Data-analytically derived flexible HbA1c thresholds for type 2 diabetes mellitus diagnostic

Glycated haemoglobin (HbA1c) is now more commonly used as an alternative test to the fasting plasma glucose and oral glucose tolerance tests for the identification of Type 2 Diabetes Mellitus (T2DM) because it is easily obtained using the point-of-care technology and represents long-term blood sugar levels. According to WHO guidelines, HbA1c values of 6.5% or above are required for a diagnosis of T2DM. However outcomes of a large number of trials with HbA1c have been inconsistent across the clinical spectrum and further research is required to determine the efficacy of HbA1c testing in identification of T2DM. Medical records from a diabetes screening program in Australia illustrate that many patients could be classified as diabetics if other clinical indicators are included, even though the HbA1c result does not exceed 6.5%. This suggests that a cutoff for the general population of 6.5% may be too simple and miss individuals at risk or with already overt, undiagnosed diabetes. In this study, data mining algorithms have been applied to identify markers that can be used with HbA1c. The results indicate that T2DM is best classified by HbA1c at 6.2% - a cutoff level lower than the currently recommended one, which can be even less, having assumed the threshold flexibility, if additionally to HbA1c being high the rule is conditioned on oxidative stress or inflammation being present, atherogenicity or adiposity being high, or hypertension being diagnosed, etc

Results from 15 years of quality surveillance for a National Indigenous Point-of-Care Testing Program for diabetes

© 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ This author accepted manuscript is made available following 12 month embargo from date of publication (July 2017) in accordance with the publisher’s archiving policyIntroduction Diabetes is a major health problem for Australia's Aboriginal and Torres Strait Islander peoples. Point-of-care testing for haemoglobin A1c (HbA1c) has been the cornerstone of a long-standing program (QAAMS) to manage glycaemic control in Indigenous people with diabetes and recently, to diagnose diabetes. Methods The QAAMS quality management framework includes monthly testing of quality control (QC) and external quality assurance (EQA) samples. Key performance indicators of quality include imprecision (coefficient of variation [CV%]) and percentage acceptable results. This paper reports on the past 15 years of quality testing in QAAMS and examines the performance of HbA1c POC testing at the 6.5% cut-off recommended for diagnosis. Results The total number of HbA1c EQA results submitted from 2002 to 2016 was 29,093. The median imprecision for EQA testing by QAAMS device operators averaged 2.81% (SD 0.50; range 2.2 to 3.9%) from 2002 to 2016 and 2.44% (SD 0.22; range 2.2 to 2.9%) from 2009 to 2016. No significant difference was observed between the median imprecision achieved in QAAMS and by Australasian laboratories from 2002 to 2016 (p = 0.05; two-tailed paired t-test) and from 2009 to 2016 (p = 0.17; two-tailed paired t-test). For QC testing from 2009 to 2016, imprecision averaged 2.5% and 3.0% for the two levels of QC tested. Percentage acceptable results averaged 90% for QA testing from 2002 to 2016 and 96% for QC testing from 2009 to 2016. The DCA Vantage was able to measure a patient and an EQA sample with an HbA1c value close to 6.5% both accurately and precisely. Conclusion HbA1c POC testing in QAAMS has remained analytically sound, matched the quality achieved by Australasian laboratories and met profession-derived analytical goals for 15 years

Identifying Clinical Phenotypes of Type 1 Diabetes for the Co-Optimization of Weight and Glycemic Control

