Long-term Instability of Fasting Plasma Glucose, a Novel Predictor of Cardiovascular Mortality in Elderly Patients With Non–Insulin-Dependent Diabetes Mellitus
The Verona Diabetes Study
Background We recently reported that long-term fasting plasma glucose (FPG) instability predicts all-cause mortality in elderly patients with non–insulin-dependent diabetes mellitus (NIDDM). The aim of the present study was to evaluate whether glucose instability, as represented by the coefficient of variation of FPG concentrations (CV-FPG) measured during a 3-year period, can predict specific causes of death in the subsequent 5 years.
Methods and Results Five hundred sixty-six elderly patients with NIDDM were followed up for 5 years to assess mortality and causes of death. All FPG determinations of the 3 years preceding the follow-up available in the clinical records were collected and analyzed. Patients were grouped in tertiles of mean FPG, CV-FPG, and the slope of FPG. These parameters of glucose control, as well as sex, age, duration of diabetes, insulin treatment, cigarette smoking, hypertension, and total cholesterol, were included in a multivariate analysis of mortality. During the follow-up, 63 men and 128 women died. Diabetes- and malignancy-related mortality were not independently associated with any parameter of glucose control, whereas cardiovascular-related mortality was independently associated with CV-FPG (P=.007) but not with the mean or the slope of FPG. In particular, the relative risk of cardiovascular mortality in subjects in tertile III versus tertile I of CV-FPG was 2.40 (95% CI, 1.28 to 4.53).
Conclusions These results indicate that FPG instability is a predictor of cardiovascular-related mortality in elderly patients with NIDDM and suggest that glucose stability might be a goal in the management of these patients.
We recently reported that long-term instability of metabolic control, as indicated by a high CV-FPG, is an independent predictor of all-cause mortality in elderly patients with NIDDM. This conclusion was reached by analyzing several fasting glucose determinations in the 3 years preceding a 5-year mortality follow-up involving 566 patients aged ≥75 years who had NIDDM.1
The notion that glucose instability is a risk factor for mortality in elderly diabetic patients is original and might suggest that the stability of fasting plasma glucose over time is one of the goals in the management of NIDDM in elderly people. This conclusion could have strong clinical implications because diabetes in the elderly is becoming a growing burden for the healthcare system. Indeed, the prevalence of known diabetes at this age is ≈10%.2 3 4
If one attributes to the statistical association between glucose instability and mortality the rank of a cause-and-effect relationship, it might be hypothesized that fasting glucose instability could be a factor directly involved in the development of chronic diabetes complications or in precipitating one or more acute events leading to death. In such a case, glucose stability should become a major goal of diabetes treatment and should be pursued to reduce chronic complications and to prevent precipitating events.
Alternatively, glucose instability might be due to an underlying disorder unrelated to diabetes but significantly associated with mortality. For example, glucose instability could be the expression of recurrent relapses of a chronic coexisting illness, which eventually might be responsible for death. If that were the case, our observation would still be interesting, but it would be meaningless from a therapeutic standpoint. Indeed, the maintenance of stable glucose levels would not prevent the underlying disorder from progressing and eventually killing the patient. In diabetic subjects, the finding of a relationship between glucose instability and death resulting from a specific cause (eg, cardiovascular disease) might clarify whether such statistical association is causal and, if so, might also result in a message for clinical practice. Thus, we looked for possible relationships between the CV-FPG and specific causes of death in a cohort of elderly subjects with NIDDM.
Details about the design, setting, and population of the present study have been described extensively in previous publications.1 4 5 Briefly, within the framework of the Verona Diabetes Study, a population-based study on diabetes prevalence and mortality, we examined a cohort of 566 patients with NIDDM who were aged ≥75 years. The main clinical features of these subjects are reported in Table 1⇓. All of these 566 patients, who regularly attended the Verona Diabetes Clinic in the years 1984 through 1986 and who were alive on December 31, 1986, had at least two fasting plasma glucose determinations during each of the years 1984, 1985, and 1986 (median, 2.7; range, 2 to 6 glucose determinations per year), and were followed up in the subsequent 5 years (January 1, 1987, through December 31, 1991) to assess mortality and causes of death.
Analysis of the fasting glucose determinations in the years 1984 through 1986 has been described previously.1 Briefly, for each individual patient, the M-FPG, CV-FPG, and S-FPG during the 3 years of observation were computed. Patients were then grouped into tertiles according to M-FPG (<7.46, 7.46 to 9.16, and ≥9.17 mmol/L), CV-FPG (<11.2%, 11.2% to 18.4%, and ≥18.5%), and S-FPG (<−0.30, −0.30 to +0.33, and >0.34 mmol/L per year).
A fasting plasma glucose level <3.9 mmol/L (70 mg/dL) was arbitrarily considered as suggestive of hypoglycemia.
Methods for mortality assessment have been described previously.1 4 5 Three of the 21 subjects who had not been traced and had been arbitrarily considered alive in previous analyses were traced and were found to be deceased by the end of the follow-up. Thus, in the present study, a total of 191 deaths were ascertained. The 18 patients who remained untraced were arbitrarily considered alive at the end of the follow-up.
