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The incidence of atheromatous disease is much greater in the diabetic than general population. It is the devastating effects of this atheromatous disease that require effective and aggressive interventions, aimed at minimising future mortality and morbidity. There is considerable evidence to support an approach that assumes, for type 2 diabetics, that prevention needs to be secondary (CVD is present) rather than primary (CVD is absent), even in those without any manifestation or evidence of vascular disease. To prevent future CVD, asymptomatic patients may have to undergo potentially unpleasant or even dangerous treatment. Such interventions are more likely to be appropriate and justifiable if both the concept of risk and the factors contributing to increased risk are understood.


Risk can be defined as the probability or expected frequency of harmful effects (due to a biological agent) occurring over a defined period of time.

Although risk can be expressed in different ways, it is useful to understand the difference between absolute and relative risk:

Where the absolute risks of two compared events or interventions are very low, small differences of risk may be relatively “large”. For example, if a treatment reduces the risk of an adverse event occurring from 2% to 1%, then the absolute risk reduction is an unimpressive 1%, but the relative risk reduction is a staggering 50%: this fact does not escape copywriters in advertising.

The results of a risk–benefit analysis of an intervention are often presented now as “number needed to treat” (NNT). NNT is the reciprocal of absolute risk reduction. If a treatment reduces absolute risk by 1 in 10 or 10%, then the NNT of that treatment is 10. NNT is a better, much less misleading, representation of a treatment’s effectiveness than relative risk reduction.

Although the term vascular can refer to the whole of the circulatory system, it is sometimes used to refer to a part of the system. In order to be precise, the term vascular should be qualified in such circumstances to indicate which part of the circulation is being described. When considering the long-term vascular complications of diabetes, it is useful to subdivide these according to vessel size into:

Discussions about vascular risk relate mostly to macrovascular disease, and the distinction needs to be made between:

These concepts are relevant when quantifying and describing risk.


Different parameters, characteristics or factors contribute, both individually and collectively, to the overall cardiovascular risk in any single individual, particularly one with diabetes. Not all factors affect cardiovascular risk equally, nor are all of them independent or susceptible to modification.

Cardiovascular risk factors can be divided into nonmodifiable and modifiable (see Table 4.1). Only modifiable factors can respond to intervention. However, some nonmodifiable risk factors are needed to calculate global cardiovascular risk and, if present, can serve as a prompt to help identify those individuals in whom this risk should be assessed and “tackled”, particularly in people normally considered to be at lower risk, such as those without diabetes.

TABLE 4.1 Cardiovascular risk factors and markers in people with diabetes mellitus

Nonmodifiable risk factors Modifiable risk factors
Age Smoking status
Gender Raised blood pressure
Ethnic group Dyslipidaemia
Family history Lack of physical activity
Poor diet
Poor glycaemic control
Excess alcohol
Elevated fibrinogen
Raised inflammatory markers

Of the modifiable risk factors for CVD, smoking, raised blood pressure and dylipidaemia are generally regarded as the most important, both for their contribution to overall cardiovascular risk and for the resultant reduction of that risk when “corrected”.

Although individual risk factors may have an independent effect upon the global cardiovascular risk, their overall effect upon cardiovascular risk is often more than additive, with different risk factors combining “at times … to become permissive for harm or create harm greater than that effected by simple addition” (Simmons 2002). In 1993 the MRFIT study demonstrated that the greater than additive adverse effect of a collection of risk factors is especially marked in diabetes, where the increase in risk attributed to any single or combination of risk factors is doubled when compared to a nondiabetic population (Stamler et al 1993). There are still gaps in the evidence base. Matters become more complicated when evaluating the efficacy of various interventions.

It is important to move away from focussing on a single risk factor to the exclusion of others. There are recognised situations or scenarios where risk factors are clustered, e.g. metabolic syndrome. Interventions that concentrate upon modifying a single risk factor may be much less effective in reducing cardiovascular risk than in adopting a multi-factorial approach.


Cardiovascular risk models have used data from the observation of a population cohort over a period of time, based upon the recording of risk factors and of CVD events. The usefulness of a risk model depends upon whether the calculation takes account of all important contributory risk factors and whether the important demographics of the individual being assessed are adequately represented in the population used in the model.

