Associations between multimorbidity and glycaemia (HbA1c) in people with type 2 diabetes: cross-sectional study in Australian general practice

Objectives: To 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). Design: Cross-sectional study. Setting: Australian general practice. Participants: 69 718 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 measures: Prevalence of multimorbidity, individual and combinations of LTCs. Multivariable linear regression models used to examine associations between multimorbidity counts and HbA1c (%). Results: Mean (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. Conclusions: Multimorbidity 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

Multimorbidity, mortality, and HbA1c in type 2 diabetes: a cohort study with UK and Taiwanese cohorts

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 <0.001). HRs for NDCMP were similar to those from UK Biobank for all multimorbidity counts. For those with two conditions in addition to T2D, cardiovascular diseases featured in 18 of the top 20 combinations most highly associated with mortality in UK Biobank and 12 of the top combinations in the Taiwan NDCMP. In UK Biobank, a combination of coronary heart disease and heart failure in addition to T2D had the largest effect size on mortality, with a HR (95% CI) of 4.37 (3.59–5.32) p < 0.001, whereas in the Taiwan NDCMP, a combination of painful conditions and alcohol problems had the largest effect size on mortality, with an HR (95% CI) of 4.02 (3.08–5.23) p < 0.001. One limitation to note is that we were unable to model for changes in multimorbidity during our study period. Conclusions: Multimorbidity patterns associated with the highest mortality differed between UK Biobank (a population predominantly comprising people of European descent) and the Taiwan NDCMP, a predominantly ethnic Chinese population. Future research should explore the mechanisms underpinning the observed relationship between increasing multimorbidity count and reduced HbA1c alongside increased mortality in people with T2D and further examine the implications of different patterns of multimorbidity across different ethnic groups. Better understanding of these issues, especially effects of condition type, will enable more effective personalisation of care

Multimorbidity, glycaemic variability and time in target range in people with type 2 diabetes: a baseline analysis of the GP-OSMOTIC trial

Aims: 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). Methods: 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. Results: 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. Conclusions: 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

Socioeconomic status and time in glucose target range in people with type 2 diabetes: a baseline analysis of the GP-OSMOTIC study

Abstract Background Optimal glycaemia, reflected by glycated haemoglobin (HbA1c) levels, is key in reducing type 2 diabetes (T2D) complications. However, most people with T2D have suboptimal recall and understanding of HbA1c. Continuous glucose monitoring (CGM) measures glucose levels every 5 to 15-min over days and may be more readily understood. Given that T2D is more common in lower socioeconomic settings, we aim to study relationships between socioeconomic status (SES) and percentage time in glucose target range (TIR) which is a key metric calculated from CGM. Methods Analysis of baseline data from the General Practice Optimising Structured MOnitoring To Improve Clinical outcomes (GP-OSMOTIC) randomised controlled trial (October 2016 – November 2017) of 300 people with T2D from 25 Victorian General Practices. FreeStyle Libre Pro® sensor patch was used for this study. SES was defined by the Index of Relative Socio-economic Disadvantage (IRSD) and educational attainment. Univariable and multivariable mixed-effects linear regression analyses controlling for age, BMI, diet, exercise and study arm were performed. Results One hundred and sixty-seven (60.1%) participants were male, the mean (SD) participant age was 61.0 (9.7) years, and the mean (SD) duration of CGM use was 12.3 (2.5) days. The 10th IRSD decile (least disadvantaged) was associated with a 15% higher TIR vs. the 1st decile (most disadvantaged) (95% CI 5, 25; p = 0.003) and a 0.6% lower HbA1c (95% CI 0.1, 1; p = 0.03). There was no evidence of an association between educational attainment and TIR/HbA1c. Conclusion Higher SES measured at an area level is associated with better achievement of glycaemic target using complementary measures of HbA1c and TIR in the GP-OSMOTIC cohort. Given that TIR may be more easily used in patient education and self-management support compared to HbA1c values, the social gradient identified in TIR provides an opportunity for clinicians and policy makers to address health inequities in T2D. Trial registration Australian and New Zealand Clinical Trials Registry Trial ACTRN12616001372471, prospective, Date registered 4/10/2016

Prescribing of diabetes medications to people with type 2 diabetes and chronic kidney disease: a national cross-sectional study

