Outcomes Following Revision Reverse Shoulder Arthroplasty for Infection.

BACKGROUND: In comparison to primary reverse shoulder arthroplasty (RSA) procedures, revision arthroplasty can be a longer and more complex procedure leading to an increased risk of complications. The reported rates of infection in primary RSA range from 1% to 19% and the cost impact on patients and healthcare systems is significant, leading to multiple revision surgeries. The purpose of this study was to evaluate the postoperative outcomes, complications, and revision rates for revision reverse shoulder arthroplasty (rRSA) due to infection compared to rRSA for non-infectious causes. METHODS: Patients who underwent rRSA between 2009 and 2020 by a single fellowship-trained orthopedic surgeon at a single institution were retrospectively identified through a prospectively collected database. Patients were separated into two cohorts based on revision diagnosis: (1) rRSA due to infection (rRSAi), and (2) rRSA due to non-infectious causes (rRSAn). Patient-reported outcome scores (PROs), including the Simple Shoulder Test (SST), Constant score, American Shoulder and Elbow Surgeons (ASES) score, University of California-Los Angeles (UCLA), Shoulder Arthroplasty Smart score (SAS), and active range of motion (ROM) were collected preoperatively and at a minimum one year follow-up. Postoperative complications and revision rates were also collected. RESULTS: A total of 93 patients (n=19 rRSAi group, n=74 rRSAn group) with a mean age of 68 years were included in this analysis. All baseline demographics were comparable between groups. No significant differences were found in preoperative or postoperative PROs and ROM between the two groups. Postoperative complication rates and revision rates were comparable between the groups. CONCLUSION: Revision reverse shoulder arthroplasty due to infection results in similar patient-reported outcome scores, range of motion, and revision rates when compared to rRSA for non-infectious causes. Our results suggest that despite the unique challenges associated with rRSA for infection, patient outcomes do not differ from cases attributed to non-infectious causes. Further efforts are warranted to further validate and contextualize these findings, considering the protentional influence of patient-specific and implant-specific factors.

Two-year minimum survivorship and radiographic analysis of a pressfit short humeral stem for total shoulder arthroplasty.

Background: Newer generation humeral stem designs in total shoulder arthroplasty (TSA) are trending towards shorter lengths and uncemented fixation. The goal of this study is to report a 2-yr minimum clinical and radiographic outcomes of an uncemented short-stem press-fit humeral stem in anatomic total shoulder arthroplasty (ATSA) and reverse total shoulder arthroplasty (RTSA). Methods: A retrospective multicenter database review was performed of all patients who received an uncemented short-length press-fit humeral stem (Equinoxe Preserve humeral stem, Exactech, Inc., Gainesville, FL, USA) in ATSA and RTSA with a minimum two-year follow-up. The primary outcome was the prevalence of humeral stems at risk of radiographic loosening. Secondary outcomes included evaluation of functional outcome scores and prevalence of revision TSA for humeral stem loosening. Two blinded observers performed radiographic analyses, which included humeral stem alignment, canal filling ratio, radiolucent lines, stress shielding (calcar and greater tuberosity), and changes in component position (subsidence and stem shift). At risk stems were defined by the presence of one or more of the following: humeral stem with shifting or subsidence, scalloping of the humeral cortex, or radiolucent lines measuring 2 mm or greater in 3 or more zones. Results: 287 patients (97 ATSA and 190 RTSA) were included in this study. The mean follow-up was 35.9 (±6.1) months. There were significant improvements for all functional outcome scores (P < .05), range of motion (P < .05), and visual analogue pain scale pain (P < .05). The prevalence of humeral stem at risk of radiographic loosening was 1% in the ATSA group (1/97) and 18.4% in the RTSA group (35/190). Calcar resorption was seen in 34% of ATSA and 19% of RTSA, with severe resorption in 12.4% of ATSA and only 3.2% of RTSA. Greater tuberosity resorption was present in 3.1% of ATSA and 7.9% of RTSA. The mean canal filling ratio was 50.2% (standard deviation 11.2%). Using logistic regression, a significant positive correlation between canal filling ratio and stress shielding (P < .01) was seen for both calcar and tuberosity stress shielding. The revision surgery rate was 0% in ATSA compared to 1.6% in RTSA. Conclusion: This retrospective study demonstrates a low revision rate and low prevalence of humeral stems at risk of radiographic loosening at two years with a press-fit short-stem humeral design in ATSA. Physiologic subsidence of humeral stems can account for higher prevalence of humeral stems at radiographic risk of loosening in RTSA compared to ATSA.

Initial clinical experience with a predictive clinical decision support tool for anatomic and reverse total shoulder arthroplasty.

