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Rademaker D, van der Wel AWT, van Eekelen R, Voormolen DN, de Valk HW, Evers IM, Mol BW, Franx A, Siegelaar SE, van Rijn BB, DeVries JH, Painter RC. Continuous glucose monitoring metrics and pregnancy outcomes in insulin-treated diabetes: A post-hoc analysis of the GlucoMOMS trial. Diabetes Obes Metab 2023; 25:3798-3806. [PMID: 37735847 DOI: 10.1111/dom.15276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 08/23/2023] [Accepted: 08/28/2023] [Indexed: 09/23/2023]
Abstract
AIM To investigate the association between continuous glucose monitoring (CGM) metrics and perinatal outcomes in insulin-treated diabetes mellitus in pregnancy. MATERIALS AND METHODS In a post-hoc analysis of the GlucoMOMS randomized controlled trial, we investigated the association between the metrics of an offline, intermittent CGM, glycated haemoglobin (HbA1c) and perinatal outcomes per trimester in different types of diabetes (type 1, 2 or insulin-treated gestational diabetes mellitus [GDM]). Data were analysed using multivariable binary logistic regression. Outcomes of interest were neonatal hypoglycaemia, pre-eclampsia, preterm birth, large for gestational age (LGA) and Neonatal Intensive Care Unit (NICU) admission. The glucose target range was defined as 3.5-7.8 mmol/L (63-140 mg/dL). RESULTS Of the 147 participants (N = 50 type 1 diabetes, N = 94 type 2 diabetes/insulin-treated GDM) randomized to the CGM group of the GlucoMOMS trial, 115 participants had CGM metrics available and were included in the current study. We found that, in pregnancies with type 1 diabetes, a higher second trimester mean glucose was associated with LGA (odds ratio 2.6 [95% confidence interval 1.1-6.2]). In type 2 and insulin-treated gestational diabetes, an increased area under the curve above limit was associated with LGA (odds ratio 10.0 [95% confidence interval 1.4-72.8]). None of the CGM metrics were associated with neonatal hypoglycaemia, pre-eclampsia, shoulder dystocia, preterm birth and NICU admission rates for pregnancies complicated by any type of diabetes. CONCLUSION In this study, in type 2 diabetes or insulin-treated GDM, the glucose increased area under the curve above limit was associated with increased LGA. In type 1 diabetes, the mean glucose was the major determinant of LGA. Our study found no evidence that other CGM metrics determined adverse pregnancy outcomes.
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Affiliation(s)
- Doortje Rademaker
- Amsterdam UMC location University of Amsterdam, Department of Obstetrics and Gynecology, Amsterdam, The Netherlands
- Amsterdam Reproduction & Development Research Institute, Amsterdam, The Netherlands
| | - Anne W T van der Wel
- Amsterdam UMC location University of Amsterdam, Department of Obstetrics and Gynecology, Amsterdam, The Netherlands
| | - Rik van Eekelen
- Amsterdam UMC location University of Amsterdam, Department of Obstetrics and Gynecology, Amsterdam, The Netherlands
| | | | - Harold W de Valk
- Department of Endocrinology, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Inge M Evers
- Department of Obstetrics and Gynecology, Amersfoort, The Netherlands
| | - Ben Willem Mol
- Department of Obstetrics and Gynecology, Monash University, Clayton, Victoria, Australia
- Aberdeen Centre for Women's Health Research, Institute of Applied Health Sciences, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Abderdeen, UK
| | - Arie Franx
- Department of Obstetrics and Gynecology, Erasmus University, Rotterdam, The Netherlands
| | - Sarah E Siegelaar
- Amsterdam UMC location University of Amsterdam, Department of Endocrinology and Metabolism, Amsterdam, The Netherlands
- Amsterdam Gastroenterology Endocrinology and Metabolism, Amsterdam, The Netherlands
| | - Bas B van Rijn
- Department of Obstetrics and Gynecology, Erasmus University, Rotterdam, The Netherlands
| | - J Hans DeVries
- Amsterdam UMC location University of Amsterdam, Department of Endocrinology and Metabolism, Amsterdam, The Netherlands
| | - Rebecca C Painter
- Amsterdam Reproduction & Development Research Institute, Amsterdam, The Netherlands
- Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Obstetrics and Gynecology, Amsterdam, The Netherlands
