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Microvascular Disease and Risk of Cardiovascular Events Among Individuals With Type 2 Diabetes: a Population-Level Cohort StudyBrownrigg JRW, MRCS1, Hughes CO, MRCS2, Burleigh D, MSc3, Karthikesalingam A, PhD1, Patterson BO, PhD1, Holt PJ, PhD1, Thompson MM, MD1, de Lusignan S, MD3, Ray KK, MD, MPhil 4*, Hinchliffe RJ, MD1*Division of Cardiovascular and Cell Sciences, St George’s University of London, London, UKDivision of Surgery and Interventional Science, University College London, London, UKDepartment of Healthcare Management and Policy, University of Surrey, Guildford, UKDepartment of Primary Care and Public Health, Imperial College London, London, UK*KKR and RJH contributed equally to this study.Word count:4206Corresponding author:Jack RW BrownriggDivision of Cardiovascular and Cell SciencesSt George’s University of LondonCranmer TerraceLondonSW17 OQTjrwbrownrigg@ABSTRACTBackgroundDiabetes confers a 2-fold excess risk of cardiovascular disease (CVD), yet predicting individual risk remains challenging. The effect of total microvascular disease burden on CVD risk among individuals with diabetes is unknown. Methods A population-based cohort of patients with type 2 diabetes from the UK Clinical Practice Research Datalink was studied (n=49 027). We used multivariable Cox models to estimate hazard ratios for the primary outcome (cardiovascular death, non-fatal myocardial infarction or non-fatal ischaemic stroke) associated with cumulative burden of retinopathy, nephropathy and peripheral neuropathy among individuals with no history of cardiovascular disease at baseline. FindingsDuring a median follow-up of 5·5 years, 2822 (5·8%) individuals experienced a primary outcome. Significant associations were observed for the primary outcome individually for retinopathy, peripheral neuropathy, and nephropathy after adjustment for established risk factors. The hazard ratios (with 95% confidence intervals) were 1·39 (1·09-1·76), 1·40 (1·19-1·66), and 1·35 (1·15-1·58), respectively. For individuals with one, two or three microvascular disease states versus none, the multivariable-adjusted hazard ratios for the primary outcome were 1·32 (1·16-1·50), 1·62 (1·42-1·85) and 1.99 (1·70-2.34), respectively. Similar trends were observed for cardiovascular death, all cause mortality and for hospitalisation for heart failure. For the primary outcome, measures of risk discrimination showed significant improvement when microvascular disease burden was added to models. In the overall cohort, the net reclassification index for US and UK guideline risk strata were 3.6% (p<0.001) and 3.8% (p<0.001), respectively. InterpretationThe cumulative burden of microvascular disease significantly impacts the risk of future cardiovascular disease among individuals with type 2 diabetes. Given the prevalence of diabetes globally, further work to understand the mechanisms behind this association and strategies to mitigate this excess risk are warranted. FundingCirculation FoundationRESEARCH IN CONTEXTEvidence before this studyWe searched Medline and EMBASE for studies published from Jan 1, 2000, to Nov 1, 2015, with the terms “microvascular disease”, “cardiovascular disease”, “type 2 diabetes”, and MeSH equivalents. The search period was selected to reflect contemporaneous data immediately before, and following the introduction of routine screening for microvascular disease in 2004 for the UK Quality and Outcomes Framework. We reviewed observational studies and clinical trials examining the association between microvascular disease and cardiovascular outcomes in ≥200 individuals. We identified 19 studies reporting positive associations between retinopathy or nephropathy and cardiovascular disease, coronary events, ischaemic stroke, and heart failure. More limited data also support a positive association between neuropathy (cardiac autonomic neuropathy or peripheral neuropathy) and cardiovascular disease outcomes. A single study in a Chinese cohort evaluated the impact of disease in two microvascular beds, with reported hazard ratios of 1.69 (95% CI 0.99-2.89) for retinopathy alone and 2.25 (95% CI 1.40-3.63) with concomitant microalbuminuria. Although some good quality studies were identified, all were limited in their scope by either small sample size with individual studies reporting on fewer than 630 events each, by the inclusion of individuals with pre-existing cardiovascular disease, selection bias, or lack of adjustment for conventional risk factors and for the presence of disease in multiple microvascular beds.Added value of this studyBased on a detailed review of the literature, this study is the first to examine the effect of disease in multiple microvascular beds in a large population cohort, with approximately 260 000 person years of exposure and 2822 first cardiovascular events. Our data reveal several important findings. The presence of isolated retinopathy, peripheral neuropathy, or nephropathy, independent of conventional risk factors, confer at least a similar risk of cardiovascular events (cardiovascular death, non-fatal myocardial infarction or non-fatal ischaemic stroke) as uncontrolled established risk factors including blood pressure (≥140/90 mmHg), HbA1c (≥7.0%) and low-density cholesterol (≥ 2.5 mmol/L). Individuals with disease in multiple microvascular beds were, in a “dose dependent fashion”, at the greatest overall risk, including