□ ORIGINAL ARTICLE □Major Increases between Pre- and Post-breakfast Glucose
Levels May Predict Nocturnal Hypoglycemia
in Type 2 Diabetes
Soichi Takeishi, Akihiro Mori, Miyuka Kawai, Yohei Yoshida, Hiroki Hachiya,
Takayuki Yumura, Shun Ito, Takashi Shibuya, Nobutoshi Fushimi,
Noritsugu Ohashi and Hiromi Kawai

Abstract
Objective The aim of this study was to determine whether nocturnal hypoglycemia may be predicted according to morning glucose levels.
Methods We retrospectively evaluated 106 patients with type 2 diabetes who underwent continuous glucose
monitoring during admission. The pre-breakfast glucose level (Pre-breakfast level), highest postprandial glucose level within 3 hours after breakfast (Highest level), time from the start of breakfast to the highest
postprandial glucose level (Highest time), difference between the pre-breakfast and highest postprandial
breakfast glucose levels (Increase), area under the glucose curve (!180 mg/dL) within 3 hours after breakfast(Morning AUC), post-breakfast glucose gradient (Gradient), and the increase-to-pre-breakfast ratio (Increase/
Pre-breakfast) were calculated. The subjects were divided into hypoglycemic and non-hypoglycemic patientsand compared for the above parameters using the t-test. A receiver operating characteristic analysis was used
to determine the optimal cut-off values to predict nocturnal hypoglycemia (Hypoglycemia).
Results Twenty-eight patients (26.4%) had hypoglycemia. The Pre-breakfast levels were significantly lower
in patients with hypoglycemia than those without (p=0.03). The Increases were significantly higher in patientswith hypoglycemia than those without (p=0.047). The Increase/Pre-breakfast ratio were significantly larger inpatients with hypoglycemia than those without (p=0.0002). Their cut-off values were as follows (level, sensitivity, specificity, and area under the curve): 123 mg/dL, 0.89, 0.55, and 0.78 (p<0.0001); 90.5 mg/dL, 0.75,
0.64, and 0.76 (p<0.0001); and 90.2%, 0.75, 0.76, and 0.78 (p<0.0001), respectively.
Conclusion Major increases between the pre- and post-breakfast glucose levels may predict nocturnal hypoglycemia in patients with type 2 diabetes.
Key words: nocturnal hypoglycemia, morning glucose increases, type 2 diabetes(Intern Med 55: 2933-2938, 2016)(DOI: 10.2169/internalmedicine.55.7085)

Introduction
Large clinical studies have shown that hypoglycemia isstrongly associated with mortality in patients with diabetes
mellitus (1-4). Although a relationship between nocturnal
hypoglycemia and sudden death has been suggested (5), predicting nocturnal hypoglycemia is challenging in patientswith type 2 diabetes, as many of these patients are unawareof their conditions, especially patients with advanced diseaseor elderly patients (6).
Nocturnal hypoglycemia has been suggested to be associated with not only major hyperglycemia in daytime (7, 8),
but also increased morning glucose levels (9). Thus, clinicalsignificance is high if morning glycemic variability can predict the presence of nocturnal hypoglycemia. However, theDepartment of Endocrinology and Diabetes, Ichinomiyanishi Hospital, Japan
Received for publication January 6, 2016; Accepted for publication February 24, 2016
Correspondence to Dr. Soichi Takeishi, souichi19811225@yahoo.co.jp2933

Intern Med 55: 2933-2938, 2016

DOI: 10.2169/internalmedicine.55.7085

Figure 1. The graph indicates glycemic variability from nighttime to morning of continuous glucose monitoring in hypoglycemic patients (p=28) or non-hypoglycemic patients (p=78). Data areshown as the mean (thick lines) and standard deviation (fine lines).

mechanism of this relationship remains unknown. The Somogyi phenomenon (10, 11) is a cause of increased morning
glucose levels. However, the dawn phenomenon (11, 12) can
also cause increased morning glucose levels. Thus, an investigation based on continuous glucose monitoring from nighttime to morning is necessary to determine whether nocturnal
hypoglycemia may be predicted based on morning glucose
levels.
We therefore retrospectively studied whether nocturnal
hypoglycemia may be predicted based on morning glucose
levels in patients with type 2 diabetes using continuous glucose monitoring (13) (CGM) data.