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Bao Y, Chen L, Chen L, Dou J, Gao Z, Gao L, Guo L, Guo X, Ji L, Ji Q, Jia W, Kuang H, Li Q, Li Q, Li X, Li Y, Li L, Liu J, Ma J, Ran X, Shi L, Song G, Wang Y, Weng J, Xiao X, Xie Y, Xi G, Yang L, Zhao Z, Zhou J, Zhou Z, Zhu D, Zou D. Chinese clinical guidelines for continuous glucose monitoring (2018 edition). Diabetes Metab Res Rev 2019; 35:e3152. [PMID: 30884108 DOI: 10.1002/dmrr.3152] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/07/2018] [Revised: 01/22/2019] [Accepted: 02/19/2019] [Indexed: 02/05/2023]
Abstract
Blood glucose monitoring is an important part of diabetes management. Continuous glucose monitoring (CGM) technology has become an effective complement to conventional blood glucose monitoring methods and has been widely applied in clinical practice. The indications for its use, the accuracy of the generated data, the interpretation of the CGM results, and the application of the results must be standardized. In December 2009, the Chinese Diabetes Society (CDS) drafted and published the first Chinese Clinical Guideline for Continuous Glucose Monitoring (2009 edition), providing a basis for the standardization of CGM in clinical application. Based on the updates of international guidelines and the increasing evidence of domestic studies, it is necessary to revise the latest CGM guidelines in China so that the recent clinical evidence can be effectively translated into clinical benefit for diabetic patients. To this end, the CDS revised the Chinese Clinical Guideline for Continuous Glucose Monitoring (2012 Edition) based on the most recent evidence from international and domestic studies.
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Affiliation(s)
- Yuqian Bao
- Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Li Chen
- Qilu Hospital of Shandong University, Jinan City, Shandong Province, China
| | - Liming Chen
- Tianjin Medical University Metabolic Disease Hospital, Tianjin, China
| | - Jingtao Dou
- Chinese People's Liberation Army General Hospital, Beijing, China
| | - Zhengnan Gao
- Dalian Municipal Central Hospital Affiliated of Dalian Medical University, Dalian City, Liaoning Province, China
| | - Leili Gao
- Peking University People's Hospital, Beijing, China
| | - Lixin Guo
- Beijing Hospital of the Ministry of Health, Beijing, China
| | - Xiaohui Guo
- Peking University First Hospital, Beijing, China
| | - Linong Ji
- Peking University People's Hospital, Beijing, China
| | - Qiuhe Ji
- Xijing Hospital of the Fourth Military Medical University, Xi'an City, Shanxi Province, China
| | - Weiping Jia
- Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Hongyu Kuang
- The First Affiliated Hospital of Harbin Medical University, Harbin City, Heilongjiang Province, China
| | - Qifu Li
- The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Qiang Li
- The Second Affiliated Hospital of Harbin Medical University, Harbin City, Heilongjiang Province, China
| | - Xiaoying Li
- Zhongshan Hospital Affiliated to Fudan University, Shanghai, China
| | - Yanbing Li
- The First Affiliated Hospital, Sun Yat-sen University, Guangzhou City, Guangdong Province, China
| | - Ling Li
- Shengjing Hospital of China Medical University, Shenyang City, Liaoning Province, China
| | - Jing Liu
- Gansu Provincial Hospital, Lanzhou City, Gansu Province, China
| | - Jianhua Ma
- Nanjing First Hospital Affiliated to Nanjing Medical University, Nanjing City, Jiangsu Province, China
| | - Xingwu Ran
- West China Hospital of Sichuan University, Chengdu City, Sichuan Province, China
| | - Lixin Shi
- The Affiliated Hospital of Guizhou Medical University, Guiyang City, Guizhou Province, China
| | - Guangyao Song
- Hebei General Hospital, Shijiazhuang City, Hebei Province, China
| | - Yufei Wang
- Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Jianping Weng
- The First Affiliated Hospital, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei City, Anhui Province, China
| | - Xinhua Xiao
- Peking Union Medical College Hospital, Beijing, China
| | - Yun Xie
- Tianjin Medical University Metabolic Disease Hospital, Tianjin, China
| | - Guangxia Xi
- Shanxi Dayi Hospital, Taiyuan City, Shanxi Province, China
| | - Liyong Yang
- The First Affiliated Hospital of Fujian Medical University, Fuzhou City, Fujian Province, China
| | - Zhigang Zhao
- Zhengzhou Yihe Hospital Affiliated to Henan University, Zhengzhou City, Henan Province, China
| | - Jian Zhou
- Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Zhiguang Zhou
- The Second Xiangya Hospital of Central South University, Changsha City, Hunan Province, China
| | - Dalong Zhu
- Drum Tower Hospital Affiliated to Nanjing University Medical School, Nanjing City, Jiangsu Province, China
| | - Dajin Zou