PURPOSE: Clinical decision support tools (CDSTs) are software that generate patient-specific assessments that can be used to better inform healthcare provider decision making. Machine learning (ML)-based CDSTs have recently been developed for anatomic (aTSA) and reverse (rTSA) total shoulder arthroplasty to facilitate more data-driven, evidence-based decision making. Using this shoulder CDST as an example, this external validation study provides an overview of how ML-based algorithms are developed and discusses the limitations of these tools. METHODS: An external validation for a novel CDST was conducted on 243 patients (120F/123M) who received a personalized prediction prior to surgery and had short-term clinical follow-up from 3 months to 2 years after primary aTSA (n = 43) or rTSA (n = 200). The outcome score and active range of motion predictions were compared to each patient's actual result at each timepoint, with the accuracy quantified by the mean absolute error (MAE). RESULTS: The results of this external validation demonstrate the CDST accuracy to be similar (within 10%) or better than the MAEs from the published internal validation. A few predictive models were observed to have substantially lower MAEs than the internal validation, specifically, Constant (31.6% better), active abduction (22.5% better), global shoulder function (20.0% better), active external rotation (19.0% better), and active forward elevation (16.2% better), which is encouraging; however, the sample size was small. CONCLUSION: A greater understanding of the limitations of ML-based CDSTs will facilitate more responsible use and build trust and confidence, potentially leading to greater adoption. As CDSTs evolve, we anticipate greater shared decision making between the patient and surgeon with the aim of achieving even better outcomes and greater levels of patient satisfaction.

Evaluating the fairness and accuracy of machine learning-based predictions of clinical outcomes after anatomic and reverse total shoulder arthroplasty.

BACKGROUND: Machine learning (ML)-based clinical decision support tools (CDSTs) make personalized predictions for different treatments; by comparing predictions of multiple treatments, these tools can be used to optimize decision making for a particular patient. However, CDST prediction accuracy varies for different patients and also for different treatment options. If these differences are sufficiently large and consistent for a particular subcohort of patients, then that bias may result in those patients not receiving a particular treatment. Such level of bias would deem the CDST "unfair." The purpose of this study is to evaluate the "fairness" of ML CDST-based clinical outcomes predictions after anatomic (aTSA) and reverse total shoulder arthroplasty (rTSA) for patients of different demographic attributes. METHODS: Clinical data from 8280 shoulder arthroplasty patients with 19,249 postoperative visits was used to evaluate the prediction fairness and accuracy associated with the following patient demographic attributes: ethnicity, sex, and age at the time of surgery. Performance of clinical outcome and range of motion regression predictions were quantified by the mean absolute error (MAE) and performance of minimal clinically important difference (MCID) and substantial clinical benefit classification predictions were quantified by accuracy, sensitivity, and the F1 score. Fairness of classification predictions leveraged the "four-fifths" legal guideline from the US Equal Employment Opportunity Commission and fairness of regression predictions leveraged established MCID thresholds associated with each outcome measure. RESULTS: For both aTSA and rTSA clinical outcome predictions, only minor differences in MAE were observed between patients of different ethnicity, sex, and age. Evaluation of prediction fairness demonstrated that 0 of 486 MCID (0%) and only 3 of 486 substantial clinical benefit (0.6%) classification predictions were outside the 20% fairness boundary and only 14 of 972 (1.4%) regression predictions were outside of the MCID fairness boundary. Hispanic and Black patients were more likely to have ML predictions out of fairness tolerance for aTSA and rTSA. Additionally, patients <60 years old were more likely to have ML predictions out of fairness tolerance for rTSA. No disparate predictions were identified for sex and no disparate regression predictions were observed for forward elevation, internal rotation score, American Shoulder and Elbow Surgeons Standardized Shoulder Assessment Form score, or global shoulder function. CONCLUSION: The ML algorithms analyzed in this study accurately predict clinical outcomes after aTSA and rTSA for patients of different ethnicity, sex, and age, where only 1.4% of regression predictions and only 0.3% of classification predictions were out of fairness tolerance using the proposed fairness evaluation method and acceptance criteria. Future work is required to externally validate these ML algorithms to ensure they are equally accurate for all legally protected patient groups.

Impact of accumulating risk factors on the acromial and scapular fracture rate after reverse total shoulder arthroplasty with a medialized glenoid-lateralized humerus onlay prosthesis.

BACKGROUND: Identifying risk factors for acromial and scapular fractures improves our understanding about which variables are relevant to these fracture complications; however, these data are difficult to integrate into clinical practice because the majority of reverse total shoulder arthroplasty (rTSA) patients have ≥1 risk factor. The goal of this study was to better facilitate preoperative identification of patients at risk of acromial and scapular fractures and quantify the impact of accumulating risk factors on the incidence of fracture. METHODS: We retrospectively analyzed 9079 rTSA patients from a multicenter database of rTSA procedures performed with a single medialized glenoid-lateralized humerus onlay rTSA prosthesis to quantify the rate of acromial and scapular fractures. Univariate and multivariate analyses were performed to identify risk factors for fracture. Next, we quantified the number of patients with 1 or multiple significant risk factors for fracture. Finally, to facilitate preoperative identification of patients most at risk of fracture, we stratified our data set using multiple combinations of age, sex, and diagnosis risk factors and calculated the odds ratio for each cohort to quantify the impact of accumulating risk factors on the incidence of fracture. RESULTS: A fracture of the acromion or scapula was radiographically identified in 138 of 9079 patients, for a rate of 1.52%. Patients with fractures were more likely to be older, of female sex, to have a diagnosis of rheumatoid arthritis and/or cuff tear arthropathy, and were less likely to have a diagnosis of diabetes. Eighty-five percent of rTSA patients had ≥1 fracture risk factor. Individually, age, sex, or diagnosis failed to identify any patient cohort with an odds ratio >2.5. Use of multiple combinations of patient risk factors refined the identification of at-risk patients better than any individual risk factor or 2-risk factor combination and demonstrated that the patients with the greatest fracture risk were female patients with a rheumatoid arthritis diagnosis who were aged >70, >75, and >80 years. CONCLUSION: This 9079-rTSA multicenter study demonstrated that 1.52% of patients experienced acromial and/or scapular fractures with a single medialized glenoid-lateralized humerus onlay rTSA prosthesis. Our analysis identified numerous risk factors and quantified the impact of accumulating risk factors on fracture incidence. Patients who are considering rTSA and who have these age, sex, and diagnosis risk factors should be made aware of their elevated complication risk.