Obesity is an increasing concern in the clinical care of youth with type 1 diabetes (T1D). Standard approaches to co-optimize weight and glycemic control are challenged by profound population-level heterogeneity. Therefore, the goal of the dissertation was to apply novel analytic methods to understand heterogeneity in the co-occurrence of weight, glycemia, and underlying patterns of minute-to-minute dysglycemia among youth with T1D. Data from the SEARCH for Diabetes in Youth study were used to characterize subgroups of youth with T1D showing similar weight status and level of glycemic control as distinct ‘weight-glycemia phenotypes’ of T1D. Cross-sectional weight-glycemia phenotypes were identified at the 5+ year follow-up visit (n=1,817) using hierarchical clustering on five measures summarizing the joint distribution of body mass index z-score (BMIz) and hemoglobin A1c (HbA1c), generated by reinforcement learning tree predictions. Longitudinal weight-glycemia phenotypes spanning eight years were identified with longitudinal k-means clustering using baseline and follow-up BMIz and HbA1c measures (n=570). Logistic regression modeling tested for differences in the emergence of early/subclinical diabetes complications across subgroups. Seven-day blinded continuous glucose monitoring (CGM) data from baseline of the Flexible Lifestyles Empowering Change randomized trial (n=234, 13-16 years, HbA1c 8-13%) was clustered with a neural network approach to identify subgroups of adolescents with T1D and elevated HbA1c sharing patterns in their CGM data as ‘dysglycemia phenotypes.’ We identified six cross-sectional weight-glycemia phenotypes, including four normal-weight, one overweight, and one subgroup with obesity. Subgroups showed striking differences in other sociodemographic and clinical characteristics suggesting underlying health inequity. We identified four longitudinal weight-glycemia phenotypes associated with different patterns of early/subclinical complications, providing evidence that exposure to co-occurring obesity and worsening glycemic control may accelerate the development and increase the burden of co-morbid complications. We identified three dysglycemia phenotypes with significantly different patterns in hypoglycemia, hyperglycemia, glycemic variability, and 18-month changes in HbA1c. Patient-level drivers of the dysglycemia phenotypes appear to be different from risk factors for poor glycemic control as measured by HbA1c. These studies provide pragmatic, clinically-relevant examples of how novel statistics may be applied to data from T1D to derive patient subgroups for tailored interventions to improve weight alongside glycemic control.Doctor of Philosoph

Visual analytics methods for retinal layers in optical coherence tomography data

Optical coherence tomography is an important imaging technology for the early detection of ocular diseases. Yet, identifying substructural defects in the 3D retinal images is challenging. We therefore present novel visual analytics methods for the exploration of small and localized retinal alterations. Our methods reduce the data complexity and ensure the visibility of relevant information. The results of two cross-sectional studies show that our methods improve the detection of retinal defects, contributing to a deeper understanding of the retinal condition at an early stage of disease.Die optische Kohärenztomographie ist ein wichtiges Bildgebungsverfahren zur Früherkennung von Augenerkrankungen. Die Identifizierung von substrukturellen Defekten in den 3D-Netzhautbildern ist jedoch eine Herausforderung. Wir stellen daher neue Visual-Analytics-Methoden zur Exploration von kleinen und lokalen Netzhautveränderungen vor. Unsere Methoden reduzieren die Datenkomplexität und gewährleisten die Sichtbarkeit relevanter Informationen. Die Ergebnisse zweier Querschnittsstudien zeigen, dass unsere Methoden die Erkennung von Netzhautdefekten in frühen Krankheitsstadien verbessern

Type 2 diabetes mellitus and dyslipidaemia: effects of genetic variation in African populations

