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Aim Diabetes is a primary cause of hospitalization and in-hospital mortality. However, studies exploring the relationships between body mass index (BMI) and hospitalization-related and mortality-related outcomes in patients with type 2 diabetes are lacking. Methods Our data were obtained from two independent retrospective cohort studies, namely, the Taiwan Diabetes Study (Taiwan DS), providing hospitalization outcome measures, and the Taichung Diabetes Study (Taichung DS) that can be linked with the National Death Registry dataset. BMI and hospitalization, in-hospital mortality, and all-cause and cause-specific death events were analyzed by Cox proportional hazard regression model. Results A total of 3,541, 38,779, and 10,399 patients died during hospitalization, hospitalized for all-cause and diabetes-related events, respectively, in the Taiwan DS cohort. Moreover, 685 deaths were identified in the Taichung DS cohort. Compared with patients with increasing-but-acceptable-risk obesity, multivariable-adjusted hazard ratios (HRs) of in-hospital mortality, all-cause hospitalization, hospitalization due to diabetes, hypoglycaemia, and renal failure for patients who were underweight were 2.09 (95% confidence interval 1.73, 2.51), 1.39 (1.28, 1.50), 1.69 (1.49, 1.90), 1.87 (1.34, 2.61), and 1.55 (1.26, 1.91). Adjusted HRs of all-cause mortality and non-expanded CVD-related mortality in patients with underweight were 2.02 (1.28, 3.21), and 2.27 (1.28, 4.03). Conclusions The BMI associated with the best survival and less hospitalization was the higher-high-risk obesity (≥ 27.5 kg/m2) category. We observed obesity paradox for mortality outcomes, which should be addressed by further research, particularly on whether randomized controlled trials of adopting a healthy lifestyle for patients with obesity can improve type 2 diabetes patients’ survival. more...

ObjectivesTo explore the prevalence of multimorbidity as well as individual and combinations of long-term conditions (LTCs) in people with type 2 diabetes (T2D) attending Australian general practice, using electronic health record (EHR) data. We also examine the association between multimorbidity condition count (total/concordant(T2D related)/discordant(unrelated)) and glycaemia (glycated haemoglobin, HbA1c).DesignCross-sectional study.SettingAustralian general practice.Participants69 718 people with T2D with a general practice encounter between 2013 and 2015 captured in the MedicineInsight database (EHR Data from 557 general practices and >3.8 million Australian patients).Primary and secondary outcome measuresPrevalence of multimorbidity, individual and combinations of LTCs. Multivariable linear regression models used to examine associations between multimorbidity counts and HbA1c (%).ResultsMean (SD) age 66.42 (12.70) years, 46.1% female and mean (SD) HbA1c 7.1 (1.4)%. More than 90% of participants with T2D were living with multimorbidity. Discordant conditions were more prevalent (83.4%) than concordant conditions (69.9 %). The three most prevalent discordant conditions were: painful conditions (55.4%), dyspepsia (31.6%) and depression (22.8%). The three most prevalent concordant conditions were hypertension (61.4%), coronary heart disease (17.1%) and chronic kidney disease (8.5%). The three most common combinations of conditions were: painful conditions and hypertension (38.8%), painful conditions and dyspepsia (23.1%) and hypertension and dyspepsia (22.7%). We found no associations between any multimorbidity counts (total, concordant and discordant) or combinations and HbA1c.ConclusionsMultimorbidity was common in our cohort of people with T2D attending Australian general practice, but was not associated with glycaemia. Although we did not explore mortality in this study, our results suggest that the increased mortality in those with multimorbidity and T2D observed in other studies may not be linked to glycaemia. Interestingly, discordant conditions were more prevalent than concordant conditions with painful conditions being the second most common comorbidity. Better understanding of the implications of different patterns of multimorbidity in people with T2D will allow more effective tailored care. more...

