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Glycemic variability and its responses to intensive

insulin treatment in newly diagnosed type 2 diabetes

Jian ZhouACDEF, Weiping JiaADEFG, Yuqian BaoAD, Xiaojing MaBC, Wei LuB,

Huating LiE, Cheng HuEF, Kunsan Xiang ADE

Shanghai Clinical Center for Diabetes, Department of Endocrinology and Metabolism, Shanghai Jiao Tong

University Affiliated Sixth People’s Hospital, Shanghai Diabetes Institute

Source of support: Shanghai United Developing Technology Project of Municipal Hospitals (SHDC12006101)

Summary

Background: Recent data show that blood glucose (BG) variability is an HbA 1c-independent risk factor for dia-

betic complications. This study investigated the characteristics of BG variability in type 2 diabeticpatients and the effect of intensive treatment.

Material/Methods: Forty-eight subjects with normal glucose regulation and 69 patients with newly diagnosed type 2 di-abetes were monitored using the continuous glucose monitoring system. A subset of the type 2 dia-betic patients (n=23) whose HbA

1c was >8.5% was monitored a second time following 2 to 3 weeks

of treatment with multiple daily injections. The mean amplitude of glycemic excursions (MAGE),mean of daily differences (MODD), and the incremental areas above preprandial glucose values(AUCpp) were used for assessing intra-day, inter-day, and postprandial BG variability.

Results: In type 2 diabetic patients, the MAGE, MODD, and AUCpp levels were all higher than those of subjects with normal glucose regulation (P <0.001). Multivariant regression analysis indicated that

AUCpp was the main independent factor influencing MAGE (Adjusted R 2=0.56), while postpran-dial hyperglycemia was most prominent following breakfast and less evident during lunch and din-ner. After intensive treatment, significant decreases in MAGE, MODD, and AUCpp were observed(41%, 29%, and 49%, respectively, P <0.001). AUCpp after breakfast was higher than after lunchand dinner (P <0.05). In 65.2% of the subjects, peak intra-day values occurred 103±30 minutes af-ter breakfast.

Conclusions: Minimizing glycemic variability in type 2 diabetic patients, especially postprandial glucose excur-sions following breakfast, may be an important aspect of glucose management.

key words: continuous glucose monitoring • type 2 diabetes • glycemic variability • HbA 1c •

hypoglycemia

Full-text PDF: http://www.medscimonit.com/fulltxt.php?ICID=869442

Word count: 2593

Tables: 2

Figures: 2

References: 40

Author’s address: Weiping Jia, Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’sHospital, 600 Yishan Road, Shanghai 200233, China, e-mail: [email protected]

Authors’ Contribution:

A Study Design

B Data Collection

C Statistical Analysis

D Data Interpretation

E Manuscript Preparation

F Literature Search

G Funds Collection

Received: 2008.03.04

Accepted: 2008.05.05

Published: 2008.11.01

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B ACKGROUND

Current therapeutic strategies in diabetes are aimed at con-trolling blood glucose (BG) levels close to the standard tar-get in order to prevent the development of diabetes-relat-ed complications, with HbA

1c being the “gold standard”

for the evaluation of glycemic control [1–3]. Recent epide-miological and interventional studies have shown that theoccurrence and development of chronic complications inpatients with diabetes is not only closely related to HbA

1c

levels, but also to BG variability. In designing strategies toreduce diabetic complications, both HbA

1c and glycemic

variability should be taken into account [4,5]. Therefore it is interesting to investigate the characteristics of glycemic

variability in subjects with type 2 diabetic as well as chang-es following different hypoglycemic treatments.

Efforts to quantify glycemic variability have relied on inter-mittent BG determinations. The continuous glucose moni-toring (CGM) system measures interstitial subcutaneous tis-

sue glucose levels continuously, recording values on averageevery 5 minutes and providing information about the style,direction, magnitude, duration, and frequency of BG vari-ability [6–9]. Recent studies with continuous glucose sensorshave found that continuous subcutaneous insulin infusionand multiple daily injection (MDI) display similar patternsof glycemic excursions, implying that factors influencing gly-cemic instability in type 1 diabetes mellitus appear to be in-dependent of treatment modality [10,11]. In overweight orobese patients with type 2 diabetes, post-breakfast hypergly-cemia appears to be the postprandial glucose excursion that remains the most resistant to calorie restriction [12].