for other endpoints such as hospitalisation for heart failure, cardiovascular death and all-cause mortality. Implications of the available evidenceThese data suggest that a continued broad assessment program for microvascular complications of diabetes has prognostic value for routine clinical care globally as it further risk stratifies people at higher cardiovascular risk than might be perceived, as well as providing morbidity specific to individual microvascular disease states. The inclusion of microvascular disease variables in cardiovascular risk algorithms resulted in a net correct reclassification of 3.6% of our cohort into higher- or lower-risk strata based on incident events. which is comparable if not slightly better than blood based biomarkers, but less than improvement observed with coronary artery calcium scoring. If information on microvascular disease were incorporated presently then 9·3% of individuals previously considered as eligible for moderate intensity statins in US guidance (predicted risk <7.5%) would be considered as candidates for high intensity statin therapy (observed risk 8·6%). Similarly, microvascular disease would reclassify 9·0% of individuals in a higher risk group (predicted risk ≥7.5%), currently considered eligible for high intensity statins, to a group who could be offered moderate intensity therapy (observed risk 6·3%). In reference to UK NICE guidance, of those currently considered ineligible for statin therapy (predicted risk <10%), 8·9% would be reclassified into a higher risk group with an observed event rate of 11·6%. Of individuals currently offered statin therapy (predicted risk ≥10%), 12·3% would be reclassified into a lower risk group with an observed 10-year event rate of 8·1%. Based on the current known prevalence of risk, in absolute terms this would represent a change in statin prescriptions for 10·6% of individuals with type 2 diabetes in the UK and 9·1% of those in the US, with accurate reclassification in 59·5% and 65·7%, respectively. As the assessment of microvascular disease should be part of routine clinical practice among those with diabetes, our findings offer a simple, convenient and cheap method for improving risk prediction as compared to more expensive blood based biomarkers or non-invasive imaging modalities for better targeting preventive therapies. It might be possible to mitigate against this excess risk, as we observed that among those with multiple microvascular disease states, event rates were substantially lower when HbA1c, BP and LDL-C were better controlled. High microvascular disease burden could be used as a criteria to enrich future clinical outcome trials, identifying a very high risk cohort of patients who might derive greater absolute benefit from more intensive risk factor control with conventional or novel therapies. Finally, our observations should enthuse further research including a better understanding of the impact of microvascular disease with different cardiovascular outcomes.INTRODUCTIONDiabetes confers a 2-fold excess risk of cardiovascular disease1 and substantial premature mortality from cardiovascular causes.2 However, individuals with diabetes are not automatically considered as a coronary heart disease (CHD) risk equivalent and many guidelines now recommend absolute risk assessment prior to considering lipid modification therapy.3 Predicting individual risk remains challenging and external validation of available risk algorithms in diabetic populations show moderate performance at best,4 highlighting the need for cheap and routinely available measures that identify those with higher absolute risk over and above established factors considered in contemporary risk algorithms.Various microvascular disease states have been reported to be associated with risk of vascular disease, including cardiac autonomic neuropathy (CAN),5,6 retinopathy,7,8 nephropathy,9,10 and peripheral neuropathy.11 Despite frequently co-existing, robust population data evaluating the effect of cumulative microvascular disease burden on cardiovascular risk in diabetes is absent. The aim of this study was to investigate whether microvascular disease states alone or in unison are independently associated with cardiovascular disease (CVD), and furthermore to compare any strength of association with conventional risk factors used in current risk equations. To assess this relationship, we used routine healthcare data from a large population-based cohort of individuals with type 2 diabetes free from CVD at baseline, with approximately 259 686 person years of follow up and 2689 first cardiovascular events. METHODSData sources and cohortThe Clinical Practice Research Datalink (CPRD) comprises data on individuals from over 600 practices in England, providing a representative UK primary care population.12 CPRD contains information on anthropometric measurements, clinical diagnoses, laboratory tests and prescription data, coded with the Read Clinical Coding system. Information on retinopathy, nephropathy and peripheral neuropathy has been routinely collected in UK primary care following the introduction of a pay for performance initiative, the Quality and Outcomes Framework,13 in April 2004, which is linked to the National Institute for Health and Care Excellence (NICE) guidance on standards of care for patients in the UK including appropriate frequency of screening and risk factor control for those with