Longitudinal analysis of shoulder arthroplasty utilization, clinical outcomes, and value: a comparative assessment of changes in improvement over 15 years with a single platform shoulder prosthesis.

BACKGROUND: The goal of this longitudinal analysis of anatomic total shoulder arthroplasty (aTSA) and reverse total shoulder arthroplasty (rTSA) utilization from 2007 to 2021 is to quantify changes in clinical outcomes, cost, and value, resulting from the introduction and adoption of new shoulder arthroplasty (SA) technologies. METHODS: We analyzed an international database of a single SA prosthesis (Equinoxe; Exactech, Inc.; Gainesville, FL, USA) for all clinical sites that have continuously enrolled cases from 2007 to 2021 to compare changes in primary aTSA and primary rTSA utilization and outcomes across 3, 5-year cohorts based upon the date of implantation. A value analysis was conducted across the 5-year implantation cohorts, with value measured by the ratio of each postoperative outcome measure at 24-36 months and 36-60 months after surgery, and the average implant selling price each year for the U.S. sites in constant 2007 U.S. dollars. These measures of value were compared between cohorts to quantify the impact of new technology introduced over the study period. RESULTS: A dramatic increase in rTSA utilization was observed across the 6 sites over the 15-year study period, along with a rapid adoption of new aTSA and rTSA technologies. The average patient receiving primary aTSA and primary rTSA changed over the 15-year study period, with significant shifts in diagnosis, comorbidities, and preoperative functional status. A comparison of postoperative results demonstrated that both aTSA and rTSA clinical and radiographic outcomes showed improvement relative to 2007-2011. Over this 15-year study period, the average aTSA implant selling price has been relatively stable while the average rTSA implant selling price has significantly declined. As a result, the value associated with the Equinoxe rTSA significantly increased for nearly every outcome measure at 24-36 months and 36-60 months after surgery, while value associated with the Equinoxe aTSA stayed relatively constant from 2007 to 2021. CONCLUSION: Our 6042-patient longitudinal analysis quantified numerous changes in utilization, outcomes, and value across 6 clinical sites over the 15-year study period. Rapid adoption of new aTSA and rTSA technologies was observed and clinical and radiographic outcomes improved relative to 2007-2011. These clinical improvements, in combination with steady aTSA and declining rTSA implant prices, have driven rTSA value to continuously increase while aTSA value has been maintained at a high-level over the 15-year study period with this particular SA system, even when considering the cost and adoption of new technologies.

Augmented baseplates yield optimum outcomes when compared with bone graft augmentation for managing glenoid deformity during reverse total shoulder arthroplasty: a retrospective comparative study.

PURPOSE: The purpose of this study was to compare the outcomes of primary reverse total shoulder arthroplasty (rTSA) using glenoid bone grafting (BG rTSA) with primary rTSA using augmented glenoid baseplates (Aug rTSA) with a minimum 2-year follow-up. METHODS: A total of 520 primary rTSA patients treated with 8° posterior glenoid augments (n = 246), 10° superior glenoid augments (n = 97), or combined 10° superior/8° posterior glenoid augments (n = 177) were compared with 47 patients undergoing glenoid bone grafting for glenoid bone insufficiency. The mean follow-up was 37.0(±16) and 53.0(±27) months, respectively. Outcomes were analyzed preoperatively and at the latest follow-up using conventional statistics and stratification by minimum clinically important difference (MCID) and substantial clinical benefit (SCB) thresholds where applicable. Radiographs were analyzed for baseplate failure, and the incidences of postoperative complications and revisions were recorded. RESULTS: The glenoid Aug rTSA cohort had greater improvements in patient-reported outcome measures (PROMs) and range of motion when compared with the BG rTSA group at a minimum of 2-year follow-up, including Simple Shoulder Test, Constant score, American Shoulder and Elbow Surgeons score, University of California Los Angeles score, Shoulder Pain and Disability Index score, shoulder function, Shoulder Arthroplasty Smart score, abduction, and external rotation (P < .05). Patient satisfaction was higher in the Aug rTSA group compared with the BG rTSA group (P = .006). The utilization of an augmented glenoid component instead of glenoid bone grafting resulted in approximately 50% less total intraoperative time (P < .001), nearly 33% less intraoperative blood loss volume (P < .001), approximately 3-fold less scapular notching (P < .01), and approximately 8-fold less adverse events requiring revision (P < .01) when compared with the BG rTSA cohort. Aside from SCB for abduction, the Aug rTSA cohort achieved higher rates of exceeding MCID and SCB for every PROM compared with BG rTSA. More specifically, 77.6% and 70.2% of the Aug rTSA achieved SCB for American Shoulder and Elbow Surgeons and Shoulder Pain and Disability Index vs. 55% and 48.6% in the BG rTSA, respectively (P = .003 and P = .013). CONCLUSION: The present midterm clinical and radiographic study demonstrates that the utilization of an augmented baseplate for insufficient glenoid bone stock is superior as judged by multiple PROMs and range of motion metrics when compared with bone graft augmentation at minimum 2-year follow-up. In addition, when analyzed according to MCID and SCB thresholds, the use of augmented baseplates outperforms the use of glenoid bone grafting. Complication and revision rates also favor the use of augmented glenoid baseplates over glenoid bone grafting. Long-term clinical and radiographic follow-up is necessary to confirm that these promising midterm results are durable.

