Continuous Glucose Monitoring in Type 1 Diabetes Pregnancy Shows That Fetal Heart Rate Correlates with Maternal Glycemia

DIABETES TECHNOLOGY & THERAPEUTICS Volume 17, Number 9, 2015 ª Mary Ann Liebert, Inc. DOI: 10.1089/dia.2014.0255

ORIGINAL ARTICLE

Continuous Glucose Monitoring in Type 1 Diabetes Pregnancy Shows that Fetal Heart Rate Correlates with Maternal Glycemia

Katarzyna Cypryk, MD, PhD,1 Lukasz Bartyzel, MD,1 Monika Zurawska-Klis, MD, PhD,1 Wojciech Mlynarski, MD, PhD,2 Agnieszka Szadkowska, MD, PhD,2 Jan Wilczynski, MD, PhD,3 Dorota Nowakowska, MD, PhD,3 Lucyna A. Wozniak, PhD,4 and Wojciech Fendler, MD, PhD2

Abstract Background: Much evidence has shown that pregnancies in women with preexisting diabetes are affected by an increased risk of maternal and fetal adverse outcomes, probably linked to poor glycemic control. Despite great progress in medical care, the rate of stillbirths remains much higher in diabetes patients than in the general population. Recent technological advances in the field of glucose monitoring and noninvasive fetal heart rate monitoring made it possible to observe the fetal–maternal dependencies in a continuous manner. Subjects and Methods: Fourteen type 1 diabetes patients were involved into the study and fitted with a blinded continuous glucose monitoring (CGM) recorder. Fetal electrocardiogram data were recorded using the Monica AN24 device (Monica Healthcare Ltd., Nottingham, United Kingdom), the recordings of which were matched with CGM data. Statistical analysis was performed using a generalized mixed-effect logistic regression to account for individual factors. Results: The mean number of paired data points per patient was 254 – 106, representing an observation period of 21.2 – 8.8 h. Mean glycemia equaled 5.64 – 0.68 mmol/L, and mean fetal heart rate was 135 – 6 beats/min. Higher glycemia correlated with fetal heart rate (R = 0.32; P < 0.0001) and was associated with higher odds of the fetus developing small accelerations (odds ratio = 1.05; 95% confidence interval, 1.00–1.10; P = 0.04). Conclusions: Elevated maternal glycemia of mothers with diabetes is associated with accelerations of fetal heart rate.

Introduction decisions, contributing to better perinatal outcomes.7 Recent technological advances in the ﬁeld of glucose monitoring and dequate metabolic control of diabetes in pregnant noninvasive fetal heart rate (FHR) monitoring made it pos- women is a crucial method of preventing neonatal and A sible to observe the fetal–maternal dependencies in a con- obstetric complications. The rate of all perinatal complica- tinuous manner. Using two devices—a continuous glucose tions correlates with the mother’s glycated hemoglobin monitoring (CGM) system and a FHR monitor—we inves- (HbA1c) concentration.1–6 Unfortunately, HbA1c is a retro- tigated association between maternal glycemic ﬂuctuations spective parameter, and thus it is not particularly useful and FHR variability. during pregnancy when self-glucose monitoring is essential. However, achieving and maintaining normoglycemia during Subjects and Methods pregnancy in women with diabetes are major challenges. Adding the continuous monitoring to standard treatment The study group consisted of 14 white pregnant women could improve metabolic control and facilitate therapeutic with diabetes, treated with insulin. All available patients

Departments of 1Diabetology and Metabolic Diseases and 2Pediatrics, Oncology, Hematology and Diabetology, Medical University of Lodz, Poland. 3Feto-Maternal and Gynecology Department, Research Institute, Polish Mother’s Memorial Hospital, Lodz, Poland. 4Department of Structural Biology, Faculty of Biomedical Sciences and Postgraduate Education, Medical University of Lodz, Lodz, Poland.

