To determine the prevalence of frailty in Emergency Departments (EDs); examine the ability of frailty to predict poor outcomes post-discharge; and identify the most appropriate instrument for routine ED use. In this prospective study we simultaneously assessed adults 65+yrs admitted and/or spent one night in the ED using Fried, the Clinical Frailty Scale (CFS), and SUHB (Stable, Unstable, Help to walk, Bedbound) scales in four Australian EDs for rapid recognition of frailty between June 2015 and March 2016. 899 adults with complete follow-up data (mean (SD) age 80.0 (8.3) years; female 51.4%) were screened for frailty. Although different scales yielded vastly different frailty prevalence (SUHB 9.7%, Fried 30.4%, CFS 43.7%), predictive discrimination of poor discharge outcomes (death, poor self-reported health/quality of life, need for community services post-discharge, or reattendance to ED after the index hospitalization) for all identical final models was equivalent across all scales (AUROC 0.735 for Fried, 0.730 for CFS and 0.720 for SUHB). This study confirms that screening for frailty in older ED patients can inform prognosis and target discharge planning including community services required. The CFS was as accurate as the Fried and SUHB in predicting poor outcomes, but more practical for use in busy clinical environments with lower level of disruption. Given the limitations of objectively measuring frailty parameters, self-report and clinical judgment can reliably substitute the assessment in EDs. We propose that in a busy ED environment, frailty scores could be used as a red flag for poor follow-up outcome.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Mobile health (mHealth) apps have potential to increase smoking cessation but little research has been conducted with Aboriginal communities in Australia. Objective: We conducted a pilot study to assess the feasibility, acceptability and explore the effectiveness of a novel mHealth application to assist Aboriginal people to quit smoking. Methods: Design: A single-blinded, pilot, randomised, controlled trial (RCT) and a process evaluation comprising usage analytics data and in-depth interviews Setting and participants: Aboriginal current smokers (aged >16 years willing to make a quit attempt in the next month) recruited from Aboriginal Community Controlled Health Services and a government telephone coaching service in New South Wales Intervention: A multifaceted Android or iOS app comprising a personalised profile and quit plan, text and in app motivational messages, and a challenge feature allowing users to ‘compete’ with others vs usual cessation support services Outcomes: Self-reported continuous smoking abstinence, verified by carbon monoxide breath testing at 6 months. Secondary outcomes included point prevalence of abstinence and use of smoking cessation therapies and services. Results: A total of 49 participants were recruited for the pilot RCT. Competing service delivery priorities, the lack of resources for research and lack of support for randomisation to a control group were the major recruitment barriers. At baseline, 47% of participants had tried to quit in recent weeks with very few having accessed support services, medication or nicotine replacement therapy. At 6 months follow-up only one participant (intervention arm) was abstinent. There were however, non-significant increases in smoking cessation medication/ nicotine replacement use in the intervention arm (18% intervention vs 9% control) and use of cessation support services (41% intervention vs 28% control). The process evaluation highlighted low to moderate app usage (3-10 new users/ month and 4–8 returning users/month), an average of 2.9 sessions/user/month and 6.3 minutes per session. Key themes from interviews with intervention participants (n=15) included: (1) the powerful influence of prevailing social norms around acceptability of smoking; (2) high usage of mobile devices for phone, text and social media but very low use of other smartphone apps; (3) the role of family and social group support in supporting quit attempts; and (4) low awareness and utilisation of smoking cessation support services. Despite broad acceptability of the app, participants also recommended technical improvements to improve functionality, greater customisation of text messages, integration with existing social media platforms and gamification features. Conclusions: Smoking cessation apps need to be integrated with commonly used functions of mobile phones and draw on social networks to support their use. Although they have potential to increase utilisation of cessation support services and treatments, more research is needed to identify optimal implementation models. Robust evaluation is critical to determine their impact, however, an RCT design is unlikely to be feasible in this setting and alternative approaches are recommended. Clinical Trial: ACTRN12616001550493

Outdoor recreational spaces have the potential to increase physical activity. This study used a quasi-experimental evaluation design to determine how a playground renovation impacts usage and physical activity of children and whether the visitations correlate with children’s physical activity levels and parental impressions of the playground. Observational data and intercept interviews were collected simultaneously on park use and park-based activity among playground visitors at pre- and postrenovation at an intervention and a comparison park during three 2-hour periods each day over two weeks. No detectable difference in use between parks was observed at followup. In the intervention park, attendance increased among boys, but decreased among girls although this (nonsignificant) decline was less marked than in the comparison park. Following renovation, there was no detectable difference between parks in the number of children engaged in MVPA (interaction between park and time:P=0.73). At the intervention park, there was a significant decline in girls engaging in MVPA at followup (P=0.04). Usage was correlated with parental/carer perceptions of playground features but not with physical activity levels. Renovations have limited the potential to increase physical activity until factors influencing usage and physical activity behavior are better understood.