Using machine learning to predict internal rotation after anatomic and reverse total shoulder arthroplasty.

BACKGROUND: Improvement in internal rotation (IR) after anatomic (aTSA) and reverse (rTSA) total shoulder arthroplasty is difficult to predict, with rTSA patients experiencing greater variability and more limited IR improvements than aTSA patients. The purpose of this study is to quantify and compare the IR score for aTSA and rTSA patients and create supervised machine learning that predicts IR after aTSA and rTSA at multiple postoperative time points. METHODS: Clinical data from 2270 aTSA and 4198 rTSA patients were analyzed using 3 supervised machine learning techniques to create predictive models for internal rotation as measured by the IR score at 6 postoperative time points. Predictions were performed using the full input feature set and 2 minimal input feature sets. The mean absolute error (MAE) quantified the difference between actual and predicted IR scores for each model at each time point. The predictive accuracy of the XGBoost algorithm was also quantified by its ability to distinguish which patients would achieve clinical improvement greater than the minimal clinically important difference (MCID) and substantial clinical benefit (SCB) patient satisfaction thresholds for IR score at 2-3 years after surgery. RESULTS: rTSA patients had significantly lower mean IR scores and significantly less mean IR score improvement than aTSA patients at each postoperative time point. Both aTSA and rTSA patients experienced significant improvements in their ability to perform activities of daily living (ADLs); however, aTSA patients were significantly more likely to perform these ADLs. Using a minimal feature set of preoperative inputs, our machine learning algorithms had equivalent accuracy when predicting IR score for both aTSA (0.92-1.18 MAE) and rTSA (1.03-1.25 MAE) from 3 months to >5 years after surgery. Furthermore, these predictive algorithms identified with 90% accuracy for aTSA and 85% accuracy for rTSA which patients will achieve MCID IR score improvement and predicted with 85% accuracy for aTSA patients and 77% accuracy for rTSA which patients will achieve SCB IR score improvement at 2-3 years after surgery. DISCUSSION: Our machine learning study demonstrates that active internal rotation can be accurately predicted after aTSA and rTSA at multiple postoperative time points using a minimal feature set of preoperative inputs. These predictive algorithms accurately identified which patients will, and will not, achieve clinical improvement in IR score that exceeds the MCID and SCB patient satisfaction thresholds.

Equal care for all? Do surgical outcomes in shoulder arthroplasty depend on insurance type?

BACKGROUND: Although it has been shown that Medicare populations have a higher overall rate of complications than those with private insurances for large cohort total joint studies, there is limited information comparing patient-reported outcomes (PROs) among private insurance patients. The purpose of this study was to determine the impact of non-Medicaid insurance type on outcomes after shoulder arthroplasty. METHODS: This retrospective case-controlled study included 203 patients who underwent shoulder arthroplasty from 2012 to 2017 by a single surgeon. Preoperative and postoperative PROs were collected and included the Simple Shoulder Test, the American Shoulder and Elbow Surgeons Shoulder Assessment Form, and the Constant Shoulder Score. Patients were categorized into groups based on insurer-preferred provider organization, health maintenance organization, Medicare, and Veterans Affairs Care program-and outcomes were compared between groups. RESULTS: The 4 insurance provider groups were matched for body mass index, surgery type, and comorbidities (P = .526). Preoperatively, no significant differences in PROs between groups were present except for the Constant Shoulder Score (P = .029). All payer groups significantly improved from preoperative to postoperative PROs (P ≤ .001). At the final follow-up, no significant difference in PROs between groups were seen (American Shoulder and Elbow Surgeons Shoulder mean 75.3 ± 20.9 [P = .757], Simple Shoulder Test of 9.1 ± 2.9 [P = .312], and Constant Shoulder Score of 65.0 ± 15.2 [P = .526]). CONCLUSIONS: Our results suggest variations in insurance type did not significantly impact outcomes for our cohort of patients undergoing shoulder arthroplasty. Although variations in patient cohorts exist, patients regardless of insurance type and coverage variations can expect significant improvements in their function and pain after shoulder arthroplasty.

Development and validation of a predictive model for outcomes in shoulder arthroplasty: a multicenter analysis of nearly 2000 patients.

