Australian Diabetes Society Research Articles

Perioperative management of diabetes audit (POMODA)

BackgroundSuboptimal perioperative management of diabetes is associated with postoperative morbidity and mortality. Australian healthcare providers should primarily be guided by the Australian Diabetes Society Perioperative Diabetes Management Guidelines in caring for the perioperative diabetic patient when local or state guidelines do not exist. MethodsA retrospective, single-center, quality improvement audit was conducted on diabetic patients aged ≥18 years undergoing surgical procedures at the Townsville University Hospital, Australia, over a 12-week period. Perioperative outcomes were analyzed to establish compliance with the guidelines. Secondary objectives analyzed outcomes for Indigenous and non-Indigenous Australian patients, and patients’ age. Results202 patients were reviewed. 53 (26%) had preoperative blood glucose levels (BGLs) measured hourly. Of the patients requiring intraoperative BGLs, 93% did not have BGLs hourly and 71% did not have any intraoperative BGL. 23 (11%) had hourly BGLs postoperatively. Average preoperative haemoglobin A1c (HbA1c) was 7.5%, above target, and not measured in 45% of patients. 16/42 (38%) on metformin having major surgery had it restated appropriately. 29/41 (71%) on Sodium-Glucose Cotransporter-2 (SGLT2) inhibitors did not have a perioperative ketone level measured. Categorizing subjects into American Society of Anesthesiologists (ASA) classes revealed a greater proportion of patients aged <60 years were of class II (34%) compared to patients aged 60–70 (16%) and >70 (15%) (p = 0.015). Indigenous patients were more likely to be younger than non-Indigenous patients, 59 compared to 68 (p<0.001), and have a higher preoperative BGL, 9.0 mmol/L (162 mg/dL) compared to 8.2 mmol/L (148 mg/dL) (p = 0.19). Conclusions: POMODA has displayed multiple areas for improvement in the perioperative management of diabetes. The authors recommend that pre-anaesthetic clinics for diabetic patients requiring surgery, particularly Indigenous Australians, be held at least two weeks prior to surgery to allow for optimisation of glycaemic control and clear perioperative instructions, and anticipate this being an important first step in improving guideline compliance.

Peri-colonoscopy Implications of Sodium-Glucose Cotransporter-2 Inhibitor Therapy: A Mini-review of Available Evidence

Sodium-glucose cotransporter-2 inhibitors (SGLT2i) are a class of oral glucose-lowering agents commonly used for the treatment of type 2 diabetes. With increased use, there has been an increase in the incidence of the rare but life-threatening complication of euglycemic diabetic ketoacidosis. A common but underappreciated precipitant is colonoscopy. In this work, we outline the pathophysiology of the interaction between colonoscopy and SGLT2i use, the evidence regarding SGLT2i use in the periprocedural setting and Australian Diabetes Society guidelines.

Web-Based Questionnaire for Healthcare Professionals on Psychosocial Support for Adolescents and Young Adults with Type1 Diabetes.

IntroductionAdolescence and young adulthood is a challenging period, particularly for those living with chronic disease such as type 1 diabetes (T1D). Effective professional support is associated with better diabetes outcomes, but little is known about what determines healthcare professionals’ decision-making for therapeutic intervention, and how to support this. Our study aimed to determine healthcare professionals’ (HCPs) self-rated awareness, capability, opportunity and motivation to provide support for psychosocial issues in the management of T1D with adolescents and young adults; and to identify factors independently predictive of HCPs’ perceptions of their confidence in, and perceived importance of, addressing psychosocial issues in this population.MethodsSurvey design was used, and data collected using an anonymous web-based questionnaire based on the Capability–Opportunity–Motivation Behaviour (COM-B) framework. The study was advertised to members of the Australian Diabetes Society, and National Association of Diabetes Centres.ResultsOf 98 respondents, 57 (58.2%) were female. Confidence and perceived importance summary scores were not significantly associated with demographic characteristics. HCPs agreed that both diabetes-dependent and external non-diabetes-specific influences were important components of psychosocial management, but self-rated themselves as less confident in their ability to provide care for these aspects. Few respondents regularly encountered psychosocial issues that they believed would lead to improved outcomes if addressed and not all HCPs knew how to access psychosocial support for their adolescent patients.ConclusionOur findings indicate discrepancies between HCPs’ self-rated capability and perceived motivation to provide support relating to psychosocial issues in the management of T1D for adolescents and young adults. Equitable opportunities are needed for training and support, to increase HCPs’ understanding and hence their perceptions of the importance and of their confidence in addressing psychosocial issues, especially considering the high levels of risk of these young people for such problems.Supplementary InformationThe online version contains supplementary material available at 10.1007/s13300-022-01202-6.

An audit of the effect of SGLT2 inhibitor cessation in a pre-admission clinic before and after Australian Diabetes Society guidelines.

Perioperative ketoacidosis is an important adverse event related to the use of sodium glucose co-transporter 2 inhibitor (SGLT2i). We compared perioperative outcomes in patients on SGLT2i, before and after protocolised pre-operative cessation of the drug. There were no cases of clinically detected diabetic ketoacidosis in the 96 patients included in the study. Withdrawal of SGLT2i did not appear to alter significantly pre-operative glycaemia.

What Gets Measured Gets Improved-Setting Standards and Accreditation for Quality Improvement for Diabetes Services in Australia.

The purpose of this article is to illustrate that setting standards of care is the cornerstone for excellence in diabetes management. This is underpinned by 3 activities: a standards and accreditation process, an audit and benchmarking program and a linked quality improvement plan. While there are many examples of local auditing and quality improvement programs, there are very few that are at a national level. The National Association of Diabetes Centres (NADC) was formed by the Australian Diabetes Society and the Australian Diabetes Educators Association to set standards of diabetes care in Australia. A rigorous accreditation process was put in place to recognize primary, secondary, and tertiary level diabetes centers that meet these standards. The NADC accreditation process is underpinned by a quality improvement plan, which must be submitted for accreditation to be granted and is informed by the Australian National Diabetes Audit (ANDA). ANDA is conducted annually to gather information about treatments, complications, self-care practices and quality of life outcomes and provides a national as well as an individual report to the participating center that is used to benchmark against other like centers. The ANDA reports are important to inform national policy and advocacy for diabetes care and to also provide information for quality improvement purposes for the individual participating center. We believe that the NADC Standards and Accreditation can be an exemplar for other countries to adapt and adopt to standardize diabetes care at the highest level.