To date, the characteristics of BG variability have not beeninvestigated in newly diagnosed patients with type 2 diabetes.The aim of this study was to investigate the characteristicsof BG variability in subjects with normal glucose regulation(NGR) or newly diagnosed type 2 diabetes by conductingCGM over three consecutive days. Additionally, changesin glycemic variability were determined in the newly diag-nosed type 2 diabetic patients after intensive treatment withMDI for 2 to 3 weeks.

M ATERIAL AND METHODS

Subjects

A total of 132 Chinese (76 with newly diagnosed type 2 diabe-tes, 56 with NGR) were recruited in Shanghai to participatein this clinical trial from October 2005 to December 2006.The study was approved by the institutional review boardof Shanghai Jiaotong University Affiliated Sixth People’sHospital, with written informed consent being obtainedfrom all participants.

No acute complications, such as diabetic ketoacidosis, hyper-glycemic hyperosmolar nonketotic syndrome, or other dis-orders affecting glucose metabolism, were reported in any of the newly diagnosed type 2 diabetic patients. No patientshad received diabetes treatment interventions (diet, exercise,

or drugs) prior to or during CGM. After the initial CGM, thenewly diagnosed type 2 diabetic patients whose HbA 1c lev-

els were >8.5% underwent intensive treatment with flexibleMDIs based on the CGM results. The selection of subjects

with HbA 1c concentrations >8.5% was based on the HbA

1c

threshold value recommended by the American Diabetes Association and the European Association for the Study of Diabetes [13]. The MDI regimen consisted of regular insulininjections before breakfast, lunch, and dinner and an NPHinsulin injection before bedtime. The target BG levels were

set in accordance with the American Diabetes Association at 5.0–7.2 mmol/l before meals and <10.0 mmol/l 1–2 hoursafter the beginning of a meal [14]. A second round of CGMover three consecutive days was then performed in 23 sub-

jects with newly diagnosed type 2 diabetes following 2 to 3 weeks of treatment with MDI.

The healthy controls had normal glucose tolerance, asdetermined by the 75-g oral glucose tolerance test [15].

Additionally, no liver, kidney, coronary artery, lipid me-tabolism, or blood pressure abnormalities were detectedin the healthy controls and none reported a family histo-ry of diabetes.

Study design

The CGM system sensor (Medtronic MiniMed) was insert-ed in all subjects by the same specialized nurse on day 0and removed midmorning on day 3. Data were download-ed and glucose profiles were evaluated based on the datacollected on days 1 and 2. The patients were instructedto input at least four calibration readings per day and thetimes of key events (meals, exercise, insulin doses). The fol-lowing cutoff criteria for optimal accuracy were adheredto: 1) when the difference in the BG values of the meterreading was ≥5.6 mmol/l, mean absolute deviation ≤28%,and correlation coefficient ≥0.79 and 2) when the differ-

ence in the BG values of meter reading was <5.6 mmol/land the mean absolute differences were ≤18% [16]. Datanot meeting the criteria were excluded. Additionally, anal-

yses were performed of the frequency of hypoglycemic epi-sodes, defined as a period with a CGM reading <3.9 mmol/lfor at least 15 minutes with an antecedent non-hypoglyce-mic episode of at least 30 min [17-18]. Readings between6:00 a.m. and 10:00 p.m. were considered daytime valuesand those between 10:00 p.m. and 6:00 a.m. were consid-ered nighttime values.

