Diabetologia

, Volume 56, Issue 5, pp 1140–1147 | Cite as

The impact of metabolic control and QTc prolongation on all-cause mortality in patients with type 2 diabetes and foot ulcers

Article

Abstract

Aims/hypothesis

The increased all-cause mortality in patients with chronic diabetic foot ulcers cannot fully be explained by traditional cardiovascular risk factors. The significance of heart-rate-corrected QT (QTc) prolongation, a finding often seen in these patients, is unknown. Recently, the importance of metabolic control and hypoglycaemia has been discussed. The aim of this study was to evaluate the impact of different HbA1c levels and QTc prolongation on all-cause mortality in the high-risk population of patients with type 2 diabetes mellitus and foot ulcers.

Methods

All patients with type 2 diabetes, younger than 80 years, visiting our diabetes foot unit, with a foot ulcer duration >4 weeks, were screened for participation. Patients on dialysis were excluded. Patients were grouped according to HbA1c level and QTc time ≤ or > 440 ms.

Results

Patients (n = 214, median age 69.1 years) were grouped according to HbA1c level (HbA1c < 7.5% [<58 mmol/mol] n = 81, 7.5–8.9% [58–74 mmol/mol] n = 70, >8.9% [>74 mmol/mol] n = 63). Baseline characteristics, including use of potential hypoglycaemic drugs, were similar between groups. During the 8 years of follow-up 151 patients died (70.6%) and HbA1c < 7.5% (<58 mmol/mol) was strongly associated with increased mortality. The highest mortality was seen in patients with a combination of HbA1c < 7.5% (<58 mmol/mol) and QTc prolongation, with an 8 year mortality of 92.1% as compared with 48.8% in those with HbA1c < 7.5% (<58 mmol/mol) but without QTc prolongation.

Conclusion/interpretations

HbA1c < 7.5% (<58 mmol/mol) in a high-risk population of patients with type 2 diabetes and foot ulcers is associated with a significantly higher mortality, particularly in patients with QTc prolongation.

Keywords

Diabetes Foot ulcers HbA1c Metabolic control Mortality QTc prolongation 

Abbreviations

ABI

Ankle brachial index

ACCORD

Action to Control Cardiovascular Risk in Diabetes

CAN

Cardiac autonomic neuropathy

CVD

Cardiovascular disease

DFU

Diabetic foot unit

eGFR

Estimated glomerular filtration rate

IQR

Interquartile range

MDRD

Modification of diet in renal disease

MI

Myocardial infarction

NICE-SUGAR

Normoglycemia in Intensive Care Evaluation – Survival Using Glucose Algorithm Regulation

PVD

Peripheral vascular disease

QTc interval

Heart-rate-corrected QT interval

Introduction

Patients with a history of diabetic foot ulcers are considered to be a high-risk population for cardiovascular disease (CVD) and increased all-cause mortality [1, 2]. This risk increment can not fully be explained by traditional CVD risk factors, such as peripheral arterial disease, history of myocardial infarction (MI) or renal dysfunction [2]. The importance of other diabetic complications, including microvascular disease and neuropathy, needs to be further evaluated.

In patients with type 2 diabetes, prospective studies have shown an association between the degree of hyperglycaemia, measured as HbA1c, and incidence of cardiovascular events [3, 4, 5, 6]. Based on these studies, EASD and ADA recommend a strict metabolic control with HbA1c <7.0% (<52 mmol/mol) for most adults with diabetes [7, 8]. However, when the ACCORD (Action to Control Cardiovascular Risk in Diabetes) study was published, showing an increased mortality among patients randomised to receive intensive glycaemic control, a less stringent HbA1c goal was suggested for patients with a history of severe hypoglycaemia, a limited life expectancy or advanced diabetic complications [9]. The importance of hypoglycaemia has frequently been discussed as a plausible factor or mediator of this increased mortality, although no study has been able to show causality [10, 11, 12]. Hypoglycaemia alters several risk factors for mortality, including vasoconstriction and cytokine responses, and increases the likelihood of lethal arrhythmias [13, 14, 15, 16, 17].

It has been demonstrated that patients with diabetes mellitus have a more frequent occurrence of heart-rate-corrected QT (QTc) interval prolongation than non-diabetic patients [18]. Prolonged QTc time is associated with an increased risk of both cardiovascular and all-cause mortality in the general population [19, 20]. Long QTc time is related to several factors–older age, coronary heart disease, intake of certain drugs and presence of cardiac autonomic neuropathy (CAN, a serious complication of diabetes), as well as hypoglycaemia [18, 21, 22].

The aim of our study was to evaluate the impact of different HbA1c levels and QTc prolongation on all-cause mortality in a predefined high-risk population consisting of patients with type 2 diabetes mellitus and a history of hard-to-heal foot ulcers.

