female patients, improvements in clinical outcome scores were apparent after RSA.

Do preoperative radiographs help predict intraoperative challenges in revision surgery after previous shoulder hemiarthroplasty?

BACKGROUND: This study compares preoperative radiographic evaluation with intraoperative video and explant data in patients undergoing revision of a hemiarthroplasty. METHODS: From 2004 to 2017, 182 shoulder hemiarthroplasties underwent revision to reverse shoulder arthroplasty for symptomatic failure. Preoperative radiographs were evaluated for stem fixation, stability, and glenohumeral registry. Intraoperative videos (n = 48) were evaluated for humeral component stability and bone loss after humeral stem extraction. All explants (n = 83) were reviewed for humeral head wear patterns and extraction artifacts (EAs). RESULTS: A well-fixed stem was reliably identified on radiographs as well fixed (true-negative rate, 95%). Of cemented implants, 94% (97 of 103) were radiographically stable and 90% (18 of 20) were stable on intraoperative video. Significant proximal humeral bone loss was identified after cemented stem extraction in 83% of cases, and severe EAs were noted in 28% (14 of 50). Of uncemented implants, 95% (75 of 79) were radiographically stable and 96% (24 of 25) were operatively stable. Significant proximal humeral bone loss was identified after extraction in 36% of cases (9 of 25) (P = .001). Severe EAs were seen in 13% of explanted stems (3 of 23). Eccentrically worn humeral head explants were associated with eccentric glenohumeral registry in 84% of cases (P = .0075). CONCLUSION: Preoperative radiographs for revision of a failed hemiarthroplasty help identify well-fixed stems and predict humeral bone loss during extraction. Cemented stems will have more EAs and result in greater bone loss than uncemented stems. Glenohumeral registry can help to predict humeral head wear. Eccentric registry leads to eccentric humeral head wear in 84% of cases.

Improving preoperative planning of revision surgery after previous anatomic total shoulder arthroplasty.

BACKGROUND: The purpose of this study was to compare preoperative radiographic evaluation with intraoperative video and explant analysis in patients undergoing revision of a previous anatomic total shoulder arthroplasty (TSA). METHODS: We evaluated the preoperative radiographs of 165 revisions of failed TSAs for component loosening and glenohumeral registry (ie, the spatial relationship of the glenoid component and the prosthetic humeral head). Seventy-nine intraoperative videos were evaluated for component stability, rotator cuff (RC) integrity, synovitis, and glenoid bone loss. Eighty-seven explants were reviewed to assess wear patterns and presence of backside cement. RESULTS: Of 79 glenoid components, 47 were radiographically loose, but only 30 of 79 were loose intraoperatively. Thirty-two were radiographically fixed, but only 26 of 32 were fixed intraoperatively. If radiographically loose, 53% had severe glenoid bone loss. If radiographically fixed, 77% had mild to moderate bone loss (P = .008). Synovitis was associated with glenoid fixation: mild with a loose glenoid (6%) and severe with a fixed glenoid (30%, P = .012). Superior registry comprised 46%. RC deficiency was associated with posterior and anterior registry (88% and 79%, respectively). Explant examination revealed an eccentric wear pattern was predominant. CONCLUSION: Radiographic evaluation of glenoid loosening in patients undergoing revision of TSAs will often differ from intraoperative findings (40% false-positive rate and 17% false-negative rate). Assessment of glenohumeral registry can help anticipate RC deficiency, with posterior and anterior registry associated with RC deficiency. Patients with a loose glenoid are more likely to have severe synovitis and more severe glenoid bone deficiencies. Failed TSAs are more likely to have asymmetrical wear of the glenoid component, suggesting altered pathomechanics that may have led to failure.

Survival of the pegged glenoid component in shoulder arthroplasty: part II.

BACKGROUND: Loosening of the glenoid component is a primary reason for failure of an anatomic shoulder arthroplasty. Pegged glenoids were designed in an effort to outperform keeled components. This study evaluated the midterm clinical and radiographic survival of a single implant design with implantation of an in-line pegged glenoid component and identified risk factors for radiographic loosening and clinical failure. MATERIALS AND METHODS: There were 330 total shoulder arthroplasties that had been implanted with a cemented, all-polyethylene, in-line pegged glenoid component evaluated with an average clinical follow-up of 7.2 years. Of these shoulders, 287 had presurgical, initial postsurgical, and late postsurgical radiographs (mean radiographic follow-up, 7.0 years). RESULTS: At most recent follow-up, 30 glenoid components had been revised for aseptic loosening. This translated to a rate of glenoid component survival free from revision for all 330 shoulders of 99% at 5 years and 83% at 10 years. Of 287 glenoid components, 120 were considered loose on the basis of radiographic evaluation. Four humeral components were considered loose. Component survival (Kaplan-Meier) free from radiographic failure at 5 and 10 years was 92% and 43%. Severe presurgical glenoid erosion (Walch A2, B2, C) and patient age <65 years were risk factors for radiographic failure. Late humeral head subluxation was associated with radiographic failure. CONCLUSION: Despite the predominant thinking that pegged glenoid components may be superior to keeled designs, midterm radiographic and clinical failure rates were high with this pegged component design, particularly after 5 years. Advanced presurgical glenoid erosion and younger patient age are risk factors for radiographic loosening. Revision rates underestimate radiographic glenoid loosening.