- Changhai Hospital Affiliated to the Second Military Medical University, Shanghai, China
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3
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Jones LV, Ray A, Moy FM, Buckley BS. Techniques of monitoring blood glucose during pregnancy for women with pre-existing diabetes. Cochrane Database Syst Rev 2019; 5:CD009613. [PMID: 31120549 PMCID: PMC6532756 DOI: 10.1002/14651858.cd009613.pub4] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
BACKGROUND There are a number of ways of monitoring blood glucose in women with diabetes during pregnancy, with self-monitoring of blood glucose (SMBG) recommended as a key component of the management plan. No existing systematic reviews consider the benefits/effectiveness of different techniques of blood glucose monitoring on maternal and infant outcomes among pregnant women with pre-existing diabetes. The effectiveness of the various monitoring techniques is unclear. This review is an update of a review that was first published in 2014 and subsequently updated in 2017. OBJECTIVES To compare techniques of blood glucose monitoring and their impact on maternal and infant outcomes among pregnant women with pre-existing diabetes. SEARCH METHODS For this update, we searched Cochrane Pregnancy and Childbirth's Trials Register, ClinicalTrials.gov, the WHO International Clinical Trials Registry Platform (ICTRP) (1 November 2018), and reference lists of retrieved studies. SELECTION CRITERIA Randomised controlled trials (RCTs) and quasi-RCTs comparing techniques of blood glucose monitoring including SMBG, continuous glucose monitoring (CGM), automated telemedicine monitoring or clinic monitoring among pregnant women with pre-existing diabetes mellitus (type 1 or type 2). Trials investigating timing and frequency of monitoring were also eligible for inclusion. RCTs using a cluster-randomised design were eligible for inclusion but none were identified. DATA COLLECTION AND ANALYSIS Two review authors independently assessed study eligibility, extracted data and assessed the risk of bias of included studies. Data were checked for accuracy. The quality of the evidence was assessed using the GRADE approach. MAIN RESULTS This review update includes a total of 12 trials (863) women (792 women with type 1 diabetes and 152 women with type 2 diabetes). The trials took place in Europe, the USA and Canada. Three of the 12 included studies are at low risk of bias, eight studies are at moderate risk of bias, and one study is at high risk of bias. Four trials reported that they were provided with the continuous glucose monitors free of charge or at a reduced cost by the manufacturer.Continuous glucose monitoring (CGM) versus intermittent glucose monitoring, (four studies, 609 women)CGM may reduce hypertensive disorders of pregnancy (pre-eclampsia and pregnancy-induced hypertension) (risk ratio (RR) 0.58, 95% confidence interval (CI) 0.39 to 0.85; 2 studies, 384 women; low-quality evidence), although it should be noted that only two of the four relevant studies reported data for this composite outcome. Conversely, this did not translate into a clear reduction for pre-eclampsia (RR 0.65, 95% CI 0.39 to 1.08; 4 studies, 609 women, moderate-quality evidence). There was also no clear reduction in caesarean section (average RR 0.94, 95% CI 0.75 to 1.18; 3 studies, 427 women; I2 = 41%; moderate-quality evidence) or large-for-gestational age (average RR 0.84, 95% CI 0.57 to 1.26; 3 studies, 421 women; I2 = 70%; low-quality evidence) with CGM. There was not enough evidence to assess perinatal mortality (RR 0.82, 95% CI 0.05 to 12.61, 71 infants, 1 study; low-quality evidence), or mortality or morbidity composite (RR 0.80, 95% CI 0.61 to 1.06; 1 study, 200 women) as the evidence was based on single studies of low quality. CGM appears to reduce neonatal hypoglycaemia (RR 0.66, 95% CI 0.48 to 0.93; 3 studies, 428 infants). Neurosensory disability was not reported.Other methods of glucose monitoringFor the following five comparisons, self-monitoring versus a different type of self-monitoring (two studies, 43 women); self-monitoring at home versus hospitalisation (one study, 100 women), pre-prandial versus post-prandial glucose monitoring (one study, 61 women), automated telemedicine monitoring versus conventional system (three studies, 84 women), and constant CGM versus intermittent CGM (one study, 25 women), it is uncertain whether any of the interventions has any impact on any of our GRADE outcomes (hypertensive disorders