Natalie Nanayakkara

Utilisation of emergency medical services for severe hypoglycaemia: An unrecognised health care burden

AIMS Diabetes is associated with several acute, life-threatening complications yet there are limited data on the utilisation of prehospital services for their management. This study aimed to examine the utilisation of emergency medical services (EMS) for prehospital hypoglycaemia, including patient characteristics and factors related to hospital transportation. METHODS An observational study of patients requiring EMS for hypoglycaemia across Victoria, Australia over three years was conducted. Pre-specified data including patient demographics, comorbidities, examination findings and transport outcomes were obtained. Logistic regression was used to assess factors associated with transportation. RESULTS During the study period, 12,411 hypoglycaemia events were attended by paramedics for people with diabetes. The majority were individuals with type 1 diabetes (58.8%), followed by type 2 diabetes (35.2%) and unspecified diabetes type (5.9%). Thirty-eight percent of patients were transported to hospital by EMS following hypoglycaemia. Factors associated with transport by EMS included extremes of age (<15 and >75years), female gender, type 2 diabetes, event at a nursing home or hospital/community clinic, presence of comorbidities and time of day. CONCLUSIONS Examination of the utilisation of EMS for hypoglycaemia has identified a previously unquantified need for emergency care for people with diabetes as well as factors related to hospital transportation.

Obesity, polycystic ovary syndrome and breastfeeding: an observational study

Polycystic ovary syndrome (PCOS) affects 9–21% of reproductive‐age women. The relations between PCOS, body mass index (BMI) and breastfeeding are unclear. Our aim was to examine breastfeeding in women with and without PCOS and the relation with BMI.

Utilisation of prehospital emergency medical services for hyperglycaemia: A community-based observational study

Aims This study examines prehospital Emergency Medical Service (EMS) utilisation and patterns of demand for hyperglycaemia management, including characteristics of individuals and factors related to hospital transport. Materials and methods A state-wide, community-based observational study of all patients requiring prehospital EMS for hyperglycaemia during a 7 year study period (Jan 2009–Dec 2015) using electronic data from the Ambulance Victoria data warehouse was conducted. Pre-specified variables related to patient demographics, comorbidities, examination findings, paramedic treatment and transport outcomes were obtained. Logistic regression was used to assess factors associated with transport to hospital. Results There were 11,417 cases of hyperglycaemia attended by paramedics during the study period, accounting for 0.3–0.4% of the total annual EMS caseload, and equating to 0.54 attendances per 100 people with diabetes in the state of Victoria, Australia, per year. There was a significant increase in annual utilisation, with a rate ratio of 1.62 between 2009 (2.42 cases per 10,000 population) and 2015 (3.91 cases per 10,000 population). Fifty-one percent of cases had type 2 diabetes, 37% had type 1 diabetes, 4% had diabetes with the type unspecified and 8% had no recorded history of diabetes. Ninety percent of cases were transported to hospital. Factors associated with increased odds of transport to hospital included no known history of diabetes, regional/rural locations, case time between 0600 and <1800 hours, increasing number of comorbidities and increasingly unstable vital sign observations. Conclusion There is substantial utilisation of prehospital EMS for hyperglycaemia. With increased population prevalence of diabetes predicted, further research on opportunities for prevention, as well as optimal management in the prehospital environment is warranted.

Time series modelling to forecast prehospital EMS demand for diabetic emergencies

BackgroundAcute diabetic emergencies are often managed by prehospital Emergency Medical Services (EMS). The projected growth in prevalence of diabetes is likely to result in rising demand for prehospital EMS that are already under pressure. The aims of this study were to model the temporal trends and provide forecasts of prehospital attendances for diabetic emergencies.MethodsA time series analysis on monthly cases of hypoglycemia and hyperglycemia was conducted using data from the Ambulance Victoria (AV) electronic database between 2009 and 2015. Using the seasonal autoregressive integrated moving average (SARIMA) modelling process, different models were evaluated. The most parsimonious model with the highest accuracy was selected.ResultsForty-one thousand four hundred fifty-four prehospital diabetic emergencies were attended over a seven-year period with an increase in the annual median monthly caseload between 2009 (484.5) and 2015 (549.5). Hypoglycemia (70%) and people with type 1 diabetes (48%) accounted for most attendances. The SARIMA (0,1,0,12) model provided the best fit, with a MAPE of 4.2% and predicts a monthly caseload of approximately 740 by the end of 2017.ConclusionsPrehospital EMS demand for diabetic emergencies is increasing. SARIMA time series models are a valuable tool to allow forecasting of future caseload with high accuracy and predict increasing cases of prehospital diabetic emergencies into the future. The model generated by this study may be used by service providers to allow appropriate planning and resource allocation of EMS for diabetic emergencies.