Methods

Patient characteristics and measurement of variables

All patients with type 2 diabetes mellitus and age below 80 years, visiting our Diabetic Foot Unit (DFU; Skåne University Hospital, Lund, Sweden) during two consecutive years were screened for study participation. Those with an ulcer that did not heal within 4 weeks of treatment were included in this study. Patients with ongoing dialysis and those without an HbA1c or ECG registration within a 4 month period following the first visit to the DFU were excluded.

Patients were grouped according to HbA1c level: group 1, HbA1c < 7.5% (<58 mmol/mol); group 2, HbA1c 7.5–8.9% (58–74 mmol/mol) and group 3, HbA1c > 8.9% (>74 mmol/mol).

HbA1c, creatinine, cholesterol, HDL-cholesterol, LDL-cholesterol and triacylglycerol were analysed in our local certified laboratory. Estimated glomerular filtration rate (eGFR) was derived from plasma creatinine level using the modification of diet in renal disease (MDRD) equation [23]. An eGFR ≥ 60 ml min−1 1.73 m−2 was considered to indicate normal renal function. Hypertension was defined as systolic blood pressure ≥140 mmHg, diastolic blood pressure ≥90 mmHg or current use of blood-pressure-lowering drugs. Hyperlipidaemia was considered present if total cholesterol was >5.0 mmol/l, LDL-cholesterol was >2.5 mmol/l or the patient was prescribed a cholesterol-lowering drug. Peripheral vascular disease (PVD) was defined by the presence of an abnormal ankle brachial index (ABI) value (≤0.9 or ≥1.4) or a history of previously performed vascular surgery including percutaneous transluminal angioplasty [24]. The ABI was measured as the ratio of systolic ankle pressure divided by arm blood pressure. Systolic ankle pressure was analysed with a pen doppler over the dorsal pedal or posterior tibial arteries.

A standard 12-lead resting ECG was taken during a regular visit to the clinic, using a Siemens ECG machine (Siemens Elema, Solna, Sweden). The QT interval was calculated from the beginning of the QRS complex to the end of the T wave, using the validated Sicard 440/740 ECG computer-analysis programme (Megacart version 3 V4, 7/2.38/23; Siemens Elema) [25, 26]. The QT intervals were then corrected for heart rate to obtain the QTc value using Bazett’s formula [27]. A QTc value greater than 440 ms was considered abnormal and patients in each HbA1c group were divided according to QTc time ≤ or >440 ms [28]. Mortality data was obtained from the Swedish National Death Registry. This study was approved by the Local Ethics Committee in Lund, Sweden and was carried out in accordance with the Declaration of Helsinki, as revised in 2000. All patients have given their consent.

Statistical analysis

Patient characteristics are summarised by descriptive statistics. Continuous variables are expressed as median and interquartile range (IQR; 25–75 percentile) and categorical variables are presented as percentages. Continuous data were compared using Mann–Whitney U test and categorical variables using Fisher’s exact test. Univariate survival analysis was performed by Kaplan–Meier analysis and overall significance was calculated by the Gehan–Wilcoxon test.

Cox proportional hazard regression models were applied to study the independent association between HbA1c level, QTc prolongation and mortality. Initial analyses included the following basal characteristics with plausible impact on mortality: sex, previous MI, heart failure, PVD, hyperlipidaemia, renal impairment (eGFR ≥60, 45–59, 30–44, <30 ml min−1 min 1.73 m−2), diabetes duration (decades), smoking, age (grouped according to decade of age) and usage of insulin, insulin-releasing agents or beta blockers. Potential confounding factors with a p value <0.10 were entered in the final analyses. The results of these Cox proportional hazards models are presented as HR with 95% CI.

All statistical analyses where performed using Statistica software version 10 (Statsoft, Tulsa, OK, USA) and statistical significance was assessed at the two-tailed 0.05 threshold.

Results

Baseline characteristics

Of the initial sample of 224 patients with type 2 diabetes and foot ulcers, ten were excluded from the study due to lack of HbA1c data. Thus, 214 patients (37.9% women) with type 2 diabetes mellitus were grouped according to their HbA1c level (HbA1c < 7.5% [<58 mmol/mol] n = 81, 7.5–8.9% [58–74 mmol/mol] n = 70, >8.9% [>74 mmol/mol] n = 63).