Background There is emerging interest in multimorbidity in type 2 diabetes (T2D), which can be either concordant (T2D related) or discordant (unrelated), as a way of understanding the burden of disease in T2D. Current diabetes guidelines acknowledge the complex nature of multimorbidity, the management of which should be based on the patient’s individual clinical needs and comorbidities. However, although associations between multimorbidity, glycated haemoglobin (HbA1c), and mortality in people with T2D have been studied to some extent, significant gaps remain, particularly regarding different patterns of multimorbidity, including concordant and discordant conditions. This study explores associations between multimorbidity (total condition counts/concordant/discordant/different combinations of conditions), baseline HbA1c, and all-cause mortality in T2D. Methods and findings We studied two longitudinal cohorts of people with T2D using the UK Biobank (n = 20,569) and the Taiwan National Diabetes Care Management Program (NDCMP) (n = 59,657). The number of conditions in addition to T2D was used to quantify total multimorbidity, concordant, and discordant counts, and the effects of different combinations of conditions were also studied. Outcomes of interest were baseline HbA1c and all-cause mortality. For the UK Biobank and Taiwan NDCMP, mean (SD) ages were 60.2 (6.8) years and 60.8 (11.3) years; 7,579 (36.8%) and 31,339 (52.5%) were female; body mass index (BMI) medians (IQR) were 30.8 (27.7, 34.8) kg/m2 and 25.6 (23.5, 28.7) kg/m2; and 2,197 (10.8%) and 9,423 (15.8) were current smokers, respectively. Increasing total and discordant multimorbidity counts were associated with lower HbA1c and increased mortality in both datasets. In Taiwan NDCMP, for those with four or more additional conditions compared with T2D only, the mean difference (95% CI) in HbA1c was −0.82% (−0.88, −0.76) p < 0.001. In UK Biobank, hazard ratios (HRs) (95% CI) for all-cause mortality in people with T2D and one, two, three, and four or more additional conditions compared with those without comorbidity were 1.20 (0.91–1.56) p < 0.001, 1.75 (1.35–2.27) p < 0.001, 2.17 (1.67–2.81) p < 0.001, and 3.14 (2.43–4.03) p < 0.001, respectively. Both concordant/discordant conditions were significantly associated with mortality; however, HRs were largest for concordant conditions. Those with four or more concordant conditions had >5 times the mortality (5.83 [4.28–7.93] p, Jason Chiang and colleagues reveal the relationship between multimorbidity, HbA1c and all-cause mortality in 2 large cohorts., Author summary Why was this study done? People with type 2 diabetes (T2D) commonly have other coexisting chronic medical conditions (‘multimorbidity’). These conditions can be either concordant (T2D related) or discordant (T2D unrelated). Multimorbidity is associated with higher mortality and hypoglycaemia; however, the effect of multimorbidity on glycaemia (measured by glycated haemoglobin [HbA1c]) is mixed. Significant knowledge gaps remain, particularly regarding the prevalence and impacts of different patterns of multimorbidity, including concordant and discordant conditions, and their associations with HbA1c and mortality. What did the researchers do and find? We assessed the associations between different counts of multimorbidity, including concordant and discordant conditions, and HbA1c and the effects of different combinations of conditions on all-cause mortality in people with T2D. In two large community cohorts of people with T2D (UK Biobank and Taiwan National Diabetes Care Management Program [NDCMP]), we found that increasing multimorbidity is significantly associated with increased mortality and with lower HbA1c. The combinations of conditions with the greatest association with mortality differed between UK Biobank, a population predominantly comprising people of European descent, and the Taiwan NDCMP, a predominantly ethnic Chinese population. What do these findings mean? To our knowledge, this is the first study to assess and compare the relationship between total, concordant, and discordant multimorbidity counts; HbA1c; and all-cause mortality in people with T2D or to look at the effects of such a range of combinations of comorbid conditions. Our findings suggest the need for further research to explore the effects of different combinations of conditions on outcomes in those with T2D across different ethnic groups. Our findings suggest that poor glycaemic control is unlikely to explain the increased mortality seen in those with increasing multimorbidity count. more...