619 620 CYPRYK ET AL. treated during the 2012–2013 period were assessed for with the CGM recording up to the nearest minute. Small FHR eligibility and asked to participate in the study. The in- accelerations and decelerations were defined, respectively, as clusion criteria were set as following: singleton pregnancy increases in the FHR from the baseline greater than 10 beats/ > 30 weeks of gestation and established type 1 diabetes. We min (bpm) and lasting for at least 15 s and as decreases of excluded patients with any comorbidities necessitating ‡ 10 bpm for ‡ 10 s. A large acceleration event was defined as pharmacological treatment, patients after in vitro fertil- an increase greater than 15 bpm and lasting for more than ization, pregnancies at risk of premature termination, ab- 15 s. A large deceleration event was defined as a fall in FHR normal findings in prenatal ultrasonography, or triple test. from the baseline, where the area below the baseline was The study was approved by the Bioethics Committee of the greater than 20 beats. Imputation of missing data was not Medical University of Lodz, Lodz, Poland. Eligible patients attempted. invited to the study, after their informed consent was ob- The paired CGM/ECG data points were used in the analysis. tained, were fitted with a CGM recorder (iPro2; Medtronic, Frequency of hypoglycemia ( < 70 mg/dL [3.9 mmol/L] and Minneapolis, MN) for a standard, at least 48-h-long, re- < 54 mg/dL [ < 3 mmol/L]) and hyperglycemia ( > 126 mg/dL cording. Throughout the study the patients had the option of [7 mmol/L]) were presented as percentage of the total CGM staying in the hospital or remaining in their own home. time. Mean glucose values and three parameters of glycemic The sensor was placed in the subcutaneous tissue using a variability (SD, M100, and J index) were calculated using an dedicated insertion device. Calibration of the CGM device online CGM variability calculator designed by the authors was done using the ACCU-CHEK glucometer (Roche, (GlyCulator) and verified using Microsoft (Redmond, WA) Basel, Switzerland), and measurements were performed at Excel. These indices of glycemic variability were selected as least four times per day. The obstetrics team was blinded to their methodology allows for noncontinuous data, which was CGM recordings during the study, and its results did not the case in our study.8–11 influence their clinical management during the study. Statistical analysis was performed using a generalized The endocrinological team was blinded to fetal electro- mixed-effect logistic regression model to estimate the cardiography data but could adjust insulin treatment de- glucose-dependent risk of FHR disturbances while account- pending on current glucose levels when necessary (blood ing for individual effects. The lme4 package for R was used glucose concentration less than 70 mg/dL [3.9 mmol/L] and for this analysis. more than 126 mg/dL [7 mmol/L]). Fetal electrocardiogram (ECG) data were recorded using the Monica AN24 device Results (Monica Healthcare Ltd., Nottingham, United Kingdom). All patients were fitted with this device between 1 p.m. and 5 Mean age of patients was 30.4 – 4.2 years (range, 25–37

p.m. after a run-in period of at least 3 h of CGM. After a years). Mean duration of diabetes was 14.6 – 7.6 years. Two calibration period of the ECG, the recording was started and patients had a body mass index of > 30 kg/m2, with the mean continued for at least 20 h. value in the whole group being 28.1 – 3.8 kg/m2.Gestational After removal of both devices, the ECG recording was week at evaluation was 33.5 – 1.0 (range, 32–36) (Table 1). No analyzed for a 5-min time frame using the manufacturer’s adverse events during the CGM/ECG recordings were noted in software (Monica DK; Monica Healthcare Ltd.), matched any of the studied patients. The mean number of paired data

Table 1. Study Group Characteristics Duration BMI Third- Gestational Neonatal Maternal of (kg/m2) trimester age Place Gestational birth Patient age Type of diabetes Insulin before HbA1c (weeks) at of age (weeks) weight ID (years) diabetes (years) therapy pregnancy (%) evaluation observation at delivery (g) 1 36 T1DM 26 MDI 28.6 6.20 33 Hospital 38 3,660 2 29 T1DM 8 CSII 26.5 5.86 33 Hospital 36 3,200 3 26 T1DM 17 CSII 27.9 6.45 33 Hospital 38 3,460 4 31 T1DM 23 CSII 34.1 5.30 33 Home 37 3,800 5 30 T1DM 18 CSII 29.4 6.03 33 Home 38 4,160 6 36 T1DM 8 CSII 24.3 5.55 33 Home 33 3,140 7 27 T1DM 2 MDI 25.1 5.60 33 Hospital 39 3,390 8 29 T1DM 25 CSII 28.8 5.68 33 Home 37 4,080 9 28 T1DM 22 CSII 37.6 6.12 34 Hospital 35 2,950 10 31 T1DM 7 CSII 24.7 6.10 35 Hospital 39 3,900 11 35 T1DM 15 MDI 25.5 6.30 34 Hospital 40 3,770 12 25 T1DM 12 CSII 28.6 6.00 36 Hospital 38 3,680 13 25 T1DM 15 CSII 23.9 6.97 32 Home 33 2,690 14 37 T1DM 7 CSII 27.8 5.16 34 Hospital 39 4,160 Mean – SD 30.4 – 4.2 — 14.6 – 7.6 — 28.1 – 3.8 5.95 – 0.48 33.5 – 1.0 — 37.1 – 2.17 3,574 – 456

