The International Diabetes Federation estimates that at present there are almost 300 million diabetic patients worldwide and an increase in the number of diabetic patients of ∼7 million per year is predicted to occur in the next few years [1,2]. Diabetic foot ulcers (DFU) are common in patients with diabetes. The annual and lifetime incidence of DFUs has been estimated as 4 and 25%, respectively [3,4]. Community surveys in the USA have documented a 3-year 5.8% DFU cumulative incidence in diabetic patients . Studies in European Countries have reported an annual incidence of 3.6% in Sweden , of 2.1% in the Netherlands , and of 2.2% in the UK . DFU represents a major health problem worldwide because this diabetic complication is associated with reduced quality of life and increased functional disability . Five to 15% of patients with DFU will have amputation during their lifespan . In addition, DFUs are increasingly recognized as important predictors of elevated mortality [10,11]. According to some studies, DFUs are the second leading cause of diabetes-related mortality, second only to diabetic cardiovascular complications [10,11]. It is, therefore, crucial to identify all factors that can favour the development of foot ulcers in diabetes.
Although DFU is considered to be a multifactorial disorder, its pathophysiology is still poorly understood. Both genetic and environmental factors may be implicated in the development of DFU. A well known risk factor for the development of DFU is poor glycaemic control as reflected by high levels of HbA1c [12,13]. Diabetic patients with DFU often exhibit increased large-artery stiffness . In addition, microvascular endothelial dysfunction has been observed in this condition sometimes preceding arterial stiffening and cardiovascular complications . If vascular abnormalities are important contributors to DFU, all factors increasing the risk of vessel disease should be searched for in diabetic patients and treated whenever possible .
In this issue of the Journal, using a nested case–control design in a large sample of diabetic patients, Brennan et al. investigated whether high visit-to-visit SBP variability (BPV) may increase the risk of incident DFU. These authors found a linear relationship between baseline BPV and DFU development. Compared with those in the lowest BPV quartile, patients in the top BPV quartile had a 29% increase in DFU risk (95% CI 24–34%). Mean within-subject SD of SBP was 4.5 ± 2.3 and 20.3 ± 4.7 mmHg, respectively, in the two groups.
High BPV is a well known predictor of adverse outcome in several clinical conditions. In diabetes, day-by-day home-measured BPV was able to predict development/progression of nephropathy [17,18]. Similar results have been found when BP was measured several times over a year or more. In a sample of type 2 diabetic patients, high BPV provided additional prognostic information to mean BP values in predicting urinary albumin excretion, arterial stiffness and low ankle–brachial index [19,20]. In the Diabetes Control and Complications Trial, SD of SBP was related to an increased risk of development/progression of nephropathy even after adjustment for mean BP levels . More recently, in diabetic patients from the US Department of Veterans Affairs healthcare system, Sohn et al. found a significant graded relationship between BPV and the incidence of nephropathy, retinopathy, and neuropathy, also after adjusting for mean SBP . In the Systolic Blood Pressure Related to Vascular Events and Premature Death in Type 2 Diabetes Mellitus study, addition of SD of SBP to the survival models significantly improved the 8-year risk classification for vascular complications and death .
The Brennan et al. study is the first report showing that BPV in diabetes is also associated with increased risk of DFU adding further support to the concept that high BPV can provide additional prognostic information to mean BP values in diabetes. An important methodological aspect addressed by Brennan et al. was the number of SBP readings used to calculate BPV. Previous studies have shown that SD of visit-to-visit SBP is proportional to the number of visits . Using consecutive visits in the Trial of Preventing Hypertension study, Levitan et al. showed that average SD was 5.6 mmHg when calculated from three visits, 6.8 mmHg from seven visits, and 7.7 mmHg from 18 visits . In the Brennan et al. study, it was possible that participants with deteriorating skin integrity have been seen more often than healthier people thereby causing an artifactual association between high BPV and DFU. To circumvent this possible source of error, in the present study, participants were categorized according to the number of SBP readings used to calculate their BPV (6 or fewer vs. 7–12). The results of the sensitivity analysis showed that the relationship between BPV-quartile and foot ulceration held in both BPV subgroups (P for trend <0.001 for both).
