The purpose of this randomized controlled trial was to compare the performance of 3 total knee joint replacement (TKJR) designs 6 months after the surgery. Patients were recruited between March 2015 and March 2018. Patients with osteoarthritis consented for TKJR were randomly allocated to a medial stabilized (MS), cruciate retaining (CR), or posterior stabilized (PS) design. Primary outcome measures were self-reported improvement in pain and function 6 months after TKJR, using the Oxford Knee Score. Secondary outcome measures were the Western Ontario and McMaster Universities Osteoarthritis Index, Veterans RAND 12-item Health Survey, Knee Society Score 2011, Timed Up and Go test, and Six-Minute Walk Test. Twelve-month outcomes were also measured. Ninety participants enrolled, 83 were randomized: PS (n = 26), CR (n = 28), and MS (n = 29) designs. One case withdrew before surgery: planned use of non-study implant; 7 did not complete all outcome measures. No 6-month between-group difference was observed for the primary outcome. A 6-month difference was observed in Knee Society Score 2011 Satisfaction: MS favored over CR and PS. Clinically meaningful 12-month differences in Western Ontario and McMaster Universities Osteoarthritis Index Pain, Function, and Global Subscales were observed: MS favored over CR. Twelve-month differences occurred in Veterans RAND 12-item Health Survey mental well-being, favoring MS and PS over CR. MS prosthesis can be expected to yield similar clinical and functional outcomes to PS and CR designs 6 months after TKJR, and patients were more satisfied with their outcome. Compared with CR, patients with MS prosthesis also reported superior pain, function, and quality-of-life outcomes at 12 months.

Background: The use of artificial intelligence (AI) in decision-making around knee replacement surgery is increasing, and this technology holds promise to improve the prediction of patient outcomes. Ambiguity surrounds the definition of AI, and there are mixed views on its application in clinical settings. Objective: In this study, we aimed to explore the understanding and attitudes of patients who underwent knee replacement surgery regarding AI in the context of risk prediction for shared clinical decision-making. Methods: This qualitative study involved patients who underwent knee replacement surgery at a tertiary referral center for joint replacement surgery. The participants were selected based on their age and sex. Semistructured interviews explored the participants’ understanding of AI and their opinions on its use in shared clinical decision-making. Data collection and reflexive thematic analyses were conducted concurrently. Recruitment continued until thematic saturation was achieved. Results: Thematic saturation was achieved with 19 interviews and confirmed with 1 additional interview, resulting in 20 participants being interviewed (female participants: n=11, 55%; male participants: n=9, 45%; median age: 66 years). A total of 11 (55%) participants had a substantial postoperative complication. Three themes captured the participants’ understanding of AI and their perceptions of its use in shared clinical decision-making. The theme Expectations captured the participants’ views of themselves as individuals with the right to self-determination as they sought therapeutic solutions tailored to their circumstances, needs, and desires, including whether to use AI at all. The theme Empowerment highlighted the potential of AI to enable patients to develop realistic expectations and equip them with personalized risk information to discuss in shared decision-making conversations with the surgeon. The theme Partnership captured the importance of symbiosis between AI and clinicians because AI has varied levels of interpretability and understanding of human emotions and empathy. Conclusions: Patients who underwent knee replacement surgery in this study had varied levels of familiarity with AI and diverse conceptualizations of its definitions and capabilities. Educating patients about AI through nontechnical explanations and illustrative scenarios could help inform their decision to use it for risk prediction in the shared decision-making process with their surgeon. These findings could be used in the process of developing a questionnaire to ascertain the views of patients undergoing knee replacement surgery on the acceptability of AI in shared clinical decision-making. Future work could investigate the accuracy of this patient group’s understanding of AI, beyond their familiarity with it, and how this influences their acceptance of its use. Surgeons may play a key role in finding a place for AI in the clinical setting as the uptake of this technology in health care continues to grow.

An increasing number of total knee replacements (TKRs) are being performed in response to the growing burden of osteoarthritis. Patients <65 years of age represent the fastest growing group of TKR recipients and are expected to account for an increasing number of primary and revision procedures. Concerns have been raised about the outcomes that can be expected by this age demographic who are more active, physically demanding, and have longer life expectancies compared to older TKR recipients. This systematic review and meta-analysis evaluated the effectiveness of TKR for osteoarthritis in patients <65 years of age, compared to older individuals. A systematic search of Embase and Medline was conducted to identify studies which examined patient-reported outcomes measured using disease-specific and generic health-related quality of life instruments. Ten studies met our inclusion criteria and were included in this review. These studies comprised 1747 TKRs performed between 1977 and 2014. In the meta-analysis of two prospective studies (288 TKRs), patients <65 years of age were able to attain large and clinically meaningful improvements in pain, function, and quality of life. One of these studies (61 TKRs) suggested that patients <55 years of age attained a larger degree of improvement compared to older individuals. Results into the second postoperative decade were less certain, with some data suggesting a high prevalence of pain and patterns of functional decline. Further research is required to investigate longer-term outcomes following TKR for osteoarthritis in younger patients.