999-P: Six Months At-Home Hybrid Closed-Loop vs. Manual Insulin Delivery with Finger-Stick Blood Glucose Monitoring in Adults with Type 1 Diabetes: A Randomized Controlled Trial

Background: Few long-term RCTs compare Hybrid Closed Loop (HCL) insulin delivery to manual (non-HCL) insulin dosing in type 1 diabetes (T1D). Objective: To examine glycemic and psychosocial outcomes in adults with T1D using HCL vs. manual insulin dosing with self-monitoring of blood glucose (SMBG) for 6 months. Methods: Adults using multiple daily injections or pumps with SMBG were randomized 1:1 after insulin dose optimization to 26 weeks of HCL (Medtronic 670G) or continuation of current therapy. The primary outcome was time in target range (70-180mg/dL) with masked CGM during the final 3 weeks. Secondary outcomes included other CGM metrics, HbA1c, treatment satisfaction (DTSQs) and diabetes distress (PAID). Intention to treat analysis was performed with ANCOVA or rank sum test. Results: HCL and control groups were well balanced at baseline (Table). At 26 weeks, mean (95% CI) CGM time in range with HCL was greater by 14.8% (11.1, 18.5), with reduced high and low glucose time, and lower HbA1c. There were no between-group differences in treatment satisfaction or diabetes distress (Table). Conclusions: HCL provided a significant and sustained glycemic benefit compared with standard therapy. Results will inform potential users and health professionals and a cost-benefit analysis may facilitate HCL access. Disclosure S.A. McAuley: Advisory Panel; Self; Medtronic. Research Support; Self; Medtronic, Roche Diabetes Care. Speaker’s Bureau; Self; Lilly Diabetes, Roche Diabetes Care. M.H. Lee: Research Support; Self; Medtronic. Speaker’s Bureau; Self; AstraZeneca, Medtronic. B. Paldus: Research Support; Self; JDRF. Speaker’s Bureau; Self; Australian Diabetes Society, Medtronic. S. Vogrin: None. M.B. Abraham: Speaker’s Bureau; Self; Lilly Diabetes. L. Bach: None. M. Burt: None. N. Cohen: Advisory Panel; Self; Abbott, AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Lilly Diabetes. Research Support; Self; Ypsomed AG. Speaker’s Bureau; Self; Novo Nordisk A/S. P.G. Colman: None. E.A. Davis: None. C. Hendrieckx: None. M. de Bock: None. J. Holmes-Walker: None. J. Kaye: Advisory Panel; Self; Abbott. Speaker’s Bureau; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, Novo Nordisk Inc. K. Kumareswaran: None. R. MacIsaac: None. R.W. McCallum: None. C.M. Sims: Stock/Shareholder; Self; Medtronic. J. Speight: Research Support; Self; Abbott, AstraZeneca, Medtronic, Sanofi-Aventis. Speaker’s Bureau; Self; American Diabetes Association, Australian Diabetes Society, Roche Diabetes Care. S. Stranks: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Lilly Diabetes, Sanofi-Aventis. S. Trawley: None. V. Sundararajan: None. G. Ward: None. A.C. Keech: Advisory Panel; Self; Amgen, Kowa Research Institute, Inc. Consultant; Self; Sanofi-Aventis. Speaker’s Bureau; Self; Abbott, Amgen. A. Jenkins: Advisory Panel; Self; Abbott, Medtronic. Research Support; Self; Abbott, GlySens Incorporated, Medtronic, Sanofi-Aventis. T. Jones: Other Relationship; Self; Medtronic. D.N. ONeal: None.

234-OR: Postprandial Glucose Control Using the Medtronic Advanced Hybrid Closed-Loop System: Faster-Acting Insulin Aspart vs. Insulin Aspart

Background: Faster-acting insulin aspart (FiAsp) may improve responsiveness of closed-loop (CL) systems and provide better postprandial glucose (PPG) management due to its more rapid onset and offset compared to insulin aspart (Asp). The Medtronic Advanced Hybrid Closed Loop (AHCL) System features auto-basal and auto-bolus functions. Aim: To compare PPG control using FiAsp vs. Asp delivered using AHCL. Methods: Twelve adults with T1D (median HbA1c 7.1% [IQR 6.8, 7.2]; 54mmol/mol [51, 55]) were assigned to FiAsp or Asp (unblinded) in random-order over two-stages (6-weeks duration each) using AHCL. Postprandial periods were defined using set time-blocks for breakfast (06:00-10:00); lunch (11:00-15:00); and dinner (17:00-21:00), based on conventional meal-times and meal distribution. CGM data was analyzed using signed-rank test. Results: With all postprandial time-block data aggregated, FiAsp demonstrated greater overall time-in-range (TIR) (70-180mg/dL) (p=0.028) and less hyperglycaemia (p=0.041) compared with Asp (Table). TIR was greater during lunch (p=0.034) for FiAsp vs. Asp, with no difference during breakfast or dinner. Over the 6-week duration, FiAsp use trended towards greater TIR vs. Asp (82.7% vs. 80.4%, p=0.07). Conclusions: FiAsp appears to confer an advantage compared with Asp for PPG control whilst using AHCL even in subjects with high overall TIR. Disclosure M.H. Lee: Research Support; Self; Medtronic. Speaker’s Bureau; Self; AstraZeneca, Medtronic. S. Vogrin: None. B. Paldus: Research Support; Self; JDRF. Speaker’s Bureau; Self; Australian Diabetes Society, Medtronic. D. Morrison: None. D. Zaharieva: Speaker’s Bureau; Self; Ascensia Diabetes Care, Insulet Corporation, Medtronic. J. Lu: None. H. Jones: None. S.A. Wyatt: Other Relationship; Self; Medtronic, Ypsomed AG. E. Netzer: None. C.M. Sims: Stock/Shareholder; Self; Medtronic. R. MacIsaac: None. B. Grosman: Employee; Self; Medtronic. A. Roy: Employee; Self; Medtronic. N. Kurtz: Employee; Self; Medtronic. A. Jenkins: Advisory Panel; Self; Abbott, Medtronic. Research Support; Self; Abbott, GlySens Incorporated, Medtronic, Sanofi-Aventis. D.N. ONeal: None.

