Medical Journal of Australia最新文献

{"title":"Participation in the National Bowel Cancer Screening Program by people with severe mental illness, Australia, 2006–2019: a national data linkage study","authors":"Oyedeji Ayonrinde, Sara Mohamed, Jenna Nensi","doi":"10.5694/mja2.52720","DOIUrl":"10.5694/mja2.52720","url":null,"abstract":"","PeriodicalId":18214,"journal":{"name":"Medical Journal of Australia","volume":"223 4","pages":""},"PeriodicalIF":8.5,"publicationDate":"2025-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144528635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimated carbon emissions for PBS-subsidised prescription respiratory inhalers, Australia, 2019–2023: a descriptive analysis","authors":"Luise Kazda,&nbsp;Alexandra L Barratt,&nbsp;Sean Docking,&nbsp;Kristen Pickles,&nbsp;Darlene Cox,&nbsp;Ross S Bailie,&nbsp;Kate Wylie,&nbsp;Katy JL Bell","doi":"10.5694/mja2.52715","DOIUrl":"10.5694/mja2.52715","url":null,"abstract":"<p>The Australian National Health and Climate Strategy<span>¹</span> identifies reducing the use of pressurised, metered dose inhalers as a high priority for decarbonising health care. These high emissions inhalers contain potent greenhouse gases as propellants, producing ten to thirty times as much in carbon dioxide equivalent (CO₂e) emissions as low emissions inhalers (dry powder and soft mist inhalers), which are often clinically equivalent.</p><p>To investigate the carbon footprint of inhalers dispensed in Australia and subsidised by the Pharmaceutical Benefits Scheme (PBS), we analysed aggregate-level PBS dispensing data for the period 1 January 2019 – 30 November 2023, based on United Kingdom estimates of emissions per inhaler.<span>²</span> We aggregated the estimated emissions for all inhalers dispensed by year and type, and summarised age-standardised population rates of inhaler dispensing. We then conducted time series analyses of monthly values, adjusted for autocorrelation, to derive regression trend lines; we estimated mean monthly percentage changes (MMPCs) using joinpoint regression analysis. For short-acting β₂ agonist inhalers, we assumed that a mean 1.5 inhalers were dispensed per script; in a sensitivity analysis, we assumed a mean of one inhaler was dispensed per script (further details: Supporting Information, part 1). The University of Canberra human research ethics committee exempted the study from formal ethics review (HREC 2024/14042). Access to the data and approval for the publication of findings based on the data were granted by Services Australia as data custodian.</p><p>The number of PBS-subsidised inhalers dispensed increased from 14.4 million in the 2019 calendar year to 15.5 million in 2023 (MMPC, 0.32%; 95% confidence interval [CI], 0.12–0.52%); estimated emissions increased from 217 510 t to 246 934 t CO₂e (MMPC, 0.46%; 95% CI, 0.22–0.71%). The increased dispensing of inhalers was primarily caused by the increased dispensing of high emissions inhalers, from 8.2 million to 9.2 million (MMPC, 0.43%; 95% CI, 0.22–0.65%); the dispensing of low emissions inhaler increased from 6.2 million to 6.3 million (MMPC, 0.15%; 95% CI, 0.01–0.29%). In 2019, 56.9% of dispensed PBS-subsidised inhalers were high emission inhalers, and 59.5% in 2023; in each year, they accounted for about 98% of total estimated PBS-subsidised inhaler-related emissions (Box 1; Box 2). The sensitivity analysis yielded similar results (Supporting Information, table 2).</p><p>Estimated emissions were greatest for short-acting β₂ agonist inhalers (4.8–5.5 million dispensed per year; 2023: 98% in high emissions inhalers; 140 558 t CO₂e, 57% of all inhaler-related emissions) and combined inhaled corticosteroid/long-acting β₂ agonist inhalers (5.6–6.4 million dispensed per year; 2023: 49% in high emissions inhalers; 83 491 t CO₂e, 34% of all inhaler-related e","PeriodicalId":18214,"journal":{"name":"Medical Journal of Australia","volume":"223 4","pages":"214-217"},"PeriodicalIF":8.5,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.5694/mja2.52715","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144497439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prescription opioid supply-restricting policies and hospital use by people prescribed opioid medications, Victoria, 2018–22: a controlled interrupted time series analysis","authors":"Suzanne Nielsen,&nbsp;Louisa Picco,&nbsp;Bosco Rowland,&nbsp;Nadine E Andrew,&nbsp;Taya A Collyer,&nbsp;Samanta Lalic,&nbsp;Rachelle Buchbinder,&nbsp;Christopher Pearce,&nbsp;J Simon Bell,&nbsp;Dan I Lubman,&nbsp;Ting Xia","doi":"10.5694/mja2.52713","DOIUrl":"10.5694/mja2.52713","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>To investigate the combined effect of two policies for reducing prescription opioid supply in Australia on hospital use by people prescribed opioids in primary care.