Assessment of intra-day glycemic variability

The mean amplitude of glycemic excursions (MAGE), de-

scribed by Service et al. [19,20] and designed to quantify major swings of glycemia and to exclude minor ones, wasused for assessing intra-day BG variability in this study. Only increases of more than one standard deviation of the meanglycemic values were taken into account. MAGE calculations

were obtained by measuring the arithmetic mean of the dif-ferences between consecutive peaks and nadirs; measure-ments in the peak-to-nadir or nadir-to-peak direction weredetermined by the first qualifying excursion.

Assessment of inter-day glycemic variability

The mean of the daily differences (MODD), described by

Molnar et al. [21,22], was used to assess day-to-day glycemic variability. MODD was calculated from the absolute differ-ence between paired continuous glucose monitoring valuesduring two successive 24 hour periods (days 1 and 2).

Med Sci Monit, 2008; 14(11): CR552-558 Zhou J et al –Glycemic variability in type 2 diabetes

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The area under the curve obtained during a 24-hour period(AUC

24h) is an indicator of the overall BG level. Division of

this 24-hour period into preprandial and postprandial pe-riods enabled the evaluation of postprandial glucose vari-ability, with AUCpp calculated during the 4-hour periodfollowing the beginning of each meal. Analysis of the post-prandial peak value and time to peak was also performed

in order to evaluate the characteristics of postprandial glu-cose excursion. All parameters above were based on themean values taken on days 1 and 2.

Laboratory examination

HbA 1c was measured by high-performance liquid chromatog-

raphy (Arkary, Japan), which has a nondiabetic normal rangeof 4.9–5.8%. Plasma glucose concentrations were determinedby the glucose oxidase method (Automatic Biochemistry

Analyzer, Beckman). Capillary glucose concentrations weremeasured by a Roche glucotrend 2 BG meter.

Statistical methods

Descriptive data were expressed as means ± standard deviation (95%CI ) unless otherwise indicated. Continuous

variables were compared using a two-sided t test or pairedt test for changes within each subject. Relationships be-tween variables were assessed using a Pearson’s correlationtest. Multiple regression models were used to explore theinfluence of different variables on MAGE and to adjust forcovariates. P <0.05 was considered to be statistically signif-icant. Data analyses were performed using the SPSS11.0software package.

RESULTS

Subject characteristics (Table 1)

All subjects tolerated the CGM for at least 3 days. Of the132 subjects, 117 (69 with newly diagnosed type 2 diabetes,48 with NGR) were available for analysis. In the remaining15 subjects the sensor was either disconnected or did not meet the criteria for optimal accuracy. Body mass index,blood pressure, triglyceride, fasting plasma glucose, two-hour postprandial plasma glucose, and HbA

1c of the sub-

jects with newly diagnosed type 2 diabetes were all greaterthan those of the subjects with NGR, whereas high-densi-

ty lipoprotein cholesterol values in the subjects with new-ly diagnosed type 2 diabetes were clearly lower than thoseobserved in the NGR group.

Subjects with normalglucose regulation

Subjects with newlydiagnosed type 2 diabetes

P value

N 48 69

Sex (M/F) 24/24 42/27 0.261

Age (years) 41±11 54±13 <0.001

Body mass index (kg/m2) 22.7±2.6 25.5±2.9 <0.001

Systolic blood pressure (mmHg) 119±10 133±17 <0.001

Diastolic blood pressure (mmHg) 78±6 84±11 0.008

Total cholesterol (mmol/l) 4.46±0.80 5.02±1.12 <0.001

Triglycerides (mmol/l) 1.15±0.70 2.57±2.02 0.021

HDL-C (mmol/l) 1.82±0.61 1.42±0.83 0.038

LDL-C (mmol/l) 2.43±0.78 2.59±1.12 0.516

Fasting plasma glucose (mmol/l) 4.65±0.48 9.10±1.43 <0.001

2-h postprandial plasma glucose (mmol/l) 5.10±1.06 15.6±1.81 <0.001

HbA1c (%) 5.54±0.46 8.02±1.46 <0.001

AUC24h

(mmol·d/l) 5.4±0.5 10.9±2.9 <0.001

SDBG (mmol/l) 0.8±0.3 2.3±0.6 <0.001

MAGE (mmol/l) 2.0±0.7 5.7±1.6 <0.001

MODD (mmol/l) 0.8±0.3 1.8±0.6 <0.001

Table 1. Clinical characteristics and glycemic parameters rom continuous glucose monitoring (CGM) o all subjects included in the study.

