Differences in Outcomes Between Initial Responders and Subsequent Responders to Health Questionnaires for Total Hip and Knee Arthroplasty: An Australian Tertiary Institutional Registry Study.

BACKGROUND: Patient-reported outcome measure (PROM) questionnaires in national arthroplasty registries often have low response rates leading to questions about data reliability. In Australia, the SMART (St. Vincent's Melbourne Arthroplasty Outcomes) registry captures all elective total hip (THA) and total knee (TKA) arthroplasty patients with an approximate 98% response rate for preoperative and 12-month PROM scores. This high response rate is due to dedicated registry staff following up patients who do not initially respond (subsequent responders). This study compared initial responders to subsequent responders to find differences in 12-month PROM outcomes for THA and TKA. METHODS: All elective THA and TKA patients for osteoarthritis from 2012 to 2021 captured by the SMART registry were included. In total, 1,333 THA and 1,340 TKA patients were included. The PROM scores were assessed using the Veterans-RAND 12 (VR12) and Western Ontario and McMasters Universities Arthritis Index (WOMAC) questionnaires. The primary outcome was differences in mean 12-month PROM scores between initial and subsequent responders. RESULTS: Baseline characteristics and PROM scores were similar between initial and subsequent responders. However, 12-month PROM scores varied significantly. The adjusted mean difference showed that for the WOMAC pain score, subsequent responders scored 3.4 points higher in the THA cohort and 7.4 points higher in the TKA cohort compared to initial responders. Significant differences were also found in other WOMAC and VR12 scores for both THA and TKA cohorts at the 12-month timepoint. CONCLUSION: This study found that significant differences in PROM outcomes postsurgery occurred in THA and TKA patients based on response to PROM questionnaires, suggesting that loss to follow-up in PROM outcomes should not be treated as missing completely at random (MCAR).

Analysis of Rates of Completion, Delays, and Participant Recruitment in Randomized Clinical Trials in Surgery.

Importance: Discontinuation and nonpublication are established sources of avoidable waste among surgical trials, but rates of delayed completion and recruiting shortfalls remain unclear. Objectives: To examine the rate of delayed completion, incomplete enrollment, and discontinuation among randomized clinical trials in surgical populations and the duration of delays and extent of recruiting shortfalls among these trials. Design, Setting, and Participants: This cross-sectional study examined randomized clinical trials in surgical populations registered on ClinicalTrials.gov between January 1, 2010, and December 31, 2014. Analysis was conducted between October 27, 2021, and June 30, 2022. Main Outcomes and Measures: The main outcomes were the percentages of trials completed on time or with full enrollment. Delays and recruiting shortfalls were identified by comparing projected enrollment and study timeframes prespecified at the time of registration with the actual study duration and enrollment reported on completion or discontinuation. Absolute and relative differences between planned and actual trial conduct were presented for discontinued trials and those completed with delays or recruiting shortfalls. Results: In total, 2542 randomized clinical trials in surgical populations were included in the study sample, of which 370 (14.6%; 95% CI, 13.2%-15.9%) were completed both on time and with full enrollment. Approximately 1 in 5 trials (20.4%; 95% CI, 18.9%-22.0%) were completed within their planned timeframe, and 1166 trials (45.9%; 95% CI, 43.9%-47.8%) met their prespecified enrollment target. The median delay among completed trials was 12.2 months (IQR, 5.1-24.3 months) or 66.7% (IQR, 30.1%-135.8%) longer than planned. Among completed trials that did not meet their prespecified enrollment target, the median recruiting shortfall was equivalent to 31.0% (IQR, 12.7%-55.5%) of the planned study sample. A total of 546 trials (21.5%; 95% CI, 19.9%-23.1%) were discontinued. The median time to discontinuation was 26.4 months (IQR, 15.2-45.7 months), and the median recruiting shortfall among discontinued trials was equivalent to 92.7% (IQR, 65.0%-100.0%) of the trial's prespecified enrollment target. Conclusions and Relevance: This cross-sectional study found that delayed completion, recruiting shortfalls, and untimely discontinuation were common among surgical trials. These findings highlight the importance of ensuring that investigators and funders do not overestimate the feasibility of planned trials.

Developing and internally validating a prediction model for total knee replacement surgery in patients with osteoarthritis.

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.

Total joint replacement may be a valuable treatment for Aboriginal and Torres Strait Islander people with osteoarthritis, but uptake is low.

