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Microvascular Disease and Risk of Cardiovascular Events Among
Individuals With Type 2 Diabetes: a Population-Level Cohort Study
Brownrigg 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*
1
Division of Cardiovascular and Cell Sciences, St George’s University of London,
London, UK
2
Division of Surgery and Interventional Science, University College London,
London, UK
3
Department of Healthcare Management and Policy, University of Surrey,
Guildford, UK
4
Department of Primary Care and Public Health, Imperial College London,
London, UK
*KKR and RJH contributed equally to this study.
Word count:
4206
Corresponding author:
Jack RW Brownrigg
Division of Cardiovascular and Cell Sciences
St George’s University of London
Cranmer Terrace
London
SW17 OQT
[email protected]
1
ABSTRACT
Background
Diabetes 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.
Findings
During 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 (1·191·66), 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.
Interpretation
The 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.
Funding
Circulation Foundation
2
RESEARCH IN CONTEXT
Evidence before this study
We 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 study
Based 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 evidence
These 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
3
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 10year 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.
4
INTRODUCTION
Diabetes 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 populationbased 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.
METHODS
Data sources and cohort
The 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.14
Individual 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).
5
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 variables
Anthropometric 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 ascertainment
The 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-
6
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 analyses
We 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.
RESULTS
7
Patient Characteristics
We 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 Measures
Event 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
8
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).
DISCUSSION
9
In 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
10
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
11
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.38,39
12
While 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.
Acknowledgements
The study was supported by a grant from the Circulation Foundation.
Contributors
13
JB, 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 Interests
KKR 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 (NIHRCS-011–008). All other authors report no declarations of interests.
14
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17
Table 1. Baseline Characteristics
Number microvascular disease states†
All
n=49 027
p value
0
n=12 385
1
n=18 631
2
n=13 886
3
n=4125
Age, years
62·6 (11·3)
69·0 (11·4)
73·7 (10.5)
74·5 (10·5)
69·2 (11·8)
<0·001
Women
5405 (43·6)
8754 (47·0)
6731 (48·5)
1943 (47·1)
22833 (46·6)
<0·001
3104 (89·7)
4730 (90·8)
3418 (92·5)
981 (91·2)
12233 (91·0)
0·12
31.0 (6·2)
30·6 (6·3)
30·3 (6·2)
30·4 (6·2)
30·6 (6·2)
<0·001
7·23 (1·25)
7·23 (1·28)
7·32 (1·34)
7·64 (1·45)
7·29 (1·31)
<0·001
5·7 (4·5)
7·2 (5·5)
9·5 (6·7)
13·8 (8·0)
8·0 (6·3)
<0·001
135·5 (12·6)
136·9 (13·3)
138·0 (14·4)
139·2 (14·8)
137·1 (13·6)
<0·001
78·1 (7·6)
76·3 (8·0)
74·5 (8·3)
74·5 (8·3)
76·0 (8·2)
<0·001
4·36 (0·89)
4·29 (0·89)
4·23 (0·93)
4·14 (0·91)
4·28 (0·90)
<0·001
1·27 (0·37)
1·27 (0·37)
1·26 (0·38)
1·24 (0·40)
1·27 (0·38)
<0·001
2·38 (0·85)
2·30 (0·84)
2·25 (0·82)
2·20 (0·84)
2·23 (0·84)
<0·001
81·4 (16.9)
70·0 (22·5)
69·5 (21·4)
52·7 (19·1)
68·5 (22·6)
<0·001
Smoking history
8999 (72·9)
13967 (75·2)
10694 (77·2)
3265 (79·2)
36925 (75·5)
<0·001
Deprivation index ≤
5th decile
4550 (54·0)
6658 (52·4)
5141 (54·0)
1527 (52·9)
17876 (53·3)
0·05
Statin use
8631 (69·7)
13558 (72·8)
10333 (74·4)
3078 (74·6)
35600 (72·6)
<0·001
ACEi/ARB
7479 (60·4)
13903 (74·6)
11717 (84·4)
3766 (91·3)
36865 (75·2)
<0·001
Blood pressure
treatment
9216 (74.4)
16146 (86.7)
13001 (93.6)
4006 (97.1)
42369 (86.4)
<0.001
Antiplatelet
6790 (54·8)
11963 (64·2)
9904 (71·3)
3136 (76·0)
31793 (64·8)
<0·001
White ethnicity
BMI, kg/m
2
HbA1c, %
Duration diabetes,
years
Systolic blood
pressure, mmHg
Diastolic blood
pressure, mmHg
Total cholesterol,
mmol/L
HDL cholesterol,
mmol/L
LDL cholesterol,
mmol/L
eGFR,
mL/min/1.73m2
† 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%)
18
Table 2. Adjusted Hazard Ratios of Clinical Outcomes by Burden of Microvascular
Disease*
Number microvascular disease states
0
n=12 385
1
n=18 631
2
n=13 886
3
n=4125
351 (2·8%)
975 (5·2%)
1072 (7·7%)
424 (10·3%)
Event rate per 1000 person years
5·00
9·82
15·69
22·10
Unadjusted hazard ratio
1·00
1·97 (1·74–2·22)
3·15 (2·80–3·56)
4·45 (3·87–5·13)
Adjusted hazard ratio (95% CI)*
1·00
1·32 (1·16–1·50)
1·62 (1·42–1·85)
1.99 (1·70–2·34)
114 (0·9%)
449 (2·4%)
611 (4·4%)
270 (6·5%)
Event rate per 1000 person years
2·76
4·85
9·53
14·88
Unadjusted hazard ratio
1·00
2·77 (2·25–3·40)
5·45 (4·46–6.66)
8·53 (6·86–10·62)
Adjusted hazard ratio (95% CI)*
1·00
1·63 (1·31–2·03)
2.24 (1·80–2·80)
2.90 (2·27–3·71)
92 (0·7%)
314 (1·7%)
384 (2·8%)
177 (4.3%)
Primary outcome
N
Hospitalisation for heart failure
N
Cardiovascular mortality
n
Event rate per 1000 person years
1·55
3·67
6·41
10·36
Unadjusted hazard ratio
1·00
2·38 (1·88–3·00)
4·16 (3·31–5·22)
6.73 (5·23–8·66)
Adjusted hazard ratio (95% CI)*
1·00
1·43 (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.
19
A
20
B
21
C
Figure 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.
22
A
B
23
C
Figure 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/m 2; 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
24
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
25