chronic diseases.14Individual patient data were linked across three datasets: the CPRD for demographic characteristics and, Hospital Episode Statistics (HES) and the Office for National Statistics (ONS) for the outcomes of interest. The HES are the English National Health Service administrative dataset and contain information on every hospital admission including diagnostic data, recorded as International Classification of Diseases, 10th revision (ICD–10), and procedural data based on the Office of Population, Census, and Surveys, version 4 (OPCS–4) codes. The ONS provide individual mortality records including cause of death (ICD–10). The study start date was 1 April 2008 to allow for 4 years of quality data on microvascular disease status among participants. The data extract provided by CPRD included data on 49 027 individuals aged 18 years and over with type 2 diabetes and complete information on the presence or absence of three microvascular diseases: retinopathy, nephropathy and peripheral neuropathy. Individuals were screened for the presence of diabetes using established criteria,15 and classified in accordance with methods described previously.16 Diabetes was defined by fasting plasma glucose ≥7.0 mmol per litre (126 mg per decilitre), random plasma glucose ≥11.1 mmol per litre (200 mg per deciliter) or the use of glucose lowering medications, based on recommendations from the American Diabetes Association.15,17 In brief, classification of T2DM was performed according to the following criteria: specific diagnostic code for T2DM (Read code C10F; ICD–10 code E11) with no contradictory code; and patients with a diagnosis of diabetes at ≥35 years of age with no insulin prescription within 1 year of diagnosis. Validation study of electronic health records using this approach corrected miscoding of diabetes type in between 6–8% of cases.16 We excluded individuals with a prior history of any cardiovascular disease. Definition of baseline variablesAnthropometric measurements and numerical data, including systolic and diastolic blood pressure, glycosylated haemoglobin, and cholesterol values were derived by taking the mean of the three most recent values in the 12 months prior to the study start date. In cases where three values were unavailable, the mean of two values was calculated. Values recorded more than 12 months prior to the study start were not considered. Smoking status was stratified into groups of never smoked, previously smoked and currently smoking at entry into the study. Code lists used to define microvascular disease states were developed in accordance with published guidance,18, 19 and are provided in the webappendix 1–3. Nephropathy was defined as microalbuminuria (a moderate increase in albuminuria: 3-30 mg/mmol, 30-300 mg/g, 30-300 mg/24h, or reagent strip urinalysis),20 and or eGFR <60ml/min per 1.73m2.Outcome ascertainmentThe follow-up period extended to the study end: either December 2014, the date of patient transfer from an included practice, or death. The primary outcome was the time to first major cardiovascular event (an a priori composite of cardiovascular death, non-fatal myocardial infarction or non-fatal ischaemic stroke). Ischaemic stroke events were defined by ICD-10 codes (I63) in accordance with published guidance.21 We combined ischaemic strokes with unclassified strokes (I64) because previous studies have shown that 87% of unclassified strokes were ischaemic.22 Information about cause-specific mortality and date of death was obtained through the established record linkage with ONS. Fatal myocardial infarction (MI) and ischaemic stroke were defined by primary cause of death (ICD–10 codes I21–I22 and I64 respectively). Patients were censored on the date of first primary outcome event. The pre-specified secondary endpoints were cardiovascular death (fatal MI or fatal ischaemic stroke), hospitalisation for heart failure and all-cause mortality. Study approval was granted by the Independent Scientific Advisory Committee of the Medicines and Healthcare products Regulatory Agency.Statistical analysesWe defined clinical characteristics and outcome data both overall and according to risk groups (absence of microvascular disease at baseline, or stratified by the number of prevalent microvascular disease states). All reported p values are two-sided. Adjusted hazard ratios and corresponding 95% confidence intervals were estimated with Cox proportional-hazards models. Adjustment in all models was performed for age, gender, on treatment systolic and diastolic blood pressure, high- and low-density cholesterol, HbA1c, body-mass index, duration of diabetes, smoking history (defined by either ex-smoker or current smoker status), antiplatelet therapy, lipid-lowering therapy, use of angiotensin converting enzyme inhibitor/ angiotensin receptor blocker, any treatment for blood pressure, ethnicity and index of multiple deprivation. The group free of microvascular disease at baseline were used as the reference category. Missing data for ethnicity and index of multiple deprivation were imputed using multiple imputation by chained equations in the “mice” algorithm in R, and these imputed data were used in the primary analysis. We assessed differences in predictive accuracy of a model including established risk factors from the Framingham risk function for a first primary outcome event (model A),23 and the same model incorporating microvascular