Background: Low-density lipoproteins (LDL) have been associated with damage to the cardiovascular system in patients with type 2 diabetes mellitus (T2DM). These patients are two (2X) to four (4X) times more likely to develop cardiovascular diseases (CVD) compared to non-diabetic patients due to dysfunctional lipoprotein metabolism. Normal lipid metabolism involves interconversion and transfer of molecules regulated by several enzymes such as Apolipoprotein E (ApoE) and proprotein convertase subtilisin/kexin type 9 (PCSK9). ApoE and PCSK9 are involved in clearance of lipoproteins and therefore, influence lipid profiles. Association between ApoE and T2DM in cardiovascular diseases have been widely reported. PCSK9 on the other hand is emerging as an important player in lipid metabolism but its effects in diabetes are not known. Studies on both ApoE and PCSK9 in African populations are in its infancy. Each year, CVD kills more people than any other cause of death. Many CVDs can be traced back to pathological process of atherosclerosis, in which fatty material collects along walls of arteries, limiting flexibility and obstructing blood flow. T2DM alone has been classified as a major factor for development of CVD and one of its complications is the development of dyslipidaemia. Unlike PCSK9, genetic polymorphisms in ApoE have been well characterised as important dyslipidaemia genetic markers associated with coronary artery disease. The association between ApoE and PCSK9 gene polymorphisms with dyslipidaemia in T2DM was evaluated. Diabetic dyslipidaemia presents as a triad of high triglycerides, high LDL and low high-density lipoprotein (HDL). Aims and Objectives: This study aimed to evaluate the role of genetic variation in genes coding for ApoE2 and PCSK9 on dyslipidaemia in South African diabetic patients. Main objectives’ included recruitment of participants, genetic characterisation of ApoE and PCSK9 and determination of the lipid profiles for the recruited participants. Methods: Two hundred and forty-four (n=244) participants were recruited from the Baragwaneth diabetic clinic, using a retrospective approach. The participants comprised of two groups, (i) dyslipidaemic, and (ii) non-dyslipidaemic (controls). The dyslipidaemic group was further divided into three groups; i) those with high cholesterol only, ii) those with high triglycerides only and iii) those with both high cholesterol and triglycerides which is referred to as the mixed group. Clinical and demographic parameters were retrieved from hospital records with the consent of the participants. Ethical clearance was obtained from the University of Cape Town and University of Witwatersrand. Genetic characterisation of ApoE was carried out using polymerase chain reaction (PCR) coupled to restriction fragment length polymorphism (RFLP) and confirmed through sequencing while characterisation for PCSK9 was carried out through Sanger sequencing. Results: Of the 244 participants, 165 were dyslipidaemic while 79 were not dyslipidaemic. The 165 dyslipidaemic participants were further divided into 33.3% (n=55) those with high cholesterol, 29.1% (n=48) those with high triglycerides and 37.6% and (n= 62) those with high cholesterol and triglycerides (mixed). The cohort comprised of 128 (52%) females, median (IQR) age 56.0 (48.0 – 64.0) years and 116 (48%) males with median (IQR) age of 56.5 (48.0 – 63.0) years. Most of the characteristics between the dyslipidaemic and nondyslipidaemic participants were significantly different as expected in a purposive sampling technique. ApoE3/4 genotype had the highest frequency distribution (41%) while ApoE2/3 genotype had the lowest frequency (7%). An uncharacterised ApoE referred to in the study as ApoE X with a frequency distribution of 6%, was reported for the first time. The selected measured parameters evaluated against a set of variables showed a significant association between HbA1c and age (p=<0.008) is reported. TC (p=0.00092), LDL (p=0.0184) and TG (p=0.0175) were strongly associated with poor glycaemic. Both LDL (p=0.0174 and HDL (p=0.0072) were associated with age. Homozygous ApoE2/2 and heterozygous ApoE2/3 genotypes correlated with poor glycaemic control with a median HbA1c of 10.95% (IQR 5.88-14.98%) and 10.20% (IQR 6.20-15.80%), respectively; while homozygous ApoE4/4 carriers displayed good glycaemic control with a median HbA1c of 6.60% (IQR 5.70 – 2.30%). Carriers of homozygous ApoE3/3 genotype had the highest median TC of 6.06mmol/L (IQR 5.48 -– 6.71mmol/L) while homozygous ApoE4/4 carriers had the highest median triglycerides of (2.94 (IQR 1.75 – 5.13 mmol/L). Carriers of homozygous PCSK9 rs505151 A/A (E670G) genotype had the highest frequency distribution in both groups of participants with dyslipidaemic (55.1%) and non-dyslipidaemic (63. 5%), followed by carriers of heterozygous PCSK9 rs505151G/A at 40.6% and lastly carriers of PCSK9 rs505151G/G at (9.5%). On the other hand, carriers of homozygous PCSK9 rs28362286 C/C genotype were predominantly distributed with a frequency of 94.2% and PCSK9rs28362286C/A had a very small frequency distribution of 5.8% while PCSK9rs28362286A/A was absent in this population. Carriers of PCSK9 rs505151A/A genotype had higher HbA1c with a median of 10.10% (IQR 7.48 – 12.90) compared to PCSK9 rs505151 G/A genotype with a median of 9.00% (IQR 7.03 –11.35). The results show that PCSK9 rs505151G/A with lower HbA1c had non-significantly higher TC, LDL, TG and non-HDL but lower HDL compared to PCSK9 rs505151A/A genotype. The results revealed no direct reciprocal relationship between glycaemic control and level or type of dyslipidaemia. Conclusions: The study showed the effects of ApoE and PCSK9 genetic variation on the dyslipidaemia seen in black South African diabetic participants. Therefore, this study through ApoE and PCSK9 genotypes show that the diabetic dyslipidaemia has an underlying genetic influence. In addition, to the well-characterised ApoE genotypes, an uncharacterised genotype referred to as ApoE X genotype is reported. With these findings, consideration to explore possible underlying genetic predisposition is recommended especially in diabetic patients with dyslipidaemia that responds poorly to standard therapy

The role of various risk factors in the prevalence of cardiac autonomic neuropathy and associated diseases

The objectives of this thesis were three-fold: The first aim was to investigate the roles of various markers in the prevalence and complications of CAN and associated diseases with emphasis on diabetes mellitus. Specifically, this study investigated the role of heart rate variability (HRV) markers as well as the roles of genetic and family history risk factors. The second aim of this study was to develop mechanisms to predict CAN disease occurrence. The third aim of this current study was to develop a model for predicting diabetes mellitus (DM) and cardiovascular disease (CVD) simultaneously using common risk factors

