Development and evaluation of a screening tool to identify people with diabetes at increased risk of medication problems relating to hypoglycaemia and medication non-adherence

Abstract Aims: To develop and evaluate a screening tool to identify people with diabetes at increased risk of medication problems relating to hypoglycaemia and medication non-adherence. Methods: A retrospective audit of attendances at a diabetes outpatient clinic at a public, teaching hospital over a 16-month period was conducted. Logistic regression was undertaken to examine risk factors associated with medication problems relating to hypoglycaemia and medication non-adherence and the most predictive set of factors comprise the Diabetes Medication Risk Screening Tool. Evaluating the tool involved assessing sensitivity and specificity, positive and negative predictive values, cut-off scores, inter-rater reliability, and content validity. Results: The Diabetes Medication Risk Screening Tool comprises seven predictive factors: age, living alone, English language, mental and behavioural problems, comorbidity index score, number of medications prescribed, and number of high-risk medications prescribed. The tool has 76.5% sensitivity, 59.5% specificity, and has a 65.1% positive predictive value, and a 71.8% negative predictive value. A score of 27 or more out of 62 was associated with high-risk of a medication problem. The inter-rater reliability of the tool was high (κ = 0.79, 95% CI 0.75 - 0.84) and the content validity index was 99.4%. Conclusion: The Diabetes Medication Risk Screening Tool has good psychometric properties and can proactively identify people with diabetes at greatest risk of medication problems relating to hypoglycaemia and medication non-adherence.

Mapping 100 years of Thornthwaite moisture index: Impact of climate change in Victoria, Australia

Geographer C. W. Thornthwaite proposed in 1948 a moisture index called Thornthwaite Moisture Index (TMI) as part of a water balance model for a new classification system for climate. The importance of TMI climatic classification has been recognised in many areas of knowledge and practice worldwide over the last 60 years. However, although past climate research was focused on developing adequate methods for climate classification, current research is more concerned with understanding the patterns of climate change. The use of TMI as an indicator for climate change is still an incipient area of research. The contributions of this paper are twofold. First, it is to fully document a methodology based on geostatistics adopted to produce a time series of TMI maps that are accurate and have high spatial resolution. The state of Victoria, in Australia, over the last century, is used as the case study. Second, by analysing these maps, the paper presents a general evaluation of the spatial patterns found in Victoria related to moisture variability across space and over time. Some potential implications of the verified moisture changes are discussed, and a number of ideas for further development are suggested. © 2014 Institute of Australian Geographers.

A parent-based intervention to promote healthy eating and active behaviours in pre-school children: evaluation of the MEND 2-4 randomized controlled trial.

BACKGROUND: There is a paucity of studies evaluating targeted obesity prevention interventions in pre-school children. OBJECTIVES: We conducted a randomized controlled trial to evaluate the efficacy of a parent-based obesity prevention intervention for pre-schoolers - MEND (Mind, Exercise, Nutrition … Do It!) 2-4 on child diet, eating habits, physical activity/sedentary behaviours, and body mass index (BMI). METHODS: Parent-child dyads attended 10 weekly 90-min workshops relating to nutrition, physical activity and behaviours, including guided active play and healthy snack time. Assessments were conducted at baseline, immediately post-intervention, and 6 and 12 months post-intervention; child intake of vegetables, fruit, beverages, processed snack foods, fussiness, satiety responsiveness, physical activity, sedentary behaviour and neophobia were assessed via parent proxy report. Parent and child height and weight were measured. RESULTS: Two hundred one parent-child dyads were randomized to intervention (n = 104) and control (n = 97). Baseline mean child age was 2.7 (standard deviation [SD] 0.6) years, and child BMI-for-age z-score (World Health Organization) was 0.66 (SD 0.88). We found significant positive group effects for vegetable (P = 0.01) and snack food (P = 0.03) intake, and satiety responsiveness (P = 0.047) immediately post-intervention. At 12 months follow-up, intervention children exhibited less neophobia (P = 0.03) than controls. CONCLUSION: Future research should focus on additional strategies to support parents to continue positive behaviour change. ACTRN12610000200088.