Materials and Methods
Study design and patient selection

We retrospectively analyzed 106 patients with type 2 diabetes who underwent CGM during admission during a 2year period from 2013 to 2015. The study was approved by
the institutional review board of Ichinomiyanishi Hospital,
Japan. All of the patient data extracted were anonymized.
Patients who were aware of their hypoglycemia and took
glucose tablets and those who had been taking αglucosidase inhibitors were excluded. We used CGM datameasured with the Medtronic ipro2 device (Medtronic MiniMed, Northridge, USA). Nocturnal hypoglycemia was de-fined as a blood glucose level of <70 mg/dL occurring from
0 am to 8 am. The subjects were also evaluated for the duration of nocturnal hypoglycemia.
Outcomes and statistical analysis

The parameters used as indices of glycemic variability included pre-breakfast glucose level (Pre-breakfast level),highest postprandial glucose level within 3 hours after
breakfast (Highest level), time from the start of breakfast to
the highest postprandial glucose level (Highest time), difference between pre-breakfast and highest postprandial breakfast glucose levels (Increase), area under the glucose curve(!
180 mg/dL) within 3 hours after breakfast (Morning
AUC), post-breakfast glucose gradient (Gradient), and theincreased glucose level/pre-breakfast glucose level ratio (Increase/Pre-breakfast) (14).
The subjects were divided into hypoglycemic and nonhypoglycemic patients and compared for the above parameters using the t-test to examine whether the occurrence ofnocturnal hypoglycemia may be predicted according to an
analysis of these parameters. We analyzed the association
between the patient characteristics [age, sex, duration of diabetes, body mass index (BMI), glycosylated hemoglobin(HbA1c) concentration, C-peptide index (CPI) and the presence of antidiabetic agents] and nocturnal hypoglycemia using a logistic regression analysis. A receiver operating characteristic (ROC) analysis was used to determine the optimal

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DOI: 10.2169/internalmedicine.55.7085

Table 1. Sample Characteristics and Parameters for Glycemic Variability Compared between Hypoglycemic and Non-hypoglycemic Patients.
Characteristic
Overall
Hypoglycemic Non-hypoglycemicp
N (Male / Female)106 (56 / 50)
28 (11 / 17)
78 (45 / 33) p2=0.09
Age, years
66.6 ± 11.0
69.8 ± 10.1
65.5 ± 11.2 p1=0.07
Duration of diabetes, years
14.7 ± 10.7
15.9 ± 11.4
14.3 ± 10.5 p1=0.51
BMI, kg/m2
23.7 ± 3.9
22.7 ± 2.9
24.1 ± 4.2 p1=0.07
HbA1c (NGSP), %8.7 ± 1.4
8.9 ± 1.7
8.6 ± 1.3 p1=0.34
HbA1c (IFCC), mmol/mol
71.2 ± 15.6
73.9 ± 18.3
70.2 ± 14.6 p1=0.34
CPI
1.0 ± 0.8
1.0 ± 1.0
1.0 ± 0.7 p1=0.87
Total daily insulin dose, U
21.1 ± 16.3
22.5 ± 20.6
20.4 ± 14.0 p1=0.65
Basal insulin ratio, %75.7 ± 26.5
79.3 ± 25.2
74.0 ± 27.1 p1=0.42
Nighttime duration of hypoglycemia, min51.7 ± 89.7
161.2 ± 86.2
0 ± 0 p1<0.0001
Pre-breakfast glucose level, mg/dL
128.7 ± 33.8
115.8 ± 35.4
133.4 ± 39.1 p1=0.03
Highest glucose level, mg/dL
226.4 ± 62.7
252.1 ± 75.6
217.2 ± 55.6 p1=0.03
Highest glucose time, min
100.8 ± 42.2
114.4 ± 41.0
96.0 ± 41.7 p1=0.047
Increase glucose level, mg/dL
97.7 ± 56.3
136.3 ± 56.8
83.9 ± 49.6 p1<0.0001
AUC (180 mg/dL), mg min/dL
7,027.4 ± 9,268.6 11,254.4 ± 12,831.5
5,510.0 ± 7,112.1 p1=0.03
Glucose gradient, mg/dL min
1.1 ± 1.2
1.3 ± 0.5
1.1 ± 1.4 p1=0.35
Increase/Pre-breakfast, %85.4 ± 62.5
124.7 ± 66.0
71.3 ± 57.4 p1=0.0002
Sulfonylurea agent, n (%)
10 (9.4)
2 (7.1)8 (10.3) p2=0.63
Metformin, n (%)
68 (64.2)
16 (57.1)
52 (66.7) p2=0.37
Thiazolidinediones, n (%)
17 (16.0)
7 (25.0)
10 (12.8) p2=0.13
Į- glucosidase inhibitor, n (%)
0 (0)Insulin, n (%)
70 (66.0)
20 (71.4)
50 (66.0) p2=0.48
DPP-4 inhibitors, n (%)
58 (54.7)
19 (67.9)
39 (50.0)
p2=0.1
GLP-1 receptor agonists, n (%)
13 (12.3)
5 (17.9)
8 (10.3) p2=0.29
Rapid-acting insulin secretagogue, n (%)
11 (10.4)
3 (10.7)
8 (10.3) p2=0.95
SGLT 2 inhibitor, n (%)
19 (17.9)
3 (10.7)
16 (20.5) p2=0.25
Insulin or sulfonylurea agent/Other agents
76/30
22/6
54/24 p2=0.35