BACKGROUND: Despite bearing a higher burden of osteoarthritis, little research has examined disparities in the access, utilisation and surgical outcomes associated with total joint replacement (TJR) among Aboriginal and Torres Strait Islander people. METHODS: We conducted a retrospective cohort study to compare the sociodemographic and clinical characteristics of all Aboriginal and Torres Strait Islander and non-Aboriginal patients who underwent primary hip and knee replacement at St Vincent's Hospital Melbourne between 1996 and 2019. RESULTS: A total of 10 277 primary total knee or hip replacements were performed in the 1996-2019 study period, of which 49 (0.5%) patients identified as either Aboriginal and/or Torres Strait Islander. Aboriginal and Torres Strait Islander patients were younger (61.7 ± 11.8 vs. 68.3 ± 10.3 years; P < 0.001), recorded higher Body Mass Index scores (median (IQR), 36.0 (29.5-41.4) vs. 30.8 (27.0-35.3); P < 0.001) and were more likely to experience multiple co-morbidities at the time of surgery. Despite these findings, Aboriginal and Torres Strait Islander patients did not experience higher complication rates and experienced comparable, clinically meaningful quality of life improvements 12-months post-surgery. CONCLUSIONS: TJR appears to be a valuable treatment option for Aboriginal and Torres Strait Islander people with end-stage osteoarthritis. Our study was limited by the small number of procedures conducted in patients who identify as Aboriginal and Torres Strait Islander. Further research is needed to understand why uptake of TJR by Aboriginal and Torres Strait Islander people is low.

Patterns and Predictors of Outpatient Antibiotic Dispensation Following Total Hip and Knee Arthroplasty.

BACKGROUND: This study aimed to evaluate the month-to-month prevalence of antibiotic dispensation in the 12 months before and after total knee arthroplasty (TKA) and total hip arthroplasty (THA) and to identify factors associated with antibiotic dispensation in the month immediately following the surgical procedure. METHODS: In total, 4,115 THAs and TKAs performed between April 2013 and June 2019 from a state-wide arthroplasty referral center were analyzed. A cross-sectional study used data from an institutional arthroplasty registry, which was linked probabilistically to administrative dispensing data from the Australian Pharmaceutical Benefits Scheme. Multivariable logistic regression was carried out to identify patient and surgical risk factors for oral antibiotic dispensation. RESULTS: Oral antibiotics were dispensed in 18.3% of patients following primary TKA and 12.0% of patients following THA in the 30 days following discharge. During the year after discharge, 66.7% of TKA patients and 58.2% of THA patients were dispensed an antibiotic at some point. Patients with poor preoperative health status were more likely to have antibiotics dispensed in the month following THA or TKA. Older age, undergoing TKA rather than THA, obesity, inflammatory arthritis, and experiencing an in-hospital wound-related or other infectious complications were associated with increased antibiotic dispensation in the 30 days following discharge. CONCLUSION: A high rate of antibiotic dispensation in the 30 days following THA and TKA has been observed. Although resource constraints may limit routine wound review for all patients by a surgeon, a select cohort may benefit from timely specialist review postoperatively. Several risk factors identified in this study may aid in identifying appropriate candidates for such changes to follow-up care.

Assessing the suitability of general practice electronic health records for clinical prediction model development: a data quality assessment.

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.

Impact of quarterly professional-mode flash glucose monitoring in adults with type 2 diabetes in general practice (GP-OSMOTIC): Secondary psychological and self-care outcomes of a pragmatic, open-label, 12-month, randomised controlled trial.

AIMS: To investigate the impact of quarterly professional-mode flash glucose monitoring on psychological outcomes in adults with type 2 diabetes in primary care. METHODS: The GP-OSMOTIC trial randomised 299 adults with type 2 diabetes in 25 general practices to quarterly use of professional-mode flash glucose monitoring (sensor worn for 14 days; data discussed at clinic visit) or usual care. At baseline and 12 months, participants completed validated measures: general emotional well-being (WHO-5), diabetes-specific quality of life (DIDP), satisfaction with glucose monitoring (GME-Q), self-care activities (SDSCA) and perceived involvement in clinical care (PICS). Linear mixed-effects models examined between-group differences at 12 months. RESULTS: At 12 months, there were no clinically important between-arm differences in any secondary psychological or self-care outcomes. Per protocol analyses showed no clinically significant between-group differences. CONCLUSIONS: The GP-OSMOTIC intervention had no significant impact, at 12 months, on general emotional well-being, diabetes-specific quality of life or satisfaction with glucose monitoring, suggesting no added psychological burden. Lack of positive impact on self-reported self-care activities or perceived involvement in clinical care may warrant closer attention to the fidelity of intervention delivery, the context (e.g. the nature of clinician-patient interactions) and/or the sensitivity of the measures, as these will help plan future studies.