Introduction: The emerging interest in multimorbidity (MM) in people with type 2 diabetes (T2D), which can be concordant (T2D-related) or discordant (unrelated), suggests the need to understand the burden of MM in T2D, and its association with all-cause mortality. We explored associations between MM conditions counts (total, concordant and discordant) and all-cause mortality in people with T2D in the UK Biobank. Methods: We examined data from a longitudinal cohort of 20,569 people with T2D in the UK Biobank recruited between 2006-2010. The number of MM conditions in addition to T2D was the primary independent variable based on self-report and hospital admissions data. All-cause mortality was the primary outcome. Multivariable Cox proportional hazard regression was used to examine associations between each of the MM counts and mortality. Results: A significant association between increasing MM and mortality was found. Compared to those with T2D with no additional chronic conditions, having 1, 2, 3 and 4+ conditions in addition to T2D, the HRs (95% CI) for all-cause mortality were 1.23 (0.90-1.68), 1.84 (1.36-2.49), 1.91 (1.40-2.60), and 3.13 (2.33-4.20), respectively. Both concordant and discordant conditions were significantly associated with mortality. For 1, 2, 3 and 4+ concordant conditions in addition to T2D, the HRs (95% CI) were 1.23 (1.04-1.48), 1.76 (1.46-2.13), 2.78 (2.22-3.48), and 4.25 (3.23-5.59), respectively and for discordant conditions 1.32 (1.13-1.55), 1.46 (1.23-1.74), 1.77 (1.45-2.17), and 2.44 (2.01-2.99), respectively. Conclusions: The association between MM and mortality is significant for total, concordant and discordant condition count, but was strongest for concordant. Our findings emphasize the need for clinical guidelines and future MM measures to consider MM in people with T2D, both concordant and discordant. Disclosure J.I. Chiang: None. P. Hanlon: None. B.D. Jani: None. 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. J. Furler: Research Support; Self; Abbott, Sanofi. B.I. Nicholl: None. F.S. Mair: None. more...

Introduction: Multimorbidity (MM) is common in people with T2D (PwT2D) who in Australia, receive medical care predominantly in family practice (FP). We explored the association between MM condition count and HbA1c in PwT2D attending Australian FP, using electronic health record (EHR) data. Methods: Cross-sectional study of 69,718 PwT2D who had a FP encounter between 2013-15 captured in the NPS MedicineInsight dataset (EHR data from >500 family practices and 3.5 million patients across Australia). MM condition count was based on coded and free text conditions in the reason for visit, prescription or medical history fields. Primary outcome: HbA1c. Multivariable mixed-effects linear regression examined associations between MM counts (total, concordant (T2D-related) and discordant (unrelated)) and HbA1c (%). Results: We found statistically significant associations between HbA1c and total and discordant MM counts. Mean HbA1c (95% CI) was lower for those having 1, 2, 3 and 4+ total conditions compared to T2D only, -0.065 (-0.089, -0.041), -0.097 (-0.128, -0.066), -0.089 (-0.133, -0.046), and -0.097 (-0.146, -0.047) respectively, and for discordant conditions -0.085 (-0.108, -0.061), -0.100 (-0.134, -0.065), -0.141 (-0.195, -0.087), and -0.204 (-0.276, -0.133). There was no statistically significant association between HbA1c and increasing concordant count. Conclusions: While EHR counts of MM and discordant conditions are associated with lower HbA1c, this is not likely to be clinically significant, suggesting the impact of MM on HbA1c remains unclear. The NPS dataset uses routine data entered by clinicians for the purpose of patient care, rather than epidemiological studies and may thus underestimate the number of conditions experienced by PwT2D. While clinicians need to consider the MM burden of PwT2D, the NPS MedicineInsight dataset needs further validation, eg through combining with other data sources, in the study of MM. Disclosure J.I. Chiang: None. J. Furler: Research Support; Self; Abbott, Sanofi. B.D. Jani: None. F.S. Mair: None. S. Thuraisingam: None. B.I. Nicholl: None. 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. Funding Royal Australian College of General Practitioners more...

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 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 & Dohme Corp., Novo Nordisk A/S, Sanofi. Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Merck Sharp & 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 & 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 & 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 & 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 more...

We investigated the association between fasting plasma glucose variability (FPG-CV) and the risk of hip fracture in elderly diabetic patients. Our finding showed a temporal association between FPG-CV and hip fracture as patients categorized as FPG-CV greater than 25.4 % showed an increased risk in hip fractures. Hip fracture is a major health burden in the population and is associated with high rates of mortality and morbidity especially in elderly. It is evident that diabetes mellitus is a risk factor of osteoporosis which is a significant risk factor of hip fracture. However, epidemiological studies exploring the risks of hip fracture among type 2 diabetic patients are limited. A retrospective study of 26,501 ethnic Chinese older persons enrolled in the National Diabetes Care Management program in Taiwan was conducted; related factors were analyzed with extended Cox proportional hazards regression models to competing risk data on hip fracture incidence. The results show a temporal association between FPG-CV and hip fracture as patients categorized as FPG-CV greater than 25.4 % showed an increased risk in hip fractures, confirming a linear relationship between the two. After multivariate adjustment, the risk of hip fracture increased among patients with FPG-CV of 25.4–42.3 % and >42.3 % compared with patients with FPG-CV of ≦ 14.3 % (hazard ratio, 1.35; 95 % confidence interval 1.14–1.60 and 1.27; 1.07–1.52, respectively). Significant linear trends among various FPG-CV were observed. Thus, the present study demonstrated the importance of glucose stability for fracture prevention in older persons with type 2 diabetes. Future studies should be conducted to explore whether reduction in glucose oscillation in older adults with diabetes mellitus can reduce the risk of hip fracture. more...