Data are shown as the mean and standard deviation (SD). p1: Welch’s t -test, p2: Chi-square test. BMI: bodymass index, HbA1c: glycosylated hemoglobin, CPI: C-peptide index, Highest glucose level, highest postprandial glucose level within 3 h after breakfast; Highest glucose time, time from the start of breakfast to the highest postprandial glucose level; Increase glucose level, difference between pre-breakfast and highest postprandial breakfast glucose levels; AUC (≥180 mg/dL), area under the glucose curve (≥180 mg/dL) within 3 h after
breakfast; Glucose gradient, post-breakfast glucose gradient; Increase/Pre-breakfast, the increased glucose level/pre-breakfast glucose level ratio; Hypoglycemia, nocturnal hypoglycemia (<70 mg/dL occurring from 0 am
to 8 am); DPP: dipeptidyl-peptidase, GLP: glucagon-like peptide, SGLT: sodium glucose co-transporter

cut-off values to predict nocturnal hypoglycemia (Hypoglycemia) (15). A p value <0.05 was considered to be statistically significant. Data are shown as the mean and standard
deviation (SD).

Results
Patient characteristics

Fig. 1 shows glycemic variability from nighttime to morning of CGM in hypoglycemic patients (n=28) and nonhypoglycemic patients (n=78). Table 1 shows sample characteristics and parameters for glycemic variability compared
between hypoglycemic and non-hypoglycemic patients. The
study included 56 men and 50 women. The baseline characteristics included: mean age of 66.6±11.0 years, body massindex of 23.7±3.9 kg/m2, HbA1c level of 8.7±1.4 % (71.2±
15.6 mmol/mol), duration of diabetes of 14.7±10.7 years,
and C-peptide index (= fasting C-peptide immunoreactivity/
FPG ×100) (CPI) of 1.0±0.8. Seventy subjects received insulin therapy [basal-bolus insulin therapy (n=27) or basal in-sulin therapy (n=43)] with long-acting insulin [insulin
glargine (n=37) or insulin degludec (n=33)]. Long-acting insulin was injected once at 8 am. The indices of glycemic
variability were as follows: Pre-breakfast level, 128.7±33.8
mg/dL; Highest level, 226.4±62.7 mg/dL; Highest time,
100.8±42.2 minutes; Increase, 97.7±56.3 mg/dL; Morning
AUC, 7,027.4±9,268.6 mg·min/dL; Gradient, 1.1±1.2 mg/dL·min; and the Increase/Pre-breakfast ratio, 85.4±62.5%.
Twenty-eight patients (26.4%) had hypoglycemia. Hypoglycemic patients were shown to have nocturnal hypoglycemia
lasting 161.2±86.2 minutes.
Primary outcomes

The Pre-breakfast levels were significantly lower among
patients with hypoglycemia at 115.8±35.4 mg/dL compared
to 133.4±39.1 mg/dL among those without (p=0.03). The
Highest levels were significantly higher among patients withhypoglycemia at 252.1±75.6 mg/dL compared to 217.2±55.6
mg/dL among those without (p=0.03). The Highest times
were significantly longer among patients with hypoglycemia
at 114.4±41.0 minutes compared to 96.0±41.7 minutes

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Table 2. The Relationship between Sample Characteristics and Hypoglycemia.