Evaluation of AUSDRISK as a screening tool for lifestyle modification programs: international implications for policy and cost-effectiveness

OBJECTIVE: To evaluate the current use of Australian Type 2 Diabetes Risk Assessment Tool (AUSDRISK) as a screening tool to identify individuals at high risk of developing type 2 diabetes for entry into lifestyle modification programs.

RESEARCH DESIGN AND METHODS: AUSDRISK scores were calculated from participants aged 40-74 years in the Greater Green Triangle Risk Factor Study, a cross-sectional population survey in 3 regions of Southwest Victoria, Australia, 2004-2006. Biomedical profiles of AUSDRISK risk categories were determined along with estimates of the Victorian population included at various cut-off scores. Sensitivity, specificity, positive predictive value (PPV), negative predictive value, and receiver operating characteristics were calculated for AUSDRISK in determining fasting plasma glucose (FPG) ≥6.1 mmol/L.

RESULTS: Increasing AUSDRISK scores were associated with an increase in weight, body mass index, FPG, and metabolic syndrome. Increasing the minimum cut-off score also increased the proportion of individuals who were obese and centrally obese, had impaired fasting glucose (IFG) and metabolic syndrome. An AUSDRISK score of ≥12 was estimated to include 39.5% of the Victorian population aged 40-74 (916 000), while a score of ≥20 would include only 5.2% of the same population (120 000). At AUSDRISK≥20, the PPV for detecting FPG≥6.1 mmol/L was 28.4%.

CONCLUSIONS: AUSDRISK is powered to predict those with IFG and undiagnosed type 2 diabetes, but its effectiveness as the sole determinant for entry into a lifestyle modification program is questionable given the large proportion of the population screened-in using the current minimum cut-off of ≥12. AUSDRISK should be used in conjunction with oral glucose tolerance testing, fasting glucose, or glycated hemoglobin to identify those individuals at highest risk of progression to type 2 diabetes, who should be the primary targets for lifestyle modification.

Changing guards: time to move beyond body mass index for population monitoring of excess adiposity

With the obesity epidemic, and the effects of aging populations, human phenotypes have changed over two generations, possibly more dramatically than in other species previously. As obesity is an important and growing hazard for population health, we recommend a systematic evaluation of the optimal measure(s) for population-level excess body fat. Ideal measure(s) for monitoring body composition and obesity should be simple, as accurate and sensitive as possible, and provide good categorization of related health risks. Combinations of anthropometric markers or predictive equations may facilitate better use of anthropometric data than single measures to estimate body composition for populations. Here, we provide new evidence that increasing proportions of aging populations are at high health-risk according to waist circumference, but not body mass index (BMI), so continued use of BMI as the principal population-level measure substantially underestimates the health-burden from excess adiposity.

Health improvement and prevention study (HIPS) - evaluation of an intervention to prevent vascular disease in general practice

Background

The Health Improvement and Prevention Study (HIPS) study aims to evaluate the capacity of general practice to identify patients at high risk for developing vascular disease and to reduce their risk of vascular disease and diabetes through behavioural interventions delivered in general practice and by the local primary care organization.

Methods/Design

HIPS is a stratified randomized controlled trial involving 30 general practices in NSW, Australia. Practices are randomly allocated to an 'intervention' or 'control' group. General practitioners (GPs) and practice nurses (PNs) are offered training in lifestyle counselling and motivational interviewing as well as practice visits and patient educational resources. Patients enrolled in the trial present for a health check in which the GP and PN provide brief lifestyle counselling based on the 5As model (ask, assess, advise, assist, and arrange) and refer high risk patients to a diet education and physical activity program. The program consists of two individual visits with a dietician or exercise physiologist and four group sessions, after which patients are followed up by the GP or PN. In each practice 160 eligible patients aged between 40 and 64 years are invited to participate in the study, with the expectation that 40 will be eligible and willing to participate. Evaluation data collection consists of (1) a practice questionnaire, (2) GP and PN questionnaires to assess preventive care attitudes and practices, (3) patient questionnaire to assess self-reported lifestyle behaviours and readiness to change, (4) physical assessment including weight, height, body mass index (BMI), waist circumference and blood pressure, (5) a fasting blood test for glucose and lipids, (6) a clinical record audit, and (7) qualitative data collection. All measures are collected at baseline and 12 months except the patient questionnaire which is also collected at 6 months. Study outcomes before and after the intervention is compared between intervention and control groups after adjusting for baseline differences and clustering at the level of the practice.