disease variables (model B). Model discrimination was assessed with the use of the C-statistic.24 To evaluate the overall improvement in risk stratification with the addition of microvascular disease to fully adjusted models, we calculated net reclassification improvement (NRI) statistic and the integrated-discrimination-improvement (IDI) statistic.25 Discrimination indices are reported across risk strata defined in both the American College of Cardiology (ACC)/ American Heart Association (AHA) treatment guidelines (lower risk <7.5%, higher risk ≥7·5%3 for 10-year CVD risk and the UK National Institute for Health and Care Excellence (NICE) guidelines which consider higher risk individuals as those with ≥10% 10-year risk of CVD.26 Statistical analyses were performed with the use of R software version 15·2. Role of the funding source The sponsors had no role in the original protocol design, data collection, data analysis, data interpretation, writing of the report, or the decision to submit the report for publication. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication. RESULTSPatient CharacteristicsWe identified a cohort of 49 027 individuals with type 2 diabetes, of whom just less than half were women. Baseline characteristics of the study population, both overall and according to microvascular disease burden, are shown in Table 1. Individuals with microvascular disease were more likely to have an adverse cardiovascular risk profile with significantly greater levels of HbA1c, systolic blood pressure and smoking history. Age and duration of diabetes significantly increased in a linear fashion with increasing burden of microvascular disease. Exceptions included a trend for more favourable low-density lipoprotein cholesterol with increasing burden of microvascular disease, likely related to the greater use of lipid-lowering therapy. A comparison of the demographic characteristics of individuals with a single manifestation of microvascular disease versus those without is provided in the webappendix 4.Primary and Secondary Outcome MeasuresEvent rates for the primary outcome per 1000 person years in those without microvascular disease were 5·00 compared with 8.22, 10.12 and 10.04 among individuals with isolated retinopathy, nephropathy and peripheral neuropathy, respectively. Each microvascular disease state studied was significantly associated with the primary outcome, and remained so following adjustment for established risk factors and after excluding individuals with multiple manifestations of microvascular disease (Table 5 webappendix). Single manifestations of microvascular disease appear to confer at least as much risk as the failure to control conventional risk factor goals in adjusted analyses (webappendix 6–8). Microalbuminuria in the absence of low eGFR (<60ml/min per 1.73m2) was independently associated with the primary outcome (webappendix 9). Further adjustment for the number of antihypertensive treatments resulted in no qualitative difference in the hazard ratios for the primary outcome.Figure 1 shows the linear relationship between increasing burden of microvascular disease and the primary outcome (Panel A), cardiovascular mortality (Panel B), and hospitalisation for heart failure (Panel C), P for linear trend <0·001 for all. Analyses for all-cause mortality were qualitatively similar (webappendix 10); we found a 4·7-fold excess risk of death from any cause among individuals with three manifestations of microvascular disease compared with none (webappendix 11). Unadjusted event rates for the primary outcome among individuals free of microvascular disease at baseline and among those with one, two, or three microvascular disease states were 5·0, 9·8, 15·7 and 22·1 per 1000 person years, respectively. After adjustment for potential confounders, the hazard ratios for the primary outcome, cardiovascular death and hospitalisation for heart failure remained significant but were attenuated across all three groups, suggesting that conventional risk factors account, in part, for the excess risk observed with cumulative burden of microvascular disease (Table 2). In fully adjusted models, a single manifestation of microvascular disease appears to as strongly associated with the primary outcome as blood pressure, low-density cholesterol, glycosylated haemoglobin and smoking history in the present analysis (Figure 2), although this may in part be due to the greater variability around the measurement of conventional risk factors when compared to a diagnosis of microvascular disease. A similar relationship was observed for cardiovascular death, hospitalisation for heart failure (Figure 2), and death from any cause (webappendix 12). This association remained when established risk factors were dichotomised to reflect recommended risk factor goals (webappendix 13). When assessed across strata of risk factor control for HbA1c (<7·0%, and ≥7·0%), low-density cholesterol (<2·5, and ≥2·5 mmol per litre) and blood pressure (<140/90, and ≥140/90 mm Hg), a consistent linear trend of greater risk of the primary outcome with cumulative burden of microvascular disease and uncontrolled risk factors was observed (Figure 3). In comparison to a Cox model based on established risk factors included in the Framingham model (model A), the addition of information on microvascular disease (model B) yielded improvements in the C-statistic from 0·679 to 0·689 respectively and an improvement