Recent data on salt intake levels in India show consumption is around 11 g per day, higher than the World Health Organization’s (WHO) recommended intake of 5 g per day. However, high-quality data on sources of salt in diets to inform a salt reduction strategy are mostly absent. A cross-sectional survey of 1283 participants was undertaken in rural, urban, and slum areas in North (n = 526) and South (n = 757) India using an age-, area-, and sex-stratified sampling strategy. Data from two 24-h dietary recall surveys were transcribed into a purpose-built nutrient database. Weighted salt intake was estimated from the average of the two recall surveys, and major contributors to salt intake were identified. Added salt contributed the most to total salt intake, with proportions of 87.7% in South India and 83.5% in North India (p < 0.001). The main food sources of salt in the south were from meat, poultry, and eggs (6.3%), followed by dairy and dairy products (2.6%), and fish and seafood (1.6%). In the north, the main sources were dairy and dairy products (6.4%), followed by bread and bakery products (3.3%), and fruits and vegetables (2.1%). Salt intake in India is high, and this research confirms it comes mainly from added salt. Urgent action is needed to implement a program to achieve the WHO salt reduction target of a 30% reduction by 2025. The data here suggest the focus needs to be on changing consumer behavior combined with low sodium, salt substitution.

Data on hyperkalemia frequency among chronic kidney disease (CKD) patients receiving renin-angiotensin aldosterone system inhibitors (RAASis) and its impact on subsequent RAASi treatment are limited. This population-based cohort study sought to assess the incidence of clinically significant hyperkalemia among adult CKD patients who were prescribed a RAASi and the proportion of patients with RAASi medication change after experiencing incident hyperkalemia. We conducted a retrospective, population-based cohort study (1 January 2013–30 June 2017) using Australian national general practice data from the NPS MedicineWise’s MedicineInsight program. The study included adults aged ≥18 years who received ≥1 RAASi prescription during the study period and had CKD (estimated glomerular filtration rate [eGFR] 6 mmol/L or a record of hyperkalemia diagnosis) and among patients who experienced incident hyperkalemia, the proportion who had RAASi medication changes (cessation or dose reduction during the 210-day period after the incident hyperkalemia event). Among 20,184 CKD patients with a median follow-up of 3.9 years, 1,992 (9.9%) patients experienced an episode of hyperkalemia. The overall incidence rate was 3.1 (95% CI: 2.9–3.2) per 100 person-years. Rates progressively increased with worsening eGFR (e.g. 3.5-fold increase in patients with eGFR <15 vs. 45–59 ml/min/1.73m²). Among patients who experienced incident hyperkalemia, 46.6% had changes made to their RAASi treatment regimen following the first occurrence of hyperkalemia (discontinuation: 36.6% and dose reduction: 10.0%). In this analysis of adult RAASi users with CKD, hyperkalemia and subsequent RAASi treatment changes were common. Further assessment of strategies for hyperkalemia management and optimal RAASi use among people with CKD are warranted.

Disposition decisions are critical to the functioning of Emergency Departments. The objectives of the present study were to derive and internally validate a prediction model for inpatient admission from the Emergency Department to assist with triage, patient flow and clinical decision making. This was a retrospective analysis of State-wide Emergency Department data in New South Wales, Australia. Adult patients (age ≥ 16 years) were included if they presented to a Level five or six (tertiary level) Emergency Department in New South Wales, Australia between 2013 and 2014. The outcome of interest was in-patient admission from the Emergency Department. This included all admissions to short stay and medical assessment units and being transferred out to another hospital. Analyses were performed using logistic regression. Discrimination was assessed using area under curve and derived risk scores were plotted to assess calibration. 1,721,294 presentations from twenty three Level five or six hospitals were analysed. Of these 49.38% were male and the mean (sd) age was 49.85 years (22.13). Level 6 hospitals accounted for 47.70% of cases and 40.74% of cases were classified as an in-patient admission based on their mode of separation. The final multivariable model including age, arrival by ambulance, triage category, previous admission and presenting problem had an AUC of 0.82 (95% CI 0.81, 0.82). By deriving and internally validating a risk score model to predict the need for in-patient admission based on basic demographic and triage characteristics, patient flow in ED, clinical decision making and overall quality of care may be improved. Further studies are now required to establish clinical effectiveness of this risk score model.