Surgery (St Vincent's) - Research Publications
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ItemNo Preview AvailablePatients' Views on AI for Risk Prediction in Shared Decision-Making for Knee Replacement Surgery: Qualitative Interview Study(JMIR PUBLICATIONS, INC, 2023-09-18)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.
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ItemNo Preview AvailableSMART choice (knee) tool: a patient-focused predictive model to predict improvement in health-related quality of life after total knee arthroplasty(WILEY, 2023-01)BACKGROUND: Current predictive tools for TKA focus on clinicians rather than patients as the intended user. The purpose of this study was to develop a patient-focused model to predict health-related quality of life outcomes at 1-year post-TKA. METHODS: Patients who underwent primary TKA for osteoarthritis from a tertiary institutional registry after January 2006 were analysed. The primary outcome was improvement after TKA defined by the minimal clinically important difference in utility score at 1-year post-surgery. Potential predictors included demographic information, comorbidities, lifestyle factors, and patient-reported outcome measures. Four models were developed, including both conventional statistics and machine learning (artificial intelligence) methods: logistic regression, classification tree, extreme gradient boosted trees, and random forest models. Models were evaluated using discrimination and calibration metrics. RESULTS: A total of 3755 patients were included in the study. The logistic regression model performed the best with respect to both discrimination (AUC = 0.712) and calibration (intercept = -0.083, slope = 1.123, Brier score = 0.202). Less than 2% (n = 52) of the data were missing and therefore removed for complete case analysis. The final model used age (categorical), sex, baseline utility score, and baseline Veterans-RAND 12 responses as predictors. CONCLUSION: The logistic regression model performed better than machine learning algorithms with respect to AUC and calibration plot. The logistic regression model was well calibrated enough to stratify patients into risk deciles based on their likelihood of improvement after surgery. Further research is required to evaluate the performance of predictive tools through pragmatic clinical trials. LEVEL OF EVIDENCE: Level II, decision analysis.
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ItemDeveloping and internally validating a prediction model for total knee replacement surgery in patients with osteoarthritis.(Elsevier BV, 2022-09)OBJECTIVE: The objective of this study was to develop and internally validate a clinical algorithm for use in general practice that predicts the probability of total knee replacement (TKR) surgery within the next five years for patients with osteoarthritis. The purpose of the model is to encourage early uptake of first-line treatment strategies in patients likely to undergo TKR and to provide a cohort for the development and testing of novel interventions that prevent or delay the progression to TKR. METHOD: Electronic health records (EHRs) from 201,462 patients with osteoarthritis aged 45 years and over from 483 general practices across Australia were linked with records from the Australian Orthopaedic Association National Joint Replacement Registry and the National Death Index. A Fine and Gray competing risk prediction model was developed using these data to predict the risk of TKR within the next five years. RESULTS: During a follow-up time of 5 years, 15,979 (7.9%) patients underwent TKR and 13,873 (6.9%) died. Predictors included in the final algorithm were age, previous knee replacement, knee surgery (other than TKR), prescribing of osteoarthritis medication in the 12 months prior, comorbidity count and diagnosis of a mental health condition. Optimism corrected model discrimination was 0.67 (95% CI: 0.66 to 0.67) and model calibration acceptable. CONCLUSION: The model has the potential to reduce some of the economic burden associated with TKR in Australia. External validation and further optimisation of the algorithm will be carried out prior to implementation within Australian general practice EHR systems.
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ItemThe Impact of Sex on the Outcomes of Prosthetic Joint Infection Treatment with Debridement, Antibiotics and Implant Retention: A Systematic Review and Individual Patient Data Meta-analysis(LIPPINCOTT WILLIAMS & WILKINS, 2022-11)BACKGROUND: The influence of sex on the failure of débridement antibiotics and implant retention (DAIR) for treating prosthetic joint infection (PJI) is important for decision-making, patient counseling, and equitable health care. However, very few studies in the orthopaedic literature conduct sex-specific analyses. AIM: The primary aim was to determine whether sex influences treatment success after DAIR. METHODS: A systematic review and individual patient data (IPD) meta-analysis was conducted. MEDLINE (Ovid), EMBASE (Ovid), Web of Science, and Google Scholar were searched, and IPD was requested via e-mail. Patients who underwent DAIR after developing PJI within 12 months of a primary total hip or knee arthroplasty were included in the analysis. Treatment failure was defined by the Delphi International Consensus criteria. Adjusted odds ratios for treatment failure were calculated using a mixed-effects logistic regression. RESULTS: The study collected and analyzed IPD of 1,116 patients from 21 cohorts. The odds of treatment failure were 29% lower in women (odds ratio, 0.71; 95% CI 0.54 to 0.017; P = 0.017), after adjusting for duration of symptoms >7 days and Staphylococcus aureus infection (methicillin-susceptible Staphylococcus aureus or any infection with S aureus). None of the 64 studies included in the systematic review conducted a sex-specific analysis. CONCLUSION: For patients who developed a PJI within 1 year postsurgery, females have lower odds of DAIR failure than males. Other factors also have varying effects on outcome for men and women. It is essential to implement sex-specific analysis in orthopaedic research.