Cohort profile: the St Vincent's Melbourne Arthroplasty Outcomes (SMART) Registry, a pragmatic prospective database defining outcomes in total hip and knee replacement 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.

Professional flash glucose monitoring and health service utilisation in type 2 diabetes: A secondary analysis of the GP-OSMOTIC study.

AIM: Professional flash glucose monitoring involves people with diabetes wearing a glucose monitor for up to two weeks, with the data downloaded by their health professional, and the information used to help guide treatment. This study describes if professional flash glucose monitoring was associated with a change in health services utilisation. METHODS: Administrative claims data from three data sources were linked to 288 participants from the GP-OSMOTIC study, a randomised controlled trial evaluating the use of professional flash glucose monitoring versus usual care in people with type 2 diabetes in primary care. Generalised linear models with the Poisson family specified and log link function were used to compare general practice consultations between the intervention and control groups at 0-6- and 6-12-month time points, with adjustment for baseline health services utilisation. RESULTS: GP consultations increased in the flash glucose monitoring group in the 6 months following initial flash glucose monitoring sensor application from a median (IQR) 6 (4,9) to 8 (5,11); (P < 0.001). Participants in the professional FGM group were 1.2 times (95 % CI 1.1-1.4 (P = 0.0014)) more likely at 6-12 months to have GP consultation visits. CONCLUSIONS: Administrative claims data identified changes in health services utilisation associated with professional flash glucose monitoring, despite minimal changes in glycaemic control.

Associations between multimorbidity and glycaemia (HbA1c) in people with type 2 diabetes: cross-sectional study in Australian general practice.

OBJECTIVES: To explore the prevalence of multimorbidity as well as individual and combinations of long-term conditions (LTCs) in people with type 2 diabetes (T2D) attending Australian general practice, using electronic health record (EHR) data. We also examine the association between multimorbidity condition count (total/concordant(T2D related)/discordant(unrelated)) and glycaemia (glycated haemoglobin, HbA1c). DESIGN: Cross-sectional study. SETTING: Australian general practice. PARTICIPANTS: 69 718 people with T2D with a general practice encounter between 2013 and 2015 captured in the MedicineInsight database (EHR Data from 557 general practices and >3.8 million Australian patients). PRIMARY AND SECONDARY OUTCOME MEASURES: Prevalence of multimorbidity, individual and combinations of LTCs. Multivariable linear regression models used to examine associations between multimorbidity counts and HbA1c (%). RESULTS: Mean (SD) age 66.42 (12.70) years, 46.1% female and mean (SD) HbA1c 7.1 (1.4)%. More than 90% of participants with T2D were living with multimorbidity. Discordant conditions were more prevalent (83.4%) than concordant conditions (69.9 %). The three most prevalent discordant conditions were: painful conditions (55.4%), dyspepsia (31.6%) and depression (22.8%). The three most prevalent concordant conditions were hypertension (61.4%), coronary heart disease (17.1%) and chronic kidney disease (8.5%). The three most common combinations of conditions were: painful conditions and hypertension (38.8%), painful conditions and dyspepsia (23.1%) and hypertension and dyspepsia (22.7%). We found no associations between any multimorbidity counts (total, concordant and discordant) or combinations and HbA1c. CONCLUSIONS: Multimorbidity was common in our cohort of people with T2D attending Australian general practice, but was not associated with glycaemia. Although we did not explore mortality in this study, our results suggest that the increased mortality in those with multimorbidity and T2D observed in other studies may not be linked to glycaemia. Interestingly, discordant conditions were more prevalent than concordant conditions with painful conditions being the second most common comorbidity. Better understanding of the implications of different patterns of multimorbidity in people with T2D will allow more effective tailored care.

Multimorbidity, glycaemic variability and time in target range in people with type 2 diabetes: A baseline analysis of the GP-OSMOTIC trial.