Abstract Background Previous studies in general practice and hospital settings have identified that prescribing of non-insulin diabetes medications may be sub-optimal in people with type 2 diabetes (T2D) and renal impairment. Since these publications, a number of new medications have become available for the management of T2D. Study aims were to, in a cohort of Australians with T2D and renal impairment attending general practice, (1) investigate whether the prescribing of non-insulin diabetes medications is consistent with dosing adjustments recommended within current Australian Diabetes Society (ADS) guidelines; and (2) identify patient socio-demographic and clinical factors associated with at least one prescription of a non-insulin diabetes medication inconsistent with current ADS guidelines for medication doses. Methods Cross-sectional study using data from the MedicineInsight general practice database managed by NPS MedicineWise. Patients with T2D who were aged 18 years and over, with an average eGFR< 60 ml/min/1.73m2 and at least one prescription of a non-insulin diabetes medication between 1st January 2015 and 30th June 2017 were included. Descriptive statistics were used to summarise patient characteristics and medication use. Marginal logistic regression models were used to estimate associations between sociodemographic and clinical factors and prescribing of ≥1non-insulin diabetes medicine not consistent with ADS guidelines. Results The majority of the 3505 patients included (90.4%) had an average eGFR of 30-59 ml/min/1.73m2. In terms of absolute numbers, metformin was the medication most frequently prescribed at a dose not consistent with current ADS guidelines for dosing in renal impairment (n = 1601 patients), followed by DPP4 inhibitors (n = 611) and sulphonylureas (n = 278). The drug classes with the highest proportion of prescriptions with dosage not consistent with ADS guidelines were SGLT2 inhibitors (83%), followed by biguanides (58%) and DPP4 inhibitors (46%). Higher HbA1c, longer known diabetes duration and diagnosis of retinopathy were associated with receiving ≥1prescription with a dosage not consistent with guidelines. Conclusions Prescribing of non-insulin diabetes medications at doses inconsistent with current ADS guideline recommendations for dosing adjustments for people with renal impairment was common. Further research is needed to understand how general practitioners access, interpret and apply the ADS guidelines and the impact this may have on patient outcomes

Prescribing of diabetes medications to people with type 2 diabetes and chronic kidney disease: a national cross-sectional study

Abstract Background Previous studies in general practice and hospital settings have identified that prescribing of non-insulin diabetes medications may be sub-optimal in people with type 2 diabetes (T2D) and renal impairment. Since these publications, a number of new medications have become available for the management of T2D. Study aims were to, in a cohort of Australians with T2D and renal impairment attending general practice, (1) investigate whether the prescribing of non-insulin diabetes medications is consistent with dosing adjustments recommended within current Australian Diabetes Society (ADS) guidelines; and (2) identify patient socio-demographic and clinical factors associated with at least one prescription of a non-insulin diabetes medication inconsistent with current ADS guidelines for medication doses. Methods Cross-sectional study using data from the MedicineInsight general practice database managed by NPS MedicineWise. Patients with T2D who were aged 18 years and over, with an average eGFR< 60 ml/min/1.73m2 and at least one prescription of a non-insulin diabetes medication between 1st January 2015 and 30th June 2017 were included. Descriptive statistics were used to summarise patient characteristics and medication use. Marginal logistic regression models were used to estimate associations between sociodemographic and clinical factors and prescribing of ≥1non-insulin diabetes medicine not consistent with ADS guidelines. Results The majority of the 3505 patients included (90.4%) had an average eGFR of 30-59 ml/min/1.73m2. In terms of absolute numbers, metformin was the medication most frequently prescribed at a dose not consistent with current ADS guidelines for dosing in renal impairment (n = 1601 patients), followed by DPP4 inhibitors (n = 611) and sulphonylureas (n = 278). The drug classes with the highest proportion of prescriptions with dosage not consistent with ADS guidelines were SGLT2 inhibitors (83%), followed by biguanides (58%) and DPP4 inhibitors (46%). Higher HbA1c, longer known diabetes duration and diagnosis of retinopathy were associated with receiving ≥1prescription with a dosage not consistent with guidelines. Conclusions Prescribing of non-insulin diabetes medications at doses inconsistent with current ADS guideline recommendations for dosing adjustments for people with renal impairment was common. Further research is needed to understand how general practitioners access, interpret and apply the ADS guidelines and the impact this may have on patient outcomes