Evaluation of a Community-wide Diabetes Prevention Program

This thesis is an evaluation of the effectiveness of a community-wide diabetes prevention program conducted in three Divisions of General Practice in Sydney, Australia. The aims were to assess whether translation of diabetes prevention programs was feasible in real-life settings and whether results achieved were comparable with those of randomised trials on which this intervention was based. Its primary goals were to assess whether the lifestyle intervention could increase participation in moderate-to-vigorous physical activity to 210 minutes per week, reduce total fat and saturated fat consumption to 30% and 10% of total daily energy intake, increase fibre consumption to 15 g/1,000 kcal/day, and lead to 5% weight loss over one year. The background section covers the physiopathology of type 2 diabetes, its risk factors, and the available population screening tools to identify people at risk. The growing morbidity and mortality burden, the economic implications of this public health problem, and the importance and feasibility of preventing or delaying the onset by intervening in the precursor stages are then summarised. Evidence for preventability is examined through a literature review of lifestyle interventions in research settings comprising highly structured and closely monitored physical activity and dietary programs under controlled conditions. Examples of the effectiveness of translation of randomised controlled trials (RCTs) into less stringent programs in community settings such as workplaces, churches, indigenous communities and whole-of-country initiatives are presented. A systematic review and meta-analysis of effectiveness of the lifestyle approaches in routine clinical practice supplements the evidence for application of prevention principles in real-life settings. The main chapters of the thesis centre on process and impact evaluation of the semi-structured Sydney-based intervention, which recruited 1,250 participants from the mainstream Australian 29 public using general practitioner services in the study area, who were followed for 12 months. The intervention’s goals aligned with those of the Finnish Diabetes Prevention Program but with less stringent entry criteria and less intensive intervention components delivered by purpose-trained lifestyle officers. The Program included an initial individual assessment and coaching session, three subsequent group sessions in the following three months, then three follow-up coaching calls at three, six and nine months. A final assessment at one year, using the same objective and self-reported measures as in the initial assessment, captured changes in body weight, physical activity and dietary habits. The process evaluation showed that it is feasible and effective to use targeted screening to identify and recruit high-risk individuals into a free-of-charge program in the general practice setting, however a quarter of participants were lost to follow-up by one year. While minor variations in aspects of the Program were required to meet local need, Program fidelity in delivering components, and self-reported adherence to diet and physical activity was high. Using a before-after study design, the impact evaluation measured 1-year changes in key Program parameters in relation to baseline. These comprised: measured weight, waist circumference, BMI, and glycaemia measurements; and self-reported dietary intake and structured physical activity, using a 3-day food record and the Physical Activity Scale for the Elderly (PASE) questionnaire, respectively. The main findings at 12 months for the 586 completers as at December 2010 were: a mean weight loss of 2.1 kg; waist circumference reduction of 2.5 cm; no significant change in glycaemia; 3% reduction of fat and saturated fat intake; 16% increase in fibre intake; and mean increase in moderate-to-vigorous physical activity of 13.7 minutes/week. All these changes were smaller than those achieved by the RCTs in research settings, most likely due to the lower intensity and monitoring of the Sydney intervention. Weight loss and waist circumference reductions were similar for participants in 30 group session and those who received telephone-only coaching. Diabetes incidence was 1% at the end of the first year. An economic appraisal of the Program implementation completes the evaluation. A cost of A$400 per kg lost among people achieving the weight goal was estimated on Program completion, but the cost was double for the overall group that included non weight losers. The cost of achieving the physical activity goal and the dietary goals was not feasible or sustainable with resources available in routine clinical settings. The costs per outcome were similar for participants not attending group sessions, who received only telephone coaching. Hence it is worth exploring this less labour-intensive modality if a general practice based Program were to be delivered as routine preventive care. In sum, the evaluation of this community-wide diabetes prevention program showed that translation of diabetes prevention programs into routine practice, while feasible at less intensive levels than in RCTs, has a somewhat lower effect on diabetes risk reduction and it can still be a financial burden in clinical settings. However, given the potential for population-wide benefit, the effectiveness of alternative delivery modes, number and duration of program components and more targeted patient sub-groups should be investigated.The Sydney Diabetes Prevention Program was funded by New South Wales Health as part of the Australian Better Health Initiative. Financial contribution and other in-kind support were provided by the Sydney South West Area Health Service and the Australian Diabetes Council -NSW