Discussion

This study will provide evidence of the effectiveness of a primary care intervention to reduce the risk of cardiovascular disease and diabetes in general practice patients. It will inform current policies and programs designed to prevent these conditions in Australian primary health care.

Evaluation of the Counterweight Programme for obesity management in primary care: a starting point for continuous improvement

Background Evaluation for obesity management in primary care is limited, and successful outcomes are from intensive clinical trials in hospital settings.

Aim To determine to what extent measures of success seen in intensive clinical trials can be achieved in routine primary care. Primary outcome measures were weight change and percentage of patients achieving ≤5% loss at 12 and 24 months.

Design of study Prospective evaluation of a new continuous improvement model for weight management in primary care.

Setting Primary care, UK.

Method Primary care practice nurses from 65 UK general practices delivered interventions to 1906 patients with body mass index (BMI) ≥30 kg/m2 or ≥28 kg/m2 with obesity-related comorbidities.

Results Mean baseline weight was 101.2 kg (BMI 37.1 kg/m2); 25% of patients had BMI ≥40 kg/m2 and 74% had ≥1 major obesity-related comorbidity. At final data capture 1419 patients were in the programme for ≥12 months, and 825 for ≥24 months. Mean weight change in those who attended and had data at 12 months (n = 642) was −3.0 kg (95% CI = −3.5 to −2.4 kg) and at 24 months (n = 357) was −2.3 kg (95% CI = −3.2 to −1.4 kg). Among attenders at specific time-points, 30.7% had maintained weight loss of ≥5% at 12 months, and 31.9% at 24 months. A total of 761 (54%) of all 1419 patients who had been enrolled in the programme for >12 months provided data at or beyond 12 months.

Conclusion This intervention achieves and maintains clinically valuable weight loss within routine primary care.

Contrast-enhanced ultrasound evaluation of the renal microcirculation response to terlipressin in hepato-renal syndrome: a preliminary report

BACKGROUND: Terlipressin improves renal function in some patients with type-1 hepato-renal syndrome (HRS). Renal contrast-enhanced ultrasound (CEUS), a novel imaging modality, may help to predict terlipressin responsiveness. OBJECTIVES: We used CEUS to estimate the effect of terlipressin on the renal cortical microcirculation in type-1 HRS. METHODS: We performed renal CEUS scans with destruction-replenishment sequences using Sonovue(®) (Bracco, Milano Italy) as a contrast agent at baseline and after the intravenous administration of 1 mg of terlipressin, in four patients with type-1 HRS. We analyzed video sequences offline using dedicated software. We derived a perfusion index (PI) at each time point for each patient. RESULTS: Patients 1 and 2 had severe presentation and were admitted to the intensive care unit. Both showed a marked increase in PI (+216% and + 567% of baseline) in response to terlipressin. Patients 3 and 4 had less severe presentations and had a decrease in PI (-53% and -20% of baseline) in response to terlipressin. Patients 1, 2, and 4, but not patient 3, responded to terlipressin therapy with a decrease in serum creatinine to <150 µmol/L. CONCLUSIONS: CEUS detected changes in renal cortical microcirculation in response to terlipressin and demonstrated heterogeneous microvascular responses to terlipressin. These initial proof-of-concept findings justify future investigations.

