ORCID Profile
0000-0002-2653-2107
Current Organisations
Dr. Avanthi Mandaleson
,
MedRecruit
,
St Vincent's Hospital Melbourne
,
The University of Auckland
,
University of Melbourne
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Publisher: Elsevier BV
Date: 10-2023
Publisher: Wiley
Date: 15-09-2022
DOI: 10.1111/ANS.18044
Abstract: Clinical predictive tools are a topic gaining interest. Many tools are developed each year to predict various outcomes in medicine and surgery. However, the proportion of predictive tools that are implemented in clinical practice is small in comparison to the total number of tools developed. This narrative review presents key principles to guide the translation of predictive tools from academic bodies of work into useful tools that complement clinical practice. Our review identified the following principles: (1) identifying a clinical gap, (2) selecting a target user or population, (3) optimizing predictive tool performance, (4) externally validating predictive tools, (5) marketing and disseminating the tool, (6) navigating the challenges of integrating a tool into existing healthcare systems, and (7) developing an ongoing monitoring and evaluation strategy. Although the review focuses on ex les in orthopaedic surgery, the principles can be applied to other disciplines in medicine and surgery.
Publisher: Elsevier BV
Date: 10-2021
Publisher: Wiley
Date: 02-12-2021
DOI: 10.1111/ANS.17398
Abstract: Current evidence for flexor tendon repair management and outcomes performed at peripheral centres is unclear. Most studies are based on evidence from specialist hand centres. This study evaluated a peripheral hospital in New Zealand where all flexor tendon repairs were performed by a generalist Orthopaedic service. The purpose of the study was to benchmark management and outcomes from a peripheral hospital in comparison to international standards. A retrospective single‐centre consecutive case series of Zones I and II flexor tendon repairs was extracted between 1 January 2014 and 1 January 2018. Medical records were used to evaluate management and outcomes of repairs. Hand therapy notes were used to evaluate rehabilitation protocols provided. The primary objective was to measure re‐rupture and re‐operation rates. Secondary objectives included auditing operative management and hand therapy compliance. Forty‐six patients (76 tendon repairs) were included in our final analysis. Mean follow up time to last clinical appointment was 11.8 weeks, and to last patient episode was 4.9 years. Most patients received timely surgery with a four‐core repair using 3–0 or larger suture. All hand therapy followed a controlled active motion protocol. The re‐operation rate was 19.6% ( P = .05) and the re‐rupture rate was 8.7% ( P = 0.28). Most flexor tendon injuries at this peripheral centre were managed according to international standards. However, high complication rates including re‐operation and re‐rupture occurred. Due to a lack of local comparison studies, confounding factors cannot be excluded as a contributor for these results.
Publisher: Elsevier BV
Date: 12-2022
Publisher: Elsevier BV
Date: 04-2022
Publisher: British Editorial Society of Bone & Joint Surgery
Date: 02-2023
DOI: 10.1302/1358-992X.2023.3.118
Abstract: Approximately 20% of patients feel unsatisfied 12 months after primary total knee arthroplasty (TKA). Current predictive tools for TKA focus on the clinician as the intended user rather than the patient. The aim of this study is to develop a tool that can be used by patients without clinician assistance, to predict health-related quality of life (HRQoL) outcomes 12 months after total knee arthroplasty (TKA). All patients with primary TKAs for osteoarthritis between 2012 and 2019 at a tertiary institutional registry were analysed. The predictive outcome was improvement in Veterans-RAND 12 utility score at 12 months after surgery. Potential predictors included patient demographics, co-morbidities, and patient reported outcome scores at baseline. Logistic regression and three machine learning algorithms were used. Models were evaluated using both discrimination and calibration metrics. Predictive outcomes were categorised into deciles from 1 being the least likely to improve to 10 being the most likely to improve. 3703 eligible patients were included in the analysis. The logistic regression model performed the best in out-of-s le evaluation for both discrimination (AUC = 0.712) and calibration (gradient = 1.176, intercept = −0.116, Brier score = 0.201) metrics. Machine learning algorithms were not superior to logistic regression in any performance metric. Patients in the lowest decile (1) had a 29% probability for improvement and patients in the highest decile (10) had an 86% probability for improvement. Logistic regression outperformed machine learning algorithms in this study. The final model performed well enough with calibration metrics to accurately predict improvement after TKA using deciles. An ongoing randomised controlled trial (ACTRN12622000072718) is evaluating the effect of this tool on patient willingness for surgery. Full results of this trial are expected to be available by April 2023. A free-to-use online version of the tool is available at smartchoice.org.au.