in the integrated discrimination index (0·003, 95% CI, 0·003–0·004, P<0·001). Across the two ACC/AHA categories of cardiovascular risk (<7.5% and ≥7.5% 10–year risk of CVD), microvascular disease reclassified 9·1% of the cohort into higher or lower risk groups as defined by US guidelines, and did so with 65·7% correct reclassification (net reclassification index 0.036, 95% CI 0.017-0.055, p<0.001). Of those individuals with a predicted <7.5% 10 year risk of CVD (32.9% of the overall cohort), 9·3% were reclassified into a higher risk group (≥7·5% 10–year risk of CVD), with an observed 10–year event rate of 8·6%. Similarly, microvascular disease reclassified 9·0% of individuals considered at higher risk (67.1% of overall cohort) to a lower risk group, with an observed 10–year CVD risk of 6·3%. According to risk categories quoted in UK guidance, microvascular disease reclassified 10·6% of individuals to a higher or lower risk group, of whom 59·5% were reclassified accurately (net reclassification index 3.8%, 95% CI 0.013-0.060, p<0.001). Among those considered at lower risk (<10% 10–year risk CVD, 48.6% of cohort), 8·9% were reclassified to a higher risk group with a 10 year observed event rate of 11·6%. Of individuals considered at higher risk (≥10% 10–year risk CVD, 51.4% of overall cohort) by conventional models, 12·3% were reclassified into a lower risk group with an observed 10-year event rate of 8·1%.In separate analyses the sequential addition of data on duration of diabetes and, in turn, microvascular disease to a model based on the Framingham risk function yielded C-statistics of 0.679 and 0.682, with respective NRIs of 0.011 (95% CI 0·001-0·022, p=0·050) and 0.024 (95% CI 0.007–0.042, p=0.007). The addition of information on duration of diabetes corresponded with a small improvement in IDI (0.0005 (95% CI 0.0002–0.0009, p=0.006), with further improvement after the addition of microvascular disease data (IDI 0.003, 95% 0.018–0.041, p<0.001). DISCUSSIONIn a population cohort of individuals with type 2 diabetes, our findings show that burden of microvascular disease is a determinant of future cardiovascular risk. The risk of a first cardiovascular event increased linearly with the number of manifestations of microvascular disease present. Furthermore, the presence of isolated retinopathy, peripheral neuropathy, or nephropathy confer at least a similar risk of cardiovascular events as factors contained in contemporary risk equations such as blood pressure, low-density lipoprotein cholesterol and haemoglobin A1c. Despite significant differences in baseline values of glycosylated haemoglobin, low-density cholesterol and blood pressure among individuals with increasing burden of microvascular disease, these factors did not abolish the associations between microvascular disease and cardiovascular outcomes. We noted no deviations from linearity in subgroups stratified by varying degrees of risk factor control. Consistent with our findings, previous reports have documented an increase in cardiovascular risk with individual microvascular disease states.5–11 However, the true impact of microvascular disease may have been overestimated because risk ratios provided in the literature are subject to confounding by a lack of adjustment for the presence of disease in multiple microvascular beds. An important advance of this study was our ability to examine the effect of both cumulative burden, and isolated microvascular disease states on first presentation of cardiovascular disease. This approach was enabled by the routine collection of microvascular disease data in the UK, and the availability of electronic health record linkage. Individual participant data from 97 prospective studies suggests the presence of diabetes is associated with a 1·8 times increased risk of death from any cause.2 However, a study of individuals with type 2 diabetes in the Swedish National Diabetes Register suggests that excess mortality risk has declined in recent years, driven in part, by substantial reductions in CVD mortality.27 The reported hazard ratios for all-cause and cardiovascular mortality, based on follow-up to 2011 in that study were 1·15 (95% CI 1·14-1·16) and 1·14 (95% CI 1·13-1·15), respectively. Although event rates in type 2 diabetes are falling and do not imply a CHD risk equivalent as previously described,28,29 lifetime risk of cardiovascular disease remains high emphasizing the need to identify early markers of risk.30 At diagnosis of type 2 diabetes, the UK Prospective Diabetes Study identified retinopathy alone in 36% of participants.31 Currently, data recorded on the presence or absence of retinopathy, nephropathy and peripheral neuropathy are used in the UK to inform risk of developing blindness, renal failure, and amputation, respectively. Our findings suggest these data may offer a simple tool to identify very high-risk individuals with type 2 diabetes who are currently perceived to be at lower absolute risk using contemporary risk models. Cardiovascular risk estimation in diabetes has important implications for primary prevention strategies. The 2013 ACC/ AHA guidelines on the control of blood cholesterol advocate moderate-intensity statin therapy in persons with diabetes who are 40–75 years of age; while high-intensity therapy is restricted to individuals with a ≥7·5% estimated 10–year risk of cardiovascular disease.3 Our findings suggest that individuals with