Trial of Vancomycin and Cefazolin as Surgical Prophylaxis in Arthroplasty.

BACKGROUND: The addition of vancomycin to beta-lactam prophylaxis in arthroplasty may reduce surgical-site infections; however, the efficacy and safety are unclear. METHODS: In this multicenter, double-blind, superiority, placebo-controlled trial, we randomly assigned adult patients without known methicillin-resistant Staphylococcus aureus (MRSA) colonization who were undergoing arthroplasty to receive 1.5 g of vancomycin or normal saline placebo, in addition to cefazolin prophylaxis. The primary outcome was surgical-site infection within 90 days after surgery. RESULTS: A total of 4239 patients underwent randomization. Among 4113 patients in the modified intention-to-treat population (2233 undergoing knee arthroplasty, 1850 undergoing hip arthroplasty, and 30 undergoing shoulder arthroplasty), surgical-site infections occurred in 91 of 2044 patients (4.5%) in the vancomycin group and in 72 of 2069 patients (3.5%) in the placebo group (relative risk, 1.28; 95% confidence interval [CI], 0.94 to 1.73; P = 0.11). Among patients undergoing knee arthroplasty, surgical-site infections occurred in 63 of 1109 patients (5.7%) in the vancomyin group and in 42 of 1124 patients (3.7%) in the placebo group (relative risk, 1.52; 95% CI, 1.04 to 2.23). Among patients undergoing hip arthroplasty, surgical-site infections occurred in 28 of 920 patients (3.0%) in the vancomyin group and in 29 of 930 patients (3.1%) in the placebo group (relative risk, 0.98; 95% CI, 0.59 to 1.63). Adverse events occurred in 35 of 2010 patients (1.7%) in the vancomycin group and in 35 of 2030 patients (1.7%) in the placebo group, including hypersensitivity reactions in 24 of 2010 patients (1.2%) and 11 of 2030 patients (0.5%), respectively (relative risk, 2.20; 95% CI, 1.08 to 4.49), and acute kidney injury in 42 of 2010 patients (2.1%) and 74 of 2030 patients (3.6%), respectively (relative risk, 0.57; 95% CI, 0.39 to 0.83). CONCLUSIONS: The addition of vancomycin to cefazolin prophylaxis was not superior to placebo for the prevention of surgical-site infections in arthroplasty among patients without known MRSA colonization. (Funded by the Australian National Health and Medical Research Council; Australian New Zealand Clinical Trials Registry number, ACTRN12618000642280.).

A Randomized Noninferiority Trial to Compare Enteral to Parenteral Phosphate Replacement on Biochemistry, Waste, and Environmental Impact and Healthcare Cost in Critically Ill Patients With Mild to Moderate Hypophosphatemia.

OBJECTIVES: Hypophosphatemia occurs frequently. Enteral, rather than IV, phosphate replacement may reduce fluid replacement, cost, and waste. DESIGN: Prospective, randomized, parallel group, noninferiority clinical trial. SETTING: Single center, 42-bed state trauma, medical and surgical ICUs, from April 20, 2022, to July 1, 2022. PATIENTS: Patients with serum phosphate concentration between 0.3 and 0.75 mmol/L. INTERVENTIONS: We randomized patients to either enteral or IV phosphate replacement using electronic medical record-embedded program. MEASUREMENT AND MAIN RESULTS: Our primary outcome was serum phosphate at 24 hours with a noninferiority margin of 0.2 mmol/L. Secondary outcomes included cost savings and environmental waste reduction and additional IV fluid administered. The modified intention-to-treat cohort comprised 131 patients. Baseline phosphate concentrations were similar between the two groups. At 24 hours, mean ( sd ) serum phosphate concentration were enteral 0.89 mmol/L (0.24 mmol/L) and IV 0.82 mmol/L (0.28 mmol/L). This difference was noninferior at the margin of 0.2 mmol/L (difference, 0.07 mmol/L; 95% CI, -0.02 to 0.17 mmol/L). When assigned IV replacement, patients received 408 mL (372 mL) of solvent IV fluid. Compared with IV replacement, the mean cost per patient was ten-fold less with enteral replacement ($3.7 [$4.0] vs. IV: $37.7 [$31.4]; difference = $34.0 [95% CI, $26.3-$41.7]) and weight of waste was less (7.7 g [8.3 g] vs. 217 g [169 g]; difference = 209 g [95% CI, 168-250 g]). C O2 emissions were 60-fold less for comparable phosphate replacement (enteral: 2 g producing 14.2 g and 20 mmol of potassium dihydrogen phosphate producing 843 g of C O2 equivalents). CONCLUSIONS: Enteral phosphate replacement in ICU is noninferior to IV replacement at a margin of 0.2 mmol/L but leads to a substantial reduction in cost and waste.

