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C l i n i c a l C a r e / E d u c a t i o n / N u t r i t i o n / P s y c h o s o c i a l R e s e a r c h
Relationships Between Daily Acute Glucose
Fluctuations and Cognitive Performance
Among Aged Type 2 Diabetic Patients

tions is still difficult. Considering that the ICHELANGELA BARBIERI, MD, PHD
brain is dependent on an appropriate sup- IRGINIA BOCCARDI, MD
ply of glucose as its principal energysource, one cannot rule out the possibilitythat plasma glucose instability over 24 h OBJECTIVE — The mean amplitude of glycemic excursions (MAGE) is a significant deter-
minant of overall metabolic control as well as increased risk for diabetes complications. Older more practical point of view, exposure to individuals with type 2 diabetes are more likely to have moderate cognitive deficits and structural changes in brain tissue. Considering that poor metabolic control is considered a deranging factor function of two components: 1) the dura- for cognitive performance in diabetic patients, we evaluated whether the contributions of MAGE to cognitive status in older patients with type 2 diabetes were independent from the main hyperglycemia and 2) the acute fluctua- markers of glycemic control, such as sustained chronic hyperglycemia (A1C), postprandialglycemia (PPG), and fasting plasma glucose (FPG).
tions of glucose over a daily period (6,7).
The first component was integrated by RESEARCH DESIGN AND METHODS — In 121 older patients with type 2 diabetes,
48-h continuous subcutaneous glucose monitoring (CSGM) were assessed. MAGE and PPG were evaluated during CSGM. The relationship of MAGE to performance on cognitive tests was assessed, with adjustment for age, glycemic control markers, and other determinants of cognitive status. The cognitive tests were a composite score of executive and attention functioning and the trol (8). The acute fluctuations of glucose Mini Mental Status Examination (MMSE).
around a mean value is more difficult toassess, but the recent development of de- RESULTS — MAGE was significantly correlated with MMSE (r ϭ 0.83; P Ͻ 0.001) and with
cognition composite score (r ϭ 0.68; P Ͻ 0.001). Moreover, MAGE was associated with theMMSE (P Ͻ 0.001) and cognition composite score (P Ͻ 0.001) independently of age, sex, BMI, waist-to-hip (WHR) ratio, drug intake, physical activity, mean arterial blood pressure, FPG, PPG, the influence of acute blood glucose fluc-tuations in real life (9). By applying this CONCLUSIONS — MAGE during a daily period was associated with an impairment of
cognitive functioning independent of A1C, FPG, and PPG. The present data suggest that inter- further insight into the respective role of ventional trials in older patients with type 2 diabetes should target not only A1C, PPG, and FPG but also daily acute glucose swings.
and acute glucose fluctuations over a dailyperiod on global cognitive functioning as Diabetes Care 33:2169–2174, 2010
well as executive and attention function-ing neuropsychological tests.
Itiswidelyknownthatolderindividu- A1Cbutnotfastingplasmaglucose(FPG)
lower scores on two cognitive tests (3).
METHODS — A total of 121 older
those without type 2 diabetes (1). The un- ing other indexes of dysglycemia, such as glucose control and cognitive function ex- the fact that several studies have investi- A1C levels. Eligibility for the study was ists (2). For instance, a cross-sectional analysis in 378 high-functioning individ- 1-year period. The main clinical and lab- diabetic cognitive disorders, an accurate oratory characteristics of the patients are ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● From the 1Department of Geriatrics and Metabolic Diseases, Second University of Naples, Naples, Italy; the of walking and other leisure-time physical 2Department of Anesthesiology and Emergency, Second University of Naples, Naples, Italy; and the activities were assessed by interview. Ex- 3Department of Surgery, Second University of Naples, Naples, Italy.
clusion criteria, assessed with self-report Corresponding author: Raffaele Marfella,
Received 27 February 2010 and accepted 16 May 2010. Published ahead of print at http://care. on 23 June 2010. DOI: 10.2337/dc10-0389.