more than one manifestation of microvascular disease would be eligible for high–intensity statin treatment based on the recorded event rates. The 10–year risk of the primary outcome in the present study was 9·8% in participants with a single manifestation of microvascular disease, 15·7% with two, and 22·1% with three microvascular beds affected. Overall, microvascular disease reclassified 9·1% of the cohort into higher or lower risk groups as defined by US guidelines, and did so with 65·7% correct reclassification. When extrapolated to the 27.9 million individuals with type 2 diabetes in the US,32 this would represent a change in the intensity of statin therapy for over 2.5 million people. If information on microvascular disease were incorporated presently then 9·3% of individuals previously considered as eligible for moderate intensity statins (predicted risk <7.5%) could now be considered as candidates for high intensity statin therapy (observed risk 8·6%). Similarly, microvascular disease would reclassify 9·0% of individuals currently considered eligible for high intensity statins (predicted risk ≥7.5%), to a group who could be offered moderate intensity therapy (observed risk 6·3%). Improvements in reclassification as suggested above not only offer potentially the correct intensity of therapy, but also offer the best net benefit avoiding potential exposure of lower CVD risk patients to potentially unnecessary dose dependent side effects on higher intensity statins, which may impact on compliance and patient engagement. In the UK the potential relevance of the present findings may be more profound. NICE guidance recommends initiating atorvastatin 20 mg or a statin of equivalent potency for primary prevention in people with type 2 diabetes and ≥10% 10–year risk of developing CVD with no recommendations for statins below this predicted risk threshold.26 The use of microvascular disease would reclassify 10·6% of individuals to a higher or lower risk group, of whom 59·5% would be reclassified accurately. This figure corresponds to 370 000 of the 3.2 million people living with type 2 diabetes in the UK presently.33 Among those currently considered ineligible for statin therapy (predicted risk <10%), 8·9% would be reclassified into a higher risk group with an observed event rate of 11·6%, reflecting potentially 135 000 new statin prescriptions in the UK. Of individuals currently offered statin therapy per NICE guidance (predicted risk ≥10%), 12·3% would be reclassified into a lower risk group (200 000 when extrapolated to UK population) with an observed 10-year event rate of 8·1%. The inclusion of microvascular disease would potentially offer cost benefits from the opportunity to prevent more events as higher risk patients would be targeted, despite resulting in a net reduction of statin prescriptions in the UK and therefore cost reductions or neutrality.Real world data suggests that acceptance of preventive therapies and implementation, for instance of statin guidelines, has been problematic in younger patients.34 A potential practical application of these data might be to highlight individuals who, despite their age, are at higher risk due to multiple manifestations of microvascular disease, and may help to overcome patient and physician reluctance to initiate statins. Furthermore these data might serve as the basis for identifying patient groups with high absolute risk who might, under current EMEA and FDA licences, benefit most from further lipid lowering with novel (more expensive) therapies, or could be used to enrich patients with higher event rates for future trials, thus reducing sample size, duration and cost of conducting large outcome studies.Among individuals with three manifestations of microvascular disease, our data indicate that good control of risk factors (HbA1c <7·0%, low-density cholesterol <2·5 mmol per litre, and blood pressure <140/90) is associated with a 43% lower risk of future cardiovascular events compared to when these factors are not at goal (17·1 versus 29·8 events per 1000 person years). However, these data are observational in nature and, although they support a positive association between poor risk factor control and cardiovascular events among individuals with prevalent microvascular disease, they cannot prove the benefit of treatments to modify HbA1c, low-density cholesterol or blood pressure to target in this population. Insights from the Steno-2 study support this observation that aggressive management of multiple risk factors might mitigate some of the excess risk associated with microvascular disease.35 It randomised patients with type 2 diabetes and persistent microalbuminuria to receive either intensive or conventional therapy for a number of modifiable risk factors including glucose control, blood pressure, total cholesterol and triglyceride levels. Intensive therapy was associated with a lower risk of both fatal and non-fatal cardiovascular events at a median follow-up of 13 years. An important caveat however is that baseline cardiovascular risk factors were significantly more adverse in Steno–2 compared to the present cohort. We also assessed the associations of microvascular disease burden with hospitalisation for heart failure and report event rates around half those observed in the recent Reduction of Atherothrombosis for Continued Health (REACH) registry.36 Among participants with established atherothrombosis and a