The Use of Artificial Intelligence for the Prediction of Periprosthetic Joint Infection Following Aseptic Revision Total Knee Arthroplasty

Periprosthetic joint infection (PJI) following revision total knee arthroplasty (TKA) for aseptic failure is associated with poor outcomes, patient morbidity, and high health care expenditures. The aim of this study was to develop novel machine learning algorithms for the prediction of PJI following revision TKA for patients with aseptic indications for revision surgery. A single-institution database consisting of 1,432 consecutive revision TKA patients with aseptic etiologies was retrospectively identified. The patient cohort included 208 patients (14.5%) who underwent re-revision surgery for PJI. Three machine learning algorithms (artificial neural networks, support vector machines, k-nearest neighbors) were developed to predict this outcome and these models were assessed by discrimination, calibration, and decision curve analysis. This is a retrospective study. Among the three machine learning models, the neural network model achieved the best performance across discrimination (area under the receiver operating characteristic curve = 0.78), calibration, and decision curve analysis. The strongest predictors for PJI following revision TKA for aseptic reasons were prior open procedure prior to revision surgery, drug abuse, obesity, and diabetes. This study utilized machine learning as a tool for the prediction of PJI following revision TKA for aseptic failure with excellent performance. The validated machine learning models can aid surgeons in patient-specific risk stratifying to assist in preoperative counseling and clinical decision making for patients undergoing aseptic revision TKA.

Cost Savings Associated With Implementing 4 Total Joint Replacement Electronic Clinical Quality Measures Nationally: 2020-2040

BACKGROUND

Digital transformation using widely available electronic data is a key component to improving health outcomes and customer choice and decreasing cost and measurement burden. Despite these benefits, existing information on the potential cost savings from electronic clinical quality measures (eCQMs) is limited.

METHODS

We assessed the costs of implementing 4 eCQMs related to total hip and/or total knee arthroplasty into electronic health record systems across healthcare systems in the United States. We used published literature and technical expert panel consultation to calculate low-, mid-, and high-range hip and knee arthroplasty surgery projections, and used empirical testing, literature, and technical expert panel consultation to develop an economic model to assess projected cost savings of eCQMs when implemented nationally.

RESULTS

Low-, mid-, and high-range projected cost savings for year's 2020, 2030, and 2040 were calculated for 4 orthopedic eCQMs. Mid-range projected cost savings for 2020 ranged from $7.9 to $31.9 million per measure per year. A breakeven of between 0.5% and 5.1% of adverse events (measure dependent) must be averted for cost savings to outweigh implementation costs.

CONCLUSIONS

All measures demonstrated potential cost savings. These findings suggest that eCQMs have the potential to lower healthcare costs and improve patient outcomes without adding to physician documentation burden. The Centers for Medicare and Medicaid Services' investment in eCQMs is an opportunity to reduce adverse outcomes and excess costs in orthopedics.

Foreign body reaction to acellular dermal matrix allograft in biologic glenoid resurfacing

BACKGROUND

Biologic glenoid resurfacing is a treatment option for young patients with glenohumeral arthritis. An optimal synthetic graft for glenoid resurfacing should allow repopulation with host cells, be durable enough to tolerate suture fixation and forces across the joint, and present no host inflammatory response. We report two cases of giant cell reaction to GraftJacket(®) after biologic glenoid resurfacing.

CASE DESCRIPTION

Two patients who underwent hemiarthroplasty and biologic glenoid resurfacing using GraftJacket(®) had a foreign body giant cell reaction that required revision surgery. Intraoperatively, both patients were observed to have a well-fixed humeral component and a dense, erythematous, synovitic membrane overlying the glenoid. Pathology specimens showed a benign reactive synovium, chronic inflammation, and foreign body giant cell reaction. After débridement and conversion to total shoulder arthroplasty, both patients continued to be pain-free at greater than 1-year followup.

LITERATURE REVIEW

Multinucleated giant cell and mononuclear cell responses have been observed in an animal model after use of GraftJacket(®). Although the use of acellular matrix-based scaffold for biologic glenoid resurfacing is not new, the possibility of foreign body reaction as a source of persistent symptoms has not been described.

CLINICAL RELEVANCE

Given the lack of data to indicate an advantage to biologic resurfacing of the glenoid over hemiarthroplasty alone, resurfacing should not introduce significant additional surgical complications. We suggest foreign body reaction be considered in the differential diagnosis for a persistently painful shoulder after biologic glenoid resurfacing using an acellular allograft patch.