BACKGROUND: Guiding expectations following shoulder arthroplasty is important in improving patient satisfaction. The purpose of this study was to develop a predictive model to calculate 2-year American Shoulder and Elbow Surgeons (ASES) scores in shoulder arthroplasty patients from a comprehensive set of preoperative patient factors and types of arthroplasty performed. METHODS: This retrospective multicenter study included 1947 shoulder arthroplasties performed from 2010 to 2015 at 3 high-volume centers. Twenty-six variables were evaluated for an association with 2-year ASES scores, and variables with P < .20 in our pair-wise analysis were used to develop a predictive model. The prediction root-mean-square error was calculated. External validation was performed using data from 233 patients who underwent shoulder arthroplasty performed by a separate shoulder surgeon at a center not involved with creation of the predictive model. RESULTS: A total of 1947 patients were analyzed, and their data were used to construct the predictive model. Variables most associated with 2-year ASES scores were patient age, preoperative ASES score, disability, chronic obstructive pulmonary disease, alcohol use, anatomic vs. reverse total shoulder arthroplasty, and primary vs. revision shoulder arthroplasty. By use of cross validation, the prediction error was 20.1, the proportion of variance explained was 25.3%, the mean absolute error was 15.9, and the C statistic for the linear regression model was 0.66. After external validation, the mean difference between predicted and actual 2-year ASES scores was 12.7 points, within the accepted minimal clinically important difference after shoulder arthroplasty. DISCUSSION: Data from nearly 2000 shoulder arthroplasties allowed the development and validation of a model to predict 2-year ASES scores following shoulder arthroplasty. The model was accurate within the minimal clinically important difference in 85% of patients.

Risk factors for complications and revision surgery after anatomic and reverse total shoulder arthroplasty.

BACKGROUND: Complications and revisions following anatomic (aTSA) and reverse (rTSA) total shoulder arthroplasty have deleterious effects on patient function and satisfaction. The purpose of this study is to evaluate patient-specific, implant-specific and technique-specific risk factors for intraoperative complications, postoperative complications, and the occurrence of revisions after aTSA and rTSA. METHODS: A total of 2964 aTSA and 5616 rTSA patients were enrolled in an international database of primary shoulder arthroplasty. Intra- and postoperative complications, as well as revisions, were reported and evaluated. Multivariate analyses were performed to quantify the risk factors associated with complications and revisions. RESULTS: aTSA patients had a significantly higher complication rate (P = .0026) and a significantly higher revision rate (P < .0001) than rTSA patients, but aTSA patients also had a significantly longer average follow-up (P < .0001) than rTSA patients. No difference (P = .2712) in the intraoperative complication rate was observed between aTSA and rTSA patients. Regarding intraoperative complications, female sex (odds ratio [OR] 2.0, 95% confidence interval [CI] 1.17-3.68) and previous shoulder surgery (OR 2.9, 95% CI 1.73-4.90) were identified as significant risk factors. In regard to postoperative complications, younger age (OR 0.987, 95% CI 0.977-0.996), diagnosis of rheumatoid arthritis (OR 1.76, 95% 1.12-2.65), and previous shoulder surgery (OR 1.42, 95% CI 1.16-1.72) were noted to be risks factors. Finally, in regard to revision surgery, younger age (OR 0.964, 95% CI 0.933-0.998), more glenoid retroversion (OR 1.03, 95% CI 1.001-1.058), larger humeral stem size (OR 1.09, 95% CI 1.01-1.19), larger humeral liner thickness or offset (OR 1.50, 95% CI 1.18-1.96), larger glenosphere diameter (OR 1.16, 95% CI 1.07-1.26), and more intraoperative blood loss (OR 1.002, 95% CI 1.001-1.004) were noted to be risk factors. CONCLUSIONS: Studying the impact of numerous patient- and implant-specific risk factors and determining their impact on complications and revision shoulder arthroplasty can assist surgeons in counseling patients and guide patient expectations following aTSA or rTSA. Care should be taken in patients with a history of previous shoulder surgery, who are at increased risk of both intra- and postoperative complications.

Validation of a machine learning-derived clinical metric to quantify outcomes after total shoulder arthroplasty.

BACKGROUND: We propose a new clinical assessment tool constructed using machine learning, called the Shoulder Arthroplasty Smart (SAS) score to quantify outcomes following total shoulder arthroplasty (TSA). METHODS: Clinical data from 3667 TSA patients with 8104 postoperative follow-up reports were used to quantify the psychometric properties of validity, responsiveness, and clinical interpretability for the proposed SAS score and each of the Simple Shoulder Test (SST), Constant, American Shoulder and Elbow Surgeons Standardized Shoulder Assessment Form (ASES), University of California Los Angeles (UCLA), and Shoulder Pain and Disability Index (SPADI) scores. RESULTS: Convergent construct validity was demonstrated, with all 6 outcome measures being moderately to highly correlated preoperatively and highly correlated postoperatively when quantifying TSA outcomes. The SAS score was most correlated with the UCLA score and least correlated with the SST. No clinical outcome score exhibited significant floor effects preoperatively or postoperatively or significant ceiling effects preoperatively; however, significant ceiling effects occurred postoperatively for each of the SST (44.3%), UCLA (13.9%), ASES (18.7%), and SPADI (19.3%) measures. Ceiling effects were more pronounced for anatomic than reverse TSA, and generally, men, younger patients, and whites who received TSA were more likely to experience a ceiling effect than TSA patients who were female, older, and of non-white race or ethnicity. The SAS score had the least number of patients with floor and ceiling effects and also exhibited no response bias in any patient characteristic analyzed in this study. Regarding clinical interpretability, patient satisfaction anchor-based thresholds for minimal clinically importance difference and substantial clinical benefit were quantified for all 6 outcome measures; the SAS score thresholds were most similar in magnitude to the Constant score. Regarding responsiveness, all 6 outcome measures detected a large effect, with the UCLA exhibiting the most responsiveness and the SST exhibiting the least. Finally, each of the SAS, ASES, Constant, and SPADI scores had similarly large standardized response mean and effect size responsiveness. DISCUSSION: The 6-question SAS score is an efficient TSA-specific outcome measure with equivalent or better validity, responsiveness, and clinical interpretability as 5 other historical assessment tools. The SAS score has an appropriate response range without floor or ceiling effects and without bias in any target patient characteristic, unlike the age, gender, or race/ethnicity bias observed in the ceiling scores with the other outcome measures. Because of these substantial benefits, we recommend the use of the new SAS score for quantifying TSA outcomes.