The median age in the whole study population was 69.1 years (range 63–76) and did not differ between groups. As shown in Table 1, QTc prolongation and PVD was most prevalent in patients with HbA1c < 7.5% (<58 mmol/mol). There were no differences between groups in the usage of drugs with potential hypoglycaemic effect, although insulin therapy was most frequently used in the group of patients with the highest HbA1c levels. Prescription of beta blockers, as well as other drugs with potential effect on the QT interval (tricyclic antidepressants, certain antibiotics [e.g. macrolides and quinolones]) did not differ between groups and did not affect the outcome of this study.
Table 1

Baseline characteristics of patients with different HbA1c levels

Characteristic

HbA1c < 7.5% (<58 mmol/mol)

HbA1c 7.5–8.9% (58–74 mmol/mol)

HbA1c > 8.9% (>75 mmol/mol)

p value

n

81

70

63

 

Age (years)

72 (67–77)

71 (65–76)

67 (61–75)

NS

Diabetes duration (years)

11 (5–16)

11 (8–15)

12 (8–20)

NS

HbA1c (%)

6.8 (6.3–7.2)

8.2 (7.8–8.5)

9.9 (9.2–10.8)

0.00000

HbA1c (mmol/mol)

51 (45–55)

66 (62–69)

85 (77–95)

 

QTc > 440 ms (%)

46.9

30.0

30.7

0.019a

Creatinine (μmol/l)

82 (68–100)

85 (66–103)

73 (56–97)

NS

eGFR < 60 ml min−1 (1.73 m)−2 (%)

28.4

34.8

27.0

NS

Sex, female/male (%)

32.1/67.9

38.6/61.4

44.4/55.6

NS

Previous MI (%)

33.3

28.9

22.2

NS

Heart failure (%)

24.7

28.6

19.1

NS

Hypertension (%)

75.3

68.6

68.3

NS

Hyperlipidaemia (%)

39.5

37.1

36.5

NS

Smoking (ever) (%)

56.8

51.4

54.0

NS

PVD (%)

58.0

42.9

25.4

0.07b

    

<0.01c

    

0.04d

Previous vascular surgical intervention in a lower limb

34.6

20.0

12.7

0.07b

    

<0.01c

    

0.35d

Glucose-lowering treatment

    

 Diet only (%)

11.1

1.4

1.6

NS

 Metformin only (%)

6.2

11.4

4.8

NS

 Sulfonylurea only (%)

19.8

14.3

11.1

NS

 Metformin + sulfonylurea (%)

11.1

17.1

9.5

NS

 Insulin alone or in combination (%)

51.9

55.7

73.0

NSb

    

0.01c

    

<0.05d

 Insulin or sulfonylurea alone or in combination (%)

82.7

87.1

93.7

NS

Beta blocker (%)

27.2

30.0

33.3

NS

Digoxin (%)

9.9

15.7

9.5

NS

Tricyclic antidepressant (%)

4.9

1.4

3.2

NS

Selective serotonin re-uptake inhibitor (%)

6.2

13.0

9.7

NS

Macrolide (%)

0

0

0

NS

Quinolone (%)

8.8

17.4

9.7

NS

Proton-pump inhibitor (%)

13.6

10.0

6.3

NS

Data are given as percentage or median (IQR)

aHbA1c < 7.5% (<58 mmol/mol) vs ≥7.5% (≥58 mmol/mol)

bHbA1c < 7.5% (<58 mmol/mol) vs 7.5–8.9% (58–74 mmol/mol)

cHbA1c < 7.5% (<58 mmol/mol) vs >8.9% (>75 mmol/mol)

dHbA1c7.5–8.9% (58–74 mmol/mol) vs >8.9% (>75 mmol/mol)

Survival analysis

During a follow-up period of 8 years, 151 patients died (70.6% of total). As shown in Fig. 1, an HbA1c level <7.5% (<58 mmol/mol) was strongly associated with increased mortality.
Fig. 1

Kaplan–Meier survival curve showing 8 year mortality in patients grouped according to HbA1c levels, p < 0.01 for pooled comparison. For separate comparisons: HbA1c < 7.5% (<58 mmol/mol) vs HbA1c 7.5–8.9% (58–74 mmol/mol), p = 0.06. HbA1c < 7.5% (<58 mmol/mol vs HbA1c > 8.9% [>74 mmol/mol]), p = 0.02. HbA1c 7.5–8.9% (58–74 mmol/mol) vs HbA1c > 8.9% (>74 mmol/mol), NS Solid line, HbA1c < 7.5% (<58 mmol/mol); dotted line, HbA1c 7.5–8.9% (58–74 mmol/mol); dashed line, HbA1c > 8.9% (>74 mmol/mol)

In a Cox hazard model including the following possible confounding factors: HbA1c level, age, sex, diabetes duration, hyperlipidaemia, renal impairment, smoking habits, presence of heart failure, previous MI, PVD, usage of insulin or insulin-releasing drugs, usage of beta blockers and QTc prolongation, only age, sex, HbA1c level and QTc prolongation were associated (p < 0.10) with mortality and thus included in the final analysis. The outcome of this analysis showed that both HbA1c < 7.5% (<58 mmol/mol) and presence of QTc prolongation were independently associated with a higher mortality (Table 2).
Table 2

Predictors of all-cause mortality in patients with type 2 diabetes mellitus and hard-to-heal ulcers based on Cox proportional analyses adjusted for plausible confounders

All-cause mortality

HbA1c < 7.5% vs ≥7.5%a

p value

Age, risk per decade

p value

Female sex

p value

QTc prolongation

p value

2 year mortality

1.88 (1.05, 3.36)