HDL-C – high-density lipoprotein cholesterol; LDL-C – low-density lipoprotein cholesterol; HbA1c – glycated hemoglobin; AUC24h – area underthe curve obtained during 24 hour continuous glucose monitoring; SDBG – standard deviation o the mean blood glucose values; MAGE – meanamplitude o glycemic excursions; MODD – mean o daily diferences.

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Blood glucose variability of newly diagnosed type 2diabetes (Table 2)

After adjustment for age and gender, the MAGE, MODD,and AUC

24hvalues of the subjects with newly diagnosed type

2 diabetes were significantly higher than those of the subjects

with NGR (P <0.001), with 1.9-, 1.2-, and 1.0-fold increasesobserved in MAGE, MODD, and AUC

24h, respectively.

A significant positive correlation between HbA 1c and

AUC24h

was identified (r =0.83, P <0.01). However, no cor-relation was detected between HbA

1c and MAGE, MODD,

or AUCpp (r =0.067, 0.151, and 0.254, respectively, P >0.05).Using MAGE as a dependent variable and HbA

1c, AUC

24h,

fasting plasma glucose, two-hour postprandial plasma glu-cose, postprandial glucose peak, and AUCpp as indepen-dent variables, multivariant regression analyses indicatedthat AUCpp influences MAGE (adjusted R

2=0.56). Further,analyses concerning characteristics of postprandial glucose

variability indicated no significant differences of AUCpp,postprandial peak value, or time to peak among threemeals in NGR subjects (P >0.05). The AUCpp of breakfast in the patients with type 2 diabetes was significantly higher

than that of lunch (P <0.01), but similar to that of dinner(P >0.05). The time to peak BG after breakfast was shorterand its peak value higher than those after lunch and din-ner (P <0.05).

Comparison between pre-treatment and post-treatment of

subjects with newly diagnosed type 2 diabetes

Among the 23 newly diagnosed type 2 diabetic patients whorepeated CGM 2–3 weeks after starting insulin treatment,MAGE, MODD, and AUC

24hvalues were all significantly low-

er after therapy. However, the values remained significantly higher in the 23 newly diagnosed type 2 diabetic patients af-ter 2–3 weeks of insulin treatment than in the subjects withNGR (P <0.01, Figure 1). MAGE levels decreased 41%, drop-ping from 6.42±1.50 to 3.80±1.20 mmol/l (P <0.001), MODDlevels decreased 29%, dropping from 1.89±0.52 to 1.34±0.43mmol/l (P <0.001), and AUC

24hlevels decreased 42%, drop-

ping from 12.37±2.65 to 7.16±0.80 mmol·d/l (P <0.001). The

breakfast, lunch, and dinner AUCpp decreased 46%, 43%,and 55%, respectively, after MDI treatment. Furthermore,the after-breakfast AUCpp was higher than that after lunchand dinner (P <0.05, Figure 2). In 65.2% of the subjects

Breakfast Lunch Dinner

AUCpp(mmol·d/l)

NGR* 0.11±0.04 0.12±0.04 0.12±0.04

Type 2 diabetes** 0.60±0.20 0.44±0.19 0.59±0.21

Postprandial glucose peak(mmol/l)

NGR* 6.9±1.1 6.7±0.8 6.9±1.1

Type 2 diabetes** 17.5±3.2 14.4±3.6 14.8±2.5

Time to postprandial glucosepeak (min)

NGR* 40±19 42±19 45±20

Type 2 diabetes** 90±37 101±41 105±35

Table 2. Comparison o incremental areas above preprandial glucose values (AUCpp), postprandial glucose peak, and time to postprandial glucosepeak rom continuous glucose monitoring (CGM) between subjects with normal glucose regulation (n=48) and newly diagnosed type 2diabetic patients (n=69).