Risk prediction tables have been used in the UK since the mid 1990s. Initially for primary prevention, the Department of Health recommended a threshold of annual risk for a CHD event of 3%, now reduced to 1.5%, above which the prescription of expensive drugs could be justified. The latest Joint British Societies’ guidelines, consistent with the aim of preventing CVD events, have a threshold of annual risk for a CVD event of 2% (Wood et al 2005).

Many risk models have derived their data from the Framingham Heart Study. These models predict risk for CVD, CHD or stroke, either over a period of 5 or 10 years or annualised. The calculations included age, gender, smoking status, blood pressure (some include only systolic blood pressure), lipid profile (total cholesterol and high-density lipoprotein), the presence or absence of diabetes, and the presence or absence of left ventricular hypertrophy. Several other geographical and time-based cohorts have been used to generate risk models. Ideally, the risk calculator should be incorporated into the software being used during the consultation. A current favourite risk model is the updated New Zealand Calculator (derived from Framingham), as it incorporates decision support and can be used to inform patients of the effectiveness of modifying risk factors (New Zealand Guidelines Group 2003).

All of these models have several flaws, listed in Table 4.2, and any calculation using models derived from Framingham data or other population cohorts should be applied with caution. The main limitations are:

TABLE 4.2 Potential drawbacks of cardiovascular risk prediction tools

Applicable to both diabetic and nondiabetic populations Applicable to a diabetic population
The use of shorter fixed time spans, as opposed to long-term or lifetime Under-representation of diabetics in the study populations, leading to a smaller database upon which to base calculations of risk
Annualised risk does not reflect the incremental increased incidence of CVD with age While risk models regard diabetes as a categorical variable, they ignore the level of glycaemia, which is probably an important predictor of CVD and CHD in patients with type 2 diabetes (Turner et al 1998)
Failure to include all the relevant risk factors contributing to cardiovascular risk Failure to include important markers or factors associated with increased cardiovascular risk in diabetics, such as microalbuminuria and raised serum triglycerides
The lack of valid data for certain ethnic groups  
Failure to take into consideration the confounding effect of modern treatments  
Different risk engines will give different risk predictions with the same data  

The UKPDS database was used to produce a diabetes-specific risk engine (Stevens et al 2001 – also available online: to predict annual CHD risk (defined as fatal or nonfatal MI or sudden death). The calculation incorporates HbA1c, systolic blood pressure, TC:HDL-C ratio, age, sex, ethnic group, smoking status and time elapsed since diabetes was diagnosed. The engine can also report the different levels of risk for CHD, PVD and cerebrovascular disease. Unlike other databases, the UKPDS database is based upon an interventional study.

However, the UKPDS database and risk engine do have the following drawbacks:

The UKPDS risk engine is a more “refined” tool to predict cardiovascular risk in diabetics without evident CVD. However, despite “imperfections”, using one of the models derived from the Framingham data is currently the best way to estimate cardiovascular risk in untreated Northern European patients, provided that caution is used when applying the actual results. To produce a more accurate figure in patients of South Asian ethnicity or with a first-degree relative who suffered a premature CVD event, clinicians should consider multiplying the result of a Framingham calculation by 1.5 (if both factors are present, the result could be doubled). Although crude, this manoeuvre may partly counteract two drawbacks of a Framingham-derived model.

NICE intends to advise on cardiovascular risk assessment, as part of its imminent guidance on lipids (to be issued in December 2007, at time of writing).



Neither research evidence nor expert consensus has found a level of blood pressure below which treatment does not confer benefit. The target blood pressure levels currently recommended by several learned bodies, summarised in Table 4.3, do not concur, but the overall trend has been downwards over recent years. If target organ damage is present, interventions should aim to achieve and maintain even lower target blood pressure levels. However, less strict targets may be appropriate in elderly or seriously ill patients with limited life expectancy.