0.033

1.72 (1.07, 2.75)

0.025

0.61 (0.32, 1.16)

NS

1.74 (0.98, 3.12)

0.060

4 year mortality

1.78 (1.16, 2.73)

0.009

1.56 (1.12, 2.17)

0.008

0.61 (0.37, 0.98)

0.042

2.08 (1.35, 3.22)

0.001

6 year mortality

1.47 (1.01, 2.14)

0.045

1.63 (1.22, 2.17)

0.001

0.64 (0.42, 0.97)

0.035

1.96 (1.34, 2.86)

0.001

8 year mortality

1.41 (1.00, 2.00)

0.052

1.51 (1.17, 1.95)

0.001

0.63 (0.43, 0.93)

0.019

2.00 (1.40, 2.85)

0.000

Data are given as HR (95% CI)

a< 58 mmol/mol vs ≥58 mmol/mol

In a subgroup analysis evaluating the impact of QTc prolongation at different HbA1c levels, highest mortality was found in patients with HbA1c < 7.5% (<58 mmol/mol) and QTc time >440 ms (Fig. 2). In these patients 8 year mortality was 92.1% as compared with 48.8% in those with HbA1c < 7.5% (<58 mmol/mol) but without QTc prolongation (p < 0.00001). A statistically non-significant trend towards worse outcome in patients with QTc prolongation was seen in the other two HbA1c groups (Fig. 2). In a Cox hazard model adjusted for the same plausible confounding factors as used in the previous analysis, HbA1c/QTc (patients with both HbA1c <7.5% [<58 mmol/mol] and QTc prolongation vs all other patients), age and sex was associated (p < 0.10) with an increased 2, 4, 6 and 8 year mortality and thus included in the final analysis. Presence of hyperlipidaemia was associated with 2 year mortality in the initial but not in the final analysis (p = 0.16). Patients with the combination of QTc time >440 ms and HbA1c < 7.5% (<58 mmol/mol) were at highest mortality risk in our study (Table 3).
Fig. 2

Kaplan–Meier survival curve showing 8 year mortality in patients grouped according to HbA1c levels and presence of QTc prolongation, defined as QTc time >440 ms. p < 0.0001 for pooled comparison. For separate comparisons: QTc prolongation and HbA1c < 7.5% (<58 mmol/mol) vs all three groups with normal QTc-time separately p < 0.0001; vs group with QTc prolongation and HbA1c 7.5–8.9% (58–74 mmol/mol) p = 0.023; and vs group with QTc prolongation and HbA1c > 8.9% (>74 mmol/mol) p = 0.015. QTc prolongation and HbA1c 7.5–8.9% (58–74 mmol/mol) vs normal QTc time and HbA1c > 8.9% (>74 mmol/mol), p = 0.025. All other comparisons NS. Blue lines, patients with QTc prolongation; red lines, patients without QTc prolongation; solid line, HbA1c < 7.5% (<58 mmol/mol); dotted line, HbA1c 7.5–8.9% (58–74 mmol/mol); dashed line, HbA1c > 8.9% (>74 mmol/mol)

Table 3

Importance of the combination of QTc prolongation and HbA1c < 7.5% (58 mmol/mol) on all-cause mortality in patients with type 2 diabetes mellitus and hard-to-heal ulcers based on Cox proportional analyses adjusted for plausible confounders

All-cause mortality

HbA1c < 7.5%a + long QTc time vs HbA1c < 7.5%a + QTc ≤440 ms and HbA1c ≥ 7.5%a

p value

Age, risk per decade

p value

Female sex

p value

2 year mortality

2.80 (1.54, 5.09)

<0.001

1.76 (1.10, 2.82)

0.019

0.56 (0.29, 1.07)

0.079

4 year mortality

2.65 (1.66, 4.24)

<0.000

1.63 (1.18, 2.27)

0.003

0.54 (0.34, 0.87)

0.012

6 year mortality

2.55 (1.67, 3.87)

<0.000

1.69 (1.27, 2.25)

<0.000

0.58 (0.39, 0.87)

0.09

8 year mortality

2.76 (1.86, 4.09)

<0.0000

1.57 (1.21, 2.02)

0.001

0.57 (0.39, 0.84)

0.004

Data are given as HRs (95% CI)

All statistically significant risk factors are presented in the table

a< 58 mmol/mol

A statistically significant correlation (r = 0.23, p = 0.034) was present between HbA1c level and QTc time in the groups of patients not using any potentially QTc-prolonging drug (beta blockers, selective serotonin re-uptake inhibitors, macrolides, quinolones, proton-pump inhibitors or tricyclic antidepressants), whereas this was not the case in patients prescribed any of these drugs.