1037-P: Glucose Control following Missed and Late Meal Boluses with a Medtronic Enhanced-Hybrid Closed-Loop (E-HCL) System

Background: A missed or late meal insulin bolus can impact glycemia in type 1 diabetes (T1D). Aim: To study glucose control after missed and late meal boluses in T1D adults using a prototype enhanced hybrid closed-loop (E-HCL) system (Medtronic) providing automated basal insulin and correction boluses. Methods: Twelve T1D adults (median HbA1c 6.8% [IQR 6.2-7.2] | 51mmol/mol [44-55] participated. After 1-week run-in at home in Open Loop, E-HCL was activated during 1-week supervised hotel phase followed by 3 weeks free-living at-home. Participants consumed a standardized 40g carbohydrate dinner in the supervised phase. Four hours of post-prandial glucose data following a standard bolus pre-meal in E-HCL at home were compared in a pairwise manner to 1) Pre-meal bolus in Open Loop Run-In; 2) 20minute Late bolus in E-HCL supervised; 3) Missed bolus in E-HCL supervised using Wilcoxon Signed-Rank Test. Results: Late bolus was associated with mild hypoglycemia and higher glucose variability; missed bolus was associated with hyperglycemia (Table). Overall time in CL was 99.98%. E-HCL at home vs. Open Loop (run-in) had greater time-in-70-180mg/dL range (85.3 vs. 75.0%, p=0.003). There was no severe hypoglycemia or ketoacidosis. Conclusions: While glucose excursions were modest, the administration and timing of meal boluses influenced post-meal glycemia in well-controlled T1D adults using E-HCL. Disclosure M.H. Lee: Research Support; Self; Medtronic. Speaker's Bureau; Self; AstraZeneca. S. Vogrin: None. B. Paldus: Other Relationship; Self; Australian Diabetes Society, JDRF, Medtronic. H. Jones: None. V.R. Obeyesekere: None. C.M. Sims: Stock/Shareholder; Self; Medtronic. S.A. Wyatt: Other Relationship; Self; Animas Corporation, Medtronic. G.M. Ward: None. S.A. McAuley: Research Support; Self; JDRF, Medtronic. Speaker's Bureau; Self; Australian Diabetes Society, Eli Lilly and Company. R. MacIsaac: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, Novo Nordisk Inc. Speaker's Bureau; Self; AstraZeneca, Novo Nordisk Inc. Other Relationship; Self; AstraZeneca, Novo Nordisk Inc. B. Krishnamurthy: None. V. Sundararajan: None. A. Jenkins: Advisory Panel; Self; Abbott, Australian Diabetes Society, Medtronic. Research Support; Self; Abbott, GlySens Incorporated, Medtronic, Mylan. Speaker's Bureau; Self; Eli Lilly and Company, Novo Nordisk Inc. D.N. O'Neal: None.

600-P: The 1000 Qatar Omics Study: Development of New Analytical Tools for Early Prediction and Treatment of Diabetic Retinopathy in Qatar

Background: According to WHO, Qatar is one of the countries most affected by type 2 diabetes T2D worldwide. Despite current treatments, patients suffering from diabetes are still at risk of developing microvascular complications. Of which, Diabetic Retinopathy DR is a debilitating microvascular complication, which leads to blindness, if left untreated. Hypothesis and Aims: the genetic variants SNPs, circulating non-coding RNAs, mRNAs, and proteins, detected in diabetic individuals progressing to DR are accurate biomarkers for DR detection, progression and can be utilized effectively in future screening programs for at-risk individuals as well as for monitoring the outcome of interventions/treatments for DR. The aim is to investigate the SNPs using WGS data, and assess microRNA, mRNA and protein signature of DR progression in T2D patients with and without DR comparing to the healthy controls. Methodology: plasma samples, WGS data of 500 T2D with and without DR and 500 healthy controls subjects were included in this study. Retinal scans are available for all the study participants to assess and classify the DR stages. Total RNA was extracted from plasma samples, microRNA customes assays profiling, proteins and mRNAs are currently at the final stages of analysis and will be ready at the time of the presentation. Preliminary Results: our preliminary analyses through genome-and proteome-wide discovery studies using cellular systems and clinical samples, identified an omics signature of DR comprising of: four mRNAs of endothelial stress, 45 microRNAs of progressing to DR, eight proteins of proliferative DR vs. no DR and candidate SNPs identified in a Qatari cohort that are associated with DR progression. Conclusion: This information will significantly impact the development of newer analytical tools and better therapies that will allow early prediction and treatment of DR, thereby reducing the burden of sight threatening diabetes complications in Qatar. Disclosure S. Subash Padmajeya: None. L. Jerman: None. A. Al-Kurbi: None. K. Fakhro: None. A.J. Jenkins: Advisory Panel; Self; Abbott, Australian Diabetes Society, Medtronic. Research Support; Self; Abbott, GlySens Incorporated, Medtronic, Mylan. Speaker's Bureau; Self; Eli Lilly and Company, Novo Nordisk Inc. A. Hardikar: None. A.S. Akil: None. Funding Qatar National Research Fund

102-LB: GP-OSMOTIC: An RCT to Determine the Effect of 3-Monthly Retrospective Continuous Glucose Monitoring (rCGM) on 12-Month HbA1c in Adults with Type 2 Diabetes (T2D) in Primary Care