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Study design</h3>\u0000 \u0000 <p>Retrospective data linkage study; controlled interrupted time series analysis of linked primary care electronic medication records and hospital admissions data.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Setting</h3>\u0000 \u0000 <p>Three Victorian health care networks (Monash Health, Eastern Health, Peninsula Health); pre-intervention period: 1 April 2018 – 31 March 2020; intervention period: 1 April 2020 – 31 March 2022.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Participants</h3>\u0000 \u0000 <p>People prescribed opioid medications at least twice during the preceding six months (opioid group) and propensity score-matched patients, based on age, gender, comorbidity, and residential postcode-based socio-economic status (control group); matching was undertaken for each month of the study period.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Intervention</h3>\u0000 \u0000 <p>Mandatory prescription drug monitoring (from 1 April 2020); tighter restriction criteria for the subsidisation of opioid medications by the Pharmaceutical Benefits Scheme (PBS) (from 1 June 2020).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Main outcome measures</h3>\u0000 \u0000 <p>Differences between the opioid and control groups in immediate changes after start of the intervention in rates of emergency department (ED) presentation and hospital admission related to opioid use, non-opioid substance use, self-harm, or mental health problems; differences between the two groups in the change in trend for these rates between the pre-intervention and intervention periods.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Propensity matching was undertaken for 179 091 people in the opioid group and a total of 389 061 people in the control group. The opioid-related ED presentation rate for the opioid group had been increasing prior to the intervention, but declined after its introduction at a rate not significantly different from that of the control group. The immediate change in non-opioid substance-related ED presentation rate was greater for the opioid group than the control group (β, 11.1 [95% confidence interval, 1.7–20.5] presentations ","PeriodicalId":18214,"journal":{"name":"Medical Journal of Australia","volume":"223 3","pages":"134-140"},"PeriodicalIF":8.5,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.5694/mja2.52713","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144497440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biology–society–environment: a changing paradigm for the changing Australian climate","authors":"Arnagretta Hunter","doi":"10.5694/mja2.52702","DOIUrl":"10.5694/mja2.52702","url":null,"abstract":"<p>Australians inhabit a continent of extraordinary natural beauty and biodiversity. But in recent years our lives have been defined by unprecedented extreme weather events — catastrophic bushfires blanketing cities in smoke for months, multiple once in a century floods, severe droughts that devastate rural communities, and record-breaking heatwaves — all of which have impacts on our health system. Climate change is not a future risk with targets for 2050 or 2100: it is a process that is reshaping Australian lives and health and wellbeing today.</p><p>The increase in the frequency and severity of extreme weather events poses significant challenges, and climate scientists warn that these events will intensify in coming decades.<span>^{1, 2}</span> Heat, for example, is already a significant contributor to mortality in Australia,<span>³</span> and will increasingly affect our health and wellbeing as our planet continues to warm. For our health system — federal and state government health departments, hospital networks and individual facilities, primary care and individual doctors — the question is how best to understand and integrate the effects of environmental variables on health and wellbeing into clinical practice to reduce the adverse impact of climate change on our health.</p><p>In this issue of the <i>MJA</i>, Stewart and colleagues report the findings of their clinical trial of a program for reducing bio-behavioural vulnerability to weather events in people with multimorbid heart disease.<span>⁴</span> Their conclusion is sobering but informative: the intervention “was ineffective in increasing the proportion of days alive and out of hospital for people … after hospital admissions with multimorbid heart disease.” But they also note “the efficacy of our intervention could be improved by modifying its components and applying it in a more targeted manner to reduce the impact of weather-triggered events.”