Aims: \ud To explore associations between multimorbidity condition counts (total; concordant (diabetes-related); discordant (unrelated to diabetes)) and glycaemia (HbA1c; glycaemic variability (GV); time in range (TIR)) using data from a randomised controlled trial examining effectiveness of continuous glucose monitoring (CGM) in people with type 2 diabetes (T2D).\ud \ud Methods: \ud Cross-sectional study: 279 people with T2D using baseline data from the General Practice Optimising Structured MOnitoring To Improve Clinical outcomes (GP-OSMOTIC) trial from 25 general practices in Australia. Number of long-term conditions (LTCs) in addition to T2D used to quantify total/concordant/discordant multimorbidity counts. GV (measured by coefficient of variation (CV)) and TIR derived from CGM data. Multivariable linear regression models used to examine associations between multimorbidity counts, HbA1c (%), GV and TIR.\ud \ud Results: \ud Mean (SD) age of participants 60.4 (9.9) years; 40.9% female. Multimorbidity was present in 89.2% of participants. Most prevalent comorbid LTCs: hypertension (57.4%), painful conditions (29.8%), coronary heart disease (22.6%) and depression (19.0%). No evidence of associations between multimorbidity counts, HbA1c, GV and TIR.\ud \ud Conclusions: \ud While multimorbidity was common in this T2D cohort, it was not associated with HbA1c, CV or TIR. Future studies should explore factors other than glycaemia that contribute to the increased mortality observed in those with multimorbidity and T2D. more...

Background General Practice Optimising Structured Monitoring to Improve Clinical Outcomes in Type 2 Diabetes (GP-OSMOTIC) is a multicentre, individually randomised controlled trial aiming to compare the use of intermittent retrospective continuous glucose monitoring (r-CGM) to usual care in patients with type 2 diabetes attending general practice. The study protocol was published in the British Medical Journal Open and described the principal features of the statistical methods that will be used to analyse the trial data. This paper provides greater detail on the statistical analysis plan, including background and justification for the statistical methods chosen, in accordance with SPIRIT guidelines. Objective To describe in detail the data management process and statistical methods that will be used to analyse the trial data. Methods An overview of the trial design and primary and secondary research questions are provided. Sample size assumptions and calculations are explained, and randomisation and data management processes are described in detail. The planned statistical analyses for primary and secondary outcomes and sub-group analyses are specified along with the intended table layouts for presentation of the results. Conclusion In accordance with best practice, all analyses outlined in the document are based on the aims of the study and have been pre-specified prior to the completion of data collection and outcome analyses. Trial registration Australian New Zealand Clinical Trials Registry, ACTRN12616001372471. Registered on 3 August 2016. more...

Introduction Type 2 diabetes (T2D) is a leading health priority worldwide. Multimorbidity (MM) is a term describing the co-occurrence of two or more chronic diseases or conditions. The majority of people living with T2D have MM. The relationship between MM and mortality and glycaemia in people with T2D is not clear. Methods and analysis Medline, Embase, Cumulative Index of Nursing and Allied Health Complete, The Cochrane Library, and SCOPUS will be searched with a prespecified search strategy. The searches will be limited to quantitative empirical studies in English with no restriction on publication date. One reviewer will perform title screening and two review authors will independently screen the abstract and full texts using Covidence software, with disagreements adjudicated by a third reviewer. Data will be extracted using a using a Population, Exposure, Comparator and Outcomes framework. Two reviewers will independently extract data and undertake the risk of bias (quality) assessment. Disagreements will be resolved by consensus. A narrative synthesis of the results will be conducted and meta-analysis considered if appropriate. Quality appraisal will be undertaken using the Newcastle-Ottawa quality assessment scale and the quality of the cumulative evidence of the included studies will be assessed using the Grading of Recommendations, Assessment, Development and Evaluation approach. This protocol was prepared in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols guidelines to ensure the quality of our review. Ethics and dissemination This review will synthesise the existing evidence about the impact of MM on mortality and glycaemic outcomes in people living with T2D and increase our understanding of this subject and will inform future practice and policy. Findings will be disseminated via conference presentations, social media and peer-reviewed publication. PROSPERO registration number CRD42017079500. more...