Examining the impact of structural uncertainty across ten type 2 diabetes models: Results from the 2022 Mount Hood Challenge.

OBJECTIVE: The Mount Hood Diabetes Challenge Network aimed to examine the impact of model structural uncertainty on the estimated cost-effectiveness of interventions for type 2 diabetes. METHODS: Ten independent modelling groups completed a blinded simulation exercise to estimate the cost-effectiveness of three interventions in two type 2 diabetes populations. Modelling groups were provided with a common baseline population, cost and utility values associated with different model health states, and instructions regarding time horizon and discounting. We collated the results to identify variation in predictions of net monetary benefit (NMB), and the drivers of those differences. RESULTS: Overall, modelling groups agreed which interventions had a positive NMB (i.e. were cost-effective), though estimates of NMB varied substantially- by up to £23,696 for one intervention. Variation was mainly driven through differences in risk equations for complications of diabetes and their implementation between models. The number of modelled health states was also a significant predictor of NMB. CONCLUSIONS: This exercise demonstrates that structural uncertainty between different health economic models impacts cost-effectiveness estimates. Whilst it is reassuring that a decision maker would likely reach similar conclusions on which interventions were cost-effective using most models, the range in numerical estimates generated across different models would nevertheless be important for price-setting negotiations with intervention developers. Minimising the impact of structural uncertainty on healthcare decision making therefore remains an important priority. Model registries, which record and compare the impact of structural assumptions, offer one potential avenue to improve confidence in the robustness of health economic modelling.

Health-related quality of life in patients with extremity bone sarcoma after surgical treatment: a systematic review.

PURPOSE: We conducted a systematic review of studies reporting on measurement of health-related quality of life (HRQoL), with a special focus on the use of the preference-weighted instruments, in patients with extremity bone sarcoma treated with limb-salvage surgery or amputation. METHODS: We searched MedLine, Embase, Cochrane Library and Web of Science for English-language studies reporting on HRQoL of patients with bone sarcoma from inception to 28 August 2023. All records found were independently reviewed by two reviewers. We used the Newcastle-Ottawa Scale (NOS) and the CONSORT 2010 checklist to assess the quality of the cohort and randomised studies, respectively. RESULTS: The search identified 1225 records, of which 16 studies were included for data extraction. Only one study used a preference-weighted instrument for measuring HRQoL in a small sample of patients (n = 28). Ten studies used the generic SF-36 questionnaire, but no preference-weighted HRQoL based on SF-6D was derived from the SF-36 scores. Most studies comparing HRQoL between amputation and limb-salvage surgery reported no significant differences. Twelve cohort studies scored six or more out of nine points based on the NOS. The only randomised study scored 54% on the CONSORT 2010 checklist. CONCLUSIONS: The approaches used to measure HRQoL were inconsistent and outcome scores varied substantially. Only one study used preference-weighted instruments for HRQoL measurement. Future research into the surgical treatment of extremity bone sarcoma should consider the use of preference-weighted instruments to measure HRQoL, which will therefore enable economic evaluation for the growing orthopaedic armamentarium of novel surgical interventions. REGISTRATION: This systematic review was registered with the PROSPERO International prospective register of systematic reviews (CRD42021282380).