* No signicant diferences o AUCpp, postprandial glucose peak and time to postprandial glucose peak among three meals in NGR subjects (P >0.05);** AUCpp, postprandial glucose peak, and time to postprandial glucose peak o breakast in patients with type 2 diabetes were signicantly diferent

rom those ater lunch and dinner (P <0.01).

G l u c o s e c o n c e n t r a t i o n ( m m o l / L )

20

16

12

8

4

00:00 3:00 6:00 9:00 12:00 16:00 19:00 22:00

Time (hour)

Figure 1. Mean blood glucose proles romcontinuous glucose monitoring in 48subjects with normal glucose regulationand in 23 subjects with newly diagnosedtype 2 diabetes beore and ater 2 to 3weeks o intensive insulin treatment., subjects with newly diagnosed type2 diabetes beore intensive treatment;Δ, subjects with newly diagnosed type2 diabetes ater intensive treatment;,subjects with normal glucose regulation.


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(n=15), the peak intra-day values (11.2±0.7 mmol/l) oc-

curred 103±30 minutes after breakfast.

Among the 23 subjects who had not experienced hypogly-cemic episodes prior to treatment, 54.5% (n=12) had a to-tal of 19 hypoglycemic episodes that lasted, on average, 50minutes (range: 30–100 minutes) after treatment. Five of the19 episodes occurred at night, with 5 episodes ≤2.8 mmol/l.The MAGE values in subjects experiencing hypoglycemicepisodes after treatment were higher compared with thoseof the subjects without hypoglycemic episodes (4.34±1.25

vs. 3.20±0.95 mmol/l, P <0.05). No statistical difference in AUC

24hwas observed between those experiencing and those

not experiencing hypoglycemic episodes after treatment

(6.99±0.57 vs. 7.34±1.00 mmol·d/l,P

>0.05). A positive cor-relation between MAGE values and the number of hypogly-cemic episodes was observed (r =0.21, P <0.05).

DISCUSSION

Hyperglycemia is a hallmark of diabetes, and both the chron-ic and sustained deleterious effects of hyperglycemia are re-flected by HbA

1c levels and glycemic variability [23]. Some

prospective clinical studies, such as the Diabetes Controland Complications Trial (DCCT) and the Verona Diabetesstudy, have shown that HbA

1c-unrelated BG profiles, such

as glycemic variability, may have an effect on the occur-rence and development of chronic complications in dia-

betes [24,25]. CGM can detect glucose variability in moredetail than conventional self-monitoring methods of BG monitoring [26–28]. MAGE, MODD, and AUCpp valuesderived from CGM can be used to characterize intra-day,inter-day, and postprandial glucose variability in type 2 dia-betic patients. In this study, in addition to an overall eleva-tion in BG levels using the CGM system, subjects with newly diagnosed type 2 diabetes presented with greater glycemic

variability. Correlation analyses demonstrated that HbA 1c

represents the overall BG level, but did not reflect glycemic variability; hence type 2 diabetic patients with similar HbA

1c

values may differ in terms of glucose variability. The pres-ent study suggests that minimizing glycemic variability may

be an important aspect of glucose management. Different therapeutic strategies should be evaluated for their poten-tial to minimize glycemic variability as well as for their abil-ity to reduce HbA

1c. Our study demonstrates that intensive

treatment with MDI for 2 to 3 weeks could significantly de-

crease the amplitude of glycemic excursions when overallBG levels are decreased in type 2 diabetic patients with se-

vere hyperglycemia.