Publisher: British Editorial Society of Bone & Joint Surgery
Date: 02-2023
DOI: 10.1302/1358-992X.2023.3.119
Abstract: Most previous studies investigating autograft options (quadriceps, hamstring, bone-patella-tendon-bone) in primary anterior cruciate ligament (ACL) reconstruction are confounded by concomitant knee injuries. This study aims to investigate the differences in patient reported outcome measures and revision rates for quadriceps tendon in comparison with hamstring tendon and bone-patella-tendon-bone autografts. We use a cohort of patients who have had primary ACL reconstruction without concomitant knee injuries. All patients from the New Zealand ACL Registry who underwent a primary arthroscopic ACL reconstruction with minimum 2 year follow-up were considered for the study. Patients who had associated ipsilateral knee injuries, previous knee surgery, or open procedures were excluded. The primary outcome was Knee Injury and Osteoarthritis Outcome Score (KOOS) and MARX scores at 2 years post-surgery. Secondary outcomes were all-cause revision and time to revision with a total follow-up period of 8 years (time since inception of the registry). 2581 patients were included in the study 1917 hamstring tendon, 557 bone-patella-tendon-bone, and 107 quadriceps tendon. At 2 years, no significant difference in MARX scores were found between the three groups (2y mean score 7.36 hamstring, 7.85 bone-patella-tendon-bone, 8.05 quadriceps, P = 0.195). Further, no significant difference in KOOS scores were found between the three groups with the exception of hamstring performing better than bone-patella-tendon-bone in the KOOS sports and recreation sub-score (2y mean score 79.2 hamstring, 73.9 bone-patella-tendon-bone, P 0.001). Similar revision rates were reported between all autograft groups (mean revision rate per 100 component years 1.05 hamstring, 0.80 bone-patella-tendon-bone, 1.68 quadriceps, P = 0.083). Autograft revision rates were independent of age and gender variables. Quadriceps tendon is a comparable autograft choice to the status quo for primary ACL reconstruction without concomitant knee injury. Further research is required to quantify the long-term outcomes for quadriceps tendon use.
Publisher: Elsevier BV
Date: 07-2023
Publisher: Elsevier BV
Date: 10-2023
Publisher: British Editorial Society of Bone & Joint Surgery
Date: 02-2023
DOI: 10.1302/1358-992X.2023.3.117
Abstract: Utility score is a preference-based measure of general health state – where 0 is equal to death, and 1 is equal to perfect health. To understand a patient's smallest perceptible change in utility score, the minimal clinically important difference (MCID) can be calculated. However, there are multiple methods to calculate MCID with no consensus about which method is most appropriate. The aim of this study is to calculate MCID values for the Veterans-RAND 12 (VR12) utility score using varying methods. Our hypothesis is that different methods will yield different MCID values. A tertiary institutional registry (SMART) was used as the study cohort. Patients who underwent unilateral TKA for osteoarthritis from January 2012 to January 2020 were included. Utility score was calculated from VR12 responses using the standardised Brazier's method. Distribution and anchor methods were used for the MCID calculation. For distribution methods, 0.5 standard deviations of the baseline and change scores were used. For anchor methods, the physical and emotional anchor questions in the VR12 survey were used to benchmark utility score outcomes. Anchor methods included mean difference in change score, mean difference in 12 month score, and receiver operating characteristics (ROC) analysis with the Youden index. Complete case analysis of 1735 out of 1809 eligible patients was performed. Significant variation in the MCID estimates for VR12 utility score were reported dependent on the calculation method used. The MCID estimate from 0.5 standard deviations of the change score was 0.083. The MCID estimate from the ROC analysis method using physical or emotional anchor question improvement was 0.115 (CI95 0.08-0.14 AUC 0.656). Different MCID calculation methods yielded different MCID values. Our results suggest that MCID is not an umbrella concept but rather many distinct concepts. A general consensus is required to standardise how MCID is defined, calculated, and applied in clinical practice.