In the present analysis, the underlying cause of death reported on the death certificate was regarded as the cause of death and was ascertained in 177 (92.7%) of the 191 subjects who had died during the observation period. When more than one underlying cause of death was reported, the first one was chosen. All death certificates were reviewed by a single trained physician, according to the International Classification of Diseases, ninth revision. Causes of death were grouped into cardiovascular diseases (codes 390 through 459), malignant neoplasms (codes 140 through 208), diabetes mellitus (code 250), and other causes (all other codes).
Univariate survival analysis was performed by use of the Kaplan-Meier method and log-rank test. Multivariate survival analysis describing the RR of mortality was accomplished by use of the Poisson regression model6 including tertiles of M-FPG, CV-FPG, and S-FPG, along with sex, age (in years), diabetes duration (in years), insulin treatment (yes/no), cigarette smoking (yes/no), and hypertension (yes/no) as the independent variables to be tested. An additional multivariate analysis including total cholesterol as an independent variable was performed in 423 subjects, ie, those in whom this parameter was available. For continuous variables, the RR of mortality for specific causes was calculated on the basis of an increase of 1 SD in the values. The Poisson regression model was chosen because the hazard associated with several variables showed a significant interaction with time.
In the period from January 1, 1987, through December 31, 1991, ie, during the 5-year follow-up, 191 patients (63 men, 128 women) died. Of these subjects, 41 (23 men, 18 women) died of malignancies, 32 (8 men, 24 women) died of diabetes mellitus, 79 (24 men, 55 women) died of cardiovascular diseases, and the remaining 39 (8 men, 31 women) died of other or unknown causes.
Table 1⇑ reports the main demographic and clinical features of survivors and subjects who died. Patients who died were slightly older and had a higher M-FPG (P=.02) and CV-FPG (P<.001) than those who survived. The latter included a larger proportion of women, a lesser number of insulin-treated diabetics, and a lesser number of smokers or ex-smokers. The duration of diabetes was not different in the two groups, nor was the prevalence of hypertension or the mean value of total cholesterol. In addition, the S-FPG, the number of fasting glucose determinations, and the percent of subjects with documented fasting hypoglycemia, as measured at the diabetes clinic, did not differ in the two groups.
The main demographic and clinical characteristics of the cohort under study after stratification by tertile of CV-FPG are summarized in Table 2⇓. We observed an increase in diabetes duration, insulin treatment (alone or with oral agents), number of glucose determinations, mean glucose levels, and number of hypoglycemic episodes and a decrease in total cholesterol and use of tolbutamide across tertiles of CV-FPG. Other parameters were not different in subjects in the three tertiles of CV-FPG. The percentage of subjects who died during the follow-up almost doubled from the lowest to the highest tertile of CV-FPG.
The Figure⇓ shows the results of the univariate survival analysis performed by use of the Kaplan-Meier method and with cardiovascular mortality assumed as an end point. Subjects in the top tertile of CV-FPG showed a markedly lower survival probability (P<.001) than did those in the other two tertiles, in which the survival probability was rather similar. The same analysis failed to document a different survival rate in subjects in different tertiles of M-FPG (data not shown).
Table 3⇓ shows the RRs of mortality resulting from diabetes, malignancies, and cardiovascular diseases as computed by the Poisson multivariate regression model. The regression model included sex, age, duration of diabetes, insulin treatment, smoking habits, hypertension, and parameters of glucose control (M-FPG, CV-FPG, and S-FPG). None of the tested variables was a statistically significant independent predictor of mortality from diabetes. Male sex was the only independent predictor of mortality from malignancies (P=.001). CV-FPG was the only significant predictor of cardiovascular mortality (P=.007).
When we repeated the multivariate analysis in the 423 subjects in whom total cholesterol values were available, the significant independent association of CV-FPG with cardiovascular mortality remained unchanged (tertile II versus tertile I: RR=1.16, CI=0.56 to 2.41; tertile III versus tertile I: RR=2.38, CI=1.20 to 4.71; P=.021).
Mortality from other causes was not significantly predicted by any parameters of glucose control (data not shown).
In a previous study,1 we observed that in elderly patients with NIDDM, fasting plasma glucose instability predicted all-cause mortality. The present study was undertaken to understand which cause(s) of death is associated with glucose instability in these subjects. Such information might have great clinical value because it might establish whether glucose stability can be numbered as one of the goals in diabetes management. In fact, if the parameter representing glucose instability (ie, CV-FPG) were associated with mortality due to malignancy or other diabetes-unrelated causes of death, the maintenance of a stable glucose concentration over time would be meaningless because it would not change the progression of the concurrent disease. On the other hand, if CV-FPG were significantly associated with mortality due to diabetes or cardiovascular diseases, ie, mortality related to diabetes or its chronic complications burdened by the larger impact on mortality, the maintenance of a stable glucose concentration over time would be crucial and perhaps mandatory.
In the present study, we found that CV-FPG was associated with mortality resulting from cardiovascular diseases but not with mortality resulting from malignancies or other causes, including diabetes per se. This was observed independently of several confounders, including mean plasma glucose. Such results support the idea that there is a cause-and-effect relationship between glucose instability and mortality, particularly mortality resulting from cardiovascular diseases.