<span>⁴</span></p><p>Despite its negative findings, this trial illustrates a critical inflection point in how we conceptualise health and disease in the context of an increasingly volatile climate, and the investigators are to be commended for explicitly incorporating environmental factors into their intervention. This is a significant shift for clinical work, but also crucial territory for exploration and research as our climate changes.</p><p>For decades, medical education, training, and research, and health care more broadly, have been served well by a conceptual model based on a biopsychosocial framework.<span>⁵</span> However, environmental changes — increasing temperature, extreme weather events, and the changing climate, as well as water, soil and air contamination — are factors that will increasingly influence health and wellbeing during the 21st century. The biopsychosocial model must evolve to more explicitly acknowledge the foundational relationship between human health and the envi","PeriodicalId":18214,"journal":{"name":"Medical Journal of Australia","volume":"223 2","pages":"75-76"},"PeriodicalIF":6.7,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.5694/mja2.52702","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144484889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Promoting resilience to weather-related and seasonal provocations to health in people with multimorbid heart disease: a prospective pragmatic, randomised trial","authors":"Simon Stewart,&nbsp;Sheila K Patel,&nbsp;Terase F Lancefield,&nbsp;Thalys Sampaio Rodrigues,&nbsp;Nicholas Doumtsis,&nbsp;Nasreen Moini,&nbsp;Ashleigh Harley,&nbsp;Emily-Rose Vaughan-Fowler,&nbsp;Yih-Kai Chan,&nbsp;Alexander Chen,&nbsp;David Chye,&nbsp;David FL Liew,&nbsp;Christopher McMaster,&nbsp;Jay Ramchand,&nbsp;Paul A Yates,&nbsp;Jason C Kwong,&nbsp;Christine F McDonald,&nbsp;Louise M Burrell","doi":"10.5694/mja2.52699","DOIUrl":"10.5694/mja2.52699","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Objective&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;To investigate whether a multifaceted intervention for building resilience to external provocations to health reduced the number of all-cause hospital re-admissions and deaths of people hospitalised with multimorbid heart disease, compared with standard post-discharge management.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Study design&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Single centre, prospective, open, randomised trial with blinded endpoint acquisition and adjudication (REsilience to Seasonal ILlness and Increased Emergency admissioNs CarE, RESILIENCE).&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Setting, participants&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Adults (aged 18 years or older) admitted as emergency medical patients with multimorbid heart disease to Austin Hospital, a tertiary hospital in Melbourne, 19 November 2020 – 28 July 2022, with planned discharge to home.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Intervention&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Standard post-discharge management, as well as the 12-month active management program: home visits by a nurse, specialist clinical review, and tailored recommendations for optimising clinical management and promoting resilience to external provocations; the nurse coordinated the additional care, provided individualised support, and arranged RESILIENCE physician reviews as required. The comparator group received standard post-discharge management only.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Major outcome measure&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Proportion of days alive and out of hospital during follow-up (minimum, twelve months) with respect to the maximum number possible.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Of 203 participants (mean age, 75.7 years; standard deviation [SD], 10.2 years; 104 women), 103 were randomly allocated to the intervention group, 100 to the standard management group; median follow-up time was 600 days (interquartile range, 416–681 days). A total of 470 hospital admissions and 3874 days of hospital stay during follow-up were recorded for 138 of the 203 trial participants (68%); 38 people (19%) died during follow-up. The days alive and out of hospital proportion was 86.5% (SD, 25.3 percentage points) for the intervention group and 88.3% (SD, 23.5 percentage points) for the standard management group (adjusted difference, 2.04 percentage points; 95% CI, –4.97 to 8.56 percentage points).