Introduction: Reviewing rCGM patterns may prompt lifestyle or therapeutic changes to achieve glycaemic targets but evidence for rCGM use in primary care management of T2D is limited. Methods: Two-arm RCT. Participants: Adults with T2D, HbA1c ≥0.5% above target, prescribed ≥2 non-insulin glycemia medications or insulin. Intervention: 1-hour diabetes education and (at 0/3/6/9/12 months): HbA1c assessment + wearing FreeStyle Libre Pro (Abbott) for up to 14 days prior to being discussed at a clinic visit. Physicians were trained in interpreting ambulatory glucose profiles. Control: 3-monthly ‘usual care’ clinic visits + r-CGM device worn (blinded, research data) at 0 and 12 months. Primary outcome: difference in mean HbA1c at 12 months. Secondary outcomes: mean differences in time in range (TIR: 4-10 mmol/L) and diabetes-specific distress (PAID) at 12 months, and HbA1c at 6 months. ITT analysis. Results: In 25 primary care practices, participants were: 299 adults with T2D, aged (mean(SD)) 60(10) years, HbA1c: 8.9(1.2)%, diabetes duration (median(IQR)) of 12(8,20) years. At 12 months, the between-group difference in mean HbA1c was 0.2% (p=0.112). The estimated mean percentage TIR was 8.4% higher in the intervention than the control arm (p=0.004). Diabetes-specific distress did not differ between arms (0.5; p=0.71). At 6 months, HbA1c was significantly lower in the intervention arm (0.5%; p&amp;lt;0.001). We found little evidence of changes in the number of glycemic medications in either arm. Discussion: Use of 3-monthly rCGM in adults with T2D in primary care does not improve HbA1c at 12 months. We showed a statistically and clinically significant reduction in HbA1c at 6 months in the intervention group, as well as significant improvements in TIR at 12 months, with no change in diabetes distress. Our findings suggest the primary impact of r-CGM use on HbA1c in this setting is short term, and not associated with increase in the number of diabetes medications. Disclosure J. Furler: Research Support; Self; Abbott, Sanofi. D.N. O’Neal: None. J. Speight: Research Support; Self; AstraZeneca, Medtronic, Sanofi. Speaker’s Bureau; Self; Novo Nordisk A/S, Roche Diabetes Care. J.E. Manski-Nankervis: Research Support; Self; Australian National Health and Medical Research Council, Boehringer Ingelheim International GmbH, Diabetes Australia, Eli Lilly and Company. Speaker’s Bureau; Self; RACGP. S. Thuraisingam: None. E. Holmes-Truscott: Research Support; Self; Sanofi. Speaker’s Bureau; Self; Novo Nordisk Inc. K.R. De La Rue: None. L.E. Ginnivan: None. R.C. Doyle: None. K. Khunti: Advisory Panel; Self; Amgen Inc., AstraZeneca, Eli Lilly and Company, Merck Sharp &amp; Dohme Corp., Novo Nordisk A/S, Sanofi. Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Merck Sharp &amp; Dohme Corp., Novartis AG, Novo Nordisk A/S, Pfizer Inc., Sanofi-Aventis, Servier, Takeda Pharmaceutical Company Limited. Research Support; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Merck Sharp &amp; Dohme Corp., Novartis AG, Novo Nordisk A/S, Pfizer Inc., Sanofi-Aventis. Speaker’s Bureau; Self; AstraZeneca, Berlin-Chemie AG, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Menarini Group, Merck Sharp &amp; Dohme Corp., Novartis AG, Novo Nordisk A/S, Roche Pharma, Sanofi, Servier, Takeda Pharmaceutical Company Limited. M. Catchpool: None. K. Dalziel: None. J.I. Chiang: None. I. Blackberry: None. R. Audehm: Advisory Panel; Self; AstraZeneca, Novartis Pharmaceuticals Corporation. M. Kennedy: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Merck Sharp &amp; Dohme Corp., Novo Nordisk Inc., Sanofi. M.J. Clark: None. A.J. Jenkins: Advisory Panel; Self; Abbott, Australian Diabetes Society, Medtronic. Research Support; Self; Abbott, GlySens Incorporated, Medtronic, Mylan. Speaker’s Bureau; Self; Eli Lilly and Company, Novo Nordisk Inc. A.S. Januszewski: None. D. Liew: Advisory Panel; Self; AstraZeneca, Bayer AG. Research Support; Self; AbbVie Inc., AstraZeneca, Bristol-Myers Squibb Company, CSL Behring, Pfizer Inc. P.M. Clarke: None. J.D. Best: Consultant; Self; Abbott. Funding National Health and Medical Research Council of Australia (APP1104241); Sanofi Australia; Abbott Diabetes Care

41-LB: Lipoprotein Subfractions Are Associated with Diabetic Microvascular Disease among 9,795 Patients in the FIELD Trial

Background: In the FIELD trial, a 5-year randomized double-blind placebo-controlled trial of fenofibrate vs. placebo in 9,795 adults with type 2 diabetes (T2D), the only standard lipid parameter correlating with microvascular (renal) events was triglycerides. Given the high prevalence of diabetic microangiopathy, we explored associations between lipoprotein subfractions and nephropathy, retinopathy, microvascular amputations (MiAmp) and neuropathy. Methods: We performed ultracentrifugation using the vertical autoprofile (VAP, Atherotech) on plasma (baseline and after 6 weeks of fenofibrate). Analyses were performed using Cox proportional hazards and logistic regression for new on-study events. Results were adjusted for gender and fenofibrate or placebo allocation. Results: HDL related analytes (HDL-C, HDL3-C, apo A1, apoA2) correlated with reduced risk for neuropathy, nephropathy, and MiAmp. Buoyant LDL (LDL1-C) and densest LDL (LDL4-C) correlated negatively with neuropathy and positively for MiAmp, respectively. Triglycerides and apo C3 increased neuropathy and nephropathy risk. VLDL species correlated with increased MiAmp and retinopathy risk. Conclusions: VAP identifies multiple lipoprotein subclasses and VAP subclass/apoprotein ratios associated with diabetic microangiopathy. Many were improved with fenofibrate. Disclosure P.P. Toth: Consultant; Self; Amarin Corporation, Amgen Inc., AstraZeneca, Kowa Pharmaceutical Europe Co. Ltd., Novo Nordisk Inc. Speaker’s Bureau; Self; Amarin Corporation, Amgen Inc., Merck &amp; Co., Inc., Novo Nordisk Inc., Regeneron Pharmaceuticals, Sanofi US. A.C. Keech: None. A.S. Januszewski: None. R.L. OConnell: None. L. Li: None. D. Sullivan: None. M. Taskinen: Advisory Panel; Self; Novo Nordisk A/S. Consultant; Self; Akcea Therapeutics, Chiesi USA, Inc. Research Support; Self; Amgen Inc., Novo Nordisk A/S. Speaker’s Bureau; Self; Amgen Inc. P.L. Drury: None. G.F. Watts: None. J.D. Best: Consultant; Self; Abbott. J. Ansquer: Research Support; Self; Abbott, Mylan. S.R. Jones: None. A.J. Jenkins: Advisory Panel; Self; Abbott, Australian Diabetes Society, Medtronic. Research Support; Self; Abbott, GlySens Incorporated, Medtronic, Mylan. Speaker’s Bureau; Self; Eli Lilly and Company, Novo Nordisk Inc.

