Does resident involvement have an impact on postoperative complications after total shoulder arthroplasty? An analysis of 1382 cases

2015 ◽  
Vol 24 (10) ◽  
pp. 1567-1573 ◽  
Author(s):  
Gregory L. Cvetanovich ◽  
William W. Schairer ◽  
Bryan D. Haughom ◽  
Gregory P. Nicholson ◽  
Anthony A. Romeo
2022 ◽  
pp. 175857322110654
Author(s):  
Hasani W Swindell ◽  
Alirio J deMeireles ◽  
Jack R Zhong ◽  
Elise C. Bixby ◽  
Bryan M Saltzman ◽  
...  

Background There is minimal work defining the economic impact of resident participation in shoulder arthroplasty. Thus, this study quantified the opportunity cost of resident participation in total shoulder arthroplasty (TSA) and hemiarthroplasty (HA) by determining differences in operative time, relative value units (RVUs)/hour, and RVUs/case. Methods A retrospective analysis of shoulder arthroplasty procedures were identified from the ACS-NSQIP database from 2006 to 2014 using CPT codes. Demographic, comorbidity, preoperative laboratory data and surgical procedure were used to develop matched cohorts. Mean differences in operative time, RVUs/case and RVUs/hour between attending-only (AO) cases and cases with resident involvement (RI) were examined. Cost analysis was performed to identify differences in RVUs generated per hour in dollars/case. Results A total of 1786 AO and 1102 RI cases were identified. With the exception of PGY-3 and PGY-4 cases, RI cases had lower mean operative times compared to AO cases. The cost of RI was highest for PGY-3 ($199.87 per case) and PGY-4 ($9 .2 9) residents with all other postgraduate years providing a cost reduction. Discussion Involvement of residents was associated with shorter operative times leading to a savings of $29.64 per case. Involvement of intermediate-level (PGY-3) residents were associated with increased costs that ultimately decreased as residents became more senior.


2017 ◽  
Vol 14 (1) ◽  
pp. 23-28 ◽  
Author(s):  
Venkat Boddapati ◽  
Michael C. Fu ◽  
William W. Schairer ◽  
Lawrence V. Gulotta ◽  
David M. Dines ◽  
...  

2019 ◽  
Vol 28 (12) ◽  
pp. e410-e421 ◽  
Author(s):  
Anirudh K. Gowd ◽  
Avinesh Agarwalla ◽  
Nirav H. Amin ◽  
Anthony A. Romeo ◽  
Gregory P. Nicholson ◽  
...  

2021 ◽  
Vol 5 ◽  
pp. 247154922110381
Author(s):  
Sai K. Devana ◽  
Akash A. Shah ◽  
Changhee Lee ◽  
Varun Gudapati ◽  
Andrew R. Jensen ◽  
...  

Background Reverse total shoulder arthroplasty (rTSA) offers tremendous promise for the treatment of complex pathologies beyond the scope of anatomic total shoulder arthroplasty but is associated with a higher rate of major postoperative complications. We aimed to design and validate a machine learning (ML) model to predict major postoperative complications or readmission following rTSA. Methods We retrospectively reviewed California's Office of Statewide Health Planning and Development database for patients who underwent rTSA between 2015 and 2017. We implemented logistic regression (LR), extreme gradient boosting (XGBoost), gradient boosting machines, adaptive boosting, and random forest classifiers in Python and trained these models using 64 binary, continuous, and discrete variables to predict the occurrence of at least one major postoperative complication or readmission following primary rTSA. Models were validated using the standard metrics of area under the receiver operating characteristic (AUROC) curve, area under the precision–recall curve (AUPRC), and Brier scores. The key factors for the top-performing model were determined. Results Of 2799 rTSAs performed during the study period, 152 patients (5%) had at least 1 major postoperative complication or 30-day readmission. XGBoost had the highest AUROC and AUPRC of 0.681 and 0.129, respectively. The key predictive features in this model were patients with a history of implant complications, protein-calorie malnutrition, and a higher number of comorbidities. Conclusion Our study reports an ML model for the prediction of major complications or 30-day readmission following rTSA. XGBoost outperformed traditional LR models and also identified key predictive features of complications and readmission.


2019 ◽  
Vol 3 (2) ◽  
pp. 99-107 ◽  
Author(s):  
Brandon E. Lung ◽  
Shrey Kanjiya ◽  
Michael Bisogno ◽  
David E. Komatsu ◽  
Edward D. Wang

2021 ◽  
pp. 175857322110273
Author(s):  
Puneet Gupta ◽  
Theodore Quan ◽  
Zachary R Zimmer

Background Octogenarians are at an increased risk of morbidity and mortality following various surgeries, but this has not yet been well explored in octogenarians undergoing revision total shoulder arthroplasty (RTSA). Thus, the purpose of this study was to analyze whether octogenarians undergoing RTSA are at an increased risk of 30-day postoperative complications, readmissions, and mortality relative to the younger geriatric population. Methods Data of patients who underwent RTSA from 2013 to 2018 were obtained from a large de-identified database. Patients were divided into two cohorts: ages 65–79 and ages 80–89. Demographic data, comorbidities, and postoperative complications were collected and compared between the two cohorts. Bivariate and multivariate analyses were performed. Results On bivariate analyses, patients aged 80–89 were more likely to develop pulmonary embolism (p = 0.014) and extended length of stay more than 3 days (p = 0.006) compared to the cohort aged 65–79. Following adjustment on multivariate analyses, 80–89 years old patients no longer had an increased likelihood of pulmonary embolism or extended length of stay compared to the 65–79 age group. Octogenarians were not found to have higher rates of 30-day readmissions (p = 0.782), mortality (p = 0.507), reoperation (p = 0.785), pneumonia (p = 0.417), urinary tract infection (p = 0.739), or sepsis (p = 0.464) compared to the cohort aged 65–79 following RTSA. Conclusion Age greater than 80 should not be used independently as a factor for evaluating whether a geriatric patient is a proper candidate for RTSA.


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