Factors Associated With 20-Year Cumulative Risk of Infection After Aseptic Index Revision Total Knee Arthroplasty.

BACKGROUND: The purpose of this study was to calculate the cumulative risk of periprosthetic joint infection (PJI) after aseptic index knee revisions and to identify the surgical, perioperative, and medical comorbidity risk factors associated with deep infection. METHODS: We retrospectively reviewed 1802 aseptic index revision total knee arthroplasties performed at our institution from 1970 to 2000. From this cohort, there were 60 reoperations performed for deep infection. RESULTS: The cumulative risk of infection at 1, 5, 10, and 20 years after index revision was 1%, 2.4%, 3.3%, and 5.6%, respectively. CONCLUSIONS: Male gender, use of constrained implants, increased operative times, increased Charlson Comorbidity Index, and a history of liver disease were all significantly associated with PJI. The development of cardiovascular disease, endocrine disorders, and renal disease were also associated with PJI.

Machine Learning Can Predict Level of Improvement in Shoulder Arthroplasty.

The ability to accurately predict postoperative outcomes is of considerable interest in the field of orthopaedic surgery. Machine learning has been used as a form of predictive modeling in multiple health-care settings. The purpose of the current study was to determine whether machine learning algorithms using preoperative data can predict improvement in American Shoulder and Elbow Surgeons (ASES) scores for patients with glenohumeral osteoarthritis (OA) at a minimum of 2 years after shoulder arthroplasty. METHODS: This was a retrospective cohort study that included 472 patients (472 shoulders) diagnosed with primary glenohumeral OA (mean age, 68 years; 56% male) treated with shoulder arthroplasty (431 anatomic total shoulder arthroplasty and 41 reverse total shoulder arthroplasty). Preoperative computed tomography (CT) scans were used to classify patients on the basis of glenoid and rotator cuff morphology. Preoperative and final postoperative ASES scores were used to assess the level of improvement. Patients were separated into 3 improvement ranges of approximately equal size. Machine learning methods that related patterns of these variables to outcome ranges were employed. Three modeling approaches were compared: a model with the use of all baseline variables (Model 1), a model omitting morphological variables (Model 2), and a model omitting ASES variables (Model 3). RESULTS: Improvement ranges of ≤28 points (class A), 29 to 55 points (class B), and >55 points (class C) were established. Using all follow-up time intervals, Model 1 gave the most accurate predictions, with probability values of 0.94, 0.95, and 0.94 for classes A, B, and C, respectively. This was followed by Model 2 (0.93, 0.80, and 0.73) and Model 3 (0.77, 0.72, and 0.71). CONCLUSIONS: Machine learning can accurately predict the level of improvement after shoulder arthroplasty for glenohumeral OA. This may allow physicians to improve patient satisfaction by better managing expectations. These predictions were most accurate when latent variables were combined with morphological variables, suggesting that both patients' perceptions and structural pathology are critical to optimizing outcomes in shoulder arthroplasty. LEVEL OF EVIDENCE: Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.

Humeral Bone Loss in Revision Shoulder Arthroplasty.

Revision shoulder arthroplasty is becoming more prevalent as the rate of primary shoulder arthroplasty in the US continues to increase. The management of proximal humeral bone loss in the revision setting presents a difficult problem without a clear solution. Different preoperative diagnoses often lead to distinctly different patterns of bone loss. Successful management of these cases requires a clear understanding of the normal anatomy of the proximal humerus, as well as structural limitations imposed by significant bone loss and the effect this loss has on component fixation. Our preferred technique differs depending on the pattern of bone loss encountered. The use of allograft-prosthetic composites, the cement-within-cement technique, and combinations of these strategies comprise the mainstay of our treatment algorithm. This article focuses on indications, surgical techniques, and some of the published outcomes using these strategies in the management of proximal humeral bone loss.