AIMS: To explore associations between multimorbidity condition counts (total; concordant (diabetes-related); discordant (unrelated to diabetes)) and glycaemia (HbA1c; glycaemic variability (GV); time in range (TIR)) using data from a randomised controlled trial examining effectiveness of continuous glucose monitoring (CGM) in people with type 2 diabetes (T2D). METHODS: Cross-sectional study: 279 people with T2D using baseline data from the General Practice Optimising Structured MOnitoring To Improve Clinical outcomes (GP-OSMOTIC) trial from 25 general practices in Australia. Number of long-term conditions (LTCs) in addition to T2D used to quantify total/concordant/discordant multimorbidity counts. GV (measured by coefficient of variation (CV)) and TIR derived from CGM data. Multivariable linear regression models used to examine associations between multimorbidity counts, HbA1c (%), GV and TIR. RESULTS: Mean (SD) age of participants 60.4 (9.9) years; 40.9% female. Multimorbidity was present in 89.2% of participants. Most prevalent comorbid LTCs: hypertension (57.4%), painful conditions (29.8%), coronary heart disease (22.6%) and depression (19.0%). No evidence of associations between multimorbidity counts, HbA1c, GV and TIR. CONCLUSIONS: While multimorbidity was common in this T2D cohort, it was not associated with HbA1c, CV or TIR. Future studies should explore factors other than glycaemia that contribute to the increased mortality observed in those with multimorbidity and T2D.

Psychosocial Moderators of the Impact of Diabetes Stigma: Results From the Second Diabetes MILES - Australia (MILES-2) Study.

OBJECTIVE: To examine the association of diabetes stigma with psychological, behavioral, and HbA1c outcomes and to investigate moderation effects of self-esteem, self-efficacy, and/or social support. RESEARCH DESIGN AND METHODS: The national Second Diabetes MILES - Australia (MILES-2) survey included adults with type 1 diabetes (n = 959, 41% of whom were male, with mean ± SD age 44 ± 15 years), insulin-treated type 2 diabetes (n = 487, 60% male, age 61 ± 9 years), and non-insulin-treated type 2 diabetes (n = 642, 55% male, age 61 ± 10 years). (Un)adjusted linear regression analyses tested the association between diabetes stigma (Diabetes Stigma Assessment Scale [DSAS]) and psychological outcomes (depressive symptoms [eight-item version of the Patient Health Questionnaire (PHQ-8)], anxiety symptoms [Generalized Anxiety Disorder 7-item (GAD-7) questionnaire], and diabetes-specific distress [20-item Problem Areas In Diabetes (PAID) scale]), behavioral outcomes (healthy diet and physical activity [Summary of Diabetes Self-Care Activities (SDSCA)]), and self-reported HbA1c. Interaction effects tested whether associations varied by self-esteem (Rosenberg Self-Esteem Scale [RSES]), self-efficacy (Confidence in Diabetes Self-Care [CIDS] scale), or diabetes-specific social support (Diabetes Support Scale [DSS]). RESULTS: Significant positive associations were observed between DSAS and PHQ-8, GAD-7, and PAID across diabetes type/treatment groups (all P < 0.001), whereby each SD increase in DSAS scores was associated with approximately one-half SD deterioration in emotional well-being. Associations between DSAS and SDSCA and HbA1c were nonmeaningful. Self-esteem moderated psychological outcomes among participants with type 1 and non-insulin-treated type 2 diabetes and diabetes distress among those with insulin-treated type 2 diabetes. Interaction effects were partially observed for social support but not for self-efficacy. CONCLUSIONS: This study provides evidence of the association between diabetes stigma and depressive/anxiety symptoms and diabetes distress and for the moderating effects of self-esteem and social support among adults with type 1 and type 2 diabetes. Further research is needed to examine associations with objectively measured behavioral and clinical outcomes.

Preoperative opioid use and complications following total joint replacement: a protocol for a systematic review and meta-analysis.

INTRODUCTION: Mounting evidence now indicates that preoperative opioid use is associated with an array of complications following total joint replacement (TJR). However, evidence of these risks remains fragmented. A comprehensive and well-integrated understanding of this body of evidence is necessary to appropriately inform treatment decisions, the allocation of limited healthcare resources, and the direction of future clinical research. The proposed systematic review and meta-analysis aims to identify and synthesise the available evidence of an association between opioid use prior to TJR and postoperative complications, categorised by complication type. METHODS AND ANALYSIS: We will search MEDLINE, EMBASE, CINAHL, PsycINFO, and Web of Science from inception to April 2020. Observational and experimental studies that compare preoperative opioid users who have undergone elective TJR to opioid naïve TJR patients will be included. The primary outcomes will be postoperative complications, which will be categorised as either mortality, morbidity, or joint-related complications. The secondary outcomes will be persistent postoperative opioid use, readmission, and length of stay. Individual study quality will be assessed using the relevant NIH-NHLBI study quality assessment tools. Findings will be reported in narrative and tabular form, and, where possible, odds ratios (dichotomous outcomes) or standardised mean differences (continuous outcomes) will be reported with 95% confidence intervals. Where appropriate, random effect meta-analyses will be conducted for each outcome, and heterogeneity will be quantified using the I2 statistic and Cochran's Q test. This study will be reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Meta-analyses Of Observational Studies in Epidemiology (MOOSE) guidelines. ETHICS AND DISSEMINATION: Ethics approval will not be required as no primary or private data are being collected. Findings will be disseminated through peer-reviewed publication and presentation at academic conferences. PROSPERO REGISTRATION NUMBER: CRD42020153047.