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ItemResponse to Letter to the Editor on "A Randomized Controlled Trial Comparing a Medial Stabilized Total Knee Prosthesis to a Cruciate Retaining and Posterior Stabilized Design: A Report of the Clinical and Functional Outcomes Following Total Knee Replacement"(CHURCHILL LIVINGSTONE INC MEDICAL PUBLISHERS, 2020-11)
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ItemA Nomogram for Predicting Non-Response to Surgery One Year after Elective Total Hip Replacement(MDPI, 2022-03)Background: Total hip replacement (THR) is a common and cost-effective procedure for end-stage osteoarthritis, but inappropriate utilization may be devaluing its true impact. The purpose of this study was to develop and test the internal validity of a prognostic algorithm for predicting the probability of non-response to THR surgery at 1 year. Methods: Analysis of outcome data extracted from an institutional registry of individuals (N = 2177) following elective THR performed between January 2012 and December 2019. OMERACT-OARSI responder criteria were applied to Western Ontario and McMaster Universities Arthritis Index (WOMAC) pain and function scores at pre- and 1 year post-THR, to determine non-response to surgery. Independent prognostic correlates of post-operative non-response observed in adjusted modelling were then used to develop a nomogram. Results: A total of 194 (8.9%) cases were deemed non-responders to THR. The degree of contribution (OR, 95% CI) of each explanatory factor to non-response on the nomogram was, morbid obesity (1.88, 1.16, 3.05), Kellgren−Lawrence grade <4 (1.89, 1.39, 2.56), WOMAC Global rating per 10 units (0.86, 0.79, 0.94) and the following co-morbidities: cerebrovascular disease (2.39, 1.33, 4.30), chronic pulmonary disease (1.64; 1.00, 2.71), connective tissue disease (1.99, 1.17, 3.39), diabetes (1.86, 1.26, 2.75) and liver disease (2.28, 0.99, 5.27). The concordance index for the nomogram was 0.70. Conclusion: We have developed a prognostic nomogram to calculate the probability of non-response to THR surgery. In doing so, we determined that both the probability of and predictive prognostic factors for non-response to THR differed from a previously developed nomogram for total knee replacement (TKR), confirming the benefit of designing decision support tools that are both condition and surgery site specific. Future external validation of the nomogram is required to confirm its generalisability.
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ItemAssessing the suitability of general practice electronic health records for clinical prediction model development: a data quality assessment(BMC, 2021-10-30)BACKGROUND: The use of general practice electronic health records (EHRs) for research purposes is in its infancy in Australia. Given these data were collected for clinical purposes, questions remain around data quality and whether these data are suitable for use in prediction model development. In this study we assess the quality of data recorded in 201,462 patient EHRs from 483 Australian general practices to determine its usefulness in the development of a clinical prediction model for total knee replacement (TKR) surgery in patients with osteoarthritis (OA). METHODS: Variables to be used in model development were assessed for completeness and plausibility. Accuracy for the outcome and competing risk were assessed through record level linkage with two gold standard national registries, Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR) and National Death Index (NDI). The validity of the EHR data was tested using participant characteristics from the 2014-15 Australian National Health Survey (NHS). RESULTS: There were substantial missing data for body mass index and weight gain between early adulthood and middle age. TKR and death were recorded with good accuracy, however, year of TKR, year of death and side of TKR were poorly recorded. Patient characteristics recorded in the EHR were comparable to participant characteristics from the NHS, except for OA medication and metastatic solid tumour. CONCLUSIONS: In this study, data relating to the outcome, competing risk and two predictors were unfit for prediction model development. This study highlights the need for more accurate and complete recording of patient data within EHRs if these data are to be used to develop clinical prediction models. Data linkage with other gold standard data sets/registries may in the meantime help overcome some of the current data quality challenges in general practice EHRs when developing prediction models.