Another strength of the present study is that the authors tested whether DFU was associated with type of antihypertensive treatment. There has been some controversy over whether the beneficial effects of some antihypertensive drugs depend not only on the average BP level achieved during treatment but also on the greater consistency of BP control over the treatment period [25,26]. In the present study, the use of calcium channel blockers was associated with a reduced risk of incident DFU compared with other drugs, suggesting that calcium channel blockers, by reducing exposure to SBP variability, are associated with a reduced risk of ulceration . The authors’ conclusion was, thus, that BPV represents a potential new and modifiable target for clinicians to reduce the burden of DFU. However, it might well be that calcium channel blockers have a more beneficial effect on vascular damage than other drugs with a consequent favourable effect on BPV. Previous studies have shown that long-term BPV is smaller for calcium channel blockers than other types of treatment. Post hoc analyses of the Anglo-Scandinavian Cardiac Outcome Trial (ASCOT) and the Medical Research Council Trial of Treatment of Hypertension in Older Adults (MRC-elderly) have reported that intraindividual BPV is favourably affected by calcium channel blockers compared with other BP-lowering drugs . In a pooled analysis of data from the ASCOT-Blood Pressure Lowering Arm, Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial, Comparison of Amlodipine Versus Enalapril to Limit Occurrences of Thrombosis, NY92011, and R-0510 trials, BPV in the top 25th percentile was lower with amlodipine vs. other treatments (13.7 ± 3.2 vs. 14.3 ± 3.5 mmHg) . At variance with the above data, in the hypertensive patients of the European Lacidipine Study on Atherosclerosis (ELSA) trial, SBP variability was only slightly lower on calcium antagonist than on β-blocker treatment and little or no between-treatment difference was found for BPV of DBP . In the present study, comparisons between treatment subgroups showed a higher SBP variability in those taking calcium channel blockers . The authors were unable to explain this association arguing that no information was available on individual patients’ BPV before drug administration. Thus, it was impossible to establish whether calcium channel blockers actually decreased BPV within individuals. In conclusion, it is unclear whether and how BPV can be modified by the choice of antihypertensive agents  and whether the association between calcium channel blockers and lower rate of DFU found in the present study may be because of a more favourable effect on BPV.
An important limitation of the Brennan et al. study is that no information on treatment adherence was available. Oscillations in BP from one visit to another may be accounted for by erratic changes in systemic haemodynamics and arterial distensibility [25,26]. Dysfunction of the autonomic nervous system in diabetic patients may amplify these BP oscillations. Changes in release of humoral factors and myogenic reactivity may also contribute to increasing BPV [25,26,30]. However, a hypothesis often put forward in the literature is that visit-to-visit BPV might depend on the degree of adherence of the patient to the prescribed treatment . In an analysis of the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT), it was shown that patients showing a lower adherence to treatment had a significantly greater BPV than those with better adherence (P < 0.001) . Thus, in studies addressing the issue of long-term BPV, knowing degree of patients’ adherence is of primary importance. In the present study, the authors found that despite more intensive antidiabetic medication, patients with DFU had worse glycaemic control . This might indicate that patients with DFU had lower adherence to medication than the rest of the group, which would account for the higher BPV observed in the DFU subgroup.
Another limitation of the Brennan et al. study is the lack of information on smoking habits. Smoking can affect both BPV and the risk of DFU. In a pooled analysis of data from a large series of clinical trials, baseline DBP, estimated glomerular filtration rate, and smoking were the main predictors of BPV, with significant two-way interactions between smoking and both age and BMI . Smoking also is a major contributor to the development of DFU in diabetic patients [32–34]. A recent survey collecting information from 502 hospitalized diabetic patients in China, showed that smoking was associated with a high risk of DFU (χ2 = 8.386, P = 0.0007) . A study from the Center for Disease Control of the United States showed an increased risk of DFU in diabetic smokers (15.8%) compared with nonsmoking patients (10.3%) . In a 10-year follow-up of 825 patients diagnosed with type 2 diabetes, Yeh et al. demonstrated that the group with high BPV had a 1.679-fold (95% CI 1.141–2.472, P = 0.009) increased risk of peripheral artery disease (PAD) and that smoking status was another independent contributor to PAD. Nicotine promotes vasoconstriction and microangiopathy that may eventually lead to tissue ischemia, which results in nonhealing ulcers [35,36]. On the other hand, smoking also increases BPV and it is thus conceivable that both variables are associated with DFU. Thus, to know the independent role of BPV in determining DFU, smoking should always be included in the regression models.