Using machine learning to predict clinical outcomes after shoulder arthroplasty with a minimal feature set.

BACKGROUND: A machine learning analysis was conducted on 5774 shoulder arthroplasty patients to create predictive models for multiple clinical outcome measures after anatomic total shoulder arthroplasty (aTSA) and reverse total shoulder arthroplasty (rTSA). The goal of this study was to compare the accuracy associated with a full-feature set predictive model (ie, full model, comprising 291 parameters) and a minimal-feature set model (ie, abbreviated model, comprising 19 input parameters) to predict clinical outcomes to assess the efficacy of using a minimal feature set of inputs as a shoulder arthroplasty clinical decision-support tool. METHODS: Clinical data from 2153 primary aTSA patients and 3621 primary rTSA patients were analyzed using the XGBoost machine learning technique to create and test predictive models for multiple outcome measures at different postoperative time points via the full and abbreviated models. Mean absolute errors (MAEs) quantified the difference between actual and predicted outcomes, and each model also predicted whether a patient would experience clinical improvement greater than the patient satisfaction anchor-based thresholds of the minimal clinically important difference and substantial clinical benefit for each outcome measure at 2-3 years after surgery. RESULTS: Across all postoperative time points analyzed, the full and abbreviated models had similar MAEs for the American Shoulder and Elbow Surgeons score (±11.7 with full model vs. ±12.0 with abbreviated model), Constant score (±8.9 vs. ±9.8), Global Shoulder Function score (±1.4 vs. ±1.5), visual analog scale pain score (±1.3 vs. ±1.4), active abduction (±20.4° vs. ±21.8°), forward elevation (±17.6° vs. ±19.2°), and external rotation (±12.2° vs. ±12.6°). Marginal improvements in MAEs were observed for each outcome measure prediction when the abbreviated model was supplemented with data on implant size and/or type and measurements of native glenoid anatomy. The full and abbreviated models each effectively risk stratified patients using only preoperative data by accurately identifying patients with improvement greater than the minimal clinically important difference and substantial clinical benefit thresholds. DISCUSSION: Our study showed that the full and abbreviated machine learning models achieved similar accuracy in predicting clinical outcomes after aTSA and rTSA at multiple postoperative time points. These promising results demonstrate an efficient utilization of machine learning algorithms to predict clinical outcomes. Our findings using a minimal feature set of only 19 preoperative inputs suggest that this tool may be easily used during a surgical consultation to improve decision making related to shoulder arthroplasty.

Opioid requirement after rotator cuff repair is low with a multimodal approach to pain.

BACKGROUND: Current practices may aim to blunt rather than understand postoperative pain. Perhaps the most common serious complication of arthroscopic rotator cuff repair (ARCR) is persistence of opiate medication intake. Patients still receive upwards of 80 oxycodone 5 mg pills, or 600 morphine milligram equivalents (MMEs), leading more than 20% of opioid-naïve subjects to continue to fill opioid prescriptions beyond 180 days after surgery. Developing evidence-based guidelines for narcotic prescription after ARCR presents an opportunity for orthopedic surgeons to address the opioid epidemic. PURPOSE: The purpose of this study was (1) to prospectively determine the requirements for opiate medications after ARCR, and (2) to create an evidence-based guideline for postoperative prescription, in contrast to the anecdotal or expert panel recommendations that currently exist. We further investigated whether a liposomal bupivacaine (LB) interscalene never block (ISNB) would reduce pain and opiate consumption compared with standard bupivacaine ISNB (control) for ARCR. METHODS: The study enrolled 100 patients who underwent primary ARCR surgery. Patients were provided with postoperative "pain journals" to document their daily pain on a numerical rating scale, satisfaction with pain management using the Likert scale, and track their daily oxycodone 5 mg pill consumption during the 14-day postoperative period. Enrolled patients were further randomized to receiving an LB (experimental) or standard bupivacaine (control) ISNB. RESULTS: A total of 77% of all patients required fewer than 15 pills postoperatively. The LB group consumed an average of 1.7 fewer pills (13.0 MMEs) on postoperative day (POD) 1 (P = .02) and reported statistically lower pain during PODs 1 and 2 (P = .01 and P = .006), as well as cumulatively throughout the study period (P = .03). In addition, LB patients remained opioid-free at a higher rate (44% vs. 15% in controls, P = .03). CONCLUSION: With a multimodal approach, the majority of patients undergoing ARCR can manage postoperative pain with 15 or fewer oxycodone 5 mg tablets (112.5 MMEs) and maintain a high degree of satisfaction. The addition of an LB ISNB may further reduce the consumption of postoperative narcotics compared with a standard ISNB. This study provides evidence that may be used for surgeon guidelines in the effort to reduce opioid prescriptions after ARCR.