In our study, we did not observe a significant association between hyperglycemia and cardiovascular mortality. Indeed, the latter was not predicted by M-FPG. This result is not consistent with those observed in a number of recent studies, most of which were performed in Scandinavia.7 8 9 10 11 12 In those studies, patients with the highest fasting plasma glucose or HbAIc levels at baseline had the greatest cardiovascular morbidity and mortality during the subsequent years. The discrepancies between these studies and our present report might be attributed to several things. First, patients in those studies were younger and had a shorter duration of diabetes than patients in the present study. Second, patients included in those studies had a poorer glucose control than patients we examined. Third, none of the above-mentioned studies included repeated measurements of fasting glycemia (or glycohemoglobin), as did our study. Thus, the evaluation of the degree of metabolic control over time was less accurate in the previous studies than in our study. Finally, and as a consequence of the latter point, the variability of glucose levels could not be assessed and controlled for in these previous studies. More recently, Frost et al13 reported that in univariate analysis, fasting serum glucose was a predictor of cardiovascular events in hypertensive nondiabetic and diabetic subjects aged >60 years. Interestingly, when we performed in our cohort a univariate analysis similar to that performed by Frost et al,13 M-FPG was a predictor of cardiovascular mortality, with an RR associated with an increase of 1 SD (RR=1.21, CI=0.99 to 1.49, P=.07), almost identical to that reported by Frost et al, who evaluated fatal and nonfatal coronary events (RR=1.22, CI=1.08 to 1.36). However, when glucose variability was taken into account in multivariate analysis, M-FPG was no longer a significant predictor of cardiovascular mortality.
In the present study, the variability in fasting plasma glucose does not seem to be an epiphenomenon of poor glycemic control because there was a weak correlation between M-FPG and CV-FPG (R2=.06). In addition, variability in fasting glucose does not seem to be a marker of a progressive deterioration of metabolic control because the S-FPG was poorly correlated with the CV-FPG (R2=.03) and was not independently associated with excess mortality in the multivariate analysis.
Our data do not enable us to establish whether glucose instability leads to cardiovascular mortality through a chronic pathogenic effect resulting in diabetes macroangiopathy or through an acute precipitating effect in subjects with long-standing macroangiopathy. In this regard, it is interesting to remember that in cultured retinal capillary pericytes, fluctuations in ambient glucose concentrations seem to yield vascular damage that is distinct from that specific to hyperglycemia.14 15 It might be that in humans, glucose variability also exerts a deleterious effect on the vascular wall of large vessels, thereby contributing to macroangiopathy and hence predisposing to cardiovascular events. On the other hand, it might be hypothesized that in subjects who are particularly vulnerable to substrate deficiency and consequent cellular energy depletion, such as elderly individuals with coronary or cerebral atherosclerosis, glucose instability could predispose to hypoglycemia. The latter might act as the precipitating factor of cardiovascular events. In this regard, it is noteworthy that patients with well-documented hypoglycemic episodes were more represented among subjects of tertile III of CV-FPG. Whatever the pathophysiological mechanism relating glucose variability to cardiovascular mortality, the finding of the present study supports the idea that in elderly patients with NIDDM, diabetes management should strive to keep glucose concentrations as stable as possible.
The fundamental tool to achieve glucose stability is probably a strict adherence to assigned treatment (diet, exercise, and drugs) and a careful plan of periodic medical visits and home blood glucose monitoring. Poor patient compliance with antidiabetic treatment, which is particularly difficult to improve in the elderly, might be one of the main causes of glucose instability. However, coexisting illnesses and medications other than hypoglycemic agents might be a cofactor of glucose variability in these subjects. In this regard, particular attention should be paid to the variation of plasma glucose during intercurrent diseases and to adverse metabolic effects or pharmacological interactions of medication to be prescribed. In addition, other unknown factors might play a role in glucose instability. The identification of such factors, if any, would be a prerequisite to pursue glucose stability.
In conclusion, elderly subjects with NIDDM have an increased risk of dying of cardiovascular disease when they have long-term glucose instability, ie, a CV-FPG approximately >20%. CV-FPG, which is easy to measure in any medical office, might be proposed as a novel parameter to estimate the life expectancy of elderly diabetic patients.
Selected Abbreviations and Acronyms
|CV-FPG||=||coefficient of variation of fasting plasma glucose concentrations|
|M-FPG||=||mean of fasting plasma glucose concentrations|
|NIDDM||=||non–insulin-dependent diabetes mellitus|
|S-FPG||=||regression coefficient (slope) of fasting plasma glucose concentrations|
The present study was supported by grant Nos. 86.01873.56, 87.00374.56, 91.00400.PF40, 92.00377.PF40, 93.00421.PF40, 94.00460.PF40, and 95.01010.PF40 from the Italian National Research Council (INV 97-3-727) and by grants from the Italian Ministry of University and Scientific and Technological Research.
- Received January 9, 1997.
- Revision received March 28, 1997.
- Accepted April 18, 1997.
- Copyright © 1997 by American Heart Association
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