Understanding the measurement relationship between EQ-5D-5L, PROMIS-29 and PROPr.

PURPOSE: Many generic patient-reported instruments are available for the measurement of health outcomes, including EQ-5D-5L, and the Patient-Reported Outcome Measurement Information System (PROMIS). Assessing their measurement characteristics informs users about the consistency between, and limits of, evidence produced. The aim was to assess the measurement relationship between the EQ-5D-5L descriptive system and value sets, the PROMIS-29 and PROPr (PROMIS value set). METHODS: Data were extracted from a cross-sectional survey administering measures of quality of life online in Australia. Descriptive analysis, agreement and construct validity assessment methods were used to compare instruments at the item, domain and value set level. RESULTS: In total, 794 Australians completed the survey. Convergent validity analysis found that similar dimensions across instruments were highly correlated (> 0.50), but the PROMIS-29 assesses additional health concepts not explicitly covered by EQ-5D (sleep and fatigue). Known-group assessment found that EQ-5D-5L and PROPr were able to detect those with and without a condition (ES range 0.78-0.83) but PROPr could more precisely detect differing levels of self-reported health. Both instruments were sensitive to differences in levels of pain. DISCUSSION: There is some consistency in what the EQ-5D-5L, PROMIS-29 and PROPr measure. Differences between value set characteristics can be linked to differences what is measured and the valuation approaches used. This has implications for the use of each in assessing health outcomes, and the results can inform decisions about which instrument should be used in which context.

Telehealth in oncology: a cost analysis to evaluate the financial impact of implementing regional trial hubs within a phase 3 cancer clinical trial.

This cost analysis, from a societal perspective, compared the cost difference of a networked teletrial model (NTTM) with four regional hubs versus conventional trial operation at a single metropolitan specialist centre. The Australian phase 3 cancer interventional randomised controlled trial included 152 of 328 regional participants (patient enrolment 2018-2021; 6-month primary end point). The NTTM significantly reduced (AU$2155 per patient) patient travel cost and time and lost productivity.

The comparative mortality of an elite group in the long run of history: an observational analysis of politicians from 11 countries.

This study aims to compare the mortality rate and life expectancy of politicians with those of the age and gender-matched general populations. This was an observational analysis of mortality rates of politicians (i.e. members of national parliaments with available data on dates of birth, death and election, gender, and life tables) in 11 developed countries. Politicians were followed from date of first election until either death or the last available year with life table data. Relative mortality differences were estimated using standardised mortality ratios (SMRs). Absolute inequalities were quantified as the difference in survival by deducting a population's remaining life expectancy from politicians' remaining life expectancy at age 45, estimated using Gompertz parametric proportional hazards models. We included 57,561 politicians (with follow-up ranging from 1816-2016 for France to 1949-2017 for Germany). In almost all countries politicians had similar rates of mortality to the general population in the early part of the twentieth century. Relative mortality and survival differences (favouring politicians) increased considerably over the course of the twentieth century, with recent SMRs ranging from 0.45 (95%CI 0.41-0.50) in Italy to 0.82 (95%CI 0.69-0.95) in New Zealand. The peak life expectancy gaps ranged from 4.4 (95% CI, 3.5-5.4) years in the Netherlands to 7.8 (95% CI, 7.2-8.4) years in the US. Our results show large relative and absolute inequalities favouring politicians in every country. In some countries, such as the US, relative inequalities are at the greatest level in over 150 years.

Evidence on the relationship between PROMIS-29 and EQ-5D: a literature review.

