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Current approaches to antibiotic dose determination in critically ill patients requiring renal replacement therapy are primarily based on the assessment of highly heterogeneous data from small number of patients. The standard modelling approaches limit the scope of constructing robust confidence boundaries of the distribution of pharmacokinetics (PK) parameters, especially when the evaluation of possible association of demographic and clinical factors at different levels of the distribution of drug clearance is of interest. Commonly used compartmental models generally construct the inferences through a linear or non-linear mean regression, which is inadequate when the distribution is skewed, multi-modal or effected by atypical observation. In this study, we discuss the statistical challenges in robust estimation of the confidence boundaries of the PK parameters in the presence of highly heterogenous patient characteristics. A novel stepwise approach to evaluate the confidence boundaries of PK parameters is proposed by combining PK modelling with mixed-effects quantile regression (MEQR) methods. This method allows the assessment demographic and clinical factors’ effects at any arbitrary quantiles of the outcome of interest, without restricting assumptions on the distributions. The MEQR approach allows us to investigate if the levels of association of the covariates are different at low, medium or high concentration. This methodological assessment is deemed as a background initial approach to support the development of a class of statistical algorithm in constructing robust confidence intervals of PK parameters which can be used for developing an optimised antibiotic dosing guideline for critically ill patients requiring renal replacement therapy.

Growing research evidence shows the value of e-health in healthcare delivery. While efforts are made to implement e-health in mainstream healthcare, relatively modest attention has been paid to develop e-health knowledge and skills in health practitioners. Using a pre-post design, in this study, we aimed to examine self-reported knowledge and perception changes associated with an e-health course offered to university undergraduate students in Australia.Pre- and postsurveys were used to examine self-reported knowledge and perception changes relating to e-health among undergraduate students. All students enrolled in an e-health course (n = 165) were asked to complete an identical survey in the first and last week of the semester.The response rates were 53% (n = 87) for the presurvey and 52% (n = 85) for the postsurvey. For all items, changes in self-reported knowledge and perception were statistically significant in pre/post median scores and dichotomized negative/positive proportions.Students believed the course helped them to improve their knowledge regarding key aspects of e-health. It is important to design an e-health curriculum targeting competencies to provide necessary knowledge and skills to help students practice e-health in their professional careers.

frailty is proposed as a summative measure of health status and marker of individual vulnerability. We aimed to investigate the discriminative capacity of a frailty index (FI) derived from interRAI Comprehensive Geriatric Assessment for Acute Care (AC) in relation to multiple adverse inpatient outcomes.in this prospective cohort study, an FI was derived for 1,418 patients ≥70 years across 11 hospitals in Australia. The interRAI-AC was administered at admission and discharge by trained nurses, who also screened patients daily for geriatric syndromes.in adjusted logistic regression models an increase of 0.1 in FI was significantly associated with increased likelihood of length of stay28 days (odds ratio [OR]: 1.29 [1.10-1.52]), new discharge to residential aged care (OR: 1.31 [1.10-1.57]), in-hospital falls (OR: 1.29 [1.10-1.50]), delirium (OR: 2.34 [2.08-2.63]), pressure ulcer incidence (OR: 1.51 [1.23-1.87]) and inpatient mortality (OR: 2.01 [1.66-2.42]). For each of these adverse outcomes, the cut-point at which optimal sensitivity and specificity occurred was for an FI0.40. Specificity was higher than sensitivity with positive predictive values of 7-52% and negative predictive values of 88-98%. FI-AC was not significantly associated with readmissions to hospital.the interRAI-AC can be used to derive a single score that predicts multiple adverse outcomes in older inpatients. A score of ≤0.40 can well discriminate patients who are unlikely to die or experience a geriatric syndrome. Whether the FI-AC can result in management decisions that improve outcomes requires further study.