Additionally, our study demonstrates that intra-day glyce-mic variability can be largely attributed to post-meal glucoseexcursion in patients with type 2 diabetes. Compared withhealthy controls, patients with type 2 diabetes had higher

values and longer duration of postprandial glucose, which at-tributed to their postprandial glucose variability. Meanwhile,the peak BG values after breakfast were higher and the timeto peak shorter than those after lunch and dinner, explain-ing the increased frequency of acute postprandial hypergly-

cemia observed after breakfast compared with lunch anddinner. Current data have shown that an acute increase inglycemia, as observed in the postprandial state, can exert deleterious effects on the arterial wall through mechanismsincluding oxidative stress, endothelial dysfunction, and ac-tivation of the coagulation cascade [29–32]. The study by Ceriello and colleagues [33] demonstrated that pramlint-ide reduced markers of oxidative stress in the postprandialperiod in patients with type 2 diabetes. Therefore, control-ling glucose variability after breakfast should be the focalpoint of glucose monitoring and intervention in patients

with type 2 diabetes. Furthermore, after intensive treat-ment with MDI, the AUCpp of breakfast was highest andthe peak intra-day values occurred after breakfast in 65.2%

of the subjects. In accordance with previous observations[34], the present study shows that postprandial hypergly-cemia was most prominent following breakfast and less evi-dent during lunch and dinner. Whether medicines, such asa-glucosidase inhibitors, rapid-acting insulin secretagogues,or short-acting insulin analogs, which aim to control post-prandial glucose could lead to the same result or not re-mains unclear and requires further research.

Meanwhile, we also found that glucose peaks after meals were at around 100 min in type 2 diabetic patients. Coletteet al. [12] assessed the nycthemeral peaks of glucose usingCGMS in type 2 diabetic patients. The results showed that

the peaks of glucose were observed 120±24 min after break-fast. The study by Wentholt [35] demonstrated that themean peak width for the postprandial glucose curves was100.8±25.0 min and for the CGMS sensor curves 110.0±20.5

A U C p p ( m m o

l • d / L )

1.0

0.9

0.8

0.7

0.60.5

0.4

0.3

0.2

0.1

0.0

0.11

0.69

0.37

0.12

0.49

0.28

0.12

0.65

0.29

Breakast Lunch Dinner

NGRPre-treatmentPost-treatment

Figure 2. The incremental areas above preprandialglucose values (AUCpp) rom continuousglucose monitoring in 48 subjects withnormal glucose regulation and in 23subjects with newly diagnosed type 2diabetes beore and ater 2 to 3 weeks o

treatment with multiple daily injection(all P <0.001, ANOVA among the groups).


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min in type 1 diabetic patients. However, a recent study us-ing CGMS found either type 1 or type 2 diabetes reacheda peak 72 minutes after eating with a variation of 23 min-utes [36]. Current data using CGMS showed that the timeof the postprandial glucose peak after a meal varies greatly among individuals [37]. Various factors contribute to the

magnitude and time of the peak BG concentration, includ-ing the timing, composition, and quantity of the meal [38].Therefore, the time to measure postprandial glycemia is not codified. Further studies are required to determine the op-timal time to measure postprandial glucose.

Iatrogenic hypoglycemia has been the main hindrance inthe management of patients with type 2 diabetes [39,40].The time distribution and type and cause of hypoglycemiacould be analyzed well by CGM. Through the use of CGM,

we found in this study that intensive glucose control wouldincrease the risk of hypoglycemia, with larger glycemic ex-cursions occurring within the day potentially representa-tive of a predictor for increased risk of hypoglycemia after

intensive treatment. Further studies are required to deter-mine the best pharmacologic strategies for minimizing gly-cemic variability and lowering the incidence of hypoglyce-mia when BG levels are controlled.

CONCLUSIONS

This study showed that type 2 diabetic patients presentedgreater glycemic variability, independent of HbA

1c. Intensive

insulin treatment could significantly decrease the amplitudeof glycemic excursions which increase the risk of the hypo-glycemia. Intra-day glycemic variability can be largely attrib-uted to postprandial glucose excursions, while postprandial

hyperglycemia was most prominent following breakfast andless evident after lunch and dinner. Our findings suggest that minimizing glycemic variability in type 2 diabetic patients, es-pecially postprandial glucose excursions following breakfast,may be an important aspect of glucose management.

Acknowledgments

We are grateful to all colleagues at the Shanghai ClinicalCenter for Diabetes for their assistance in recruiting pa-tients.

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