&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 ","PeriodicalId":18214,"journal":{"name":"Medical Journal of Australia","volume":"223 2","pages":"77-84"},"PeriodicalIF":6.7,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.5694/mja2.52699","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144484891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Innovative approaches to fall prevention in community-dwelling older adults","authors":"Kim Delbaere,&nbsp;Catherine Sherrington,&nbsp;Catherine M Said,&nbsp;Vasikaran Naganathan","doi":"10.5694/mja2.52714","DOIUrl":"10.5694/mja2.52714","url":null,"abstract":"&lt;p&gt;Falls among community-dwelling older adults represent a major public health challenge in Australia, and globally. Every day, about 400 older Australians are admitted to hospital due to falls. The consequences can be life-changing, with fall-related injuries often leading to long term disability, loss of independence, social isolation and premature entry into long term care. These impacts extend beyond the individual, placing significant strain on families, carers and the broader health care system. Falls cost more than $2.8 billion annually and reduce the availability of health care resources for people of all ages.&lt;span&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;/span&gt; Despite evidence from more than 600 trials — summarised across 12 Cochrane reviews — indicating that 20–30% of falls are preventable,&lt;span&gt;&lt;sup&gt;2&lt;/sup&gt;&lt;/span&gt; fall prevention in Australia remains fragmented, underfunded and inconsistently implemented.&lt;span&gt;&lt;sup&gt;3&lt;/sup&gt;&lt;/span&gt; This perspective article reviews the evidence on traditional and innovative approaches to fall prevention in community-dwelling older adults, highlighting hybrid models that combine in-person programs with digital solutions to improve accessibility and cost-effectiveness. A summary of these traditional and innovative approaches is presented in the Box.&lt;/p&gt;&lt;p&gt;The &lt;i&gt;World guidelines for falls prevention and management for older adults&lt;/i&gt; recommend a stratified approach to fall prevention: (i) health promotion and community exercise for older adults at low risk; (ii) tailored exercise and home safety interventions for those at intermediate risk; and (iii) comprehensive multifactorial assessments and targeted medical interventions (eg, medication reviews, cataract surgery) for those at high risk.&lt;span&gt;&lt;sup&gt;4&lt;/sup&gt;&lt;/span&gt; Multifactorial interventions, combining assessment with medical and allied health management, can be highly effective by addressing multiple risk factors simultaneously.&lt;span&gt;&lt;sup&gt;5&lt;/sup&gt;&lt;/span&gt; However, these programs are resource-intensive and logistically challenging, particularly for older adults in rural or remote areas, and long waiting lists limit timely and equitable access. Population-based interventions, such as public health campaigns, have also been explored, but their effectiveness remains unclear,&lt;span&gt;&lt;sup&gt;6&lt;/sup&gt;&lt;/span&gt; unless supported by funded, local services.&lt;span&gt;&lt;sup&gt;7&lt;/sup&gt;&lt;/span&gt; Structured exercise programs remain the strongest evidence-based solution. An updated Cochrane review of 116 trials demonstrated that exercise programs reduce fall rates by about 23%, with programs involving three hours per week and a focus on balance achieving reductions up to 42%.&lt;span&gt;&lt;sup&gt;2&lt;/sup&gt;&lt;/span&gt; Home safety modifications and occupational therapy interventions can reduce falls by up to 38% among frailer, high risk groups.&lt;span&gt;&lt;sup&gt;8&lt;/sup&gt;&lt;/span&gt; Community-based fall prevention programs, such as Stepping On, the Otago Exercise Program and structured group exercise classes, have been successfully implemented bey","PeriodicalId":18214,"journal":{"name":"Medical Journal of Australia","volume":"223 4","pages":"174-176"},"PeriodicalIF":8.5,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.5694/mja2.52714","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144484890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The prevalence of and variation in indicators of the quality and safety of long term aged care in Australia, 2019: a cross-sectional population-based study","authors":"Tesfahun C Eshetie,&nbsp;Gillian E Caughey,&nbsp;Catherine Lang,&nbsp;Olivia Ryan,&nbsp;Renuka Visvanathan,&nbsp;Craig Whitehead,&nbsp;Keith Evans,&nbsp;Janet K Sluggett,&nbsp;Jyoti Khadka,&nbsp;Carolyn Dawkins,&nbsp;Helena Williams,&nbsp;Miranda Starke,&nbsp;Sara Blunt,&nbsp;Anne Liddell,&nbsp;Megan Corlis,&nbsp;Anna Sheppeard,&nbsp;Penelope Lello,&nbsp;Marilyn von Thien,&nbsp;Steven L Wesselingh,&nbsp;Maria C Inacio","doi":"10.5694/mja2.52709","DOIUrl":"10.5694/mja2.52709","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>To examine the prevalence of and variation in indicators of the quality and safety of care provided to older Australians who received subsidised long term care during 2019, by type of care (residential aged care or home care packages).