139-LB: Haptoglobin Phenotype and Levels in Type 2 Diabetes and Effects of Fenofibrate

Background: Haptoglobin (Hp) is a plasma protein with anti-oxidant, anti-inflammatory and pro-angiogenic properties. Based on the Hp gene alleles there are three Hp phenotypes (1-1, 2-1 and 2-2). In diabetes, Hp-2 is associated with substantially increased risk of cardiac and renal damage relative to Hp-1. AIMS: To evaluate 1) associations between Hp phenotype and levels; and 2) effects of fenofibrate vs. placebo on Hp levels. Methods: A substudy of 180 adults with type 2 diabetes (T2D) (50% females) from the FIELD trial. Average age was 60±6 years, BMI 30.4±5.1 kg/m2 and HbA1c 6.8±1.3%. Plasma (citrate) samples were evaluated at baseline, after 6-weeks daily 200 mg co-micronised fenofibrate (end of active run-in) and 2-years after randomisation to fenofibrate or placebo. Results: Hp phenotype 1-1 was detected in 19%, Hp 2-1 in 48% and Hp 2-2 in 33% subjects. Hp levels at baseline were 1.44±1.10, 1.31±0.49 and 0.99±0.46 mg/mL in type 1-1, 2-1 and 2-2 respectively (all p&amp;lt;0.0001). In Hp type 2-2 baseline Hp levels correlated with HbA1c (r=0.35, p=0.005), BMI (r=0.30, p=0.02) and HDL-C (r=0.29, p=0.02). No such correlations were observed for Hp type 1-1 and 2-1. After 6-weeks fenofibrate Hp levels dropped by 22.3, 19.9 and 17.7% in type 1-1. 2-1 and 2-2 respectively (all p&amp;lt;0.0001; difference between types p=ns.). After 2-years of fenofibrate vs. placebo Hp levels in the placebo group had increased back to baseline values whereas Hp levels in the fenofibrate group remained reduced similar to 6-weeks levels. In Hp 1-1 subjects Hp levels dropped after 6-weeks fenofibrate in 94% of subjects, in Hp 2-1 - in 92% and in Hp 2-2 only in 73% of subjects (difference between phenotypes: p=0.002). Conclusions: Hp levels differ by Hp phenotype in T2D adults. Fenofibrate lowers Hp levels in all phenotypes, however the effect is significantly attenuated in Hp 2-2. Disclosure A.S. Januszewski: None. H.K. Young: Other Relationship; Self; Medtronic. L. Li: None. R.L. OConnell: None. T. Lyons: None. C.B. Kelly: None. D. Sullivan: None. R. Scott: None. A.C. Keech: None. A. Jenkins: Advisory Panel; Self; Abbott, Australian Diabetes Society, Medtronic. Research Support; Self; Abbott, GlySens Incorporated, Medtronic, Mylan. Speaker’s Bureau; Self; Eli Lilly and Company, Novo Nordisk Inc. Funding Sydney Medical School Foundation; National Health and Medical Research Council of Australia

22-LB: Baseline and Short-Term Change in Plasma Uric Acid on Fenofibrate Predict Cardiovascular Risk: A Post Hoc Analysis of FIELD

Background: Fenofibrate increases renal clearance of uric acid (UA). Relationships between baseline and short-term changes in plasma UA with fenofibrate and subsequent cardiovascular risk in patients with type 2 diabetes (T2D) are unknown. Method: Post hoc analyses of the FIELD trial explored the relationships between CVD events and 1) baseline UA level; and 2) short-term change in UA level over 6-week single-blind active fenofibrate run-in. Results: The FIELD trial showed 11% fewer cardiovascular events in patients with T2D assigned to fenofibrate compared to placebo over 5 years (HR = 0.89, 95% CI: 0.80-0.99, p = 0.035). Baseline UA (n=9622) ranged between 0.11 to 0.79 mmol/L (mean = 0.33, SD = 0.078). Each 0.1 mmol/L higher baseline UA increased CVD events by 21% (HR = 1.21 95% CI: 1.13-1.29, p &amp;lt; 0.001; Fig. 1A), and remained after adjusting for other classic risk factors (HR = 1.12, 95% CI: 1.04-1.21, p = 0.002). Fall in UA level with fenofibrate run-in also predicted lower CVD risk, adjusted for baseline UA and irrespective of trial treatment allocation (HR = 0.86, 95% CI: 0.76-0.97, p = 0.015; Fig. 1B). Discussion: Baseline and short-term fenofibrate-induced lowering of UA predict cardiovascular risk in patients with T2D, irrespective of long-term trial treatment allocation. The reduction in total CVD events with fenofibrate was not shown to be mediated through lowering of UA levels. Disclosure J.Y. Cao: None. B. Waldman: None. R.L. OConnell: None. D. Sullivan: None. V. Gebski: None. A.S. Januszewski: None. I. Marschner: None. R. Scott: None. M. Taskinen: Advisory Panel; Self; Novo Nordisk A/S. Consultant; Self; Akcea Therapeutics, Chiesi USA, Inc. Research Support; Self; Amgen Inc., Novo Nordisk A/S. Speaker’s Bureau; Self; Amgen Inc. R. Simes: None. N. McGill: None. A.J. Jenkins: Advisory Panel; Self; Abbott, Australian Diabetes Society, Medtronic. Research Support; Self; Abbott, GlySens Incorporated, Medtronic, Mylan. Speaker’s Bureau; Self; Eli Lilly and Company, Novo Nordisk Inc. A.C. Keech: None.

38-LB: Discovery Analysis of MicroRNAs (miRs) Associated with Microvascular Complications in Adults with Type 1 Diabetes