PURPOSE: EQ-5D and PROMIS-29 are both concise, generic measures of patient-reported outcomes accompanied by preference weights that allow the estimation of quality-adjusted life years (QALYs). Both instruments are candidates for use in economic evaluation. However, they have different features in terms of the domains selected to measure respondents' self-perceived health and the characteristics of (and methods used to obtain) the preference weights. It is important to understand the relationship between the instruments and the implications of choosing either for the evidence used in decision-making. This literature review aimed to synthesise existing evidence on the relationship between PROMIS-29 (and measures based on it, such as PROMIS-29+2) and EQ-5D (both EQ-5D-3L and EQ-5D-5L). METHODS: A literature review was conducted in PubMed and Web of Science to identify studies investigating the relationship between PROMIS-29 and EQ-5D-based instruments. RESULTS: The literature search identified 95 unique studies, of which nine studies met the inclusion criteria, i.e. compared both instruments. Six studies examined the relationship between PROMIS-29 and EQ-5D-5L. Three main types of relationship have been examined in the nine studies: (a) comparing PROMIS-29 and EQ-5D as descriptive systems; (b) mapping PROMIS-29 domains to EQ-5D utilities; and (c) comparing and transforming PROMIS-29 utilities to EQ-5D utilities. CONCLUSION: This review has highlighted the lack of evidence regarding the relationship between PROMIS-29 and EQ-5D. The impact of choosing either instrument on the evidence used in cost-effectiveness analysis is currently unclear. Further research is needed to understand the relationship between the two instruments.

Development of a life expectancy table for individuals with type 1 diabetes.

AIMS/HYPOTHESIS: Tables reporting life expectancies by common risk factors are available for individuals with type 2 diabetes; however, there is currently no published equivalent for individuals with type 1 diabetes. We aimed to develop a life expectancy table using a recently published simulation model for individuals with type 1 diabetes. METHODS: The simulation model was developed using data from a real-world population of patients with type 1 diabetes selected from the Swedish National Diabetes Register. The following six important risk factors were included in the life table: sex; age; current smoking status; BMI; eGFR; and HbA1c. For each of 1024 cells in the life expectancy table, a synthetic cohort containing 1000 individuals was created, with other risk factors assigned values representative of the real-world population. The simulations were executed for all synthetic cohorts and life expectancy for each cell was calculated as mean survival time of the individuals in the respective cohort. RESULTS: There was a substantial variation in life expectancy across patients with different risk factor levels. Life expectancy of 20-year-old men varied from 29.3 years to 50.6 years, constituting a gap of 21.3 years between those with worst and best risk factor levels. In 20-year-old women, this gap was 18.9 years (life expectancy range 35.0-53.9 years). The variation in life expectancy was a function of the combination of risk factor values, with HbA1c and eGFR consistently showing a negative and positive correlation, respectively, with life expectancy at any level combination of other risk factors. Individuals with the lowest level (20 kg/m2) and highest level of BMI (35 kg/m2) had a lower life expectancy compared with those with a BMI of 25 kg/m2. Non-smokers and women had a higher life expectancy than smokers and men, respectively, with the difference in life expectancy ranging from 0.4 years to 2.7 years between non-smokers and smokers, and from 1.9 years to 5.9 years between women and men, depending on levels of other risk factors. CONCLUSIONS/INTERPRETATION: The life expectancy table generated in this study shows a substantial variation in life expectancy across individuals with different modifiable risk factors. The table allows for rapid communications of risk in an easily understood format between healthcare professionals, health economists, researchers, policy makers and patients. Particularly, it supports clinicians in their discussion with patients about the benefits of improving risk factors.

Development and Use of Prediction Models for Classification of Cardiovascular Risk of Remote Indigenous Australians.