of pregnancy, caesarean section, large-for-gestational age) because the quality of the evidence was found to be very low. This was due to evidence largely being derived from single trials, with design limitations and limitations with imprecision (wide CIs, small sample sizes, and few events). There was not enough evidence to assess perinatal mortality and neonatal mortality and morbidity composite. Other important outcomes, such as neurosensory disability, were not reported in any of these comparisons. AUTHORS' CONCLUSIONS Two new studies (406 women) have been incorporated to one of the comparisons for this update. Although the evidence suggests that CGM in comparison to intermittent glucose monitoring may reduce hypertensive disorders of pregnancy, this did not translate into a clear reduction for pre-eclampsia, and so this result should be viewed with caution. No differences were observed for other primary outcomes for this comparison. The evidence base for the effectiveness of other monitoring techniques analysed in the other five comparisons is weak and based on mainly single studies with very low-quality evidence. Additional evidence from large well-designed randomised trials is required to inform choices of other glucose monitoring techniques and to confirm the effectiveness of CGM.
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Affiliation(s)
- Leanne V Jones
- The University of LiverpoolCochrane Pregnancy and Childbirth, Department of Women's and Children's HealthFirst Floor, Liverpool Women's NHS Foundation TrustCrown StreetLiverpoolUKL8 7SS
| | - Amita Ray
- DM Wayanad Institute of Medical SciencesDepartment of Obstetrics and GynaecologyNaseera Nagar ,Meppadi (PO)WayanadWayanadKeralaIndia673577
| | - Foong Ming Moy
- Faculty of Medicine, University of MalayaJulius Centre University of Malaya, Department of Social and Preventive MedicineKuala LumpurWilayah PersekutuanMalaysia50603
| | - Brian S Buckley
- University of the Philippines, ManilaDepartment of SurgeryManilaPhilippines
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Voormolen DN, DeVries JH, Sanson RME, Heringa MP, de Valk HW, Kok M, van Loon AJ, Hoogenberg K, Bekedam DJ, Brouwer TCB, Porath M, Erdtsieck RJ, NijBijvank B, Kip H, van der Heijden OWH, Elving LD, Hermsen BB, Potter van Loon BJ, Rijnders RJP, Jansen HJ, Langenveld J, Akerboom BMC, Kiewiet RM, Naaktgeboren CA, Mol BWJ, Franx A, Evers IM. Continuous glucose monitoring during diabetic pregnancy (GlucoMOMS): A multicentre randomized controlled trial. Diabetes Obes Metab 2018; 20:1894-1902. [PMID: 29603547 DOI: 10.1111/dom.13310] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2018] [Revised: 03/22/2018] [Accepted: 03/25/2018] [Indexed: 11/27/2022]
Abstract
AIM Diabetes is associated with a high risk of adverse pregnancy outcomes. Optimal glycaemic control is fundamental and is traditionally monitored with self-measured glucose profiles and periodic HbA1c measurements. We investigated the effectiveness of additional use of retrospective continuous glucose monitoring (CGM) in diabetic pregnancies. MATERIAL AND METHODS We performed a nationwide multicentre, open label, randomized, controlled trial to study pregnant women with type 1 or type 2 diabetes who were undergoing insulin therapy at gestational age < 16 weeks, or women who were undergoing insulin treatment for gestational diabetes at gestational age < 30 weeks. Women were randomly allocated (1:1) to intermittent use of retrospective CGM or to standard treatment. Glycaemic control was assessed by CGM for 5-7 days every 6 weeks in the CGM group, while self-monitoring of blood glucose and HbA1c measurements were applied in both groups. Primary outcome was macrosomia, defined as birth weight above the 90th percentile. Secondary outcomes were glycaemic control and maternal and neonatal complications. RESULTS Between July 2011 and September 2015, we randomized 300 pregnant women with type 1 (n = 109), type 2 (n = 82) or with gestational (n = 109) diabetes to either CGM (n = 147) or standard treatment (n = 153). The incidence of macrosomia was 31.0% in the CGM group and 28.4% in the standard treatment group (relative risk [RR], 1.06; 95% CI, 0.83-1.37). HbA1c levels were similar between treatment groups. CONCLUSIONS In diabetic pregnancy, use of intermittent retrospective CGM did not reduce the risk of macrosomia. CGM provides detailed information concerning glycaemic fluctuations but, as a treatment strategy, does not translate into improved pregnancy outcome.