The mechanisms whereby high BPV can promote DFU in diabetic patients are not obvious. A possible explanation is that high BPV in the long run causes microvascular and macrovascular alterations that may favour PAD and development of DFU. On the other hand, the starting point could be a primitive diabetic-related vascular damage, which can lead to both increased BPV and DFU. Although the role played by high BPV in this setting is difficult to establish, the association of BPV with DFU shown by Brennan et al. in their study supports the recommendation of avoiding large BP oscillations from one visit to another chiefly by improving patients’ adherence to treatment.
Conflicts of interest
There are no conflicts of interest.
1. van Baal J, Hubbard R, Game F, JeQcoate W. Mortality associated with acute charcot foot and neuropathic foot ulceration. Diabetes Care
2. Boulton AJ, Vileikyte L, Ragnarson-Tennvall G, Apelqvist J. The global burden of diabetic foot disease. Lancet
3. Omar MT, Alghadir A, Al-Wahhabi KK, Al-Askar AB. Efficacy of shockwave therapy on chronic diabetic foot ulcer: a single-blinded randomized controlled clinical trial. Diabetes Res Clin Pract
4. Singh N, Armstrong DG, Lipsky BA. Preventing foot ulcers in patients with diabetes. JAMA
5. Ramsey SC, Newton K, Blough D, McCullogh DK, Sandhu N, Reiber GE, et al. Incidence, outcomes, and cost of foot ulcers in patients with diabetes. Diabetes Care
6. Henriksson F, Agardh CD, Berne C, Bolinder J, Lonnqvist F, Stenstrøm P, et al. Direct medical cost for patients with type 2 diabetes in Sweden. J Int Med
7. Muller IS, Grauw WJC, Gerwen WHEM, Barthelin ML, Hoogen HJM, Rutten GEHM. Foot ulceration and lower limb amputation in type 2 diabetic patients in Dutch primary healthcare. Diabetes Care
8. Abbott CA, Carrington AL, Ashe H, Bath S, Every LC, Griffiths J, et al. The North West Diabetes Foot Care Study: incidence of and risk factors for new diabetic foot ulcerations in a community based patients cohort. Diabet Med
9. Margolis DJ, Kantor J, Santanna J, Strom BL, Berlin JA. Risk factors for delayed healing of neuropathic diabetic foot ulcers: A pooled analysis. Arch Dermatol
10. Brennan MB, Hess TM, Bartle B, Cooper JM, Kang J, Huang ES, et al. Diabetic foot ulcer severity predicts mortality among veterans with type 2 diabetes. J Diabetes Complications
11. Walsh JW, Hoffstad OJ, Sullivan MO, Margolis DJ. Association of diabetic foot ulcer and death in a population-based cohort from the United Kingdom. Diabet Med
12. Lehto S, Ronnemaa T, Pyorala K, Laakso M. Risk factors predicting lower extremity amputations in patients with NIDDM. Diabetes Care
13. Rathsman B, Jensen-Urstad K, Nyström T. Intensified insulin treatment is associated with improvement in skin microcirculation and ischaemic foot ulcer in patients with type 1 diabetes mellitus: a long-term follow-up study. Diabetologia
14. Feihl F, Liaudet L, Waeber B, Levy BI. Hypertension: a disease of the microcirculation? Hypertension
15. Boulton AJ. The diabetic foot: from art to science. The 18th Camillo Golgi lecture. Diabetologia
16. Brennan MB, Guihan M, Budiman-Mak E, Kang H, Lobo JM, Sutherland BL, et al. Increasing SBP variability is associated with an increased risk of developing incident diabetic foot ulcers. J Hypertens
17. Tamura K, Azushima K, Umemura S. Day-by-day home-measured blood pressure variability: another important factor in hypertension with diabetic nephropathy? Hypertens Res
18. Ushigome E, Fukui M, Hamaguchi M, Senmaru T, Sakabe K, Tanaka M, et al. The coefficient variation of home blood pressure is a novel factor associated with macroalbuminuria in type 2 diabetes mellitus. Hypertens Res
19. Okada H, Fukui M, Tanaka M, Inada S, Mineoka Y, Nakanishi N, et al. Visit-to-visit variability in systolic blood pressure is correlated with diabetic nephropathy and atherosclerosis in patients with type 2 diabetes. Atherosclerosis
20. Parati G, Ochoa JE, Salvi P, Lombardi C, Bilo G. Prognostic value of blood pressure variability and average blood pressure levels in patients with hypertension and diabetes. Diabetes Care
2013; 36 (Suppl 2):S312–S324.
