JSES international
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Recent "multimodal" approaches to pain, although understudied, have shown promise in reducing reliance on narcotics in shoulder arthroplasty (SA). Many surgeons report being unsure of how many narcotic pills to prescribe after the surgery. As result, patients are prescribed upwards of 60 oxycodone 5-mg pills for a 6-to-12-week treatment period despite studies showing postoperative pain can be managed without any medication at all. ⋯ With a multimodal approach, most patients undergoing SA can manage postoperative pain with 15 or fewer oxycodone 5-mg tablets, or 112.5 morphine milligram equivalents. The addition of a liposomal bupivacaine interscalene nerve block may further reduce the consumption of postoperative narcotics compared with a standard interscalene nerve block. This study provides evidence that may be used for surgeon guidelines in the effort to reduce opioid prescriptions after SA.
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Machine learning has shown potential in accurately predicting outcomes after orthopedic surgery, thereby allowing for improved patient selection, risk stratification, and preoperative planning. This study sought to develop machine learning models to predict nonhome discharge after total shoulder arthroplasty (TSA). ⋯ Both the boosted decision tree and ANN models performed well in predicting nonhome discharge with similar overall accuracy, but the ANN had higher discriminative ability. Based on the findings of this study, machine learning has the potential to accurately predict nonhome discharge after elective TSA. Surgeons can use such tools to guide patient expectations and to improve preoperative discharge planning, with the ultimate goal of decreasing hospital length of stay and improving cost-efficiency.