2010 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. See http://creativecommons.
illness during the 3-month period preced- org/licenses/by-nc-nd/3.0/ for details.
ing the investigation, and cerebrovascular The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. DIABETES CARE, VOLUME 33, NUMBER 10, OCTOBER 2010 Glycemic control and cognitive performance
Table 1—Clinical characteristics of patients
medica, Milan, Italy) (intra-assay coefficient of variation 3.1 ϩ 0.3%; cross-reactivity days 1, 2, and 3. After an overnight fast, quantified from fresh samples drawn after participants had been fasting for at least breakfast, respectively. The standardized glyceride (Roche Diagnostics) levels.
white matter lesions, significant signs of cortical or subcortical atrophy. Patients present study for assessing glucose fluc- white matter lesions or cortical or subcor- tical atrophy were considered lost to fol- data on study days 1 and 2, i.e., from con- blinded to the study design. In brief, all Data are means Ϯ SD, n, or n (%).
mia, is of particular interest because the ness of the far wall was evaluated as the distance between the luminal-intimal inter- face and the medial-adventitial interface.
sis over a period of 3 consecutive days by were obtained from 10 contiguous sites at 1-mm intervals, and the average of the 10 Menarini Diagnostics, Florence, Italy) as measurements were used for the analysis.
described previously (10). The sensor was inserted on day 0 and removed on day 3 at consists of two parts: TMT-A and TMT-B.
one to draw a line connecting consecutive on days 1 and 2 to avoid bias due to both thus, to insufficient stabilization of the and letters in alternating sequence (14).
glucose pattern of each patient was calcu- for assays. Plasma insulin was determined typically used to examine aspects of atten- DIABETES CARE, VOLUME 33, NUMBER 10, OCTOBER 2010 Rizzo and Associates
Figure 1—A: Relationship between MMSE and MAGE. B: Relationship between cognitive composite score and MAGE. quired for the study to reject the null hy- of cognitive efficiency (15). The Wechsler pothesis 99% of the time (i.e., with a one- tailed type II error rate of 0.01) when r was Ն0.80 with a two-tailed type I error well as of brief storage and mental manip- at the 0.05 level of significance. Because this calculation led to a sample size of at (DSP–Backward) requires the participant least 110, the number of required patients plaque at 20 –25% without significant al- listen to increasingly longer lists of digits was set at 121. A cluster analysis, using terations in blood flow) on a carotid ultra- presented for immediate recall in the re- the squared sum of z scores, showed lesions or significant signs of cortical or (data not show). All patients were treated participants to generate as many words as we created a cognition composite score of alone (10 –15 mg/day in 19 patients) or possible in 1 min for a given letter (F, A, S) attention and executive functions, as sum of the z scores of TMT-A, TMT-B, DIFF Verbal Fluency. A z score indicates the day) (in 51 patients) or a combination of position of an individual value of a vari- able in the total distribution of the vari- lidinediones (4 mg/day) (in 13 patients).
able in the population and is calculated as follows: (individual value – mean value)/ those with a score of 26 were directed to ual test scores to z scores, summing these evaluation of older individuals with cog- of several covariates. The effect of therapy etiology was established using a standard in patients categorized for number of an- MMSE (r ϭ 0.83 P Ͻ 0.001) and with the cognition composite score (r ϭ 0.68, P Ͻ teria (18). All participants with diagnosed ANOVA, and Ptrend was calculated. P Ͻ 0.05 was used of levels of significance in thropometric (BMI and waist-to-hip ratio[WHR]), metabolic (FPG and 2-h PPG RESULTS — The study group had
All data are expressed as means Ϯ SD.