Multimorbidity, mortality, and HbA1c in type 2 diabetes: A cohort study with UK and Taiwanese cohorts.

BACKGROUND: There is emerging interest in multimorbidity in type 2 diabetes (T2D), which can be either concordant (T2D related) or discordant (unrelated), as a way of understanding the burden of disease in T2D. Current diabetes guidelines acknowledge the complex nature of multimorbidity, the management of which should be based on the patient's individual clinical needs and comorbidities. However, although associations between multimorbidity, glycated haemoglobin (HbA1c), and mortality in people with T2D have been studied to some extent, significant gaps remain, particularly regarding different patterns of multimorbidity, including concordant and discordant conditions. This study explores associations between multimorbidity (total condition counts/concordant/discordant/different combinations of conditions), baseline HbA1c, and all-cause mortality in T2D. METHODS AND FINDINGS: We studied two longitudinal cohorts of people with T2D using the UK Biobank (n = 20,569) and the Taiwan National Diabetes Care Management Program (NDCMP) (n = 59,657). The number of conditions in addition to T2D was used to quantify total multimorbidity, concordant, and discordant counts, and the effects of different combinations of conditions were also studied. Outcomes of interest were baseline HbA1c and all-cause mortality. For the UK Biobank and Taiwan NDCMP, mean (SD) ages were 60.2 (6.8) years and 60.8 (11.3) years; 7,579 (36.8%) and 31,339 (52.5%) were female; body mass index (BMI) medians (IQR) were 30.8 (27.7, 34.8) kg/m2 and 25.6 (23.5, 28.7) kg/m2; and 2,197 (10.8%) and 9,423 (15.8) were current smokers, respectively. Increasing total and discordant multimorbidity counts were associated with lower HbA1c and increased mortality in both datasets. In Taiwan NDCMP, for those with four or more additional conditions compared with T2D only, the mean difference (95% CI) in HbA1c was -0.82% (-0.88, -0.76) p < 0.001. In UK Biobank, hazard ratios (HRs) (95% CI) for all-cause mortality in people with T2D and one, two, three, and four or more additional conditions compared with those without comorbidity were 1.20 (0.91-1.56) p < 0.001, 1.75 (1.35-2.27) p < 0.001, 2.17 (1.67-2.81) p < 0.001, and 3.14 (2.43-4.03) p < 0.001, respectively. Both concordant/discordant conditions were significantly associated with mortality; however, HRs were largest for concordant conditions. Those with four or more concordant conditions had >5 times the mortality (5.83 [4.28-7.93] p <0.001). HRs for NDCMP were similar to those from UK Biobank for all multimorbidity counts. For those with two conditions in addition to T2D, cardiovascular diseases featured in 18 of the top 20 combinations most highly associated with mortality in UK Biobank and 12 of the top combinations in the Taiwan NDCMP. In UK Biobank, a combination of coronary heart disease and heart failure in addition to T2D had the largest effect size on mortality, with a HR (95% CI) of 4.37 (3.59-5.32) p < 0.001, whereas in the Taiwan NDCMP, a combination of painful conditions and alcohol problems had the largest effect size on mortality, with an HR (95% CI) of 4.02 (3.08-5.23) p < 0.001. One limitation to note is that we were unable to model for changes in multimorbidity during our study period. CONCLUSIONS: Multimorbidity patterns associated with the highest mortality differed between UK Biobank (a population predominantly comprising people of European descent) and the Taiwan NDCMP, a predominantly ethnic Chinese population. Future research should explore the mechanisms underpinning the observed relationship between increasing multimorbidity count and reduced HbA1c alongside increased mortality in people with T2D and further examine the implications of different patterns of multimorbidity across different ethnic groups. Better understanding of these issues, especially effects of condition type, will enable more effective personalisation of care.