Background & Aims Most colorectal cancers (CRC) arise from colorectal adenomas, yet there is not enough information on global prevalence to inform health care policy. We examined the prevalence of any type of adenomas, advanced adenomas (AADs), and CRC according to age, sex, ethnicity, geographic regions, and anatomic location (proximal vs distal). Methods MEDLINE and Embase were searched from their inception through May 1, 2018, to identify population-based, observational studies that reported the prevalence of colorectal neoplasia. Studies on participants 15 years or older, with a sample size of 500 persons or more, were included. Metaprop (College Station, TX) was used to model within-study variability by binomial distribution and Freeman–Tukey Double Arcsine Transformation to stabilize the variances. The prevalence figures were presented by proportions and their 95% CIs using random-effects models. Results Our meta-analysis included 70 studies involving 637,414 individuals. The overall prevalence rates of adenoma (23.9%; 95% CI, 22.2%–25.8%), AAD (4.6%; 95% CI, 3.8%–5.5%), and CRC (0.4%, 95% CI, 0.3%–0.5%) were calculated. Subgroup analysis indicated that prevalence values (adenomas, AADs, and CRCs) were higher among men (29.7%, 6.5%, and 0.8%, respectively) than women (19.3%, 3.8% and 0.4%, respectively), among older adults (25.9%, 5.2%, and 0.6%, respectively) than younger adults (14.6%, 1.6%, and 0.1%, respectively), among Caucasians (23.7%, 6.6%, and 0.5%, respectively) than other ethnicities, in European countries (25.9%, 8.4%, and 0.8%, respectively) than other countries, and among patients with proximal (25.9%, 5.3%, and 0.1%, respectively) vs distal neoplasia. Conclusions In a systematic review and meta-analysis, we found a high prevalence of colorectal neoplasia among some populations. This indicates a need to expand CRC screening programs for these groups. The pooled prevalence estimates can be used as quality indicators for established CRC screening programs. more...

IntroductionOptimal glycaemia can reduce type 2 diabetes (T2D) complications. Observing retrospective continuous glucose monitoring (r-CGM) patterns may prompt therapeutic changes but evidence for r-CGM use in T2D is limited. We describe the protocol for a randomised controlled trial (RCT) examining intermittent r-CGM use (up to 14 days every three months) in T2D in general practice (GP).Methods and analysisGeneral Practice Optimising Structured MOnitoring To achieve Improved Clinical Outcomes is a two-arm RCT asking ‘does intermittent r-CGM in adults with T2D in primary care improve HbA1c?’Primary outcomeAbsolute difference in mean HbA1c at 12 months follow-up between intervention and control arms. Secondary outcomes: (a) r-CGM per cent time in target (4–10 mmol/L) range, at baseline and 12 months; (b) diabetes-specific distress (Problem Areas in Diabetes).EligibilityAged 18–80 years, T2D for ≥1 year, a (past month) HbA1c>5.5 mmol/mol (0.5%) above their individualised target while prescribed at least two non-insulin hypoglycaemic therapies and/or insulin (therapy stable for the last four months). Our general glycaemic target is 53 mmol/mol (7%) (patients with a history of severe hypoglycaemia or a recorded diagnosis of hypoglycaemia unawareness will have a target of 64 mmol/mol (8%)).Our trial compares r-CGM use and usual care. The r-CGM report summarising daily glucose patterns will be reviewed by GP and patient and inform treatment decisions. Participants in both arms are provided with 1 hour education by a specialist diabetes nurse.The sample (n=150/arm) has 80% power to detect a mean HbA1c difference of 5.5 mmol/mol (0.5%) with an SD of 14.2 (1.3%) and alpha of 0.05 (allowing for 10% clinic and 20% patient attrition).Ethics and disseminationUniversity of Melbourne Human Ethics Sub-Committee (ID 1647151.1). Dissemination will be in peer-reviewed journals, conferences and a plain-language summary for participants.Trial registration number>ACTRN12616001372471; Pre-results. more...