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MESH Headings
- Adult
- Blood Glucose/analysis
- Combined Modality Therapy
- Diabetes Mellitus, Type 1/blood
- Diabetes Mellitus, Type 1/physiopathology
- Diabetes Mellitus, Type 1/therapy
- Diabetes Mellitus, Type 2/blood
- Diabetes Mellitus, Type 2/physiopathology
- Diabetes Mellitus, Type 2/therapy
- Diabetes, Gestational/blood
- Diabetes, Gestational/physiopathology
- Diabetes, Gestational/therapy
- Female
- Fetal Macrosomia/epidemiology
- Fetal Macrosomia/etiology
- Fetal Macrosomia/prevention & control
- Glycated Hemoglobin/analysis
- Humans
- Hyperglycemia/prevention & control
- Hypoglycemia/prevention & control
- Incidence
- Infant, Newborn
- Intention to Treat Analysis
- Lost to Follow-Up
- Male
- Monitoring, Ambulatory
- Netherlands/epidemiology
- Patient Dropouts
- Pregnancy
- Pregnancy in Diabetics/blood
- Pregnancy in Diabetics/physiopathology
- Pregnancy in Diabetics/therapy
- Risk
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Affiliation(s)
- Daphne N Voormolen
- Department of Obstetrics and Gynecology, Division of Women and Baby, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - J Hans DeVries
- Department of Endocrinology, Academic Medical Centre, Amsterdam, The Netherlands
| | - Rieneke M E Sanson
- Department of Internal Medicine, Meander Medical Centre, Amersfoort, The Netherlands
| | - Martijn P Heringa
- Department of Obstetrics and Gynecology, Division of Women and Baby, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Harold W de Valk
- Department of Endocrinology, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Marjolein Kok
- Department of Obstetrics and Gynecology, Academic Medical Centre, Amsterdam, The Netherlands
| | - Aren J van Loon
- Department of Obstetrics and Gynecology, Martini Hospital, Groningen, The Netherlands
| | - Klaas Hoogenberg
- Department of Internal Medicine, Martini Hospital, Groningen, The Netherlands
| | - Dick J Bekedam
- Department of Obstetrics and Gynecology, OLVG, Amsterdam, The Netherlands
| | - Teri C B Brouwer
- Department of Internal Medicine, OLVG, Amsterdam, The Netherlands
| | - Martina Porath
- Department of Obstetrics and Gynecology, Maxima Medical Centre, Veldhoven, The Netherlands
| | - Ronald J Erdtsieck
- Department of Internal Medicine, Maxima Medical Centre, Veldhoven, The Netherlands
| | - Bas NijBijvank
- Department of Obstetrics and Gynecology, Isala Hospital, Zwolle, The Netherlands
| | - Huib Kip
- Department of Internal Medicine, Isala Hospital, Zwolle, The Netherlands
| | | | - Lammy D Elving
- Department of Internal Medicine, University Medical Centre St Radboud, Nijmegen, The Netherlands
| | - Brenda B Hermsen
- Department of Obstetrics and Gynecology, St Lucas Andreas Hospital, Amsterdam, The Netherlands
| | - B J Potter van Loon
- Department of Internal Medicine, St Lucas Andreas Hospital, Amsterdam, The Netherlands
| | - Robert J P Rijnders
- Department of Obstetrics and Gynecology, Jeroen Bosch Hospital, Den Bosch, The Netherlands
| | - Henry J Jansen
- Department of Internal Medicine, Jeroen Bosch Hospital, Den Bosch, The Netherlands
| | - Josje Langenveld
- Department of Obstetrics and Gynecology, Zuyderland Medical Centre, Heerlen, The Netherlands
| | - Bettina M C Akerboom
- Department of Obstetrics and Gynecology, Albert Schweitzer Hospital, Dordrecht, The Netherlands
| | - Rosalie M Kiewiet
- Department of Internal Medicine, Albert Schweitzer Hospital, Dordrecht, The Netherlands
| | - Christiana A Naaktgeboren
- Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Ben W J Mol
- The Robinson Research Institute, School of Medicine, University of Adelaide, Adelaide, Australia
- The South Australian Health and Medical Research Institute Adelaide, Adelaide, Australia
| | - Arie Franx
- Department of Obstetrics and Gynecology, Division of Women and Baby, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Inge M Evers
- Department of Obstetrics and Gynecology, Meander Medical Centre, Amersfoort, The Netherlands