prior ischaemic event enrolled in REACH, 6·5% of patients were hospitalised for heart failure corresponding to a rate of 16 per 1000 person years. This compared to an overall rate of 6 per 1000 person years in this study of individuals free of cardiovascular disease at baseline. Those with disease in three microvascular beds were at significantly greater risk, with event rates of 15 per 1000 person years, similar to those with a history of MI or stroke in REACH. In comparison with diabetic patients free from microvascular disease, the adjusted hazards for heart failure with the presence of one, two, or three microvascular disease states were 1·63, 2·24, and 2·90, respectively. The mechanisms behind this association are unclear but plausible contributors include CAN, which frequently co-exists with other microvascular disease states,37 and may be the diabetes-specific process that explains part of the excess risk of heart failure not accounted for by increased burden of atherothrombosis.38,39While the present data derive from a validated and nationally representative sample of England, results should not be extrapolated to dissimilar populations. Important limitations of the study include our reliance on comprehensive code lists for any given baseline or outcome variable. This is a limitation common to all studies using routinely recorded data and was mitigated through the use of a validated approach for defining baseline and outcome parameters.16,19 Individuals were screened for diabetes using established criteria that may not reflect population samples identified through other methods and may imply lower overall cardiovascular risk compared to cohorts with type 2 diabetes diagnosed through case finding or clinical symptoms. Limitations exist in the amount of clinical detail presently recorded in national administrative datasets such as CPRD, which offer the benefit of large cohorts at the expense of granularity that is common to bespoke epidemiological studies. In this regard, quantitative data on albuminuria or albumin-to-creatinine ratio was not consistently available and would have been preferable, given these measures have been previously shown by the CKD Prognosis Consortium to improve the discrimination of cardiovascular outcomes beyond traditional risk factors among individuals with diabetes.10 Furthermore, greater detail on the classification of retinopathy into non-proliferative and proliferative types was not available in sufficient numbers to permit meaningful analyses across these categories. Analyses were restricted to individuals in whom complete information was available on prevalent microvascular disease and may be subject to selection bias. Examination of the association between microvascular disease and CVD among individuals with data missing on all three diseases showed no qualitative difference with the complete cohort (webappendix 14). Ethnicity data were missing in just under three quarters of patients and social deprivation was missing in a third; these confounding variables were imputed and included in the primary analysis. Results may have been affected by unmeasured variables such as diet, which was not considered in our analyses because these data are unreliably recorded. Finally, the data presented here are observational in nature and although attempts have been made to reduce confounding by statistical adjustment we cannot exclude the possibility of residual confounding as part of the explanation for our findings.In this linked primary and secondary care study of diabetic adults, microvascular disease was found to confer a risk equivalent to conventional factors including smoking, hypertension and dyslipidaemia. Cardiovascular risk and mortality increased with the total number of microvascular beds affected, suggesting a continued broad assessment program for retinopathy, nephropathy and peripheral neuropathy can provide reliable information on cardiovascular risk, in addition to morbidity linked to individual microvascular disease states. Such prognostic data has implications for cardiovascular risk stratification and prevention strategies.AcknowledgementsThe study was supported by a grant from the Circulation Foundation. ContributorsJB, RH, and KR designed the study protocol. JB, CH, and DB did the statistical analyses. SdeL, BP, and AK provided support in the statistical analyses and interpretation of results. PH, MT provided critical appraisal of initial drafts. All authors took part in the writing of this report.Declaration of InterestsKKR reports to having received honoraria for serving on the steering committee, clinical endpoint adjudication committee, advisory boards or lectures from Agerion, Abbvie, Pfizer, AZ, Sanofi, Regeneron, Amgen, MSD, Roche, Kowa, Algorithm, Novartis, Novo Nordisk, Lily, Resverlogix, ISIS Pharma, Cipla, Takeda, Boehringer Ingelheim. RJH is supported by a career salary award from The Higher Education Funding Council for England. MMT has received research grants from Medtronic, Cook Endovascular, and Endologix. PH is a Clinician Scientist financially supported by the National Institute for Health Research (NIHR-CS-011–008). All other authors report no declarations of interests.REFERENCES1.The Emerging Risk Factors Collaboration. Diabetes Mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies. 