Purpose The St Vincent’s Melbourne Arthroplasty Outcomes (SMART) Registry is an institutional clinical registry housed at a tertiary referral hospital in Australia. The SMART Registry is a pragmatic prospective database, which was established to capture a broad range of longitudinal clinical and patient-reported outcome data to facilitate collaborative research that will improve policy and practice relevant to arthroplasty surgery for people with advanced arthritis of the hip or knee. The purpose of this cohort profile paper is to describe the rationale for the SMART Registry’s creation, its methods, baseline data and future plans for the Registry. A full compilation of the data is provided as a reference point for future collaborators. Participants The SMART Registry cohort comprises over 13 000 consecutive arthroplasty procedures in more than 10 000 patients who underwent their procedure at St Vincent’s Hospital Melbourne, since January 1998. Participant recruitment, data collection and follow-up is ongoing and currently includes up to 20 years follow-up data. Findings to date SMART Registry data are used for clinical audit and feedback, as well as for a broad range of research including epidemiological studies, predictive statistical modelling and health economic evaluations. At the time of writing, there were 46 publications from SMART Registry data, with contributions from more than 67 coauthors. Future plans With the recent linking of the SMART Registry with Medicare Benefits Schedule and Pharmaceutical Benefits Scheme data through the Australian Institute of Health and Welfare, research into prescribing patterns and health system utilisation is currently underway. The SMART Registry is also being updated with the Clavien-Dindo classification of surgical complications.

Total knee arthroplasty (TKA) is a highly effective procedure for advanced osteoarthritis of the knee. Thirty-day hospital readmission is an adverse outcome related to complications, which can be mitigated by identifying associated risk factors. We aimed to identify patient-related characteristics associated with unplanned 30-day readmission following TKA, and to determine the effect size of the association between these risk factors and unplanned 30-day readmission. We searched MEDLINE and EMBASE from inception to 8 September 2020 for English language articles. Reference lists of included articles were searched for additional literature. Patients of interest were TKA recipients (primary and revision) compared for 30-day readmission to any institution, due to any cause, based on patient risk factors; case series were excluded. Two reviewers independently extracted data and carried out critical appraisal. In-hospital complications during the index admission were the strongest risk factors for 30-day readmission in both primary and revision TKA patients, suggesting discharge planning to include closer post-discharge monitoring to prevent avoidable readmission may be warranted. Further research could determine whether closer monitoring post-discharge would prevent unplanned but avoidable readmissions. Increased comorbidity burden correlated with increased risk, as did specific comorbidities. Body mass index was not strongly correlated with readmission risk. Demographic risk factors included low socioeconomic status, but the impact of age on readmission risk was less clear. These risk factors can also be included in predictive models for 30-day readmission in TKA patients to identify high-risk patients as part of risk reduction programs.

Acromial and scapular spine stress fractures are common complications post reverse shoulder arthroplasty. A systematic review with meta-analysis was conducted to evaluate the clinical outcomes of conservatively treated acromial and scapular spine stress fractures post reverse shoulder arthroplasty in comparison to nonfracture control. Embase, MEDLINE, and Web of Science were searched on September 9, 2022, using various terms related to fracture, acromion, scapula, and reverse shoulder arthroplasty. Meta-analysis using a random effects model was performed on common outcome scores. Risk of bias was assessed using the Joanna Briggs Institute tools for case-controlled studies. Sensitivity analysis was performed for imputed standard deviations and studies with <20 participants. Thirteen studies with a total of 339 fracture and 3142 control patients were included in the systematic review. Meta-analysis was performed on 12 studies assessing active forward flexion, abduction, external rotation, Constant-Murley score, American Shoulder and Elbow Surgeons Standardized Shoulder Assessment Form, pain score, Simple Shoulder Test, and Single Assessment Numeric Evaluation. Fracture patients experienced significantly poorer functional outcome compared with control patients when the fractures were managed conservatively. Levy III fractures tend to experience worse outcomes. Pain score did not demonstrate a statistically significant difference between the fracture and nonfracture cohort. Currently, literature regarding surgical management is lacking, partially because of a dearth of high-quality literature but also hindered by a lack of standardized techniques. This review was limited by inclusion of studies of low evidence, small sample sizes, and inconsistency in outcome measurement and follow-up period. Overall, patients with acromial and scapular spine stress fractures treated conservatively are expected to have reduced shoulder function compared to nonfracture patients, with the spine of scapula fracture patients suffering the poorest outcomes. Future studies should aim to use the same sets of outcomes parameters to assess the patients at fixed time intervals and report outcomes stratified by Levy classification. This will enable interinstitutional collaboration and pooling of results.