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Panyakat WS, Phatihattakorn C, Sriwijitkamol A, Sunsaneevithayakul P, Phaophan A, Phichitkanka A. Correlation Between Third Trimester Glycemic Variability in Non-Insulin-Dependent Gestational Diabetes Mellitus and Adverse Pregnancy and Fetal Outcomes. J Diabetes Sci Technol 2018; 12:622-629. [PMID: 29320884 PMCID: PMC6154249 DOI: 10.1177/1932296817752374] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Gestational diabetes mellitus (GDM) is a pregnancy-related metabolic complication. Despite optimal glycemic control from self-monitoring blood glucose (SMBG) in non-insulin-dependent GDM, variations in pregnancy outcomes persist. Glycemic variability is believed to be a factor that causes adverse pregnancy outcomes. Continuous glucose monitoring system (CGMS) detects interstitial glucose values every 5 minutes, and glycemic variability data from CGMS during the third trimester may be a predictor of fetal birth weight and pregnancy outcomes. The aim of this study was to investigate correlation between third trimester glycemic variability in non-insulin-dependent GDM and fetal birth weight. METHOD This prospective study was conducted in 55 pregnant volunteers with non-insulin-dependent GDM that were recruited at 28 to 32 weeks' gestation from the outpatient clinic of the Department of Obstetrics and Gynecology, Faculty of Medicine Siriraj Hospital during the study period of August 1 to December 31, 2016. Patients had CGMS installed for at least 72 hours and glycemic variability data were analyzed. RESULTS Of 55 enrolled volunteers, the data from 47 women were included in the analysis. Mean CGMS duration was 85.5 ± 12.83 hours. No statistically significant correlation was identified between glycemic variability in third trimester and birth weight percentiles, or between third trimester CGMS parameters and pregnancy outcomes in the study. CONCLUSION Based on these findings, third trimester glycemic variability data from CGMS are not a predictor of fetal birth weight percentile, and no significant association was found between CGMS parameters and adverse pregnancy outcomes; thus, CGMS is not necessary in non-insulin-dependent GDM.
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Affiliation(s)
- Wanwadee Sapmee Panyakat
- Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Chayawat Phatihattakorn
- Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
- Chayawat Phatihattakorn, MD, Department of Obstetrics and Gynecology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkoknoi, Bangkok 10700, Thailand.
| | - Apiradee Sriwijitkamol
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Prasert Sunsaneevithayakul
- Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Amprapha Phaophan
- Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Aporn Phichitkanka
- Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
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Abstract
PURPOSE OF REVIEW The purpose of the study is to discuss emerging technologies available in the management of type 1 diabetes in pregnancy. RECENT FINDINGS The latest evidence suggests that continuous glucose monitoring (CGM) should be offered to all women on intensive insulin therapy in early pregnancy. Studies have additionally demonstrated the ability of CGM to help gain insight into specific glucose profiles as they relate to glycaemic targets and pregnancy outcomes. Despite new studies comparing insulin pump therapy to multiple daily injections, its effectiveness in improving glucose and pregnancy outcomes remains unclear. Sensor-integrated insulin delivery (also called artificial pancreas or closed-loop insulin delivery) in pregnancy has been demonstrated to improve time in target and performs well despite the changing insulin demands of pregnancy. Emerging technologies show promise in the management of type 1 diabetes in pregnancy; however, research must continue to keep up as technology advances. Further research is needed to clarify the role technology can play in optimising glucose control before and during pregnancy as well as to understand which women are candidates for sensor-integrated insulin delivery.