Publisher: Elsevier BV
Date: 05-2023
Publisher: Springer Science and Business Media LLC
Date: 24-02-2022
DOI: 10.1186/S12891-022-05123-0
Abstract: Approximately 1 in 5 patients feel unsatisfied after total knee arthroplasty (TKA). Prognostic tools may aid in the patient selection process and reduce the proportion of patients who experience unsatisfactory surgery. This study uses the prognostic tool SMART Choice (Patient Prognostic Tool for Total Knee Arthroplasty) to predict patient improvement after TKA. The tool aims to be used by the patient without clinician input and does not require clinical data such as X-ray findings or blood results. The objective of this study is to evaluate the SMART Choice tool on patient decision making, particularly willingness for surgery. We hypothesise that the use of the SMART Choice tool will influence willingness to undergo surgery, especially when used earlier in the patient TKA journey. This is a multicentred, pragmatic, randomised controlled trial conducted in Melbourne, Australia. Participants will be recruited from the St. Vincent’s Hospital, Melbourne (SVHM) Orthopaedic Clinic, and the client base of HCF, Australia (private health insurance company). Patients over 45 years of age who have been diagnosed with knee osteoarthritis and considering TKA are eligible for participation. Participants will be randomised to either use the SMART Choice tool or treatment as usual. The SMART Choice tool provides users with a prediction for improvement or deterioration / no change after surgery based on utility score change calculated from the Veterans-RAND 12 (VR-12) survey. The primary outcome of the study is patient willingness for TKA surgery. The secondary outcomes include evaluating the optimal timing for tool use and using decision quality questionnaires to understand the patient experience when using the tool. Participants will be followed up for 6 months from the time of recruitment. The SMART Choice tool has the potential to improve patient decision making for TKA. Although many prognostic tools have been developed for other areas of surgery, most are confined within academic bodies of work. This study will be one of the first to evaluate the impact of a prognostic tool on patient decision making using a prospective clinical trial, an important step in transitioning the tool for use in clinical practice. Australia and New Zealand Clinical Trials Registry (ANZCTR) - ACTRN12622000072718 . Prospectively registered – 21 January 2022.
Publisher: Elsevier BV
Date: 11-2023
Publisher: Springer Science and Business Media LLC
Date: 30-09-2023
Publisher: Springer Science and Business Media LLC
Date: 03-2022
DOI: 10.1186/S13256-022-03318-6
Abstract: Subcutaneous low molecular weight heparin is a commonly used anticoagulant. Catastrophic hemorrhage is a known adverse outcome associated with anticoagulant use. Of all potential bleeding sites, hemorrhage into the rectus sheath is a rare and unusual complication. In this case report, we document a patient who developed rectus sheath hematoma following new commencement of therapeutic low molecular weight heparin. A 71-year-old New Zealand European woman presented to a peripheral hospital with suspected unstable angina. She was started on therapeutic subcutaneous low molecular weight heparin. While awaiting inpatient transfer to a tertiary hospital for coronary angiography, she developed a large rectus sheath hematoma associated with hemodynamic instability. She required an urgent laparotomy to decompress the hematoma and achieve hemostasis. Postoperatively, her anticoagulation therapy was stopped, and she made a full recovery. Rectus sheath hematoma is a condition that is difficult to diagnose. The risk of adverse events must always be considered against the indication and potential benefits of new medications, especially with high-risk medications such as anticoagulants.
Publisher: South African Medical Association NPC
Date: 05-06-2019
Publisher: Elsevier BV
Date: 06-2023
Publisher: Springer Science and Business Media LLC
Date: 09-03-2023
Publisher: Elsevier BV
Date: 2022
Publisher: Wiley
Date: 2023
DOI: 10.1111/ANS.18250
Abstract: 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. 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. 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. 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 II, decision analysis.
No related grants have been discovered for Yuxuan Zhou.