Discussion(n = 106)
Variable
Age, years
Male sex, nDuration of diabetes, years
BMI, kg/m2
HbA1c (NGSP), %CPI
Total daily insulin dose, U
Basal insulin ratio, %Sulfonylurea agent, nMetformin, nThiazolidinediones, nInsulin, n
DPP-4 inhibitors, n
GLP-1 receptor agonists, n
Rapid-acting insulin secretagogue, n
SGLT 2 inhibitor, nInsulin or Sulfonylurea agent, nHypoglycemia
OR (95% CI)
1.04 (0.995-1.09)
0.47 (0.20-1.15)
1.01 (0.97-1.06)
0.91 (0.81-1.03)
1.18 (0.87-1.59)
1.05 (0.61-1.81)
1.01 (0.98-1.04)
2.16 (0.33-14.16)
0.67 (0.13-3.38)
0.67 (0.28-1.61)
2.27 (0.77-6.69)
1.40 (0.55-3.59)
2.11 (0.85-5.24)
1.90 (0.57-6.40)
1.05 (0.26-4.27)
0.47 (0.12-1.74)
1.63 (0.59-4.53)

p
0.08
0.1
0.49
0.13
0.28
0.85
0.6
0.42
0.63
0.36
0.14
0.48
0.11
0.3
0.95
0.25
0.35

Data were analyzed using a univariate logistic regression analysis.
OR: odds ratio, CI: confidence interval

among those without (p=0.047). The Increases were significantly higher among patients with hypoglycemia at 136.3±
56.8 mg/dL compared to 83.9±49.6 mg/dL among those
without (p=0.047). The Morning AUC were significantly
larger among patients with hypoglycemia at 11,254.4±
12,831.5 mg・min/dL compared to 5,510.0±7,112.1 mg・min/dL among those without (p=0.03). The Increase/Prebreakfast ratio were significantly larger among patients withhypoglycemia at 124.7±66.0% compared to 71.3±57.4%
among those without (p=0.0002). The Gradient was not significantly different between the two groups (Table 1).
According to a univariate analysis, the patient characteristics and use of antidiabetic agents were not associated with
Hypoglycemia (Table 2).
In the subjects receiving insulin therapy, the total daily insulin dose and basal insulin ratio were not associated with
Hypoglycemia. Insulin degludec (vs. insulin glargine) therapy was associated with Hypoglycemia (OR, 0.32; 95% CI,
0.11-0.92; p=0.03).
Fig. 2 shows the ROC curves for hypoglycemia according
to the indices of glycemic variability. Regarding the Prebreakfast glucose level, a cut-off value of 123 mg/dL, which
had the highest predictive ability, had a sensitivity of 89%
and specificity of 55%. The AUC for hypoglycemia was
0.78 (95% CI 0.68-0.87, p<0.0001). Regarding Increase, acut-off value of 90.5 mg/dL, which had the highest predictive ability, had a sensitivity of 75% and specificity of 64%.
The AUC for hypoglycemia was 0.76 (95% CI 0.65-0.86,
p<0.0001). Regarding the Increase/Pre-breakfast ratio, a cutoff value of 90.2%, which had the highest predictive ability,
had a sensitivity of 75% and specificity of 76%. The AUC
for hypoglycemia was 0.78 (95% CI 0.69-0.87, p<0.0001).