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death for Indigenous Australians. There is widespread belief that current tools have deficiencies for assessing CVD risk in this high-risk population. We sought to develop a 5-year CVD risk score using a wide range of known risk factors to further improve CVD risk prediction in this population. METHODS: We used clinical and demographic information on Indigenous people aged between 30 and 74 years without a history of CVD events who participated in the Well Person's Health Check (WPHC), a community-based survey. Baseline assessments were conducted between 1998 and 2000, and data were linked to administrative hospitalisation and death records for identification of CVD events. We used Cox proportional hazard models to estimate the 5-year CVD risk, and the Harrell's c-statistic and the modified Hosmer-Lemeshow (mH-L) χ2 statistic to assess the model discrimination and calibration, respectively. RESULTS: The study sample consisted of 1,583 individuals (48.1% male; mean age 45.0 year). The risk score consisted of sex, age, systolic blood pressure, diabetes mellitus, waist circumference, triglycerides, and albumin creatinine ratio. The bias-corrected c-statistic was 0.72 and the bias-corrected mH-L χ2 statistic was 12.01 (p-value, 0.212), indicating good discrimination and calibration, respectively. Using our risk score, the CVD risk of the Indigenous Australians could be stratified to a greater degree compared to a recalibrated Framingham risk score. CONCLUSIONS: A seven-factor risk score could satisfactorily stratify 5-year risk of CVD in an Indigenous Australian cohort. These findings inform future research targeting CVD risk in Indigenous Australians.

Computer Modeling of Diabetes and Its Transparency: A Report on the Eighth Mount Hood Challenge.

OBJECTIVES: The Eighth Mount Hood Challenge (held in St. Gallen, Switzerland, in September 2016) evaluated the transparency of model input documentation from two published health economics studies and developed guidelines for improving transparency in the reporting of input data underlying model-based economic analyses in diabetes. METHODS: Participating modeling groups were asked to reproduce the results of two published studies using the input data described in those articles. Gaps in input data were filled with assumptions reported by the modeling groups. Goodness of fit between the results reported in the target studies and the groups' replicated outputs was evaluated using the slope of linear regression line and the coefficient of determination (R2). After a general discussion of the results, a diabetes-specific checklist for the transparency of model input was developed. RESULTS: Seven groups participated in the transparency challenge. The reporting of key model input parameters in the two studies, including the baseline characteristics of simulated patients, treatment effect and treatment intensification threshold assumptions, treatment effect evolution, prediction of complications and costs data, was inadequately transparent (and often missing altogether). Not surprisingly, goodness of fit was better for the study that reported its input data with more transparency. To improve the transparency in diabetes modeling, the Diabetes Modeling Input Checklist listing the minimal input data required for reproducibility in most diabetes modeling applications was developed. CONCLUSIONS: Transparency of diabetes model inputs is important to the reproducibility and credibility of simulation results. In the Eighth Mount Hood Challenge, the Diabetes Modeling Input Checklist was developed with the goal of improving the transparency of input data reporting and reproducibility of diabetes simulation model results.

Use of Proton Pump Inhibitors and Risks of Fundic Gland Polyps and Gastric Cancer: Systematic Review and Meta-analysis.

BACKGROUND & AIMS: There have been increasing numbers of case reports and observational studies of adverse events in patients receiving long-term therapy with proton pump inhibitors (PPIs). The effects of PPI therapy on risks of fundic gland polyps (FGPs) and gastric cancer have received considerable attention. We performed a systematic review with a meta-analysis of randomized controlled trials and observational studies that assessed these risks. METHODS: We searched the PUBMED, EMBASE, and Cochrane Central Register of Controlled Trials databases for relevant studies published through July 2015. We calculated pooled odds ratio for FGPs and the risk ratio for gastric cancer in PPI users compared with PPI nonusers using fixed- and random-effects models. RESULTS: We analyzed data from 12 studies, comprising more than 87,324 patients: 1 randomized controlled trial reporting the effect of PPIs on gastric polyps (location not specified), 6 cohort and 1 case-control studies on FGPs, and 1 cohort and 3 case-control studies on gastric cancer. Pooled odds ratios for FGPs were 1.43 (95% confidence interval, 1.24-1.64) and 2.45 (95% confidence interval, 1.24-4.83) from fixed- and random-effects models, respectively. The pooled risk ratio for gastric cancer was 1.43 (95% confidence interval, 1.23-1.66) from each model. We observed significant heterogeneity among studies reporting on FGPs, but not among studies reporting on gastric cancer. CONCLUSIONS: Based on a systematic review with meta-analysis, long-term use of PPIs (≥12 months) is associated with an increased risk of FGPs. PPI therapy might also increase the risk of gastric cancer, but this association could be biased, because of the limited number of studies and possible confounding factors.