Developing prediction models for total knee replacement surgery in patients with osteoarthritis: Statistical analysis plan.

Background: Approximately 12-20% of those with osteoarthritis (OA) in Australia who undergo total knee replacement (TKR) surgery do not report any clinical improvement. There is a need to develop prediction tools for use in general practice that allow early identification of patients likely to undergo TKR and those unlikely to benefit from the surgery. First-line treatment strategies can then be implemented and optimised to delay or prevent the need for TKR. The identification of potential non-responders to TKR may provide the opportunity for new treatment strategies to be developed and help ensure surgery is reserved for those most likely to benefit. This statistical analysis plan (SAP) details the statistical methodology used to develop such prediction tools. Objective: To describe in detail the statistical methods used to develop and validate prediction models for TKR surgery in Australian patients with OA for use in general practice. Methods: This SAP contains a brief justification for the need for prediction models for TKR surgery in general practice. A description of the data sources that will be linked and used to develop the models, and estimated sample sizes is provided. The planned methodologies for candidate predictor selection, model development, measuring model performance and internal model validation are described in detail. Intended table layouts for presentation of model results are provided. Conclusion: Consistent with best practice guidelines, the statistical methodologies outlined in this SAP have been pre-specified prior to data pre-processing and model development.

Use of professional-mode flash glucose monitoring, at 3-month intervals, in adults with type 2 diabetes in general practice (GP-OSMOTIC): a pragmatic, open-label, 12-month, randomised controlled trial.

BACKGROUND: Continuous glucose monitoring, either real-time (personal) or retrospective (professional mode), can identify day-to-day glucose profiles to guide management decisions for people with type 2 diabetes. We aimed to examine the effects of professional-mode flash glucose monitoring, done at 3-month intervals, in adults with type 2 diabetes in general practice. METHODS: We did a pragmatic, two-arm, open label, 12-month, individually randomised controlled trial (GP-OSMOTIC) in 25 general practices in Victoria, Australia. Eligible participants were adults aged 18-80 years, with type 2 diabetes diagnosed for at least 1 year and HbA1c at least 5·5 mmol/mol (0·5%) above their target in the past month despite being prescribed at least two non-insulin glucose-lowering drugs, insulin, or both (with therapy stable for at least 4 months). We randomly assigned participants (1:1) to either use of a professional-mode flash glucose monitoring system or usual clinical care (control). All participants wore the flash glucose monitoring sensor at baseline, and electronic randomisation (using permuted block sizes of four and six, and stratified by clinic) was done after the sensor was attached. Masking of participants and treating clinicians to group allocation was not possible, but the study statistician was masked to allocation when analysing the data. At baseline, and 3, 6, 9, and 12 months, participants in the flash glucose monitoring group wore the professional-mode flash glucose monitoring sensor for 5-14 days before their general practice visit. The sensor recorded interstitial glucose concentrations every 15 min, but the glucose data were not available to the participant until their general practice visit, where the sensor output would be uploaded to a computer by the health professional and discussed. Control group participants wore the sensor at baseline and at 12 months for data analysis only, and had usual care visits every 3 months. The primary outcome was the between-group difference in mean HbA1c at 12 months. Secondary outcomes were the between-group differences in: mean percentage time in target glucose range (4-10 mmol/L), based on ambulatory glucose profile data at 12 months; mean diabetes-specific distress (assessed with the Problem Areas In Diabetes [PAID] scale) at 12 months; and mean HbA1c at 6 months. Analysis was done by intention to treat. This trial is registered at the Australian and New Zealand Clinical Trials Registry, ACTRN12616001372471. FINDINGS: Between Oct 4, 2016, and Nov 17, 2017, we randomly assigned 299 adults: 149 to flash glucose monitoring and 150 to usual care. At 6 months, HbA1c was lower in the flash glucose monitoring group than in the usual care group (difference -0·5%, 95% CI -0·8% to -0·3%; p=0·0001). However, at 12 months (primary outcome), there was no significant between-group difference in estimated mean HbA1c (8·2% [95% CI 8·0 to 8·4] for flash glucose monitoring vs 8·5% [8·3 to 8·7] for usual care; between-group difference -0·3%, 95% CI -0·5 to 0·01; [66 mmol/mol, 95% CI 64 to 68 vs 69 mmol/mol, 67 to 72; between-group difference -3·0, 95% CI -5·0 to 0·1]; p=0·059). Mean percentage time spent in target glucose range at 12 months was 7·9% (95% CI 2·3 to 13·5) higher in the flash glucose monitoring group than in the usual care group (p=0·0060). Diabetes-specific distress PAID scores were unchanged at 12 months (between-group difference -0·7, 95% CI -3·3 to 1·9; p=0·61). No episodes of severe hypoglycaemia or treatment-related deaths were reported. One participant died during the study from causes unrelated to the intervention (following complications post-myocardial infarction with multiple comorbidities). INTERPRETATION: Professional-mode flash glucose monitoring in adults with type 2 diabetes in general practice did not improve the primary outcome of HbA1c at 12 months or diabetes-specific distress compared with usual care, but did improve time in target glucose range at 12 months and HbA1c at 6 months. Our findings suggest that professional-mode flash glucose monitoring can be implemented in a pragmatic primary care environment. Although there was no change in HbA1c at 12 months, the improved time in target range might reflect the potential of the technology to support personalised clinical care by providing insights into glycaemic profiles for some people with type 2 diabetes. FUNDING: National Health and Medical Research Council of Australia, Sanofi Australia, and Abbott Diabetes Care.