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Study design</h3>\u0000 \u0000 <p>Cross-sectional population-based study; analysis of linked data from the Registry of Senior Australians (ROSA) National Historical Cohort (National Aged Care Data Clearinghouse, National Death Index, Medicare Benefits Schedule, Pharmaceutical Benefits Scheme databases; South Australian, New South Wales, Victorian, and Queensland hospital admissions and emergency department [ED] presentations databases).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Setting, participants</h3>\u0000 \u0000 <p>All people in the ROSA National Historical Cohort who received residential or home-based aged care during the 2019 calendar year.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Main outcome measures</h3>\u0000 \u0000 <p>Risk-adjusted prevalence estimates (with 95% confidence intervals, CIs) for quality and safety indicators of care (twelve for residential care, fifteen for home care packages); proportions by indicator of outlier residential facilities and home care services (outside 95% CI for mean value) as a measure of variation in quality of care.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In 2019, 244 754 people received residential aged care in 2746 facilities; 149 104 people received home care packages through 2407 home care services. For residential aged care, indicator prevalence and variation were highest for antibiotic use (prevalence: 64.5% [95% CI, 64.3–64.7%]; 13.9% of facilities beyond upper 95% CI bound), high sedative load (prevalence: 45.2%, [95% CI, 45.0–45.4%]; 12.4% beyond upper 95% CI bound), and ED presentations (prevalence: 37.8% [95% CI, 37.6–38.0%]; 19.3% beyond upper 95% CI bound). For home care services, indicator prevalence and variation were highest for waiting time longer than six months (prevalence: 81.8% [95% CI, 81.4–82.1%]; 17.5% of services beyond upper 95% CI bound), ED presentations (prevalence: 43.2% [95% CI, 43.0–43.5%]; 14.7% beyond upper 95% CI bound), chronic disease management plans (prevalence: 43.2% [95% CI, 42.9–43.5%]; 12.9% below lower 95% CI bound), and home medicines reviews (prevalence: 3.2% [95% CI, 3.1–3.3%]; 28.9% below lower 95% CI bound). The proportions of home care recipients were larger than for facility residents for hospitalisations wit","PeriodicalId":18214,"journal":{"name":"Medical Journal of Australia","volume":"223 4","pages":"189-196"},"PeriodicalIF":8.5,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.5694/mja2.52709","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144484892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Australasian Diabetes in Pregnancy Society (ADIPS) 2025 consensus recommendations for the screening, diagnosis and classification of gestational diabetes","authors":"Arianne Sweeting,&nbsp;Matthew JL Hare,&nbsp;Susan J de Jersey,&nbsp;Alexis L Shub,&nbsp;Julia Zinga,&nbsp;Cecily Foged,&nbsp;Rosemary M Hall,&nbsp;Tang Wong,&nbsp;David Simmons","doi":"10.5694/mja2.52696","DOIUrl":"10.5694/mja2.52696","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Introduction&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;In the context of a global obesity and diabetes epidemic, gestational diabetes mellitus and other forms of hyperglycaemia in pregnancy are increasingly common. Hyperglycaemia in pregnancy is associated with short and long term complications for both the woman and her baby. These 2025 consensus recommendations from the Australasian Diabetes in Pregnancy Society (ADIPS) update the guidance for the screening, diagnosis and classification of hyperglycaemia in pregnancy based on available evidence and stakeholder consultation.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Main recommendations&lt;/h3&gt;\u0000 \u0000 &lt;div&gt;\u0000 \u0000 &lt;ul&gt;\u0000 \u0000 \u0000 &lt;li&gt;Overt diabetes in pregnancy (overt DIP) should be diagnosed at any time in pregnancy if one or more of the following criteria are met: (i) fasting plasma glucose (FPG) ≥ 7.0 mmol/L; (ii) two-hour plasma glucose (2hPG) ≥ 11.1 mmol/L following a 75 g two-hour pregnancy oral glucose tolerance test (POGTT); and/or (iii) glycated haemoglobin (HbA&lt;sub&gt;1c&lt;/sub&gt;) ≥ 6.5% (≥ 48 mmol/mol).&lt;/li&gt;\u0000 \u0000 \u0000 &lt;li&gt;Irrespective of gestation, gestational diabetes mellitus should be diagnosed using one or more of the following criteria during a 75 g two-hour POGTT: (i) FPG ≥ 5.3–6.9 mmol/L; (ii) one-hour plasma glucose (1hPG) ≥ 10.6 mmol/L; (iii) 2hPG ≥ 9.0–11.0 mmol/L.