Discussion

It is well documented that improved metabolic control reduces microvascular complications in patients with type 2 diabetes mellitus, although it is not clear whether patients with type 2 diabetes mellitus and hard-to-heal foot ulcers benefit from strict glycaemic control. In our 8 year follow-up study evaluating survival in type 2 diabetes patients with hard-to-heal foot ulcers, short- as well as long-term all-cause mortality was higher in patients with HbA1c levels below 7.5% (58 mmol/mol). Our finding is in accordance with the increased mortality in the intensively treated arm in the ACCORD trial and with the outcome of a large British cohort study including 47,970 patients with type 2 diabetes [9, 29]. The outcome of this latter study by Currie and co-workers showed a U-formed association between HbA1c and all-cause mortality, with the lowest HR at an HbA1c level of about 7.5% (58 mmol/mol). The adjusted HR of all-cause mortality for patients with the lowest HbA1c decile was 1.59 [29]. Similar outcomes have been seen in studies evaluating the impact of HbA1c levels in diabetic patients with severe renal complications [30, 31]. In a large cohort study including all diabetic patients with stage 3 and 4 chronic kidney disease in Alberta, Canada, the association between all-cause mortality and HbA1c was J-shaped [30]. In a smaller study prospectively evaluating all-cause mortality in diabetic patients beginning dialysis treatment, a decreased mortality risk was observed with increasing HbA1c [31]. The follow-up time in these studies was 46 and 32 months, respectively. Contrarily, in-hospital mortality following acute MI was not associated with HbA1c levels in an American study using data from a nationwide voluntary register [32].

A plausible explanation for this increased mortality might be a higher frequency of hypoglycaemic episodes in patients with a lower HbA1c. It is well proven that the use of insulin or insulin secretagogues can cause severe and fatal hypoglycaemia. In type 1 diabetes mellitus, 6–10% of all mortality is estimated to be associated with hypoglycaemia [33, 34, 35]. In addition, in the Normoglycemia in Intensive Care Evaluation – Survival Using Glucose Algorithm Regulation (NICE-SUGAR) study a strong association between hypoglycaemia and all-cause mortality was seen [11]. The follow-up period in NICE-SUGAR was 90 days and the median time from the first episode of hypoglycaemia to death was 7 days. A causal relationship between hypoglycaemia and mortality is likely for several reasons. Cardiac arrhythmias occurring during hypoglycaemia were first described in psychiatric patients treated with insulin shock in the 1930s [36]. Several case reports have also described an association between arrhythmia and spontaneous hypoglycaemia [37, 38]. Further, hypoglycaemia triggers an array of counter-regulatory responses that would normally return blood glucose to non-pathological levels. Glucagon, adrenaline (epinephrine), noradrenaline (norepinephrine), cortisol, growth hormone, corticotropin, pancreatic polypeptide and the autonomic nervous system are all activated, leading to alterations in blood flow and blood composition, vasoconstriction, white-cell activation and a release of inflammatory mediators and cytokines[13, 14, 15, 17]. Several studies have also shown an association between hypoglycaemia and QTc prolongation in type 1 as well as type 2 diabetes mellitus [39, 40]. In our study QTc prolongation might be linked to hypoglycaemia, as it was more frequently present in the group of patients with the lowest HbA1c levels (47 vs 30% in the other two groups), wherein 83% were prescribed drugs with hypoglycaemic effects (insulin or sulfonylurea). Further, a negative correlation between QTc time and HbA1c was present in our patients without QTc-prolonging drugs, suggesting a plausible association between these two risk factors.

QTc prolongation, a condition known to be associated with CAN, has been shown to increase the risk of arrhythmia and sudden death in diabetic patients [41, 42]. In the ACCORD trial, the presence of CAN, defined as a combination of pathological QT index and abnormal heart-rate variability, was associated with increased mortality risk [43]. The highest mortality rate in our study was among patients with both QTc prolongation and HbA1c < 7.5% (<58 mmol/mol). In this group 8 year mortality was 92% as compared with 49% in those patients with similar HbA1c but normal QTc time.

Although a causal relationship between these two factors and mortality is plausible, it will be difficult (and perhaps impossible) to sort out the true determinants of our outcome. However, the increased mortality in the group of patients with prolonged QTc time and the lowest HbA1c level could not be explained by differences in traditional cardiovascular risk factors, such as MI, heart failure, hypertension or smoking habits, and our findings were sustained after being adjusted for possible confounders. PVD, as well as a history of previous vascular surgical intervention in the lower limb, was more frequently present in the group of patients with the lowest HbA1c. The 8 year mortality rate was higher in patients with a history of vascular intervention in a lower limb than in those without such intervention (74.1 vs 58.6%, p = 0.032); however, in the Cox proportional hazard model neither this intervention nor presence of PVD were independently associated with mortality. This outcome is in accordance with the result of a UK study evaluating factors associated with mortality in diabetic patients with novel foot ulcers [44]. In this study presence of PVD was associated with a higher mortality rate but after adjustment for confounding factors only older age turned out to be a significant predictor of mortality.