TABLE 4.3 Target blood pressure levels for diabetics recommended by different organisations

Blood pressure target (mmHg) Learned body/organisation Date published
145/85 New GP Contract 2003, reviewed 2006
140/90 NICE (North of England 2004) August 2004
140/90 NICE (NICE 2006a) June 2006
140/80 SIGN (SIGN 2001) November 2001
140/80 National Clinical Guidelines for Type 2 Diabetes (Hutchinson et al 2002) October 2002
140/80 UKPDS 36 (Adler et al 2000) 2000
130/80 (optimal) British Hypertension Society Guidelines 2004
140/80 (acceptable) BHS-IV (Williams 2004)  
130/80 American Diabetes Association (ADA 2007) January 2006
130/80 JBS 2 (Wood et al 2005) December 2005

Reaching such tight targets may not be possible in or acceptable to some type 2 diabetics, despite or because of the concurrent prescribing of several agents. However, small reductions of blood pressure, maintained over a few years, can significantly reduce cardiovascular risk in all diabetics: many studies achieved reductions of the order of 10 mmHg systolic and 5 mmHg diastolic. Rather than aiming always for a fixed endpoint, an individualised target based upon the starting level of blood pressure and an achievable reduction may be more realistic and appropriate for many patients. Professionals should bear in mind that, from the patient’s perspective, lowering blood pressure is less “meaningful” than reducing the risk of suffering a real event (such as MI, stroke or diabetic complication).


Measurement of blood pressure

It is being increasingly recognised that the measurement of blood pressure need not be restricted to the encounter with a health-care professional:

However, routine use of automated ambulatory blood pressure monitoring or home monitoring devices in primary care is not currently recommended by NICE (NICE 2006a): further research is needed to determine their precise role.

A variety of automated sphygmomanometers are now available. Before purchasing any model, the buyer is advised to enquire whether the device has passed independent validation using the protocols of the British Hypertension Society (BHS) and the Association for the Advancement of Medical Instrumentation Standard (AAMI) (O’Brien et al 2001). Additional useful advice may be available from the local hospital’s medical physics department. Further independent evaluation of the available blood pressure measuring devices is being undertaken and may be published at some point in the future.

The use of mercury sphygmomanometers is still legal (the problems arise with safe disposal of mercury). When set up properly they can be as accurate as the best automated machine. Many aneroid sphygmomanometers lose accuracy when jolted.

Due to pressures of time and less than ideal ergonomics, many health professionals do not invariably measure a patient’s blood pressure correctly. Detailed authoritative guidance on how it should be done is given in Table 4.4, a counsel of perfection. To minimise inaccuracies, some key points to remember when measuring blood pressure include:

TABLE 4.4 Guidelines for Blood Pressure Measurement

Blood pressure measurement: procedure
Measure sitting blood pressure routinely: standing blood pressure should be recorded at least once at the initial estimation
Try to standardise the procedure:

Correctly wrap a cuff containing an appropriately sized bladder around the upper arm and connect to a manometer. Cuffs should be marked to indicate the range of permissible arm circumferences; these marks should be easily seen when the cuff is being applied to an arm Palpate the brachial pulse in the antecubital fossa of that arm Rapidly inflate the cuff to 20 mmHg above the point where the brachial pulse disappears Deflate the cuff and note the pressure at which the pulse re-appears: the approximate systolic pressure Re-inflate the cuff to 20 mmHg above the point at which the brachial pulse disappears Using one hand, place the stethoscope over the brachial artery ensuring complete skin contact with no clothing in between

When the sounds have disappeared, quickly deflate the cuff completely When possible, take readings at the beginning and end of consultations. Take the mean of at least two readings. More recordings are needed if marked differences between initial measurements are found

(from North of England 2004, O’Brien et al 2003, British Hypertension Society website)


The huge range and quantity of blood-pressure-lowering drugs available mirrors that of blood glucose-lowering medication. Before discussing the individual drug classes, several key concepts need to be borne in mind:

In support of the Diabetes NSF, the National Clinical Guidelines for type 2 diabetes published its recommendations for the pharmacological management of raised blood pressure in 2002 (Hutchinson et al 2002). However, these have been superseded by the 2006 guidelines from NICE (NICE 2006a), and the 2005 JBS 2 guidance on the prevention of CVD. The Quality and Outcomes Framework of the GMS contract sets a unified threshold for intervention and target (see Appendix 3).