Impact on total population health and societal cost, and the implication on the actual cost-effectiveness of including tumour necrosis factor-α antagonists in management of ankylosing spondylitis: a dynamic population modelling study.

BACKGROUND: Sequential treatment of ankylosing spondylitis (AS) that includes tumour necrosis factor-α antagonists (anti-TNF agents) has been applied in most of the Western countries. Existing cost-effectiveness (CE) models almost exclusively presented the incremental CE of anti-TNF agents using a closed cohort while budget impact studies are mainly lacking. Notwithstanding, information on impact on total population health and societal budget as well as on actual incremental CE for a given decision time span are important for decision makers. This study aimed at quantifying, for different decision time spans starting from January 1, 2014 in the Dutch society, (1) impact of sequential drug treatment strategies without and with inclusion of anti-TNF agents (Strategies 1 and 2, respectively) on total population health and societal cost, and (2) the actual incremental CE of Strategy 2 compared to Strategy 1. METHODS: Dynamic population modelling was used to capture total population health and cost, and the actual incremental CE. Distinguishing the prevalent AS population on January 1, 2014 and the incident AS cohorts in the subsequent 20 years, the model tracked individually an actual number of AS patients until death or end of the simulation time. During the simulation, data on patient characteristics, history of drug use, costs and health at discrete time points were generated. In Strategy 1, five nonsteroidal anti-inflammatory drugs (NSAIDs) were available but anti-TNF agents withdrawn. In Strategy 2, five NSAIDs and two anti-TNF agents continued to be available. RESULTS: The predicted size of the prevalent AS population in the Dutch society varied within the range of 67,145-69,957 with 44-46 % of the patients receiving anti-TNF agents over the period 2014-2034. The use of anti-TNF agents resulted in an increase in the annual drug costs (168.54-205.28 million Euros), but at the same time caused a decrease in the annual productivity costs (12.58-31.21 million Euros) and in annual costs of healthcare categories other than drugs (7.23-11.90 million Euros). Incremental cost (Euros) per QALY gained in Strategy 2 compared to Strategy 1 corresponding to decision time spans of 5, 10, 15 and 20 years improved slightly from 75,379 to 67,268, 63,938 and 61,129, respectively. At willingness-to-pay thresholds of 118,656, 112,067, 110,188 and 110,512 Euros, it was 99 % certain that Strategy 2 was cost-effective for decision time spans of 5, 10, 15 and 20, respectively. CONCLUSIONS: Using the dynamic population approach, the present model can project real-time data to inform a healthcare system decision that affects all actual number of AS patients eligible for anti-TNF agents within different decision time spans. The predicted total population costs of different categories in the present study can help plan the organization of the healthcare resources based on the national budget for the disease.

Early cost-utility analysis of general and cerebrospinal fluid-specific Alzheimer's disease biomarkers for hypothetical disease-modifying treatment decision in mild cognitive impairment.

INTRODUCTION: The study aimed to determine the room for improvement of a perfect cerebrospinal fluid (CSF) biomarker and the societal incremental net monetary benefit of CSF in subjects with mild cognitive impairment (MCI) assuming a hypothetical disease-modifying Alzheimer's disease (AD) treatment. METHODS: A decision model compared current practice to a perfect biomarker and to two strategies positioning CSF as add-on test when current practice concluded the presence or absence of AD. RESULTS: The simulated MCI population was aged on average 68.3 and 49% had AD. The room for improvement by the perfect CSF test was 0.39 quality adjusted life years, €33,622 ($43,372) savings, 2.0 potential beneficial treatment years, and 1.3-year delay in dementia conversion. DISCUSSION: The results indicated more potential benefit from a biomarker positioned to verify subjects who are not expected to have AD (i.e., to prevent undertreatment) rather than to verify subjects expected to have AD (prevent overtreatment). Sensitivity analyses explored different CSF positions.