&lt;/li&gt;\u0000 \u0000 \u0000 &lt;li&gt;Women with risk factors for hyperglycaemia in pregnancy should be advised to have the HbA&lt;sub&gt;1c&lt;/sub&gt; measured in the first trimester. Women with HbA&lt;sub&gt;1c&lt;/sub&gt; ≥ 6.5% (≥ 48 mmol/mol) should be diagnosed and managed as having overt DIP.&lt;/li&gt;\u0000 \u0000 \u0000 &lt;li&gt;Before 20 weeks’ gestation, and ideally between ten and 14 weeks’ gestation, if tolerated, women with a previous history of gestational diabetes mellitus or early pregnancy HbA&lt;sub&gt;1c&lt;/sub&gt; ≥ 6.0-6.4% (≥ 42–47 mmol/mol), but without diagnosed diabetes, should be advised to undergo a 75 g two-hour POGTT.&lt;/li&gt;\u0000 \u0000 \u0000 &lt;li&gt;All women (without diabetes already detected in the current pregnancy) should be advised to undergo a 75 g two-hour POGTT at 24–28 weeks’ gestation.&lt;/li&gt;\u0000 &lt;/ul&gt;\u0000 &lt;/div&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Changes in management as a result from this consensus statement&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;These updated recommendations raise the diagnostic glucose thresholds for gestational diabetes mellitus and clarify approaches to early pregnancy screening for women wi","PeriodicalId":18214,"journal":{"name":"Medical Journal of Australia","volume":"223 3","pages":"161-167"},"PeriodicalIF":8.5,"publicationDate":"2025-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.5694/mja2.52696","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144369053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Platform trials: key features, when to use them and methodological challenges","authors":"Robert Mahar,&nbsp;Steve Webb,&nbsp;Ian Marschner,&nbsp;Andrew B Forbes,&nbsp;Katherine J Lee","doi":"10.5694/mja2.52711","DOIUrl":"10.5694/mja2.52711","url":null,"abstract":"&lt;p&gt;A revolution in evidence-based medicine is currently underway that is being driven by significant innovation in clinical trial design.&lt;span&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;/span&gt; At the vanguard of this revolution is the platform trial.&lt;span&gt;&lt;sup&gt;2, 3&lt;/sup&gt;&lt;/span&gt; A working definition of a platform trial is that of a randomised trial design that compares at least one intervention to a control and that has the capacity to add and remove interventions over time according to rules defined in a master (or core) protocol. In this way, platform trials can investigate multiple research questions under a shared and ongoing trial infrastructure, leading to operational efficiencies and improved allocation of resources. A recently published review identified, as of July 2022, 127 registered platform trials with a combined 823 arms, at either an ongoing (67.7%), completed (20.5%), discontinued (7.9%), planning (3.1%), or unclear (0.8%) stage of implementation, with most being started within the last five years.&lt;span&gt;&lt;sup&gt;4&lt;/sup&gt;&lt;/span&gt; In Australia, multiple platform trials serve as examples of the possibilities of these designs, and a list of platform trials currently running in Australia can be found on the Australian Clinical Trials Alliance website (https://clinicaltrialsalliance.org.au/resource/adaptive-platform-trial-operations-special-interest-group-trial-summaries/).&lt;/p&gt;&lt;p&gt;Typically, platform trials include statistical adaptations, such as early stopping rules, that are used to make an early conclusion about treatment efficacy,&lt;span&gt;&lt;sup&gt;5&lt;/sup&gt;&lt;/span&gt; or response adaptive randomisation.&lt;span&gt;&lt;sup&gt;6&lt;/sup&gt;&lt;/span&gt; These features can reduce sample sizes, lead to preferential allocation to the best-known treatments, and expedite conclusions. However, a platform trial may not include such adaptations. For example, platform trials may randomise all treatments in parallel batches or sequentially based on pre-specified sample sizes. The “platform” in platform trials can be thought of as the infrastructure component (ie, a flexible protocol implemented under a shared infrastructure) that may have many possible statistical features (eg, multistage early stopping or factorial design).&lt;/p&gt;&lt;p&gt;To illustrate, we consider a platform trial that starts as a simple two-arm trial with pre-specified stopping rules and statistical design that allows the adding and dropping of treatments (Box). In this example, stopping rules are included for specific interventions, including an efficacy rule (ie, an intervention is better than control), and a futility rule (ie, the intervention is ineffective or is unlikely to be shown to be effective), with the set of control and interventions changing over time in response to these rules. Clearly, this trial has operational efficiencies compared with the alternative of conducting three independent two-arm trials.