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Affiliation(s)
- Jennifer M Yamamoto
- Department of Medicine, Division of Endocrinology and Metabolism, University of Calgary, Calgary, AB, Canada
| | - Helen R Murphy
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
- Women's Health Academic Centre, Division of Women's and Children's Health, King's College London, London, UK.
- Norwich Medical School, University of East Anglia, Floor 2, Bob Champion Research and Education Building, James Watson Road, Norwich Research Park, Norwich, NR4 7UQ, UK.
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7
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Raman P, Shepherd E, Dowswell T, Middleton P, Crowther CA. Different methods and settings for glucose monitoring for gestational diabetes during pregnancy. Cochrane Database Syst Rev 2017; 10:CD011069. [PMID: 29081069 PMCID: PMC6485695 DOI: 10.1002/14651858.cd011069.pub2] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
BACKGROUND Incidence of gestational diabetes mellitus (GDM) is increasing worldwide. Blood glucose monitoring plays a crucial part in maintaining glycaemic control in women with GDM and is generally recommended by healthcare professionals. There are several different methods for monitoring blood glucose which can be carried out in different settings (e.g. at home versus in hospital). OBJECTIVES The objective of this review is to compare the effects of different methods and settings for glucose monitoring for women with GDM on maternal and fetal, neonatal, child and adult outcomes, and use and costs of health care. SEARCH METHODS We searched the Cochrane Pregnancy and Childbirth Group Trials Register (30 September 2016) and reference lists of retrieved studies. SELECTION CRITERIA Randomised controlled trials (RCTs) or quasi-randomised controlled trials (qRCTs) comparing different methods (such as timings and frequencies) or settings, or both, for blood glucose monitoring for women with GDM. DATA COLLECTION AND ANALYSIS Two authors independently assessed study eligibility, risk of bias, and extracted data. Data were checked for accuracy.We assessed the quality of the evidence for the main comparisons using GRADE, for:- primary outcomes for mothers: that is, hypertensive disorders of pregnancy; caesarean section; type 2 diabetes; and- primary outcomes for children: that is, large-for-gestational age; perinatal mortality; death or serious morbidity composite; childhood/adulthood neurosensory disability;- secondary outcomes for mothers: that is, induction of labour; perineal trauma; postnatal depression; postnatal weight retention or return to pre-pregnancy weight; and- secondary outcomes for children: that is, neonatal hypoglycaemia; childhood/adulthood adiposity; childhood/adulthood type 2 diabetes. MAIN RESULTS We included 11 RCTs (10 RCTs; one qRCT) that randomised 1272 women with GDM in upper-middle or high-income countries; we considered these to be at a moderate to high risk of bias. We assessed the RCTs under five comparisons. For outcomes assessed using GRADE, we downgraded for study design limitations, imprecision and inconsistency. Three trials received some support from commercial partners who provided glucose meters or financial support, or both. Main comparisons Telemedicine versus standard care for glucose monitoring (five RCTs): we observed no clear differences between the telemedicine and standard care groups for the mother, for:- pre-eclampsia or pregnancy-induced hypertension (risk ratio (RR) 1.49, 95% confidence interval (CI) 0.69 to 3.20; 275 participants; four RCTs; very low quality evidence);- caesarean section (average RR 1.05, 95% CI 0.72 to 1.53; 478 participants; 5 RCTs; very low quality evidence); and- induction of labour (RR 1.06, 95% CI 0.63 to 1.77; 47 participants; 1 RCT; very low quality evidence);or for the child, for:- large-for-gestational age (RR 1.41, 95% CI 0.76 to 2.64; 228 participants; 3 RCTs; very low quality evidence);- death or serious morbidity composite (RR 1.06, 95% CI 0.68 to 1.66; 