Prediction of suitable outpatient candidates following revision total knee arthroplasty using machine learning

Yeramosu, Teja; Ahmad, Waleed; Satpathy, Jibanananda; Farrar, Jacob M.; Golladay, Gregory J.; Patel, Nirav K.

doi:10.1302/2633-1462.46.bjo-2023-0044.r1

Cited by 9 publications

(4 citation statements)

References 43 publications

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“…Many studies on revision TAA report similar constraints, particularly within TAA, 13 but also within other forms of TJA. 4,7,11,16,22,30,33 We used only INBONE II for revision TAA, and although the INBONE II system was not designed specifically for revision TAA, it has been widely used for revision cases.…”

Section: Discussionmentioning

confidence: 99%

Revision Total Ankle Arthroplasty Using the INBONE II System

Wu,

Anastasio,

Lee

et al. 2024

Foot Ankle Int.

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Background: The utilization of total ankle arthroplasty (TAA) for managing severe ankle osteoarthritis has become increasingly common, leading to a higher occurrence of revision TAA procedures because of failure of primary TAA. This study aims to examine the clinical results associated with revision TAA using the INBONE II system. Given the growing number of TAA revision procedures and a focus on motion-preserving salvage options, we evaluated our early experience with revision TAA. Methods: A retrospective analysis was conducted on a group of 60 presumed noninfected patients who underwent revision TAA with the INBONE II system. Detailed information was collected on patient demographics, implant characteristics, concurrent procedures, and complications. The implant survival was estimated using Kaplan-Meier analysis. Results: The study revealed high complication rates but generally fair clinical outcomes for revision TAA using the INBONE II system. Complications were observed in 22 patients (36.7%), including persistent pain (n = 6), nerve injury/impingement (n = 5), infection (n = 3), fracture (n = 3), implant failure (n = 3), impaired wound healing (n = 2), and osteolysis (n = 3). The 3-year survivorship rate from reoperation was 92.0% (82.7%-100.0%) whereas the 3-year survivorship rate from major complications was 90.4% (80.8%-100.0%). Conclusion: We report high complication rates but generally fair clinical results for revision TAA utilizing the INBONE II system. Level of Evidence: Level IV, retrospective case series study.

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Section: Discussionmentioning

confidence: 99%

Revision Total Ankle Arthroplasty Using the INBONE II System

Wu,

Anastasio,

Lee

et al. 2024

Foot Ankle Int.

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“…Importantly, anticipating a patient's specific postoperative outcome and clinical trajectory requires simultaneous consideration of several different patient-specific factors. Applications of AI in preoperative evaluation include determining candidacy for surgery and identification of factors associated with achieving meaningful, patient-specific postoperative outcomes 34-60 (Table I), which may currently be the most frequent application of AI within orthopaedics. Because the current value-driven health care system places importance on clinically significant outcome improvements, PROMs serve an important role in the quantification of patient-perceived improvement and therefore help determine the quality of care that patients receive 61-65 .…”

Section: Preoperative Evaluation For Operative Planning and Patient-s...mentioning

confidence: 99%

Enabling Personalized Medicine in Orthopaedic Surgery Through Artificial Intelligence

Huffman,

Pasqualini,

Khan

et al. 2024

JBJS Reviews

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» The application of artificial intelligence (AI) in the field of orthopaedic surgery holds potential for revolutionizing health care delivery across 3 crucial domains: (I) personalized prediction of clinical outcomes and adverse events, which may optimize patient selection, surgical planning, and enhance patient safety and outcomes; (II) diagnostic automated and semiautomated imaging analyses, which may reduce time burden and facilitate precise and timely diagnoses; and (III) forecasting of resource utilization, which may reduce health care costs and increase value for patients and institutions.» Computer vision is one of the most highly studied areas of AI within orthopaedics, with applications pertaining to fracture classification, identification of the manufacturer and model of prosthetic implants, and surveillance of prosthesis loosening and failure.» Prognostic applications of AI within orthopaedics include identifying patients who will likely benefit from a specified treatment, predicting prosthetic implant size, postoperative length of stay, discharge disposition, and surgical complications. Not only may these applications be beneficial to patients but also to institutions and payors because they may inform potential cost expenditure, improve overall hospital efficiency, and help anticipate resource utilization.» AI infrastructure development requires institutional financial commitment and a team of clinicians and data scientists with expertise in AI that can complement skill sets and knowledge. Once a team is established and a goal is determined, teams (1) obtain, curate, and label data; (2) establish a reference standard; (3) develop an AI model; (4) evaluate the performance of the AI model; (5) externally validate the model, and (6) reinforce, improve, and evaluate the model's performance until clinical implementation is possible.» Understanding the implications of AI in orthopaedics may eventually lead to wide-ranging improvements in patient care. However, AI, while holding tremendous promise, is not without methodological and ethical limitations that are essential to address. First, it is important to ensure external validity of programs before their use in a clinical setting. Investigators should maintain high quality data records and registry surveillance, exercise caution when evaluating others' reported AI applications, and increase transparency of the methodological conduct of current models to improve external validity and avoid propagating bias. By addressing these challenges and responsibly embracing the potential of AI, the medical field may eventually be able to harness its power to improve patient care and outcomes.

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“…The random-forest model had the best accuracy, and variables of importance were joint-line change, postoperative femorotibial angle, and hemoglobin A1c 64 . Yeramosu et al 65 compared a multivariable logistic regression model and diverse machine learning techniques and found that 1 of the models (random forest) had an accuracy (AUC) of 0.810 for identifying candidates for same-day discharge after revision TKA. According to that model, the factors of importance for same-day discharge, in decreasing order, were operative time, anesthesia type, age, BMI, American Society of Anesthesiologists (ASA) class, race, diabetes, revision TKA type, sex, and smoking.…”

Section: Machine Learning and Artificial Intelligencementioning

confidence: 99%

What’s New in Adult Reconstructive Knee Surgery

Villa,

Hosseinzadeh,

Higuera-Rueda

2023

Journal of Bone and Joint Surgery

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In the current Guest Editorial, we evaluate and summarize the most relevant findings from recent, meaningful, peer-reviewed publications in different research areas. Articles at various Levels of Evidence were included, but increased attention was paid to Level-I and award-winning reports. EconomicsConsiderable debate continues with regard to the economics of reconstructive knee surgery. An updated Medicare projection revealed that, by 2040, the annual number of revision total knee arthroplasties (TKAs) performed would be 115,147, whereas, by 2060, it would be 286,740. These values are important for understanding the future health-care resource utilization involving revision TKA, which is only expected to increase 1 . A secondary analysis of a randomized clinical trial (RCT) evaluating health-care resource utilization up to 12 months after primary TKA, among dissatisfied and satisfied patients, showed that patients dissatisfied with their return to function incurred a mean cost of $19,007.70, compared with $13,523.83 for satisfied patients (p = 0.07). Although the cost difference was not significant, its magnitude deserves attention 2 . Data from the New Zealand Joint Registry indicated that patients undergoing TKA have a mortality rate 8% higher than that of the general population 3 . Assessing mortality after primary TKA is relevant for future economic analyses.

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Prediction of suitable outpatient candidates following revision total knee arthroplasty using machine learning

Cited by 9 publications

References 43 publications

Revision Total Ankle Arthroplasty Using the INBONE II System

Revision Total Ankle Arthroplasty Using the INBONE II System

Enabling Personalized Medicine in Orthopaedic Surgery Through Artificial Intelligence

What’s New in Adult Reconstructive Knee Surgery

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