Autonomic neuropathy, which might not only lead to decreased adrenergic awareness of hypoglycaemia but also to increased risk of cardiac arrhythmia, may have been more frequently present in those patients with prolonged QTc time[45]. An alternative explanation is that QTc prolongation in combination with a low HbA1c level, occurs as a result of disease processes that confer a predisposition to death, and that this cluster of risk factors represents a marker, rather than a cause, of an increased risk of death.

Possible limitations of this study include selection bias, although this is not a critical issue as all patients with diabetic foot problems in our catchment area are, with few exceptions, referred to our clinic. Our registry, including all patients visiting our clinic, as well as all charts from the years of inclusion, was carefully monitored. Mortality data are robust as the Swedish National Death Registry capture data on 100% of all deaths. The fact that we only included baseline clinical variables and did not account for time-varying covariates, might affect outcome. Further, QTc time might be influenced by several factors, including drugs and acute heart disease. All ECGs at our clinic were taken during non-acute, resting conditions, which limits (although does not exclude) biases such as myocardial ischaemia or acute heart failure. Neither could we identify any significant differences in prescription patterns of the most commonly used drugs with plausible QTc-prolonging actions (including beta blockers, tricyclic antidepressants, macrolides and quinolones) between groups. We did not collect data on the frequency of hypoglycaemia, so we can therefore only speculate on its importance as a possible cause or mediator of the increased mortality seen in patients with low HbA1c level and prolonged QTc interval. Still, a causal relationship is plausible, and in the EURODIAB insulin dependent diabetes mellitus (IDDM) complications trial an annual occurrence of at least three severe hypoglycaemic events was, independently of confounders, associated with presence of QTc prolongation [46]. Another confounder might be that HbA1c may decrease with older age, as well as being associated with terminal disease, but in our study no differences in age, medications or comorbidities were seen between HbA1c groups. In this study we have neither evaluated cause of death nor autonomic nervous function, which limits our opportunity to identify any relationship between QTc time, autonomic function and cause of death. Despite these limitations we identified a group of patients with clinically and statistically significant increased mortality. However, to fully evaluate the importance of metabolic control and QTc time on mortality in this high-risk population a larger prospective multicentre study needs to be initiated.

In conclusion, in this high-risk population of patients with type 2 diabetes mellitus and hard-to-heal foot ulcers, an HbA1c level below 7.5% (58 mmol/mol) was associated with higher mortality, particularly in the presence of QTc prolongation. This finding indicates the clinical importance of ECG screening and suggests that, in patients with prolonged QT intervals, drugs which are known to affect QT interval and hypoglycaemia should be avoided.

Notes

Funding

This study was supported by the Swedish Diabetes Foundation, Sydvästra Skånes Diabetesförening, Krapperup Foundation, Crafoord Foundation, Skane county council’s research and development foundation and Faculty of Medicine (ALF), Lund University, Sweden.

Duality of interest

Both authors declare there is no duality of interest associated with this manuscript.

Contribution statement

Both authors have substantially contributed to the conception and design of the study, acquisition of data, analysis and interpretation of data, drafted the article and given final approval of the version to be published.