Effectiveness of a Mental Health Service Navigation Website (Link) for Young Adults: Randomized Controlled Trial.

BACKGROUND: Mental health and substance use disorders are the main causes of disability among adolescents and young adults yet fewer than half experiencing these problems seek professional help. Young people frequently search the Web for health information and services, suggesting that Web-based modalities might promote help-seeking among young people who need it. To support young people in their help-seeking, we developed a Web-based mental health service navigation website called Link. Link is based on the Theory of Planned Behavior and connects young people with treatment based on the type and severity of mental health symptoms that they report. OBJECTIVE: The study aimed to investigate the effect of Link on young people's positive affect (PA) compared with usual help-seeking strategies immediately post intervention. Secondary objectives included testing the effect of Link on negative affect (NA), psychological distress, barriers to help-seeking, and help-seeking intentions. METHODS: Young people, aged between 18 and 25 years, were recruited on the Web from an open access website to participate in a randomized controlled trial. Participants were stratified by gender and psychological distress into either the intervention arm (Link) or the control arm (usual help-seeking strategies). Baseline, immediate postintervention, 1-month, and 3-month surveys were self-reported and administered on the Web. Measures included the PA and NA scales, Kessler psychological distress scale (K10), barriers to adolescent help-seeking scale (BASH), and the general help-seeking questionnaire (GHSQ). RESULTS: In total 413 young people were recruited to the trial (intervention, n=205; control, n=208) and 78% (160/205) of those randomized to the intervention arm visited the Link website. There was no evidence to support a difference between the intervention and control arms on the primary outcome, with PA increasing equally by approximately 30% between baseline and 3 months in both arms. NA decreased for the intervention arm compared with the control arm with a difference of 1.4 (95% CI 0.2-2.5) points immediately after the intervention and 2.6 (95% CI 1.1-4.1) at 1 month. K10 scores were unchanged and remained high in both arms. No changes were found on the BASH or GHSQ; however, participants in the intervention arm appeared more satisfied with their help-seeking process and outcomes at 1 and 3 months postintervention. CONCLUSIONS: The process of prompting young people to seek mental health information and services appears to improve their affective state and increase help-seeking intentions, regardless of whether they use a Web-based dedicated youth-focused tool, such as Link, or their usual search strategies. However, young people report greater satisfaction using tools designed specifically for them, which may encourage future help-seeking. The ability of Web-based tools to match mental health needs with appropriate care should be explored further. CLINICAL TRIAL: Australian New Zealand Clinical Trials Registry ACTRN12614001223628; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=366731.

Update on the General Practice Optimising Structured Monitoring to Improve Clinical Outcomes in Type 2 Diabetes (GP-OSMOTIC) trial: statistical analysis plan for a multi-centre randomised controlled trial.

BACKGROUND: General Practice Optimising Structured Monitoring to Improve Clinical Outcomes in Type 2 Diabetes (GP-OSMOTIC) is a multicentre, individually randomised controlled trial aiming to compare the use of intermittent retrospective continuous glucose monitoring (r-CGM) to usual care in patients with type 2 diabetes attending general practice. The study protocol was published in the British Medical Journal Open and described the principal features of the statistical methods that will be used to analyse the trial data. This paper provides greater detail on the statistical analysis plan, including background and justification for the statistical methods chosen, in accordance with SPIRIT guidelines. OBJECTIVE: To describe in detail the data management process and statistical methods that will be used to analyse the trial data. METHODS: An overview of the trial design and primary and secondary research questions are provided. Sample size assumptions and calculations are explained, and randomisation and data management processes are described in detail. The planned statistical analyses for primary and secondary outcomes and sub-group analyses are specified along with the intended table layouts for presentation of the results. CONCLUSION: In accordance with best practice, all analyses outlined in the document are based on the aims of the study and have been pre-specified prior to the completion of data collection and outcome analyses. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry, ACTRN12616001372471 . Registered on 3 August 2016.