Preoperative external rotation deficit does not predict poor outcomes or lack of improvement after reverse total shoulder arthroplasty.

INTRODUCTION: The purpose was to compare postoperative outcomes and functional improvement between patients with preoperative aER deficits vs. preserved aER function. RESULTS: There were 115 patients in the <0° aER group and 314 in the ≥30° aER group. Preoperative patients in the <0° group were worse for all measures except subjective pain while post-operatively, they had significantly greater improvement for all measures of motion. Postoperatively, both groups achieved comparable scores for forward elevation, pain, SST and ASES. CONCLUSION: This study demonstrates that patients with a complete aER deficit can recover substantial and comparable function after RTSA.

The influence of preoperative external rotation weakness or stiffness on reverse total shoulder arthroplasty.

BACKGROUND: Some reverse total shoulder arthroplasty (rTSA) patients may have limited preoperative external rotation (ER) because of stiffness or weakness. Currently it is not known if this affects their clinical outcome or if their ER will improve after surgery. METHODS: A multicenter shoulder arthroplasty database was queried to analyze patients undergoing a primary rTSA using a single prosthesis design featuring a medial glenoid-lateral humerus. Their pre- and postoperative range of motion was evaluated in addition to 5 outcome measures. Patients with limited preoperative ER due to weakness or stiffness were compared to patients with normal preoperative range of motion. The following questions were asked: (1) Does a preoperative ER deficit impact the postoperative outcome? (2) Do patients with preoperative ER deficits due to stiffness or weakness regain ER after rTSA? and (3) Does a preoperative ER lag sign predict a poor outcome? RESULTS: 608 patients were included in this study. Active external rotation (preoperative/postoperative) was as follows for the 3 patient groups: Normal patients (45°/44°), Stiff (-4°/30°), and Weak (16°/32°). Weak patients had a preoperative ER lag of 30°, which improved by 16° after surgery. The clinical outcome scores for all 3 groups improved after rTSA. Stiff patients had significantly greater improvement than Weak and Normal patients. Outcome scores were equivalent for Normal and Stiff patients. Weak patients tended to have slightly lower outcome scores. CONCLUSIONS: Patients with limited preoperative ER can obtain a good clinical result with rTSA using a medial glenoid-lateral humerus prosthesis, ER range of motion can improve after rTSA, and stiff patients have a particularly good prognosis for recovery.

What Is the Accuracy of Three Different Machine Learning Techniques to Predict Clinical Outcomes After Shoulder Arthroplasty?

BACKGROUND: Machine learning techniques can identify complex relationships in large healthcare datasets and build prediction models that better inform physicians in ways that can assist in patient treatment decision-making. In the domain of shoulder arthroplasty, machine learning appears to have the potential to anticipate patients' results after surgery, but this has not been well explored. QUESTIONS/PURPOSES: (1) What is the accuracy of machine learning to predict the American Shoulder and Elbow Surgery (ASES), University of California Los Angeles (UCLA), Constant, global shoulder function, and VAS pain scores, as well as active abduction, forward flexion, and external rotation at 1 year, 2 to 3 years, 3 to 5 years, and more than 5 years after anatomic total shoulder arthroplasty (aTSA) or reverse total shoulder arthroplasty (rTSA)? (2) What is the accuracy of machine learning to identify whether a patient will achieve clinical improvement that exceeds the minimum clinically important difference (MCID) threshold for each outcome measure? (3) What is the accuracy of machine learning to identify whether a patient will achieve clinical improvement that exceeds the substantial clinical benefit threshold for each outcome measure? METHODS: A machine learning analysis was conducted on a database of 7811 patients undergoing shoulder arthroplasty of one prosthesis design to create predictive models for multiple clinical outcome measures. Excluding patients with revisions, fracture indications, and hemiarthroplasty resulted in 6210 eligible primary aTSA and rTSA patients, of whom 4782 patients with 11,198 postoperative follow-up visits had sufficient preoperative, intraoperative, and postoperative data to train and test the predictive models. Preoperative clinical data from 1895 primary aTSA patients and 2887 primary rTSA patients were analyzed using three commercially available supervised machine learning techniques: linear regression, XGBoost, and Wide and Deep, to train and test predictive models for the ASES, UCLA, Constant, global shoulder function, and VAS pain scores, as well as active abduction, forward flexion, and external rotation. Our primary study goal was to quantify the accuracy of three machine learning techniques to predict each outcome measure at multiple postoperative timepoints after aTSA and rTSA using the mean absolute error between the actual and predicted values. Our secondary study goals were to identify whether a patient would experience clinical improvement greater than the MCID and substantial clinical benefit anchor-based thresholds of patient satisfaction for each outcome measure as quantified by the model classification parameters of precision, recall, accuracy, and area under the receiver operating curve. RESULTS: Each machine learning technique demonstrated similar accuracy to predict each outcome measure at each postoperative point for both aTSA and rTSA, though small differences in prediction accuracy were observed between techniques. Across all postsurgical timepoints, the Wide and Deep technique was associated with the smallest mean absolute error and predicted the postoperative ASES score to ± 10.1 to 11.3 points, the UCLA score to ± 2.5 to 3.4, the Constant score to ± 7.3 to 7.9, the global shoulder function score to ± 1.0 to 1.4, the VAS pain score to ± 1.2 to 1.4, active abduction to ± 18 to 21°, forward elevation to ± 15 to 17°, and external rotation to ± 10 to 12°. These models also accurately identified the patients who did and did not achieve clinical improvement that exceeded the MCID (93% to 99% accuracy for patient-reported outcome measures (PROMs) and 85% to 94% for pain, function, and ROM measures) and substantial clinical benefit (82% to 93% accuracy for PROMs and 78% to 90% for pain, function, and ROM measures) thresholds. CONCLUSIONS: Machine learning techniques can use preoperative data to accurately predict clinical outcomes at multiple postoperative points after shoulder arthroplasty and accurately risk-stratify patients by preoperatively identifying who may and who may not achieve MCID and substantial clinical benefit improvement thresholds for each outcome measure. CLINICAL RELEVANCE: Three different commercially available machine learning techniques were used to train and test models that predicted clinical outcomes after aTSA and rTSA; this device-type comparison was performed to demonstrate how predictive modeling techniques can be used in the near future to help answer unsolved clinical questions and augment decision-making to improve outcomes after shoulder arthroplasty.