Plasma insulin and triglycerides were log 88 – 65 years), A1C of 7.9 Ϯ 0.3%, and and fasting insulin was observed (r ϭ DIABETES CARE, VOLUME 33, NUMBER 10, OCTOBER 2010 Glycemic control and cognitive performance
Table 2—Linear multivariate analyses with MMSE and composite score as dependent variable
For MMSE: R2 ϭ 0.73 (model 1); R2 ϭ 0.73 (model 2); R2 ϭ 0.77 (model 3). For composite score: R2 ϭ 0.40 (model 1); R2 ϭ 0.41 (model 2); R2 ϭ 0.44 (model3). SBP, systolic blood pressure; DBP, diastolic blood pressure.
nitive function (Table 2, model 3). All of scores were tested in three different mul- sults, even after adjustment for education CONCLUSIONS — Our study shows
having, respectively, age, sex, BMI, WHR, associated with daily acute glucose fluc- postprandial glucose (model 3) as covari- To assess the impact of antidiabetes ther- functioning, and this relationship was in- apy, all patients were categorized in three tion, physical activity, mean arterial blood according to antidiabetes treatment: gly- of the different glycemic indexes partici- pating in diabetic cognitive disorders (2– 4), accurate assessment of their respective contributions is still being debated. By us- thiazolidinediones, 73.8 Ϯ 23. No differ- DIABETES CARE, VOLUME 33, NUMBER 10, OCTOBER 2010 Rizzo and Associates
certainly an independent risk factor of de- as observed over interprandial periods. As diabetes. For instance, it has been estab- type 2 diabetes might also evoke a decline cognitive function in individuals withtype 2 diabetes and other cardiovascular risk factors: the action to control cardio- bolic activity in the brain, the rapid glu- (20). The toxicity of these substances can levels during postprandial periods to low mia and cognitive function in older adults decline of metabolic activity in the brain ited a more specific triggering effect on Grella R, Arciello A, Laieta MT, Acampora glucose nadirs, may affect cognitive func- R, Passariello N, Cacciapuoti F, Paolisso G.
tion in older individuals, increasing oxi- and cognitive functioning in aged type 2 di- appropriate brain supply of glucose.
These observations provide a possible ex- 5. Cox DJ, Kovatchev BP, Gonder-Frederick tive stress caused by free radicals damages the endothelial cells in the blood vessels, adults with type 1 and type 2 diabetes. Di-abetes Care 2005;28:71–77 6. Diabetes Control and Complications Trial complications of type 2 diabetes. Various the present study is its cross-sectional, ob- tive stress can lead to microvascular cere- servational nature, and it is therefore dif- ficult to draw causal relationships.
cations Trial. Diabetes 1995;44:968 –983 7. Ceriello A, Hanefeld M, Leiter L, Monnier reason for high risk of microvascular ce- are risk factors for mild cognitive impair- ilehto J. Postprandial glucose regulation 8. Monnier L, Lapinski H, Colette C. Contri- tional studies with the aim of treating gly- bution of fasting and postprandial plasma glucose increments to the overall diurnal hyperglycemia of type 2 diabetic patients: flattening acute glucose fluctuations.
variations with increasing levels of HbA .
Acknowledgments — No potential conflicts of
toring: roadmap for 21st century therapy.
interest relevant to this article were reported.
10. Marfella R, Barbieri M, Ruggiero R, Rizzo lyzed and interpreted data, wrote the manu- script, and revised/edited the manuscript.
olisso G. Bariatric surgery reduces oxida- M.B., V.B., and F.V. analyzed and interpreted tive stress by blunting 24-h acute glucose ers of upward variations, there is a reason data. B.L. designed the study and revised/ fluctuations in type 2 diabetic obese pa- study, wrote the manuscript, and revised/ 11. Service FJ, Molnar GD, Rosevear JW, Ack- study, analyzed and interpreted data, and re- associated with cognitive functioning in- sure of diabetic instability. Diabetes 1970; 12. Service FJ, O’Brien PC, Rizza RA. Mea- References
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