Prescribing of diabetes medications to people with type 2 diabetes and chronic kidney disease: a national cross-sectional study.

BACKGROUND: Previous studies in general practice and hospital settings have identified that prescribing of non-insulin diabetes medications may be sub-optimal in people with type 2 diabetes (T2D) and renal impairment. Since these publications, a number of new medications have become available for the management of T2D. Study aims were to, in a cohort of Australians with T2D and renal impairment attending general practice, (1) investigate whether the prescribing of non-insulin diabetes medications is consistent with dosing adjustments recommended within current Australian Diabetes Society (ADS) guidelines; and (2) identify patient socio-demographic and clinical factors associated with at least one prescription of a non-insulin diabetes medication inconsistent with current ADS guidelines for medication doses. METHODS: Cross-sectional study using data from the MedicineInsight general practice database managed by NPS MedicineWise. Patients with T2D who were aged 18 years and over, with an average eGFR< 60 ml/min/1.73m2 and at least one prescription of a non-insulin diabetes medication between 1st January 2015 and 30th June 2017 were included. Descriptive statistics were used to summarise patient characteristics and medication use. Marginal logistic regression models were used to estimate associations between sociodemographic and clinical factors and prescribing of ≥1non-insulin diabetes medicine not consistent with ADS guidelines. RESULTS: The majority of the 3505 patients included (90.4%) had an average eGFR of 30-59 ml/min/1.73m2. In terms of absolute numbers, metformin was the medication most frequently prescribed at a dose not consistent with current ADS guidelines for dosing in renal impairment (n = 1601 patients), followed by DPP4 inhibitors (n = 611) and sulphonylureas (n = 278). The drug classes with the highest proportion of prescriptions with dosage not consistent with ADS guidelines were SGLT2 inhibitors (83%), followed by biguanides (58%) and DPP4 inhibitors (46%). Higher HbA1c, longer known diabetes duration and diagnosis of retinopathy were associated with receiving ≥1prescription with a dosage not consistent with guidelines. CONCLUSIONS: Prescribing of non-insulin diabetes medications at doses inconsistent with current ADS guideline recommendations for dosing adjustments for people with renal impairment was common. Further research is needed to understand how general practitioners access, interpret and apply the ADS guidelines and the impact this may have on patient outcomes.

Prescribing for people with type 2 diabetes and renal impairment in Australian general practice: A national cross sectional study.

AIM: To determine whether the prescribing of non-insulin anti-hyperglycaemic medications in Australian general practice is consistent with current guidelines for treatment of type 2 diabetes (T2D) in people with renal impairment. METHODS: Cross-sectional study of 9624 people with T2D in the NPS MedicineInsight dataset aged≥18years with average estimated glomerular filtration rate (eGFR) <60ml/min/1.73m2 and prescribed at least one non-insulin anti-hyperglycaemic medication from October 2014 to September 2015. The primary outcome was the proportion of non-insulin anti-hyperglycaemic medications prescribed at doses inconsistent with current guidelines. RESULTS: 4650 (48.3%) patients were prescribed at least one non-insulin anti-hyperglycaemic medication at a dose inconsistent with Australian Diabetes Society guidelines. The majority (88.0%) had an average eGFR of 30-59ml/min/1.73m2. Metformin was the most frequently prescribed agent (n=7408; 77.0%), and was prescribed at a dose inconsistent with guidelines for 52% of patients. 123/136 (90.5%) people prescribed a sodium glucose co-transporter 2 inhibitor and 1114/2194 (50.8%) prescribed a dipeptidyl peptidase-4 inhibitor were prescribed a dose inconsistent with guidelines. Decreasing age, being male or being on insulin was associated with greater odds of at least one prescription inconsistent with guidelines. CONCLUSION: Nearly half of people with T2D and renal impairment were prescribed a non-insulin anti-hyperglycaemic medication at a dose inconsistent with current Australian guidelines, the majority of whom had an eGFR consistent with stage 3 chronic kidney disease.