Aims To investigate the probability of developing type 2 diabetes mellitus (T2DM) at different body mass index levels compared to matched non-diabetic controls in a multi-ethnic population. Materials and methods This was a case-control study of 90 367 patients with incident diabetes and 362 548 age-sex-ethnicity matched controls from UK primary care. The probability of developing T2DM was estimated. Results Case and control patients were 56 years old at index and 56% were male. Patients with T2DM had significantly higher mean BMI levels by about 5 kg/m2 at diagnosis (32.2 kg/m2) compared to the matched controls (27.4 kg/m2). White Europeans (n = 79 270), African-Caribbeans (n = 4115) and South Asians (n = 7252) were 58, 48 and 46 years old with a mean BMI of 32.5, 31.1 and 29.2 kg/m2, respectively, at diagnosis. More South Asians developed T2DM at BMI below 30 kg/m2 (38%) than White Europeans (26%) and African-Caribbeans (29%) (all P

Background It is a well-described clinical phenomenon that females live longer than males, yet tend to experience greater levels of co-morbidity and disability. Females can therefore be considered both more frail (because they have poorer health status) and less frail (because they have a lower risk of mortality). This systematic review aimed to determine whether this ageing paradox is demonstrated when the Frailty Index (FI) is used to measure frailty. Methods Medline, EMBASE and CINAHL databases were searched for observational studies that measured FI and mortality in community-dwellers over 65 years of age. In five-year age groups, meta-analysis determined the sex differences in mean FI (MD = mean FI female − mean FI male ) and mortality rate. Results Of 6482 articles screened, seven articles were included. Meta-analysis of data from five studies (37,426 participants) found that MD values were positive (p 2 = 72.7%), reflecting methodological differences. Meta-analysis of mortality data (13,127 participants) showed that male mortality rates exceeded female mortality rates up until the 90 to 94-years age group. Individual studies reported higher mortality for males at each level of FI, and higher risk of death for males when controlling for age and FI. Conclusions The pattern of sex differences in the FI and mortality of older adults was consistent across populations and confirmed a ‘male-female health-survival paradox’.

Continuous blood glucose monitoring systems (CGMS) capture interstitial glucose levels at frequent intervals over time, and are used by people with diabetes and their health care professionals to assess glycaemic variability. This information helps to adjust treatment to achieve optimum glycaemic control, as well as potentially providing early warning of imminent and dangerous hypoglycaemia. Although a number of studies has reported the possibilities of predicting hypoglycaemia in insulin dependent type 1 diabetes (T1DM) patients, the prediction paradigm is still unreliable, as glucose fluctuations in people with diabetes are highly volatile and depend on many factors. Studies have proposed the use of linear auto-regressive (AR) and state space time series models to analyse the glucose profiles for predicting upcoming glucose levels. However, these modelling approaches have not adequately addressed the inherent dependencies and volatility aspects in the glucose profiles. We have investigated the utility of generalized autoregressive conditional heteroscedasticity (GARCH) models to explore glucose time-series trends and volatility, and possibility of reliable short-term forecasting of glucose levels. GARCH models were explored using CGMS profiles of young children (4 to

Background Undiagnosed comorbid diseases that independently lead to weight loss before type 2 diabetes mellitus (T2DM) diagnosis could explain the observed increased mortality risk in T2DM patients with normal weight. Objectives To evaluate the impact of weight change patterns before the diagnosis of T2DM on the association between body mass index (BMI) at diagnosis and mortality risk. Methods This was a longitudinal cohort study using 145,058 patients from UK primary care, with newly diagnosed T2DM from January 2000. Patients aged 18–70, without established disease history at diagnosis (defined as the presence of cardiovascular diseases, cancer, and renal diseases on or before diagnosis) were followed up to 2014. Longitudinal 6-monthly measures of bodyweight three years before (used to define groups of patients who lost bodyweight or not before diagnosis) and 2 years after diagnosis were obtained. The main outcome was all-cause mortality. Results At diagnosis, mean (SD) age was 52 (12) years, 56% were male, 52% were current or ex-smokers, mean BMI was 33 kg/m2, and 66% were obese. Normal weight and overweight patients experienced a small but significant reduction in body weight 6 months before diagnosis. Among all categories of obese patients, consistently increasing body weight was observed within the same time window. Among patients who did not lose body weight pre-diagnosis (n = 117,469), compared with the grade 1 obese, normal weight patients had 35% (95% CI of HR: 1.17, 1.55) significantly higher adjusted mortality risk. However, among patients experiencing weight loss before diagnosis (n = 27,589), BMI at diagnosis was not associated with mortality risk (all p > 0.05). Conclusions Weight loss before the diagnosis of T2DM was not associated with the observed increased mortality risk in normal weight patients with T2DM. This emphasises the importance of addressing risk factors post diagnosis for excess mortality in this group.