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ItemImpact of surgical experience on outcomes in total joint arthroplasties(WILEY-BLACKWELL, 2016-12)BACKGROUND: Outcomes of primary total hip and knee arthroplasties performed by consultant surgeons were compared with those performed by orthopaedic trainees. Furthermore, outcomes of these procedures performed by senior trainees were compared with those performed by junior trainees. METHODS: Data from the St Vincent's Melbourne Arthroplasty Outcomes Registry and the surgical log kept by trainees were reviewed to investigate if an association exists between surgical experience and clinical outcomes following primary total hip and knee arthroplasties. Multivariate logistic regression analyses were conducted to produce odds ratios with 95% confidence intervals to assess these relationships. RESULTS: Arthroplasties performed by trainees were not significantly different from those performed by consultant surgeons in regards to medical, surgical and wound complications. Trainee-performed primary total hip arthroplasties were associated with a 30% increase in the risk of requiring a transfusion compared with consultant cases. Primary total knee arthroplasties performed by junior trainees were associated with a 50% increase in the risk of developing a wound complication compared with those performed by senior trainees. CONCLUSIONS: Overall, senior orthopaedic trainees working independently and junior orthopaedic trainees under supervision as the primary surgeon have the ability to achieve a level of clinical outcomes similar to a consultant surgeon. Junior trainees with supervision have the ability to achieve a level of clinical outcomes similar to senior trainees. These findings can be used to further improve orthopaedic training to reduce adverse events during supervised surgery.
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ItemEarly surgical complications of total hip arthroplasty related to surgical approach(WILEY, 2020-10)BACKGROUND: Total hip arthroplasty (THA) can be performed through a number of surgical approaches. The aim was to compare the incidence of early surgical complications in THA related to approach. METHODS: A retrospective review of prospectively recorded data extracted from St. Vincent's Melbourne Arthroplasty Registry was performed between January 2006 and December 2016. Surgical approach was identified: lateral, posterior, anterior and superior. Primary outcome measure was return to theatre (RTT) for any cause within 1 year. Age, comorbidity, body mass index and femoral fixation were assessed for potential confounding. Secondary outcomes were RTT for revision procedure and for specific complications: intra or post-operative fracture, dislocation/instability, aseptic loosening and prosthetic joint injection (PJI). Variables were assessed for their association with outcome using unadjusted and adjusted quantile median regression for continuous outcomes and Cox proportional hazards regression for binary time-to-event outcomes. RESULTS: There were a total of 2906 consecutive THA's recorded, 1413 lateral, 1188 posterior, 233 anterior and 72 superior. A total of 140 cases (4.5%) required RTT within 1 year. No approach was associated with RTT on unadjusted analyses or multivariate modelling. There was no association between approach and revision, PJI or periprosthetic fracture. The posterior approach was associated with 2.90 times the rate of dislocation relative to the lateral (P = 0.005). CONCLUSIONS: There was no difference in the RTT rate between surgical approaches for THA. There was no difference in revision rates, PJI or periprosthetic fracture. The posterior approach was associated with a higher rate of dislocation relative to the lateral, but not the anterior.
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ItemPopulation growth, ageing and obesity do not sufficiently explain the increased utilization of total knee replacement in Australia(WILEY, 2020-07)BACKGROUND: The utilization of total knee replacement (TKR) has increased significantly. The objective of this study was to assess the impact of changes in population demography (population growth, ageing and gender) and body mass indices (BMIs) on the additional volume of knee replacement surgery undertaken in Australia. METHODS: Using national data, we compared estimates based on changes in population demography and BMIs to the reported increase in TKR between 2007 and 2017. The costs of additional surgery were estimated using the National Hospital Cost Data Collection. RESULTS: An additional 25 814 TKRs were performed in 2017 compared to 2007. Contributions from population growth, ageing and changing BMIs were 27.1%, 10.4%, and 6.3%-15.3%, respectively. Other drivers contributed between 47.2% and 56.2%, representing 12 176-14 506 TKRs at a financial cost of A$320.9 million to A$382.3 million per year in 2017. CONCLUSION: The volume of additional surgery being performed considerably exceeded estimates based on changing population demography and rising rates of obesity. The other drivers of additional TKR utilization will likely have significant implications for the health budget and warrant further investigation. This may involve an examination of the current indications for surgery and the cost-effectiveness of TKR in various settings, reviewing patient expectations and preferences, and assessing the impact of policies which relate to the funding and provision of TKR.