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Baseline CharacteristicsNumber microvascular disease states?All n=49 027p value0n=12 3851n=18 6312n=13 8863n=4125Age, years62·6 (11·3)69·0 (11·4)73·7 (10.5)74·5 (10·5)69·2 (11·8)<0·001Women5405 (43·6)8754 (47·0)6731 (48·5)1943 (47·1)22833 (46·6)<0·001White ethnicity3104 (89·7)4730 (90·8)3418 (92·5)981 (91·2)12233 (91·0)0·12BMI, kg/m231.0 (6·2)30·6 (6·3)30·3 (6·2)30·4 (6·2)30·6 (6·2)<0·001HbA1c, %7·23 (1·25)7·23 (1·28)7·32 (1·34)7·64 (1·45)7·29 (1·31)<0·001Duration diabetes, years5·7 (4·5)7·2 (5·5)9·5 (6·7)13·8 (8·0)8·0 (6·3)<0·001Systolic blood pressure, mmHg135·5 (12·6)136·9 (13·3)138·0 (14·4)139·2 (14·8)137·1 (13·6)<0·001Diastolic blood pressure, mmHg78·1 (7·6)76·3 (8·0)74·5 (8·3)74·5 (8·3)76·0 (8·2)<0·001Total cholesterol, mmol/L4·36 (0·89)4·29 (0·89)4·23 (0·93)4·14 (0·91)4·28 (0·90)<0·001HDL cholesterol, mmol/L1·27 (0·37)1·27 (0·37)1·26 (0·38)1·24 (0·40)1·27 (0·38)<0·001LDL cholesterol, mmol/L2·38 (0·85)2·30 (0·84)2·25 (0·82)2·20 (0·84)2·23 (0·84)<0·001eGFR, mL/min/1.73m281·4 (16.9)70·0 (22·5)69·5 (21·4)52·7 (19·1)68·5 (22·6)<0·001Smoking history8999 (72·9)13967 (75·2)10694 (77·2)3265 (79·2)36925 (75·5)<0·001Deprivation index ≤ 5th decile4550 (54·0)6658 (52·4)5141 (54·0)1527 (52·9)17876 (53·3)0·05Statin use 8631 (69·7)13558 (72·8)10333 (74·4)3078 (74·6)35600 (72·6)<0·001ACEi/ARB7479 (60·4)13903 (74·6)11717 (84·4)3766 (91·3)36865 (75·2)<0·001Blood pressure treatment9216 (74.4)16146 (86.7)13001 (93.6)4006 (97.1)42369 (86.4)<0.001Antiplatelet6790 (54·8)11963 (64·2)9904 (71·3)3136 (76·0)31793 (64·8)<0·001? Microvascular diseases considered include retinopathy, microalbuminuria and peripheral neuropathy. Data are mean (SD) or number (%). BMI indicates body mass index; HbA1c, glycosylated haemoglobin; HDL, high-density lipoprotein; LDL, low density lipoprotein; eGFR, estimated glomerular filtration rate; ACEi/ARB, angiotensin converting enzyme inhibitor/ angiotensin receptor blocker. P values from Chi square test or ANOVA are provided for the overall trend with increasing number of microvascular disease states. Missing values: The following variables had missing values: Ethnicity (n=35590, 72.6%), BMI (n=94, 0.2%), HbA1c (n=94, 0·2%), Systolic BP (n=6, 0·01%), Diastolic BP (n=6, 0·01%), Total cholesterol (n=25, 0·05%), HDL cholesterol (n=3778, 7·7%), LDL cholesterol (n=8347, 17·0%), eGFR (n=523, 1.1%), Smoking status (n=108, 0·2%), Deprivation index (n=.15495, 31·6%)Table 2. Adjusted Hazard Ratios of Clinical Outcomes by Burden of Microvascular Disease*Number microvascular disease states0n=12 3851n=18 6312n=13 8863n=4125Primary outcome N351 (2·8%)975 (5·2%)1072 (7·7%)424 (10·3%) Event rate per 1000 person years5·009·8215·6922·10 Unadjusted hazard ratio1·001·97 (1·74–2·22)3·15 (2·80–3·56)4·45 (3·87–5·13) Adjusted hazard ratio (95% CI)*1·001·32 (1·16–1·50)1·62 (1·42–1·85)1.99 (1·70–2·34)Hospitalisation for heart failure N114 (0·9%)449 (2·4%)611 (4·4%)270 (6·5%) Event rate per 1000 person years2·764·859·5314·88 Unadjusted hazard ratio1·002·77 (2·25–3·40)5·45 (4·46–6.66)8·53 (6·86–10·62) Adjusted hazard ratio (95% CI)*1·001·63 (1·31–2·03)2.24 (1·80–2·80)2.90 (2·27–3·71)Cardiovascular mortality n92 (0·7%)314 (1·7%)384 (2·8%)177 (4.3%) Event rate per 1000 person years1·553·676·4110·36 Unadjusted hazard ratio1·002·38 (1·88–3·00)4·16 (3·31–5·22)6.73 (5·23–8·66) Adjusted hazard ratio (95% CI)*1·001·43 (1·12–1·83)1·83 (1·42–2·34)2·53 (1·91–3·36)* Adjusted for age, gender, systolic BP, diastolic BP, LDL-C, HDL-C, HbA1c, BMI, duration of diabetes, smoking status, antiplatelet therapy, lipid-lowering treatment, RAS blockade, other blood pressure treatment, ethnicity, index of multiple deprivation. Numerical data were entered into models as continuous data. A B CFigure 1. Unadjusted freedom from the primary outcome (A), hospitalisation for heart failure (B), and cardiovascular mortality (C) by cumulative burden of microvascular disease. The primary outcome measure was cardiovascular mortality, non-fatal myocardial infarction or non-fatal ischaemic stroke. Log-rank test for the linear association between cumulative burden of microvascular disease for the primary outcome p<0.001; hospitalisation for heart failure p<0.001; and for all-cause mortality p<0.001. A B CFigure 2. Adjusted hazard ratio for the primary outcome (A), hospitalisation for heart failure (B), and cardiovascular mortality (C) by cumulative burden of microvascular disease and per 1 SD difference in values for established risk factors*The primary outcome measure was cardiovascular mortality, non-fatal myocardial infarction or non-fatal ischaemic stroke. 1 SD of each established risk factor is: BP 13.5/8.4 mmHg; LDL 0.9 mmol/L; BMI 6.3 kg/m2; HbA1c 1.3%.Adjusted for age, gender, systolic BP, diastolic BP, LDL-C, HDL-C, HbA1c, BMI, duration of diabetes, smoking status, antiplatelet therapy, lipid-lowering treatment, RAS blockade, other blood pressure treatment, ethnicity, index of multiple deprivation Figure 3. Adjusted event rates for the primary outcome by cumulative burden of microvascular disease and established risk factor goals*The primary outcome measure was cardiovascular mortality, non-fatal myocardial infarction or non-fatal ischaemic stroke.* Adjusted for age, gender, systolic BP, diastolic BP, LDL-C, HDL-C, HbA1c, BMI, duration of diabetes, smoking status, antiplatelet therapy, lipid-lowering treatment, RAS blockade, any blood pressure treatment, ethnicity, index of multiple deprivation ................
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