21. Kilpatrick ES, Rigby AS, Atkin SL. The role of blood pressure variability in the development of nephropathy in type 1 diabetes. Diabetes Care
22. Sohn MW, Epstein N, Huang ES, Huo Z, Emanuele N, Stukenborg G, et al. Visit-to-visit systolic blood pressure variability and microvascular complications among patients with diabetes. J Diabetes Complications
23. Ohkuma T, Woodward M, Jun M, Muntner P, Hata J, Colagiuri S, et al. Prognostic value of variability in systolic blood pressure related to vascular events and premature death in type 2 diabetes mellitus: the ADVANCE-ON Study. Hypertension
24. Levitan EB, Kaciroti N, Oparil S, Julius S, Muntner P. Relationships between metrics of visit-to-visit variability of blood pressure. J Hum Hypertens
25. Mancia G. Short- and long-term blood pressure variability: present and future. Hypertension
26. Parati G, Ochoa JE, Lombardi C, Bilo G. Assessment and management of blood pressure variability. Nat Rev Cardiol
27. Rothwell PM, Howard SC, Dolan E, O’Brien E, Dobson JE, Dahlöf B, et al. ASCOT-BPLA, MRC Trial Investigators. Effects of beta blockers and calcium-channel blockers on withinindividual variability in blood pressure and risk of stroke. Lancet Neurol
28. Wang JG, Zhou D, Jeffers BW. Predictors of visit-to-visit blood pressure variability in patients with hypertension: an analysis of trials with an amlodipine treatment arm. J Am Soc Hypertens
29. Mancia G, Facchetti R, Parati G, Zanchetti A. Visit-to-visit blood pressure variability in the European Lacidipine Study on Atherosclerosis: methodological aspects and effects of antihypertensive treatment. J Hypertens
30. Mancia G. Visit-to-visit blood pressure variability: an insight into the mechanisms. Hypertension
31. Kronish IM, Lynch AI, Oparil S, Whittle J, Davis BR, Simpson LM, et al. The association between antihypertensive medication nonadherence and visit-to-visit variability of blood pressure: findings from the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial. Hypertension
32. Zhong A, Li G, Wang D, Sun Y, Zou X, Li B. The risks and external effects of diabetic foot ulcer on diabetic patients: a hospital-based survey in Wuhan area, China. Wound Repair Regen
33. Centers for Disease Control and Prevention. History of foot ulcer among persons with diabetes–United States, 2000–2002. Morb Mortal Wkly Rep
34. Yeh CH, Yu HC, Huang TY, Huang PF, Wang YC, Chen TP, Yin SY. High systolic and diastolic blood pressure variability is correlated with the occurrence of peripheral arterial disease in the first decade following a diagnosis of type 2 diabetes mellitus: a new biomarker from old measurement. Biomed Res Int
35. Śliwińska-Mossoń M, Milnerowicz H. The impact of smoking on the development of diabetes and its complications. Diab Vasc Dis Res
36. Liu CC, Yeh HI. Nicotine: a double-edged sword in atherosclerotic disease. Acta Cardiol Sin