Objective: Despite therapeutic advances, type 1 diabetes (T1D) is associated with a risk of development of micro- and macrovascular complications. Early treatment of complications is associated with a more favorable prognosis, hence biomarkers to enable early detection and to monitor treatments may be useful. Methods: Plasma (EDTA) samples were obtained from 30 adult (M/F = 20/10) individuals with T1D, age 42±16 years, T1D duration 24±11 years, HbA1c 7.5±1.2% and BMI 26.5±4.0 kg/m2 (15 with microvascular complications (retinopathy or nephropathy) - CX+, and 15 without complications - CX-) and compared with 15 nondiabetic controls (CON, matched age, gender, smoking and BMI). T1D CX+ and CX- individuals were matched for age, gender, diabetes duration, smoking, BMI, HbA1c and insulin therapy modality (CSII/MDI). In these discovery cohort samples, profiling of 754 miRs was done using a high throughput probe based quantitative PCR on nanofluidics Open Array platform . Results were analyzed using independent T test, Mann-Whitney test and classification trees. Statistical analysis was undertaken using R (ver. 3.5.1) and XLStat (ver. 2018.6). Results: Of 754 available miRs on the array, 186 miRs were detectable in plasma. Using an unbiased approach expression of 32 miRs differed significantly in CON vs. T1D and 16 miRs were differentially expressed between CX+ and CX- T1D subjects. Using a Random Forest wrapper algorithm 5 miRs were identified with importance for segregating CX+ vs. CX- status: miR-483-5p, miR-328, miR-1274B, miR-7 and miR-30a-5p. In logistic regression those 5 miRs provided a ROC curve with AUC=0.90 for the CX+ vs. CX- discrimination. Conclusion: In a discovery analysis of well- matched CX+ and CX- selected miRs provided good discrimination between T1D CX status. Validation studies in a larger cohort of cross-sectional and longitudinal samples are in progress. Disclosure A.S. Januszewski: None. E.S. Scott: None. M. Joglekar: None. L. Carroll: None. R. Farr: None. W. Wong: None. D.N. O’Neal: None. C. Karschimkus: None. G. Fulcher: Advisory Panel; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Janssen Research &amp; Development, Merck Sharp &amp; Dohme Corp., Novo Nordisk Inc. Consultant; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Janssen Research &amp; Development, Merck Sharp &amp; Dohme Corp., Novo Nordisk Inc. Research Support; Self; Novo Nordisk Inc. A. Hardikar: None. A.J. Jenkins: Advisory Panel; Self; Abbott, Australian Diabetes Society, Medtronic. Research Support; Self; Abbott, GlySens Incorporated, Medtronic, Mylan. Speaker’s Bureau; Self; Eli Lilly and Company, Novo Nordisk Inc. Funding Sydney Medical School Foundation; National Health and Medical Research Council of Australia

1391-P: Longitudinal Changes of Plasma Sphingomyelins during Gestation in Women With and Without Type 1 Diabetes and Preeclampsia

Preeclampsia (PE), a major cause of maternal and fetal morbidity and mortality worldwide, has significantly higher incidence in women with type 1 diabetes mellitus (T1DM) than in nondiabetic populations (∼20% vs. 5%, respectively). Sphingolipids are key signaling molecules, and have many roles in the structure and regulation of cellular functions. Sphingomyelin (SM) is the most abundant sphingolipid in plasma lipoproteins. There is evidence that altered SM metabolism may contribute to cardiovascular and renal complications in diabetes. We aimed to determine whether plasma concentrations of 12 SM species were associated with PE in T1DM in a prospective study of pregnancy of 23 T1DM women who developed PE and 24 T1DM who remained normotensive. Additionally, 19 normotensive nondiabetic pregnant women were included for reference. All subjects were free of microalbuminuria and hypertension at enrolment, and all visits (12, 22, 32 weeks’ gestation) preceded clinical PE onset. Results: There were no cross-sectional differences in total SM, or in any individual SM species, between diabetic women with and without PE, or between normotensive women with and without diabetes at any stage of gestation. With advancing gestation in all groups, C18-SM, C18:1-SM, C20-SM, C20:1-SM, C22-SM, C22:1-SM, C24-SM, and C24:1-SM increased (all p&amp;lt;0.001). LDL- and VLDL-cholesterol also increased, while HDL-cholesterol did not change. In contrast, C14-SM, C16-SM, C26-SM and C26:1-SM decreased (all p&amp;lt;0.001). There were no correlations between any SM species and conventional lipid profiles. Conclusions: With advancing gestation, plasma concentrations of most SM species increased, as did LDL and VLDL; however, two long-chain and two very long-chain SM species decreased. Although there were no differences in SM according to diabetes or PE status at any time point, further studies should address the significance of differential changes of SM species during pregnancy. Disclosure C.B. Kelly: None. S.M. Hammad: None. R.L. Klein: None. M.F. Lopes-Virella: None. M.J. Leyva: None. J. Yu: None. A.J. Jenkins: Advisory Panel; Self; Abbott, Australian Diabetes Society, Medtronic. Research Support; Self; Abbott, GlySens Incorporated, Medtronic, Mylan. Speaker's Bureau; Self; Eli Lilly and Company, Novo Nordisk Inc. A.J. Nankervis: None. K.F. Hanssen: None. S.K. Garg: Advisory Panel; Self; Eli Lilly and Company, Roche Pharma, Sanofi-Aventis, Zealand Pharma A/S. Research Support; Self; Eli Lilly and Company, WebMD. J.A. Scardo: None. C.E. Aston: None. T. Lyons: None. Funding JDRF; Novo Nordisk; National Institutes of Health

123-LB: Continuous Subcutaneous Insulin Infusion from Diagnosis of Type 1 Diabetes Improves Intermediate Glycaemic Variability in Children

Background: Glucose variability (GV) may be reflected by variation in either the short-term glucose levels (assessed by continuous glucose monitoring (CGM)) or the long-term by HbA1c or intermediate by 1,5-anhydroglucitol (1,5-AG). In patients with T1DM management by continuous subcutaneous insulin infusion (CSII) is usually associated with improved glycaemia compared to multiple daily insulin injections (MDI). Serum 1,5-anhydroglucitol (1,5-AG) correlates with GV on CGM in adult and pediatric T1D groups. It is not known whether CSII therapy without CGM improves intermediate GV. Methods: Blood was obtained from children (mean age 14.1 +/- 1.3 years) within 3-months of T1D diagnosis. Children were treated with CSII (n=12) or MDI (n=15) and followed for a further 1 to 3 time points (median, LQ-UQ 535, 519-563 days follow-up). GV was assessed measuring 1,5-anhydroglucitol (1,5-AG) (GlycoMark, Inc., Winston-Salem, NC). The mean difference, standard deviation (SD) and coefficient of variation (CV) of 1,5-AG and HbA1c was compared between treatment arms. Results: There was no difference between treatment modalities in baseline HbA1c (median, LQ-UQ 11.8, 10.2-13.5 % (105, 87-124 mmol/mol) vs. 12.6, 10.3-14.0 % (114, 89-130 mmol/mol) CSII vs. MDI) nor baseline 1,5-AG (median, LQ-UQ 2.8, 1.8-4.0 μg/mL vs. 3.6, 2.1-12.1 μg/mL CSII vs. MDI). 1,5-AG improved more (increased) in the CSII vs. MDI group (3.1 +/- 4.1 vs. -2.2 +/- 7.0 μg/ml respectively, P=0.029). This difference persisted following adjustment for the duration of follow-up. There was no significant difference in the HbA1c improvement between the CSII and MDI groups. There was no significant difference in the SD or CV of 1,5-AG or HbA1c between groups. Conclusions: Early use of CSII post-T1D-diagnosis in a pediatric population is associated with a higher 1,5-AG than with MDI therapy implying reduced glycaemic variability. Disclosure E.S. Scott: None. A.S. Januszewski: None. G. Fulcher: Advisory Panel; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Janssen Research &amp; Development, Merck Sharp &amp; Dohme Corp., Novo Nordisk Inc. Consultant; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Janssen Research &amp; Development, Merck Sharp &amp; Dohme Corp., Novo Nordisk Inc. Research Support; Self; Novo Nordisk Inc. T. Jones: Research Support; Self; Dexcom, Inc., Medtronic MiniMed, Inc. Speaker's Bureau; Self; Eli Lilly and Company, Roche Diabetes Care. E.A. Davis: None. A.J. Jenkins: Advisory Panel; Self; Abbott, Australian Diabetes Society, Medtronic. Research Support; Self; Abbott, GlySens Incorporated, Medtronic, Mylan. Speaker’s Bureau; Self; Eli Lilly and Company, Novo Nordisk Inc.