Patient-reported outcomes of reverse total shoulder arthroplasty: a comparative risk factor analysis of improved versus unimproved cases.

BACKGROUND: The purpose of this study was to compare characteristics of patients who reported to be subjectively unimproved vs. improved after reverse total shoulder arthroplasty. METHODS: Data were derived from a prospective registry of patients who underwent reverse total shoulder arthroplasty with a minimum 2-year follow-up. Patients were asked to rate their subjective satisfaction and then divided into those who were unchanged or worse (unimproved group [UG]) vs. better or much better (improved group [IG]). The groups were compared for differences in demographic characteristics, preoperative factors, functional outcomes, and complications. RESULTS: There were 1425 patients in the IG and 134 patients in the UG. Patients in the IG were more likely to have a diagnosis of osteoarthritis. Patients in the UG were more likely to have coronary artery disease and diabetes and to have undergone prior surgery. No differences in implant configuration were found between groups. Preoperative measures for patients in the UG were worse for pain and function but not for range of motion. The outcomes in patients in the UG were worse for all postoperative measures, as well as for preoperative-to-postoperative improvement. Of the patients in the UG, 48% continued to have moderate to severe pain postoperatively. The complication rate was significantly higher in the UG. DISCUSSION: Up to 8.5% of patients rate themselves as unimproved after surgery. These patients are more likely to have certain comorbidities and to have undergone prior surgery. Although outcomes were significantly worse for all measures in the UG, improvement occurred in all measures despite patients subjectively being worse or unchanged. Residual pain and difficulty sleeping play a substantial role in subjective assessment of overall outcome.

Effect of Tuberosity Healing on Clinical Outcomes in Elderly Patients Treated With a Reverse Shoulder Arthroplasty for 3- and 4-Part Proximal Humerus Fractures.

OBJECTIVES: To evaluate tuberosity union rate and clinical outcome after 3- and 4-part proximal humerus fractures in the elderly. DESIGN: Retrospective, multicenter database cohort study. SETTING: Level I and Level II trauma centers. PATIENTS: Fifty-five patients older than 65 years had insertion of reverse shoulder arthroplasty (RTSA) for OTA/AO 11-B and 11-C proximal humerus fractures. INTERVENTION: Treatment with RTSA using a dedicated low profile onlay fracture stem using variable tuberosity fixation. MAIN OUTCOME MEASURES: Constant score, the American Shoulder and Elbow Surgeons score, Shoulder Pain and Disability Index score, University of California at Los Angeles score, Simple Shoulder Test score, visual analog pain score, shoulder function score, active range of motion, external rotation (ER)-specific tasks and position, rate of greater tuberosity healing, effect of tuberosity healing on overall clinical metrics, incidence of humeral lucency, and scapular notching. RESULTS: Eighty-three percent of the greater tuberosities that were repaired united. Greater tuberosity union resulted in greater active ER (P = 0.0415). There was a statistically significant difference in the ability to do ER-type activities between the 2 cohorts reflected in the ability to position one's hand behind their head with the elbow forward (P = 0.002) and comb their hair (P < 0.001). CONCLUSION: The use of a low profile onlay fracture stem in RTSA for acute 3- and 4-part proximal humerus fractures in the elderly can result in a high tuberosity union rate. Greater tuberosity healing significantly influences ER and ER-type activities that are not apparent by analysis of the overall metrics studied. LEVEL OF EVIDENCE: Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.

Subscapularis-Sparing Approaches to Total Shoulder Arthroplasty: Ready for Prime Time?

To minimize the risk of subscapularis failure after shoulder replacement, a method of preserving the subscapularis while allowing access to the glenohumeral joint was developed. Only the inferior 30% to 50% of the subscapularis tendon is detached from the humerus, leaving the superior aspect attached to the lesser tuberosity. This subscapularis-sparing, minimally invasive approach to the glenohumeral joint was evaluated in 43 subjects with a minimum 2-year follow-up and subscapularis strength equal to the opposite side. The approach provided adequate exposure for shoulder replacement surgery and decreased risk of postoperative failure of the subscapularis tendon.