Evaluation of a Community-wide Diabetes Prevention Program

This thesis is an evaluation of the effectiveness of a community-wide diabetes prevention program conducted in three Divisions of General Practice in Sydney, Australia. The aims were to assess whether translation of diabetes prevention programs was feasible in real-life settings and whether results achieved were comparable with those of randomised trials on which this intervention was based. Its primary goals were to assess whether the lifestyle intervention could increase participation in moderate-to-vigorous physical activity to 210 minutes per week, reduce total fat and saturated fat consumption to 30% and 10% of total daily energy intake, increase fibre consumption to 15 g/1,000 kcal/day, and lead to 5% weight loss over one year. The background section covers the physiopathology of type 2 diabetes, its risk factors, and the available population screening tools to identify people at risk. The growing morbidity and mortality burden, the economic implications of this public health problem, and the importance and feasibility of preventing or delaying the onset by intervening in the precursor stages are then summarised. Evidence for preventability is examined through a literature review of lifestyle interventions in research settings comprising highly structured and closely monitored physical activity and dietary programs under controlled conditions. Examples of the effectiveness of translation of randomised controlled trials (RCTs) into less stringent programs in community settings such as workplaces, churches, indigenous communities and whole-of-country initiatives are presented. A systematic review and meta-analysis of effectiveness of the lifestyle approaches in routine clinical practice supplements the evidence for application of prevention principles in real-life settings. The main chapters of the thesis centre on process and impact evaluation of the semi-structured Sydney-based intervention, which recruited 1,250 participants from the mainstream Australian 29 public using general practitioner services in the study area, who were followed for 12 months. The intervention’s goals aligned with those of the Finnish Diabetes Prevention Program but with less stringent entry criteria and less intensive intervention components delivered by purpose-trained lifestyle officers. The Program included an initial individual assessment and coaching session, three subsequent group sessions in the following three months, then three follow-up coaching calls at three, six and nine months. A final assessment at one year, using the same objective and self-reported measures as in the initial assessment, captured changes in body weight, physical activity and dietary habits. The process evaluation showed that it is feasible and effective to use targeted screening to identify and recruit high-risk individuals into a free-of-charge program in the general practice setting, however a quarter of participants were lost to follow-up by one year. While minor variations in aspects of the Program were required to meet local need, Program fidelity in delivering components, and self-reported adherence to diet and physical activity was high. Using a before-after study design, the impact evaluation measured 1-year changes in key Program parameters in relation to baseline. These comprised: measured weight, waist circumference, BMI, and glycaemia measurements; and self-reported dietary intake and structured physical activity, using a 3-day food record and the Physical Activity Scale for the Elderly (PASE) questionnaire, respectively. The main findings at 12 months for the 586 completers as at December 2010 were: a mean weight loss of 2.1 kg; waist circumference reduction of 2.5 cm; no significant change in glycaemia; 3% reduction of fat and saturated fat intake; 16% increase in fibre intake; and mean increase in moderate-to-vigorous physical activity of 13.7 minutes/week. All these changes were smaller than those achieved by the RCTs in research settings, most likely due to the lower intensity and monitoring of the Sydney intervention. Weight loss and waist circumference reductions were similar for participants in 30 group session and those who received telephone-only coaching. Diabetes incidence was 1% at the end of the first year. An economic appraisal of the Program implementation completes the evaluation. A cost of A$400 per kg lost among people achieving the weight goal was estimated on Program completion, but the cost was double for the overall group that included non weight losers. The cost of achieving the physical activity goal and the dietary goals was not feasible or sustainable with resources available in routine clinical settings. The costs per outcome were similar for participants not attending group sessions, who received only telephone coaching. Hence it is worth exploring this less labour-intensive modality if a general practice based Program were to be delivered as routine preventive care. In sum, the evaluation of this community-wide diabetes prevention program showed that translation of diabetes prevention programs into routine practice, while feasible at less intensive levels than in RCTs, has a somewhat lower effect on diabetes risk reduction and it can still be a financial burden in clinical settings. However, given the potential for population-wide benefit, the effectiveness of alternative delivery modes, number and duration of program components and more targeted patient sub-groups should be investigated.The Sydney Diabetes Prevention Program was funded by New South Wales Health as part of the Australian Better Health Initiative. Financial contribution and other in-kind support were provided by the Sydney South West Area Health Service and the Australian Diabetes Council -NSW