Feasibility of Embedding a Randomised Clinical Trial (RCT) into an Electronic Medical Record (EMR) for Patients Admitted to an Intensive Care Unit (ICU).

To establish the feasibility of embedding an RCT into EMR in the ICU, we evaluated the route of phosphate replacement. The EMR screened 207 patients who met the inclusion criteria from 20 April 2022 to 30 June 2022. 162 patients were randomised and 145 patients allocated to treatment. Our study showed that it was feasible to embed screening, randomisation, and treatment allocation for an RCT within an EMR in the ICU.

Can flash glucose monitoring improve glucose management for Aboriginal and Torres Strait Islander peoples with type 2 diabetes? A protocol for a randomised controlled trial.

BACKGROUND: Aboriginal and Torres Strait Islander peoples are disproportionately impacted by type 2 diabetes. Continuous glucose monitoring (CGM) technology (such as Abbott Freestyle Libre 2, previously referred to as Flash Glucose Monitoring) offers real-time glucose monitoring that is convenient and easy to use compared to self-monitoring of blood glucose (SMBG). However, this technology's use is neither widespread nor subsidised for Aboriginal and Torres Strait Islander peoples with type 2 diabetes. Building on existing collaborations with a national network of Aboriginal and Torres Strait Islander communities, this randomised controlled trial aims to assess the effect of CGM compared to SMBG on (i) haemoglobin A1c (HbA1c), (ii) achieving blood glucose targets, (iii) reducing hypoglycaemic episodes and (iv) cost-effective healthcare in an Aboriginal and Torres Strait Islander people health setting. METHODS: This is a non-masked, parallel-group, two-arm, individually randomised, controlled trial (ACTRN12621000753853). Aboriginal and Torres Strait Islander adults with type 2 diabetes on injectable therapy and HbA1c ≥ 7.5% (n = 350) will be randomised (1:1) to CGM or SMBG for 6 months. The primary outcome is change in HbA1c level from baseline to 6 months. Secondary outcomes include (i) CGM-derived metrics, (ii) frequency of hypoglycaemic episodes, (iii) health-related quality of life and (iv) incremental cost per quality-adjusted life year gained associated with the CGM compared to SMBG. Clinical trial sites include Aboriginal Community Controlled Organisations, Aboriginal Medical Services, primary care centres and tertiary hospitals across urban, rural, regional and remote Australia. DISCUSSION: The trial will assess the effect of CGM compared to SMBG on HbA1c for Aboriginal and Torres Strait Islander people with type 2 diabetes in Australia. This trial could have long-term benefits in improving diabetes management and providing evidence for funding of CGM in this population. TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry ACTRN12621000753853. Registered on 15th June 2021.

Predicting high health-cost users among people with cardiovascular disease using machine learning and nationwide linked social administrative datasets.

OBJECTIVES: To optimise planning of public health services, the impact of high-cost users needs to be considered. However, most of the existing statistical models for costs do not include many clinical and social variables from administrative data that are associated with elevated health care resource use, and are increasingly available. This study aimed to use machine learning approaches and big data to predict high-cost users among people with cardiovascular disease (CVD). METHODS: We used nationally representative linked datasets in New Zealand to predict CVD prevalent cases with the most expensive cost belonging to the top quintiles by cost. We compared the performance of four popular machine learning models (L1-regularised logistic regression, classification trees, k-nearest neighbourhood (KNN) and random forest) with the traditional regression models. RESULTS: The machine learning models had far better accuracy in predicting high health-cost users compared with the logistic models. The harmony score F1 (combining sensitivity and positive predictive value) of the machine learning models ranged from 30.6% to 41.2% (compared with 8.6-9.1% for the logistic models). Previous health costs, income, age, chronic health conditions, deprivation, and receiving a social security benefit were among the most important predictors of the CVD high-cost users. CONCLUSIONS: This study provides additional evidence that machine learning can be used as a tool together with big data in health economics for identification of new risk factors and prediction of high-cost users with CVD. As such, machine learning may potentially assist with health services planning and preventive measures to improve population health while potentially saving healthcare costs.