Depression and diabetes distress in adults with type 2 diabetes: results from the Australian National Diabetes Audit (ANDA) 2016

This study explores the prevalence of, and factors associated with, likely depression and diabetes distress in adults with type 2 diabetes in a large, national sample. Australian National Diabetes Audit data were analysed from adults with type 2 diabetes attending 50 diabetes centres. The Brief Case find for Depression and Diabetes Distress Score 17 were administered to screen for likely depression and diabetes-related distress, respectively. A total of 2,552 adults with type 2 diabetes participated: (mean ± SD) age was 63 ± 13 years, diabetes duration was 12 ± 10 years, and HbA1c was 8 ± 2%. Twenty-nine percent of patients had likely depression, 7% had high diabetes distress, and 5% had both. Difficulty following dietary recommendations, smoking, forgetting medications, and diabetes distress were all associated with greater odds of depression whereas higher own health rating was associated with lower odds (all p < 0.02). Female gender, increasing HbA1c, insulin use, difficulty following dietary recommendations and depression were all associated with greater odds of diabetes distress & older age, higher own health rating and monitoring blood glucose levels as recommended were associated with lower odds (all p < 0.04). Depression was associated with sub-optimal self-care, while diabetes distress was associated with higher HbA1c and sub-optimal self-care.

Risk-adjustment of diabetes health outcomes improves the accuracy of performance benchmarking

Benchmarking clinical performance by comparing diabetes health outcomes across healthcare providers drives quality improvement. Non-care related patient risk factors are likely to confound clinical performance, but few studies have tested this. This cross-sectional study is the first Australian investigation to analyse the effect of risk-adjustment for non-care related patient factors on benchmarking. Data from 4,670 patients with type 2 (n = 3,496) or type 1 (n = 1,174) were analysed across 49 diabetes centres. Diabetes health outcomes (HbA1c levels, LDL-cholesterol levels, systolic blood pressure and rates of severe hypoglycaemia) were risk-adjusted for non-care related patient factors using multivariate stepwise linear and logistic regression models. Unadjusted and risk-adjusted funnel plots were constructed for each outcome to identify low-performing and high-performing outliers. Unadjusted funnel plots identified 27 low-performing outliers and 15 high-performing outliers across all diabetes health outcomes. After risk-adjustment, 22 (81%) low-performing outliers and 13 (87%) high-performing outliers became inliers. Additionally, one inlier became a low-performing outlier. Risk-adjustment of diabetes health outcomes significantly reduced false positives and false negatives for outlier performance, hence providing more accurate information to guide quality improvement activity.

Younger people with Type 2 diabetes have poorer self-care practices compared with older people: results from the Australian National Diabetes Audit.

This cross‐sectional study compares the self‐care practices of younger and older people with Type 2 diabetes.

Age-related differences in glycaemic control, cardiovascular disease risk factors and treatment in patients with type 2 diabetes: a cross-sectional study from the Australian National Diabetes Audit

Objective To compare the glycaemic control and cardiovascular risk factor profiles of younger and older patients with type 2 diabetes. Cross-sectional analysis of data from the 2015 Australian National Diabetes Audit was undertaken. Methods Data were obtained from adults with type 2 diabetes presenting to Australian secondary/tertiary diabetes centres. Logistic regression examined associations with glycated haemoglobin A1c (HbA1c) >7% (53 mmol/mol) and cardiovascular risk factors. Results Data from 3492 patients were analysed. Mean (±SD) age was 62.9±12.5 years, mean diabetes duration 13.5±9.4 years and mean HbA1c 8.2%±1.8%. Mean HbA1c was 8.6%±2.1% and 8.0%±1.6% for the younger (<60 years) and older subgroups (≥60 years), respectively (p<0.001). The adjusted OR (aOR) of HbA1c above >7.0% was 1.5 times higher (95% CI 1.22 to 1.84) for younger patients compared with older patients after adjustment for gender, smoking, diabetes duration, renal function and body mass index. Younger patients were also more likely to have dyslipidaemia (aOR 2.02, 95% CI 1.53 to 2.68; p<0.001), be obese (aOR 1.25, 95% CI 1.05 to 1.49; p<0.001) and be current smokers (aOR 2.13 95% CI 1.64 to 2.77; p<0.001) than older patients. Conclusions Younger age was associated with poorer glycaemic control and adverse cardiovascular risk factor profiles. It is imperative to optimise and monitor treatment in order to improve long-term outcomes.

Age, age at diagnosis and diabetes duration are all associated with vascular complications in type 2 diabetes

BACKGROUND Type 2 diabetes (T2DM) is increasingly diagnosed in younger patients. The trajectory of complications in patients diagnosed at a younger or older age is not well understood. We examine the associations between age, age at diagnosis and diabetes duration and vascular complications in patients with T2DM. METHODS A cross-sectional study of pre-specified demographic and clinical data, from 3419 adults with T2DM participating in the Australian National Diabetes Audit (2015). Factors associated with diabetes complications were analysed using logistic regression. RESULTS Mean (±SD) current age was 62.9±12.5years, age at diagnosis was 49.4±12.3years and mean diabetes duration was 13.5±9.4years. Macrovascular complications were more prevalent in patients who were older at diabetes diagnosis whereas microvascular complications were more prevalent in patients who were younger at diabetes diagnosis. Age, age at diagnosis and diabetes duration were all independently associated with increased risk of macrovascular complications after adjustment for sex, smoking, BMI and microvascular complications (all p<0.001). In contrast, only diabetes duration was independently associated with microvascular complications after adjustment for sex, smoking, BMI and macrovascular complications (p<0.001). CONCLUSIONS Age, age at diagnosis, and diabetes duration were all independently associated with macrovascular complications whereas only diabetes duration was independently associated with microvascular complications.