References

  1. 1.
    Boulton AJ (2008) The diabetic foot: grand overview, epidemiology and pathogenesis. Diabetes Metabol Res Rev 24(Suppl 1):S3–S6CrossRefGoogle Scholar
  2. 2.
    Gershater MA, Londahl M, Nyberg P et al (2009) Complexity of factors related to outcome of neuropathic and neuroischaemic/ischaemic diabetic foot ulcers: a cohort study. Diabetologia 52:398–407PubMedCrossRefGoogle Scholar
  3. 3.
    UK Prospective Diabetes Study (UKPDS) Group (1998) Effect of intensive blood-glucose control with metformin on complications in overweight patients with type 2 diabetes (UKPDS 34). Lancet 352:854–865CrossRefGoogle Scholar
  4. 4.
    UK Prospective Diabetes Study (UKPDS) Group (1998) Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). Lancet 352:837–853CrossRefGoogle Scholar
  5. 5.
    Gaede P, Lund-Andersen H, Parving HH, Pedersen O (2008) Effect of a multifactorial intervention on mortality in type 2 diabetes. N Engl J Med 358:580–591PubMedCrossRefGoogle Scholar
  6. 6.
    Holman RR, Paul SK, Bethel MA, Matthews DR, Neil HA (2008) 10-year follow-up of intensive glucose control in type 2 diabetes. N Engl J Med 359:1577–1589PubMedCrossRefGoogle Scholar
  7. 7.
    American Diabetes Association (2012) Standards of medical care in diabetes–2012. Diabetes Care 35(Suppl 1):S11–S63Google Scholar
  8. 8.
    Inzucchi SE, Bergenstal RM, Buse JB et al (2012) Management of hyperglycaemia in type 2 diabetes: a patient-centered approach. Position statement of the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetologia 55:1577–1596PubMedCrossRefGoogle Scholar
  9. 9.
    Gerstein HC, Miller ME, Byington RP et al (2008) Effects of intensive glucose lowering in type 2 diabetes. N Engl J Med 358:2545–2559PubMedCrossRefGoogle Scholar
  10. 10.
    Dluhy RG, McMahon GT (2008) Intensive glycemic control in the ACCORD and ADVANCE trials. N Engl J Med 358:2630–2633PubMedCrossRefGoogle Scholar
  11. 11.
    Finfer S, Liu B, Chittock DR et al (2012) Hypoglycemia and risk of death in critically ill patients. N Engl J Med 367:1108–1118PubMedCrossRefGoogle Scholar
  12. 12.
    Cryer PE (2011) Death during intensive glycemic therapy of diabetes: mechanisms and implications. Am J Med 124:993–996PubMedCrossRefGoogle Scholar
  13. 13.
    Gogitidze Joy N, Hedrington MS, Briscoe VJ, Tate DB, Ertl AC, Davis SN (2010) Effects of acute hypoglycemia on inflammatory and pro-atherothrombotic biomarkers in individuals with type 1 diabetes and healthy individuals. Diabetes Care 33:1529–1535PubMedCrossRefGoogle Scholar
  14. 14.
    Wright RJ, Newby DE, Stirling D, Ludlam CA, Macdonald IA, Frier BM (2010) Effects of acute insulin-induced hypoglycemia on indices of inflammation: putative mechanism for aggravating vascular disease in diabetes. Diabetes Care 33:1591–1597PubMedCrossRefGoogle Scholar
  15. 15.
    Adler GK, Bonyhay I, Failing H, Waring E, Dotson S, Freeman R (2009) Antecedent hypoglycemia impairs autonomic cardiovascular function: implications for rigorous glycemic control. Diabetes 58:360–366PubMedCrossRefGoogle Scholar
  16. 16.
    Wright RJ, Frier BM (2008) Vascular disease and diabetes: is hypoglycaemia an aggravating factor? Diabetes Metabol Res Rev 24:353–363CrossRefGoogle Scholar
  17. 17.
    Keller-Wood ME, Shinsako J, Dallman MF (1983) Inhibition of the adrenocorticotropin and corticosteroid responses to hypoglycemia after prior stress. Endocrinology 113:491–496PubMedCrossRefGoogle Scholar
  18. 18.
    Festa A, D'Agostino R Jr, Rautaharju P, Mykkanen L, Haffner SM (2000) Relation of systemic blood pressure, left ventricular mass, insulin sensitivity, and coronary artery disease to QT interval duration in nondiabetic and type 2 diabetic subjects. Am J Cardiol 86:1117–1122PubMedCrossRefGoogle Scholar
  19. 19.
    Goldberg RJ, Bengtson J, Chen ZY, Anderson KM, Locati E, Levy D (1991) Duration of the QT interval and total and cardiovascular mortality in healthy persons (The Framingham Heart Study experience). Am J Cardiol 67:55–58PubMedCrossRefGoogle Scholar
  20. 20.
    Montanez A, Ruskin JN, Hebert PR, Lamas GA, Hennekens CH (2004) Prolonged QTc interval and risks of total and cardiovascular mortality and sudden death in the general population: a review and qualitative overview of the prospective cohort studies. Arch Intern Med 164:943–948PubMedCrossRefGoogle Scholar
  21. 21.
    Macfarlane PW, McLaughlin SC, Devine B, Yang TF (1994) Effects of age, sex, and race on ECG interval measurements. J Electrocardiol 27(Suppl):14–19PubMedCrossRefGoogle Scholar
  22. 22.
    Dekker JM, Schouten EG, Klootwijk P, Pool J, Kromhout D (1994) Association between QT interval and coronary heart disease in middle-aged and elderly men. The Zutphen Study. Circulation 90:779–785PubMedCrossRefGoogle Scholar
  23. 23.
    Levey AS, Coresh J, Greene T et al (2006) Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Ann Intern Med 145:247–254PubMedGoogle Scholar
  24. 24.