Impact of health risk factors on healthcare resource utilization, work-related outcomes and health-related quality of life of Australians: a population-based longitudinal data analysis.

Background: Health risk factors, including smoking, excessive alcohol consumption, overweight, obesity, and insufficient physical activity, are major contributors to many poor health conditions. This study aimed to assess the impact of health risk factors on healthcare resource utilization, work-related outcomes and health-related quality of life (HRQoL) in Australia. Methods: We used two waves of the nationally representative Household, Income, and Labor Dynamics in Australia (HILDA) Survey from 2013 and 2017 for the analysis. Healthcare resource utilization included outpatient visits, hospitalisations, and prescribed medication use. Work-related outcomes were assessed through employment status and sick leave. HRQoL was assessed using the SF-6D scores. Generalized estimating equation (GEE) with logit or log link function and random-effects regression models were used to analyse the longitudinal data on the relationship between health risk factors and the outcomes. The models were adjusted for age, sex, marital status, education background, employment status, equilibrium household income, residential area, country of birth, indigenous status, and socio-economic status. Results: After adjusting for all other health risk factors covariates, physical inactivity had the greatest impact on healthcare resource utilization, work-related outcomes, and HRQoL. Physical inactivity increased the likelihood of outpatient visits (AOR = 1.60, 95% CI = 1.45, 1.76 p < 0.001), hospitalization (AOR = 1.83, 95% CI = 1.66-2.01, p < 0.001), and the probability of taking sick leave (AOR = 1.31, 95% CI = 1.21-1.41, p < 0.001), and decreased the odds of having an above population median HRQoL (AOR = 0.48, 95% CI = 0.45-0.51, p < 0.001) after adjusting for all other health risk factors and covariates. Obesity had the greatest impact on medication use (AOR = 2.02, 95% CI = 1.97-2.29, p < 0.001) after adjusting for all other health risk factors and covariates. Conclusion: Our study contributed to the growing body of literature on the relative impact of health risk factors for healthcare resource utilization, work-related outcomes and HRQoL. Our results suggested that public health interventions aim at improving these risk factors, particularly physical inactivity and obesity, can offer substantial benefits, not only for healthcare resource utilization but also for productivity.

Study protocol for TARGET protein: The effect of augmented administration of enteral protein to critically ill adults on clinical outcomes: A cluster randomised, cross-sectional, double cross-over, clinical trial.

Background: It is unknown whether increasing dietary protein to 1.2-2.0 g/kg/day as recommended in international guidelines compared to current practice improves outcomes in intensive care unit (ICU) patients. The TARGET Protein trial will evaluate this. Objective: To describe the study protocol for the TARGET Protein trial. Design setting and participants: TARGET Protein is a cluster randomised, cross-sectional, double cross-over, pragmatic clinical trial undertaken in eight ICUs in Australia and New Zealand. Each ICU will be randomised to use one of two trial enteral formulae for three months before crossing over to the other formula, which is then repeated, with enrolment continuing at each ICU for 12 months. All patients aged ≥16 years in their index ICU admission commencing enteral nutrition will be eligible for inclusion. Eligible patients will receive the trial enteral formula to which their ICU is allocated. The two trial enteral formulae are isocaloric with a difference in protein dose: intervention 100g/1000 ml and comparator 63g/1000 ml. Staggered recruitment commenced in May 2022. Main outcomes measures: The primary outcome is days free of the index hospital and alive at day 90. Secondary outcomes include days free of the index hospital at day 90 in survivors, alive at day 90, duration of invasive ventilation, ICU and hospital length of stay, incidence of tracheostomy insertion, renal replacement therapy, and discharge destination. Conclusion: TARGET Protein aims to determine whether augmented enteral protein delivery reduces days free of the index hospital and alive at day 90. Trial registration: Australian New Zealand Clinical Trials Registry (ACTRN12621001484831).