Future predictions of body mass index and overweight prevalence in Australia, 2005-2025

To predict current and future body mass index (BMI) and prevalence of overweight and obesity in Australian children and adults based on sex, age and year of birth (cohort). These predictions are needed for population health planning and evaluation. Data were drawn from 11 cross-sectional national or state population surveys conducted in Australia between 1969 and 2004. These included representative population samples of children (n= 27,635) and adults (n= 43,447) aged 5 years or older with measured height and weight data. Multiple linear regression analyses of measured log-transformed BMI data were conducted to determine the independent effects of age and year of birth (cohort) on ln(BMI) for males and females, respectively. Regression coefficients for cohort obtained from these analyses were applied to the National Nutrition Survey 1995 data set to predict mean BMI and prevalence of overweight (BMI 25-29.99 kg/m(2)) and obesity (BMI ≥ 30 kg/m(2)) in 2005, 2015 and 2025. Based on past trends, BMI is predicted to continue to increase for both males and females and across the age span. This would result in increases in the prevalence of overweight and obesity of between 0.4 and 0.8% per year, such that by 2025 around one-third of 5-19 year olds will be overweight or obese as will 83% of males and 75% of females aged 20 years and over. The increases in prevalence and mean BMI predicted in this study will have significant impacts on disease burden, healthcare costs and need for prevention and treatment programmes.

Development and preliminary evaluation of the OsteoArthritis Questionnaire (OA-Quest): a psychometric study

OBJECTIVE: This study reports the development of the OsteoArthritis Questionnaire (OA-Quest) - a new measure designed to comprehensively capture the potentially modifiable burden of osteoarthritis.

DESIGN: Item development was guided by the a priori conceptual framework of the Personal Burden of Osteoarthritis (PBO) which captures 8 dimensions of osteoarthritis burden (Physical distress, Fatigue, Physical limitations, Psychosocial distress, Physical de-conditioning, Financial hardship, Sleep disturbances, Lost productivity). One hundred and twenty three candidate items were pretested in a clinical sample of 18 osteoarthritis patients. The measurement properties of the OA-Quest were assessed with exploratory factor analysis (EFA), Rasch modelling, and confirmatory factor analysis (CFA) in a community-based sample (n = 792).

RESULTS: EFA replicated 7 of the 8 PBO domains. An exception was PBO Fatigue domain, with items merging into the Physical distress subscale in the OA-Quest. Following item analysis, a 42-item 7-subscale questionnaire was constructed, measuring Physical distress (seven items, Cronbach's α = 0.93), Physical limitations (11 items, α = 0.95), Psychosocial distress (seven items, α = 0.93), Physical de-conditioning (four items, α = 0.87), Financial hardship (four items, α = 0.93), Sleep disturbances (five items, α = 0.96), and Lost productivity (four items α = 0.90). A highly restricted 7-factor CFA model had excellent fit with the data (χ(2)(113) = 316.36, P < 0.001; chi-square/degrees of freedom = 2.8; comparative fit index [CFI] = 0.97; root mean square error of approximation [RMSEA] = 0.07), supporting construct validity of the new measure.

CONCLUSIONS: The OA-Quest is a new measure of osteoarthritis burden that is founded on a comprehensive conceptual model. It has strong evidence of construct validity and provides reliable measurement across a broad range of osteoarthritis burden.

Evaluation of process capability indices of linear profiles

Purpose: In profile monitoring, which is a growing research area in the field of statistical process control, the relationship between response and explanatory variables is monitored over time. The purpose of this paper is to focus on the process capability analysis of linear profiles. Process capability indices give a quick indication of the capability of a manufacturing process. Design/methodology/approach: In this paper, the proportion of the non-conformance criteria is employed to estimate process capability index. The paper has considered the cases where specification limits is constant or is a function of explanatory variable X. Moreover, cases where both equal and random design schemes in profile data acquisition is required (as the explanatory variable) is considered. Profiles with the assumption of deterministic design points are usually used in the calibration applications. However, there are other applications where design points within a profile would be i.i.d. random variables from a given distribution. Findings: Simulation studies using simple linear profile processes for both fixed and random explanatory variable with constant and functional specification limits are considered to assess the efficacy of the proposed method. Originality/value: There are many cases in industries such as semiconductor industries where quality characteristics are in form of profiles. There is no method in the literature to analyze process capability for theses processes, however recently quite a few methods have been presented in monitoring profiles. Proposed methods provide a framework for quality engineers and production engineers to evaluate and analyze capability of the profile processes. © Emerald Group Publishing Limited.