&lt;/p&gt;&lt;p&gt;More complicated platform trial protocols might expand on the simple design shown in the Box, leading to additional efficiencies, for e","PeriodicalId":18214,"journal":{"name":"Medical Journal of Australia","volume":"223 3","pages":"120-122"},"PeriodicalIF":8.5,"publicationDate":"2025-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.5694/mja2.52711","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144369054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"New evidence supports a greater focus on streptococcal skin infections to prevent rheumatic fever","authors":"Michael G Baker,&nbsp;Julie Bennett,&nbsp;Teuila Percival,&nbsp;Alison Leversha,&nbsp;Jason Gurney,&nbsp;Nicole J Moreland","doi":"10.5694/mja2.52708","DOIUrl":"10.5694/mja2.52708","url":null,"abstract":"&lt;p&gt;We noted with interest the recent report finding a relationship between establishment of a skin health program and a sustained reduction in impetigo for children living in remote communities in Western Australia.&lt;span&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;/span&gt; Although the results suggest it was the impact of heightened awareness which caused this reduction, rather than the intervention itself, this study is an important reminder of the multiple benefits from reducing skin infections. These benefits include the potential to protect against post-streptococcal diseases such as acute rheumatic fever (ARF) and acute post-streptococcal glomerulonephritis (APSGN).&lt;span&gt;&lt;sup&gt;2, 3&lt;/sup&gt;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;ARF can progress to rheumatic heart disease (RHD), resulting in considerable global morbidity and mortality, mainly in low and middle-income countries,&lt;span&gt;&lt;sup&gt;4&lt;/sup&gt;&lt;/span&gt; but also for Indigenous and Pacific Peoples in Australia and Aotearoa New Zealand.&lt;span&gt;&lt;sup&gt;5, 6&lt;/sup&gt;&lt;/span&gt; Group A &lt;i&gt;Streptococcus&lt;/i&gt; (GAS) infection is the established trigger for the immune dysregulation that causes ARF.&lt;span&gt;&lt;sup&gt;2&lt;/sup&gt;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;For many decades prevention of ARF has focused on the treatment of GAS pharyngitis; however, there is growing evidence that GAS skin infections can also trigger ARF.&lt;span&gt;&lt;sup&gt;7, 8&lt;/sup&gt;&lt;/span&gt; Two recent case–control studies add weight to this conclusion and support the need to explore skin infection prevention and treatment as a key intervention to prevent ARF and RHD.&lt;span&gt;&lt;sup&gt;9, 10&lt;/sup&gt;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;The first of these paediatric case–control studies investigated risk factors for ARF in Auckland, Aotearoa New Zealand.&lt;span&gt;&lt;sup&gt;9&lt;/sup&gt;&lt;/span&gt; It found that while most cases of ARF were preceded by a reported throat infection, some cases were preceded by only a skin infection. Other major modifiable factors were exposure to household crowding and barriers to accessing primary health care.&lt;span&gt;&lt;sup&gt;9&lt;/sup&gt;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;The second study investigated risk factors for GAS skin and throat infections.&lt;span&gt;&lt;sup&gt;10&lt;/sup&gt;&lt;/span&gt; These GAS infections were also associated with barriers to accessing primary health care. There were no other specific risk factors for GAS throat infection. By contrast, GAS skin infection had a very similar pattern of risk factors to ARF, including household crowding, suggesting these infections may be a pathway by which poor housing conditions drive an increased ARF risk.&lt;/p&gt;&lt;p&gt;Further evidence supporting a role for skin infections in initiating ARF comes from a large-scale record linkage study of 1.9 million throat and skin swabs in Aotearoa New Zealand.&lt;span&gt;&lt;sup&gt;11&lt;/sup&gt;&lt;/span&gt; These swabs, collected from the Auckland population over an eight-year period (2010–2017), were individually linked to cases of ARF that occurred in the same population over the subsequent year. The risk of ARF following a GAS infection was highest in the eight to 90 days after swabbing, calculated by comparing rates observed in children with GAS-pos","PeriodicalId":18214,"journal":{"name":"Medical Journal of Australia","volume":"223 3","pages":"114-116"},"PeriodicalIF":8.5,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.5694/mja2.52708","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144326120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}