595-P: Progression of Retinopathy in Adolescents with Type 1 Diabetes

Aim: Current guidelines recommend screening for retinopathy from 11 years in youth with type 1 diabetes (T1D) and 2-5 years T1D duration. We examined the longitudinal progression and regression of retinopathy in adolescents seen at our Diabetes Complications assessment service (DCAS) clinic. Methods: We analyzed digitized retinal photographs taken from 2000-2018 (n=814) in youth with &amp;gt;3 assessments. Retinopathy was graded using the modified Airlie house classification. Generalized estimating equations were used to explore the association between progression/regression and covariates (HbA1c, gender, and diabetes duration). Results: Mean age at baseline was 13.3+2.6 years, mean T1D duration 6.1+&amp;gt;3.4 years and mean follow- up 7.4 years. Retinopathy was present in 18.7% (n=152) at baseline assessment; with progression in 32.6% (n=266), regression in 7% (n=57) and persistence in 60.3% (n=491). Of those with progression, 185/266 (22.7%) had one step and 81 (9.9%) had &amp;gt; 2 step progression. Factors associated with retinopathy progression were HbA1c and T1D duration and for regression T1D duration (Table 1). Neither height nor SBP was significant for other outcomes. Conclusion: In adolescents with T1D, retinopathy persistence or progression was greater than of regression. Follow-up of into adulthood will inform the development of appropriate retinopathy screening schedules. Disclosure V. Velayutham: None. G. Liew: None. A.S. Januszewski: None. Y. Cho: None. P.Z. Benitez-Aguirre: None. M.E. Craig: None. A. Jenkins: Advisory Panel; Self; Abbott, Australian Diabetes Society, Medtronic. Research Support; Self; Abbott, GlySens Incorporated, Medtronic, Mylan. Speaker's Bureau; Self; Eli Lilly and Company, Novo Nordisk Inc. K.C. Donaghue: None.

456-P: The REMOVAL Trial: Effect of Metformin on Markers of Cardiometabolic Risk in Patients with Type 1 Diabetes

Background: In REMOVAL (NCT01483560), adjunct metformin treatment in adults with type 1 diabetes reduced body weight and LDL cholesterol (secondary outcomes) and progression of averaged maximal carotid intima-media thickness (tertiary outcome). Here, we report effects of metformin on tissue plasminogen activator antigen (tPA), soluble E-selectin (sE-selectin) and soluble intracellular-adhesion molecule 1 (sICAM-1) (tertiary outcomes) as well as other exploratory biomarkers. Methods: Samples were available at 0, 12, 24 and 36 months from 428 men and women with type 1 diabetes randomly assigned to metformin 1000 mg or matching placebo twice daily for three years: (mean±SD) age 55±8·5 years, HbA1c 8·0±0·82%, BMI 28·4±4·3 kg/m2, duration of diabetes 34±10·8 years, 82% on statin therapy. Commercial ELISA kits were used for tPA, sE-selectin, and sICAM-1 and automated platforms for apolipoproteins (Apo) A-1 and B, C-reactive protein (CRP), and high sensitivity cardiac troponin T (cTnT). Results: Metformin reduced tPA (22.2%, p&amp;lt;0.001; tertiary outcome), CRP (15.8%, p=0.041), and Apo B (4.6%, p=0.012) but did not affect sE-selectin, sICAM-1, Apo A-1 or cTnT (repeated measures ANCOVA). Conclusion: The reductions in tPA and CRP observed with metformin in type 1 diabetes indicate modest antithrombotic and anti-inflammatory effects consistent with previous studies in type 2 diabetes. Disclosure P. Welsh: Research Support; Self; AstraZeneca, Boehringer Ingelheim International GmbH. N. Greenlaw: None. H. Colhoun: Advisory Panel; Self; Eli Lilly and Company, Novartis Pharmaceuticals Corporation, Sanofi-Aventis. Research Support; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Novo Nordisk A/S, Pfizer Inc., Regeneron Pharmaceuticals, Roche Pharma, Sanofi-Aventis. Speaker's Bureau; Self; Eli Lilly and Company, Regeneron Pharmaceuticals, Sanofi. Stock/Shareholder; Self; Bayer AG, Roche Pharma. N. Chaturvedi: Advisory Panel; Self; AstraZeneca. I. Ford: None. I. Hramiak: Advisory Panel; Self; AstraZeneca, Eli Lilly and Company, GlaxoSmithKline plc., Insulet Corporation, Janssen Pharmaceuticals, Inc., Merck &amp; Co., Inc., Novo Nordisk Inc., Sanofi. Research Support; Self; AstraZeneca, Eli Lilly and Company, GlaxoSmithKline plc., Novo Nordisk A/S, Sanofi. Speaker's Bureau; Self; Merck &amp; Co., Inc. A.D. Hughes: Advisory Panel; Spouse/Partner; AstraZeneca. A. Jenkins: Advisory Panel; Self; Abbott, Australian Diabetes Society, Medtronic. Research Support; Self; Abbott, GlySens Incorporated, Medtronic, Mylan. Speaker's Bureau; Self; Eli Lilly and Company, Novo Nordisk Inc. B.E.K. Klein: None. R. Klein: None. M. Brouwers: None. P. Rossing: Advisory Panel; Self; AstraZeneca, Bayer AG, Boehringer Ingelheim Pharmaceuticals, Inc. Speaker's Bureau; Self; Eli Lilly and Company, Merck Sharp &amp; Dohme Corp. Other Relationship; Self; Novartis AG, Novo Nordisk A/S. C.D. Stehouwer: None. N. Sattar: Advisory Panel; Self; Amgen Inc., AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Novo Nordisk A/S. Consultant; Self; NAPP Pharmaceuticals Limited. Research Support; Self; Boehringer Ingelheim Pharmaceuticals, Inc. Speaker's Bureau; Self; Amgen Inc., Eli Lilly and Company, Mitsubishi Tanabe Pharma Corporation, Novo Nordisk A/S, Roche Diagnostics France, Sanofi. J.R. Petrie: Advisory Panel; Self; Novo Nordisk A/S. Consultant; Self; Novo Nordisk A/S. Research Support; Self; Itamar Medical Ltd., Merck KGaA. Other Relationship; Self; Applied Clinical Intelligence, LLC, Boehringer Ingelheim International GmbH, Diabetes UK, Quintiles. Funding JDRF (17-2011-272)