Individual data of all 14 participants are presented in the respective rows. Means with SDs are presented in the last row. BMI, body mass index; CSII, continuous subcutaneous insulin infusion; HbA1c, glycated hemoglobin; MDI, multiple daily injections; T1DM, type 1 diabetes mellitus.

Table 2. Individual Data Recording Characteristics Patient ID Mean – SD or 1 2 3 4 5 6 7 8 9 10 11 12 13 14 median (25–75%) Glucose concentration (mmol/L) Mean 5.34 4.71 6.52 5.52 6.90 5.06 5.00 5.84 5.85 5.06 5.59 5.03 6.67 5.92 5.64 – 0.68 SD 2.00 1.50 2.07 1.76 2.14 1.10 1.29 0.90 2.06 1.37 2.15 1.49 2.11 1.68 1.69 – 0.42 M100 9.55 6.47 4.66 4.12 5.22 2.03 2.90 0.96 5.01 2.54 5.66 3.37 5.27 3.06 4.34 – 2.15 J index 17.45 12.46 23.87 17.2 26.5 12.29 12.86 17.87 20.28 13.39 19.41 13.77 24.96 18.7 17.93 – 4.74 Glucose concentration (mmol/L) Minimum 2.83 2.44 3 2.33 3.22 2.22 3.83 4.56 2.44 2.78 2.83 2.67 4.67 3.17 3.07 – 0.78 Maximum 9.89 10 10.78 8.11 9.78 8.22 7.61 8.11 9.89 8.11 10.61 10.22 10.78 9.44 9.40 – 1.28 621 % > 7 mmol/L 23.4 10.0 15.9 3.3 53.6 4.4 9.9 28.4 23.4 4.4 21.3 14.7 54.1 17.4 16.65 (9.93–23.40) % < 3.9 mmol/L 8.1 46.0 11.7 15.7 5.3 13.7 1.7 0.0 7.7 12.4 28.7 14.9 0.0 5.5 9.90 (5.35–14.60) % < 3.0 mmol/L 1.4 11.2 2.2 6.2 0.0 3.4 0.0 0.0 2.4 1.7 2.4 2.2 0.0 0.0 1.95 (0.00–2.40) FHR (bpm) Mean 128 138 131 123 135 133 138 137 144 136 132 133 145 134 135 – 6 SD 6.03 7.19 7.49 9.06 6.05 8.24 4.57 8.49 8.26 7.84 6.23 9.52 5.35 8.11 7.32 – 1.46 FHR (bpm) Minimum 117 116 101 105 115 112 122 113 125 115 117 112 133 114 116 – 8 Maximum 142 165 156 147 153 164 150 163 179 166 157 159 167 157 159 – 9 Percentage small Acceleration 0.43 0.41 0.33 0.37 0.38 0.39 0.49 0.5 0.4 0.43 0.23 0.46 0.44 0.47 0.41 – 0.07 Deceleration 0.18 0.24 0.31 0.31 0.18 0.09 0.18 0.13 0.18 0.18 0.25 0.29 0.19 0.32 0.22 – 0.07 R for FHR/glycemia correlation 0.29a 0.25a 0.21b 0.09 0.36a - 0.02 0.11 0.21a 0.38a 0.11b 0.35a 0.40a 0.10 0.34a NA

aP < 0.0001, bP < 0.05. bpm, beats/min; FHR, fetal heart rate; NA, not applicable; R, Pearson’s correlation coefﬁcient. 622 CYPRYK ET AL.