Assessing the suitability of general practice electronic health records for clinical prediction model development: a data quality assessment

Abstract Background The use of general practice electronic health records (EHRs) for research purposes is in its infancy in Australia. Given these data were collected for clinical purposes, questions remain around data quality and whether these data are suitable for use in prediction model development. In this study we assess the quality of data recorded in 201,462 patient EHRs from 483 Australian general practices to determine its usefulness in the development of a clinical prediction model for total knee replacement (TKR) surgery in patients with osteoarthritis (OA). Methods Variables to be used in model development were assessed for completeness and plausibility. Accuracy for the outcome and competing risk were assessed through record level linkage with two gold standard national registries, Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR) and National Death Index (NDI). The validity of the EHR data was tested using participant characteristics from the 2014–15 Australian National Health Survey (NHS). Results There were substantial missing data for body mass index and weight gain between early adulthood and middle age. TKR and death were recorded with good accuracy, however, year of TKR, year of death and side of TKR were poorly recorded. Patient characteristics recorded in the EHR were comparable to participant characteristics from the NHS, except for OA medication and metastatic solid tumour. Conclusions In this study, data relating to the outcome, competing risk and two predictors were unfit for prediction model development. This study highlights the need for more accurate and complete recording of patient data within EHRs if these data are to be used to develop clinical prediction models. Data linkage with other gold standard data sets/registries may in the meantime help overcome some of the current data quality challenges in general practice EHRs when developing prediction models

Screening and diagnosis of chronic kidney disease in people with type 2 diabetes attending Australian general practice

Australian guidelines recommend annual screening and monitoring of chronic kidney disease (CKD) in people with type 2 diabetes (T2D). A cross-sectional study utilising data from NPS MedicineWise MedicineInsight program from June 2015 to May 2016 was undertaken to explore: (1) the proportion of patients with T2D attending general practice who have had screening for, or ongoing monitoring of, CKD; (2) the proportion of patients without a documented diagnosis of CKD who have pathology consistent with CKD diagnosis; and (3) the patient factors associated with screening and the recording of a diagnosis of CKD. Of 90 550 patients with T2D, 44 394 (49.0%) were appropriately screened or monitored. There were 8030 (8.9%) patients with a recorded diagnosis of CKD, whereas 6597 (7.3%) patients had no recorded diagnosis of CKD despite pathology consistent with a diagnosis. Older age and diagnosis of hypertension or hyperlipidaemia were associated with increased odds of CKD diagnosis being recorded. Older patients, males, those with recorded diagnoses of hypertension or hyperlipidaemia and those who had their medical record opened more frequently were more likely to be screened appropriately. Screening and monitoring of CKD appears suboptimal. Research to explore barriers to screening, recording and monitoring of CKD, and strategies to address these, is required

Prescribing for people with type 2 diabetes and renal impairment in Australian general practice : a national cross sectional study

Aim: To determine whether the prescribing of non-insulin anti-hyperglycaemic medications in Australian general practice is consistent with current guidelines for treatment of type 2 diabetes (T2D) in people with renal impairment. Methods: Cross-sectional study of 9624 people with T2D in the NPS MedicineInsight dataset aged ≥18 years with average estimated glomerular filtration rate (eGFR) <60ml/min/1.73m2 and prescribed at least one non-insulin anti-hyperglycaemic medication from October 2014 to September 2015. The primary outcome was the proportion of non-insulin anti-hyperglycaemic medications prescribed at doses inconsistent with current guidelines. Results: 4650 (48.3%) patients were prescribed at least one non-insulin anti-hyperglycaemic medication at a dose inconsistent with Australian Diabetes Society guidelines. The majority (88.0%) had an average eGFR of 30–59ml/min/1.73m2. Metformin was the most frequently prescribed agent (n= 7408; 77.0%), and was prescribed at a dose inconsistent with guidelines for 52% of patients. 123/136 (90.5%) people prescribed a sodium glucose co-transporter 2 inhibitor and 1114/2194 (50.8%) prescribed a dipeptidyl peptidase-4 inhibitor were prescribed a dose inconsistent with guidelines. Decreasing age, being male or being on insulin was associated with greater odds of at least one prescription inconsistent with guidelines