499-P: The Relative Roles of Pro-oxidant Enzymes Nox4 and Nox5 in Diabetic Kidney Disease

Background: Renal oxidative stress plays an important role in mediating kidney injury in diabetes. There is increasing evidences that recently discovered pro-oxidant enzyme, Nox5 plays a significant role in human diabetic kidney disease (DKD). We examined the role of Nox5 in human DKD, in human renal cell populations as well as in a high fat fed and alloxan rabbit model of DKD. In addition, we also examined the contribution of Nox5 in the in DKD in the absence of Nox4 expression using renal cell specific Nox5Tg mice. Results: Expression of Nox5 was increased in both glomerular and tubular compartments of kidney biopsies obtained from diabetic individuals. Nox5 is the Nox isoform which shows the highest upregulation in response to high glucose. Silencing of Nox5 reduces ROS formation and expression of proinflammatory and profibrotic cytokines and growth factors as well as putative elements that are implicated in DKD. Our data also suggest that Nox5 is upstream of Nox4 and that Nox5 inhibition downregulates Nox4, but not vice versa. High fat feeding and alloxan induced diabetes rabbits showed upregulation of Nox5 and increased ROS in association with increased mesangial area, ECM protein accumulation and upregulation of a range of pro-inflammatory (MCP-1) and pro-fibrotic genes (CTGF) as analysed by RNAseq and confirmed by RT-PCR. In addition, over expression of Nox5 in mesangial cells of Nox4 KO diabetic mice demonstrated 30% increase in albuminuria, mesangial expansion, increased renal injury and inflammation via enhanced ROS production. Conclusions: These studies will for the first time explore in a comprehensive manner the role of Nox5 in recently generated Nox5KO rabbit models in the context of type 1 and type 2 diabetes as well as delineate the relative role of Nox4 versus Nox5 in diabetic complications. These studies will provide evidence if Nox5 blockade alone or combined with Nox4/Nox5 blockade is the optimal approach to treat and prevent diabetic complications, in particular nephropathy. Disclosure J.C. Jha: None. M.E. Cooper: Advisory Panel; Self; AstraZeneca, Lilly Diabetes. Consultant; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Servier. Research Support; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Novo Nordisk A/S. Speaker's Bureau; Self; Bayer AG, Merck Sharp &amp; Dohme Corp., Novartis AG. C. Kennedy: Research Support; Self; Prometic Life Sciences Inc. K. Jandeleit-Dahm: Advisory Panel; Self; Australian Diabetes Society, Genkyotex. Consultant; Self; Metavention.

23-LB: Lipoprotein Subfractions Are Associated with Diabetic Cardiovascular Disease and Death among 9,795 Patients in the FIELD Trial

Background: The FIELD study, a 5-year randomized double-blind placebo-controlled trial of fenofibrate vs. placebo in 9,795 adults with type 2 diabetes (T2D), was designed to evaluate effects on coronary and cardiovascular (CV) events. In this analysis we explored associations between lipoprotein subfractions and on-study CV events and death. Methods: We performed ultracentrifugation using the vertical auto profile (VAP, Atherotech) on plasma at baseline and after 6 weeks of fenofibrate (active run-in) exposure. Analyses were performed using Cox proportional hazards and logistic regression analysis. Results were adjusted for gender, with log transformation as necessary. Results: Total CVD and CV death correlated negatively with HDL-C and its subfractions, as well as apoA1 and apoA2. In addition to LDL-C, small, dense LDL (LDL4-C), non-HDL-C, apo B, triglycerides, and apoC3 increased risk for total CVD. For CVD death, HDL-C and its subfractions were protective, while apo B, triglycerides, apo C3, and various VLDL-C species were associated with increased risk. Conclusions: Detailed lipoprotein analysis identifies multiple lipoprotein subclasses and apolipoproteins and their ratios associated with acute cardiovascular events and death. Serum levels of a number of these lipoprotein and apoprotein species were improved by fenofibrate therapy. Disclosure S.R. Jones: None. A.J. Jenkins: Advisory Panel; Self; Abbott, Australian Diabetes Society, Medtronic. Research Support; Self; Abbott, GlySens Incorporated, Medtronic, Mylan. Speaker’s Bureau; Self; Eli Lilly and Company, Novo Nordisk Inc. A.S. Januszewski: None. R.L. OConnell: None. L. Li: None. D. Sullivan: None. M. Taskinen: Advisory Panel; Self; Novo Nordisk A/S. Consultant; Self; Akcea Therapeutics, Chiesi USA, Inc. Research Support; Self; Amgen Inc., Novo Nordisk A/S. Speaker’s Bureau; Self; Amgen Inc. R. Scott: None. G.F. Watts: None. P.J. Barter: Advisory Panel; Self; Merck &amp; Co., Inc., Pfizer Inc. R. Simes: None. P.P. Toth: Consultant; Self; Amarin Corporation, Amgen Inc., AstraZeneca, Kowa Pharmaceutical Europe Co. Ltd., Novo Nordisk Inc. Speaker’s Bureau; Self; Amarin Corporation, Amgen Inc., Merck &amp; Co., Inc., Novo Nordisk Inc., Regeneron Pharmaceuticals, Sanofi US. A.C. Keech: None.