FIG. 1. Correlation between the time-point-matched maternal glycemia and fetal heart rate for pooled data points of all available patients/recordings. points per patient was 254 – 106, representing an observation In our study we did not observe any large, long-lasting period of 21.2 – 8.8 h. The mean glucose level equaled deceleration, the most dangerous heart disturbance, probably 5.64 – 0.68 mmol/L, and the mean FHR was 135 – 6bpm. because diabetes control achieved in the studied patients was Glycemic variability data and FHR characteristics are excellent. The mean HbA1c was 5.95 – 0.48%, and glycemia summarized in Table 2. In nine patients FHR showed sig- during the observation ranged from 2.22 to 10.78 mmol/L. nificant, positive correlation with the time-point-matched maternal glycemia, which consequently held true for an Discussion aggregate correlation analysis (R = 0.32; P < 0.0001) (Fig. 1). In five patients no such correlations were noted, and in one Adequate metabolic control of diabetes in pregnant case a significant negative correlation was noted. In mixed- women is a crucial method of preventing neonatal and ob- effect logistic regression analysis, higher glucose levels stetric complications. Hyperglycemia in pregnant women can were associated with higher odds of the fetus developing cause fetal malformations, growth disturbances, development small accelerations (odds ratio = 1.05; 95% confidence in- delay of the central nervous system, chronic hypoxemia, and, terval, 1.00–1.10; P = 0.04). None of the analyzed individual- finally, spontaneous abortion, stillbirth, prematurity, and level factors, like patient’s age (P = 0.38), body mass index many other fetal complications, including hypoglycemia, (P = 0.66), duration of diabetes (P = 0.32), gestational week macrosomy, etc. Those are well documented in the in vitro (P = 0.93), or nighttime measurements (P = 0.07), signifi- and in human studies.1–5 cantly affected the association between maternal glucose A Swedish study proved that stillbirth rate in women with and FHR accelerations. The risk of small decelerations did type 1 diabetes was more than three times higher than in the not, however, depend significantly on current maternal glu- background population.6 Cardiotocography (fetal ECG) is an cose levels (odds ratio = 0.97; 95% confidence interval, established method to monitor fetal well-being and is es- 0.92–1.03; P = 0.32), with nighttime measurements signifi- sential to avoid intrauterine death by early detection of fetal cantly decreasing the odds of deceleration events (odds ra- compromise. Bjo¨rklund et al.12 revealed that maternal hy- tio = 0.49; 95% confidence interval, 0.41–0.58; P < 0.0001). poglycemia induced during hyperinsulinemic/hypoglycemic Similarly, with acceleration events, none of the evaluated clamp with induction and maintenance of an arterial blood individual factors—patient’s age (P = 0.51), body mass in- glucose level of about 2.2 mmol/L was associated with an dex (P = 0.56), duration of diabetes (P = 0.83), or gestational increase in frequency and amplitude of FHR accelerations week (P = 0.35)—showed any associations with the odds of and a slight decrease in the pulsatility index of the umbilical deceleration events. artery and with a rise in the maternal catecholamine levels. FETAL HEART RATE AND MATERNAL GLYCEMIA 623

However, Reece et al.13 did not observe an influence of of the mother and fetal well-being in various levels of gly- maternal hypoglycemia in pregnant women with diabetes on cemic control. the mean number of fetal limb, body, and breathing move- ments or a heart rate, although maternal epinephrine and Acknowledgments growth hormone levels were significantly increased. This study was supported financially by funds of the In a study by Serra-Serra et al.14 the impact of maternal Medical University of Lodz (project number 502-03/0-160- blood glucose concentration on cardiotocographic results in 01/502-04-014). pre- and postmeal stage was measured. The authors con- cluded that FHR parameters are unaffected by prandial glycemic changes over a wide range (4.2–14.8 mmol/L) of Author Disclosure Statement maternal glucose levels in any of the groups of women with No competing financial interests exist. gestational diabetes, pregestational diabetes, and healthy pregnant volunteers without diabetes.14 On the other hand, Buscicchio et al.15 showed that gesta- References tional diabetes did impact FHR. The alteration was slight but 1. Vargas R, Repke JT, Ural SH: Type 1 diabetes mellitus and 15 evident, and it correlated with neonatal reactivity. Un- pregnancy. Rev Obstet Gynecol 2010;3:92–100. fortunately, in this study the blood glucose level was mea- 2. Inkster ME, Fahey TP, Donnan PT, Leese GP, Mires GJ, sured only once, at delivery. 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