    Marso SP, Hiatt WR (2006) Peripheral arterial disease in patients with diabetes. J Am Coll Cardiol 47:921–929PubMedCrossRefGoogle Scholar
  25. 25.
    Willems JL, Abreu-Lima C, Arnaud P et al (1991) The diagnostic performance of computer programs for the interpretation of electrocardiograms. N Engl J Med 325:1767–1773PubMedCrossRefGoogle Scholar
  26. 26.
    Macfarlane PW, Devine B, Latif S, McLaughlin S, Shoat DB, Watts MP (1990) Methodology of ECG interpretation in the Glasgow program. Meth Inform Med 29:354–361PubMedGoogle Scholar
  27. 27.
    Bazett H (1920) An analysis of time relations of the electrocardiogram. Heart 7:353–370Google Scholar
  28. 28.
    Algra A, Tijssen JG, Roelandt JR, Pool J, Lubsen J (1993) QT interval variables from 24 hour electrocardiography and the two year risk of sudden death. Br Heart J 70:43–48PubMedCrossRefGoogle Scholar
  29. 29.
    Currie CJ, Peters JR, Tynan A et al (2010) Survival as a function of HbA(1c) in people with type 2 diabetes: a retrospective cohort study. Lancet 375:481–489PubMedCrossRefGoogle Scholar
  30. 30.
    Shurraw S, Hemmelgarn B, Lin M et al (2011) Association between glycemic control and adverse outcomes in people with diabetes mellitus and chronic kidney disease: a population-based cohort study. Arch Intern Med 171:1920–1927PubMedCrossRefGoogle Scholar
  31. 31.
    Sturm G, Lamina C, Zitt E et al (2011) Association of HbA1c values with mortality and cardiovascular events in diabetic dialysis patients. The INVOR study and review of the literature. PLoS One 6:e20093PubMedCrossRefGoogle Scholar
  32. 32.
    Britton KA, Aggarwal V, Chen AY et al (2011) No association between hemoglobin A1c and in-hospital mortality in patients with diabetes and acute myocardial infarction. Am Heart J 161(657–663):e651Google Scholar
  33. 33.
    Tanenberg RJ, Newton CA, Drake AJ (2010) Confirmation of hypoglycemia in the ‘dead-in-bed’ syndrome, as captured by a retrospective continuous glucose monitoring system. Endocr Pract 16:244–248PubMedCrossRefGoogle Scholar
  34. 34.
    Skrivarhaug T, Bangstad HJ, Stene LC, Sandvik L, Hanssen KF, Joner G (2006) Long-term mortality in a nationwide cohort of childhood-onset type 1 diabetic patients in Norway. Diabetologia 49:298–305PubMedCrossRefGoogle Scholar
  35. 35.
    Jacobson AM, Musen G, Ryan CM et al (2007) Long-term effect of diabetes and its treatment on cognitive function. N Engl J Med 356:1842–1852PubMedCrossRefGoogle Scholar
  36. 36.
    Goldman D (1940) The electrocardiogram in insulin shock. Arch Intern Med 66:93–108CrossRefGoogle Scholar
  37. 37.
    Chelliah YR (2000) Ventricular arrhythmias associated with hypoglycaemia. Anaesth Intensive Care 28:698–700PubMedGoogle Scholar
  38. 38.
    Shimada R, Nakashima T, Nunoi K, Kohno Y, Takeshita A, Omae T (1984) Arrhythmia during insulin-induced hypoglycemia in a diabetic patient. Arch Intern Med 144:1068–1069PubMedCrossRefGoogle Scholar
  39. 39.
    Murphy NP, Ford-Adams ME, Ong KK et al (2004) Prolonged cardiac repolarisation during spontaneous nocturnal hypoglycaemia in children and adolescents with type 1 diabetes. Diabetologia 47:1940–1947PubMedCrossRefGoogle Scholar
  40. 40.
    Landstedt-Hallin L, Englund A, Adamson U, Lins PE (1999) Increased QT dispersion during hypoglycaemia in patients with type 2 diabetes mellitus. J Intern Med 246:299–307PubMedCrossRefGoogle Scholar
  41. 41.
    Pappachan JM, Sebastian J, Bino BC et al (2008) Cardiac autonomic neuropathy in diabetes mellitus: prevalence, risk factors and utility of corrected QT interval in the ECG for its diagnosis. Postgrad Med J 84:205–210PubMedCrossRefGoogle Scholar
  42. 42.
    Veglio M, Chinaglia A, Cavallo-Perin P (2004) QT interval, cardiovascular risk factors and risk of death in diabetes. J Endocrinol Investig 27:175–181Google Scholar
  43. 43.
    Pop-Busui R, Evans GW, Gerstein HC et al (2010) Effects of cardiac autonomic dysfunction on mortality risk in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. Diabetes Care 33:1578–1584PubMedCrossRefGoogle Scholar
  44. 44.
    Moulik PK, Mtonga R, Gill GV (2003) Amputation and mortality in new-onset diabetic foot ulcers stratified by etiology. Diabetes Care 26:491–494PubMedCrossRefGoogle Scholar
  45. 45.
    Cryer PE (2001) Hypoglycemia-associated autonomic failure in diabetes. Am J Physiol Endocrinol Metab 281:E1115–E1121PubMedGoogle Scholar
  46. 46.
    Gruden G, Giunti S, Barutta F et al (2012) QTc interval prolongation is independently associated with severe hypoglycemic attacks in type 1 diabetes from the EURODIAB IDDM complications study. Diabetes Care 35:125–127PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Institution of Clinical Sciences in LundLund UniversityLundSweden
  2. 2.MAVA, Department of Emergency MedicineSkåne University HospitalLundSweden
  3. 3.Department of EndocrinologySkåne University HospitalLundSweden

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