A high risk of abnormal QT prolongation in the earlymorning in diabetic and non-diabetic patients with severe
hypoglycemia has been reported (16). The relationships between hypoglycemia and abnormal QT prolongation, cardiac
arrhythmia, and sudden death in patients with type 2 diabetes have been also reported (17). High risks of silent hypoglycemia and arrhythmias in patients with type 2 diabetes
and cardiovascular diseases have been clarified (18). Thus,
hypoglycemia in patients with type 2 diabetes may cause
sudden death due to fatal arrhythmia, therefore hypoglycemia awareness is crucial. However, determining nocturnal
hypoglycemia unawareness is difficult and often becomesproblematic in everyday clinical practice (6).
On the other hand, hypoglycemia has been known tocause subsequent increases in the glucose level (Somogyi
phenomenon) (19). Thus, if we evaluate patients with increased morning glucose levels in detail, we may detect patients who have nocturnal hypoglycemia. However, thecauses of increased morning glucose levels are the effect ofthe dawn phenomenon (20) and increased glucose level after
the first meal (breakfast) (21), as well as the Somogyi phenomenon, which are difficult to distinguish by merely measuring morning hyperglycemia. In fact, a previous report
could not show the relationship between severe morning hyperglycemia and nocturnal hypoglycemia (22). Thus, we focused on not only morning hyperglycemia, but also glycemic variability from nighttime to morning using CGM.
CGM allows for the detection of continuous glycemic variations and is useful to evaluate variability (23, 24). As a result, we suggest that nocturnal hypoglycemia may be predicted when pre-breakfast glucose levels are <120 mg/dL,
glucose levels increase to !90 mg/dL, and the Increase/Prebreakfast ratios are !
90%. This indicates that patients who
have highly elevated morning glucose levels, despite rather
low pre-breakfast glucose levels, are likely to have nocturnal
hypoglycemia. The results of the ROC analysis in this study
suggest that simple pre-breakfast glucose levels can predict
nocturnal hypoglycemia to the same degree as increased glucose levels or Increase/Pre-breakfast ratios. Naturally, lower
pre-breakfast glucose levels can greater predict nocturnal hypoglycemia. As a result, it is significant that the predictive
abilities of increased glucose levels or Increased/Prebreakfast ratios are similar to the pre-breakfast glucose levels.
Although these results were analyzed using the CGM
data, only two points can predict nocturnal hypoglycemia(pre- and post-breakfast levels). Therefore, it is possible tosubstitute the self-measurement of blood glucose (SMBG)
for CGM. Determining nocturnal hypoglycemia unawarenessby a 2-point SMBG is easy and useful with a high clinicalsignificance. We consider that the Somogyi phenomenon is
likely in patients with major increases between pre- andpost-breakfast glucose levels, despite low pre-breakfast glu-

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1

0.8

0.6
Sensitivity
0.4

0.2

Pre-breakfast glucose level

AUC 0.78 (95% CI: 0.68 - 0.87, p < 0.0001)
Cutoff: 123 mg/dL, Sensitivity: 0.89, Specificity: 0.55

Increase glucose level

AUC 0.76 (95% CI: 0.65 - 0.86, p < 0.0001)
Cutoff: 90.5 mg/dL, Sensitivity: 0.75, Specificity: 0.64

Increase/Pre-breakfast

AUC 0.78 (95% CI: 0.69 - 0.87, p < 0.0001)
Cutoff: 90.2 %, Sensitivity: 0.75, Specificity: 0.76

0
0

0.2

0.4

0.6

0.8

1

1 - Specificity

Figure 2. ROC curves for hypoglycemia in indices for glycemic variability. Pre-breakfast glucose
level: The cut-off value of 123 mg/dL, which had the highest predictive ability, had a sensitivity of
89% and specificity of 55%. The AUC for hypoglycemia was 0.78 (95% CI 0.68-0.87, p<0.0001). Increase glucose level: The cut-off value of 90.5 mg/dL, which had the highest predictive ability, had asensitivity of 75% and specificity of 64%. The AUC for hypoglycemia was 0.76 (95% CI 0.65-0.86,
p<0.0001). Increase/Pre-breakfast: The cut-off value of 90.2%, which had the highest predictive ability, had a sensitivity of 75% and specificity of 76%. The AUC for hypoglycemia was 0.78 (95% CI
0.69-0.87, p<0.0001). ROC: receiver operating characteristic, AUC: area under the curve, CI: confidence interval, Increase glucose level, difference between pre-breakfast and highest postprandial
breakfast glucose levels; Increase/Pre-breakfast, the increased glucose level/pre-breakfast glucose
level ratio.

cose levels. In this case, we consider that treatments should
be adjusted in order to reduce nocturnal hypoglycemia.
This study showed that major increases between pre- andpost-breakfast glucose levels may predict nocturnal hypoglycemia in patients with type 2 diabetes. However, this study
was conducted retrospectively and the antidiabetic agentsused in this study were not standardized (sulfonylurea agent
or insulin were used). Hence, the validity of these resultsmust be evaluated in a prospective study where the use ofantidiabetic agents is standardized.

of the Hong Kong Society of Endocrinology, Metabolism andReproduction, November 21 and 22, 2015.

References

The authors state that they have no Conflict of Interest (COI).
Financial Support
This work was supported in part by Ichinomiyanishi Hospital.
Acknowledgement
Parts of this study were presented in oral presentation form at
the 7th AASD Scientific Meeting and Annual Scientific Meeting
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