Drug classes for the treatment of raised blood pressure

Five classes of blood-pressure-lowering drugs have been shown to be effective in reducing cardiovascular mortality and morbidity in patients with type 2 diabetes and raised blood pressure:

Although some of the supporting evidence came from trials comparing treatments against placebo, more data are now available comparing different effective treatments or combinations. An overview of this evidence is found in Table 4.5. The trials cited below are referred to by their acronyms, with their full names given in Appendix 5. The indications, cautions and contraindications for the major classes of antihypertensive drugs are summarised in Table 4.6.

In addition, there are other drug classes of blood-pressure-lowering drugs that are sometimes used in patients with diabetes:

Further details of the names and dosages of different blood-pressure-lowering agents are given in Appendix 1 and in the BNF Section 2.

Angiotensin converting enzyme (ACE) inhibitors

This drug class blocks the conversion of angiotensin-I to angiotensin-II (a powerful vasoconstrictor and an indirect facilitator of the sympathetic nervous system) by inhibiting the angiotensin converting enzyme. This produces a reduction in angiotensin-II levels, leading to arteriolar and venous dilatation and a fall in blood pressure. The antihypertensive effect of ACE inhibitors is dose-related.

Angiotensin-II has other actions that are thought to be harmful to the cardiovascular system, contributing to the pathogenesis of large and small vessel structural changes in hypertension and other CVD (Luft 2001). ACE inhibitors also suppress aldosterone secretion, increase renal blood flow (producing natriuresis) and increase circulating levels of bradykinin, a vasodilating cytokine which can cause cough. ACE inhibitors have little effect upon heart rate or airways resistance. ACE inhibitors have no adverse effects upon lipid metabolism or glucose tolerance, but there have been reports that they may be less effective in Afro-Caribbean patients. Drugs in this class have generic names ending in “-pril”. They include captopril, cilazapril, enalapril, fosinopril, imidapril, lisinopril, moexipril, perindopril, quinapril, quinopril, ramipril and trandolapril.

Class side-effects include:

ACE inhibitors should not be prescribed to women who are likely to become pregnant, due to the teratogenic risk of foetal renal maldevelopment, nor to patients with bilateral renal artery disease, as this might precipitate deterioration in renal function leading to renal failure. Concurrent prescribing of ACE inhibitors with potassium supplements or potassium-sparing diuretics should be avoided, unless specifically required and with careful electrolyte monitoring.

Initiating an ACE inhibitor can produce a sharp fall in blood pressure in patients when the renin-angiotensin system is activated (e.g. when dehydration, heart failure, or accelerated hypertension are present), but this sudden drop is rarely seen in uncomplicated hypertension. Although renal artery stenosis may be detected by the presence of a renal artery bruit, it is often sub-clinical. As a precaution, serum eGFR or creatinine should be checked within 2 weeks of initiating an ACE inhibitor in order to detect any loss of renal function early enough to stop the drug and prevent significant irreversible deterioration. A change of less than 10% from the baseline value is not clinically significant.

The ABCD (Estacio et al 1998) and FACET (Tatti et al 1998) studies found ACE inhibitors to be superior to dihydropyridine calcium channel blockers in preventing cardiovascular events in type 2 diabetics. ACE inhibitors have been shown to improve cardiovascular outcomes in high cardiovascular risk patients with diabetes, independently of whether hypertension was present (HOPE 2000, PROGRESS 2001). In the ASCOT study, the treatment group, in which the ACE inhibitor perindopril was the add-in drug, achieved lower blood pressures, had fewer CVAs and total CVD events, and lower all-cause mortality (Dahlöf et al 2005). Some of these differences could be attributed to the lower blood pressure levels achieved and improvements in other cardiovascular risk factors in this group. ASCOT was stopped early due to differences in mortality between the two treatment groups: as a result, it lacked sufficient power to detect a statistically significant difference between the groups for the primary endpoint (nonfatal MI or CHD death).

Beta (β) blockers

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