Objectives The aim of the present study was to describe trends in and age and gender distributions of presentations of older people to Australian emergency departments (EDs) from July 2006 to June 2011, and to develop ED utilisation projections to 2050. Methods A retrospective analysis of data collected in the National Non-admitted Patient Emergency Department Care Database was undertaken to assess trends in ED presentations. Three standard Australian Bureau of Statistics population growth models, with and without adjustment for current trends in ED presentation growth and effects of climate change, were examined with projections of ED presentations across three age groups (0–64, 65–84 and ≥85 years) to 2050. Results From 2006–07 to 2010–11, ED presentations increased by 12.63%, whereas the Australian population over this time increased by only 7.26%. Rates of presentation per head of population were greatest among those aged ≥85 years. Projections of ED presentations to 2050 revealed that overall ED presentations are forecast to increase markedly, with the rate of increase being most marked for older people. Conclusion Growth in Australian ED presentations from 2006–07 to 2010–11 was greater than that expected from population growth alone. The predicted changes in demand for ED care will only be able to be optimally managed if Australian health policy, ED funding instruments and ED models of care are adjusted to take into account the specific care and resource needs of older people. What is known about the topic? Rapid population aging is anticipated over coming decades. International studies and specific local-level Australian studies have demonstrated significant growth in ED presentations. There have been no prior national-level Australian studies of ED presentation trends by age group. What does this paper add? The present study examined national ED presentation trends from July 2006 to June 2011, with specific emphasis on trends in presentation by age group. ED presentation growth was found to exceed population growth in all age groups. The rate of ED presentations per head of population was highest among those aged ≥85 years. ED utilisation projections to 2050, using standard Australian Bureau of Statistics population modelling, with and without adjustment for current ED growth, were developed. The projections demonstrated linear growth in ED presentation for those aged 0–84 years, with growth in ED presentations of the ≥85 year age group demonstrating marked acceleration after 2030. What are the implications for practitioners? Growth in ED presentations exceeding population growth suggests that current models of acute health care delivery require review to ensure that optimal care is delivered in the most fiscally efficient manner. Trends in presentation of older people emphasise the imperative for ED workforce planning and education in care of this complex patient cohort, and the requirement to review funding models to incentivise investment in ED avoidance and substitutive care models targeting older people.

Refractive imaging of wave fields in an established experimental technique. We consider the associated reconstruction problem and investigate some statistically motivated refinements, including (a) bias correction of local slope estimates, (b) regularization of directional slopes, (c) spatially weighted reconstruction using the estimated variability of local slope estimates, and (d) more accurate estimates of reference light profiles from time sequence data. These refinements are based on a nonparametric observational model for refractive imaging data. Simulation studies show that the refinements can result in substantial improvements in the mean squared error of reconstruction. A computationally efficient algorithm that exploits sparsity is used to evaluate the regularized estimator. Our approach is illustrated by an application to real image data.

Background: A better understanding of the health status of older inpatients could underpin the delivery of more individualised, appropriate health care. Methods: 1418 patients aged ≥70 years admitted to 11 hospitals in Australia were evaluated at admission using the interRAI assessment system for Acute Care. This instrument surveys a large number of domains, including cognition, communication, mood and behaviour, activities of daily living, continence, nutrition, skin condition, falls, and medical diagnosis. Results: Variables across multiple domains were selected as health deficits. Dichotomous data were coded as symptom absent (0 deficit) or present (1 deficit). Ordinal scales were recoded as 0, 0.5 or 1 deficit based on face validity and the distribution of data. Individual deficit scores were summed and divided by the total number considered (56) to yield a Frailty index (FI-AC) with theoretical range 0–1. The index was normally distributed, with a mean score of 0.32 (±0.14), interquartile range 0.22 to 0.41. The 99% limit to deficit accumulation was 0.69, below the theoretical maximum of 1.0. In logistic regression analysis including age, gender and FI-AC as covariates, each 0.1 increase in the FI-AC increased the likelihood of inpatient mortality twofold (OR: 2.05 [95% CI 1.70 – 2.48]). Conclusions: Quantification of frailty status at hospital admission can be incorporated into an existing assessment system, which serves other clinical and administrative purposes. This could optimise clinical utility and minimise costs. The variables used to derive the FI-AC are common to all interRAI instruments, and could be used to precisely measure frailty across the spectrum of health care.