57 participants; 1 RCT; very low quality evidence); and- neonatal hypoglycaemia (RR 1.14, 95% CI 0.48 to 2.72; 198 participants; 3 RCTs; very low quality evidence).There were no perinatal deaths in two RCTs (131 participants; very low quality evidence). Self-monitoring versus periodic glucose monitoring (two RCTs): we observed no clear differences between the self-monitoring and periodic glucose monitoring groups for the mother, for:- pre-eclampsia (RR 0.17, 95% CI 0.01 to 3.49; 58 participants; 1 RCT; very low quality evidence); and- caesarean section (average RR 1.18, 95% CI 0.61 to 2.27; 400 participants; 2 RCTs; low quality evidence);or for the child, for:- perinatal mortality (RR 1.54, 95% CI 0.21 to 11.24; 400 participants; 2 RCTs; very low quality evidence);- large-for-gestational age (RR 0.82, 95% CI 0.50 to 1.37; 400 participants; 2 RCTs; low quality evidence); and- neonatal hypoglycaemia (RR 0.64, 95% CI 0.39 to 1.06; 391 participants; 2 RCTs; low quality evidence). Continuous glucose monitoring system (CGMS) versus self-monitoring of glucose (two RCTs): we observed no clear differences between the CGMS and self-monitoring groups for the mother, for:- caesarean section (RR 0.91, 95% CI 0.68 to 1.20; 179 participants; 2 RCTs; very low quality evidence);or for the child, for:- large-for-gestational age (RR 0.67, 95% CI 0.43 to 1.05; 106 participants; 1 RCT; very low quality evidence) and- neonatal hypoglycaemia (RR 0.79, 95% CI 0.35 to 1.78; 179 participants; 2 RCTs; very low quality evidence).There were no perinatal deaths in the two RCTs (179 participants; very low quality evidence). Other comparisons Modem versus telephone transmission for glucose monitoring (one RCT): none of the review's primary outcomes were reported in this trial Postprandial versus preprandial glucose monitoring (one RCT): we observed no clear differences between the postprandial and preprandial glucose monitoring groups for the mother, for:- pre-eclampsia (RR 1.00, 95% CI 0.15 to 6.68; 66 participants; 1 RCT);- caesarean section (RR 0.62, 95% CI 0.29 to 1.29; 66 participants; 1 RCT); and- perineal trauma (RR 0.38, 95% CI 0.11 to 1.29; 66 participants; 1 RCT);or for the child, for:- neonatal hypoglycaemia (RR 0.14, 95% CI 0.02 to 1.10; 66 participants; 1 RCT).There were fewer large-for-gestational-age infants born to mothers in the postprandial compared with the preprandial glucose monitoring group (RR 0.29, 95% CI 0.11 to 0.78; 66 participants; 1 RCT). AUTHORS' CONCLUSIONS Evidence from 11 RCTs assessing different methods or settings for glucose monitoring for GDM suggests no clear differences for the primary outcomes or other secondary outcomes assessed in this review.However, current evidence is limited by the small number of RCTs for the comparisons assessed, small sample sizes, and the variable methodological quality of the RCTs. More evidence is needed to assess the effects of different methods and settings for glucose monitoring for GDM on outcomes for mothers and their children, including use and costs of health care. Future RCTs may consider collecting and reporting on the standard outcomes suggested in this review.
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Affiliation(s)
| | - Emily Shepherd
- The University of AdelaideARCH: Australian Research Centre for Health of Women and Babies, Robinson Research Institute, Discipline of Obstetrics and GynaecologyAdelaideSouth AustraliaAustralia5006
| | - Therese Dowswell
- The University of LiverpoolCochrane Pregnancy and Childbirth Group, Department of Women's and Children's HealthFirst Floor, Liverpool Women's NHS Foundation TrustCrown StreetLiverpoolUKL8 7SS
| | - Philippa Middleton
- Healthy Mothers, Babies and Children, South Australian Health and Medical Research InstituteWomen's and Children's Hospital72 King William RoadAdelaideSouth AustraliaAustralia5006
| | - Caroline A Crowther
- The University of AdelaideARCH: Australian Research Centre for Health of Women and Babies, Robinson Research Institute, Discipline of Obstetrics and GynaecologyAdelaideSouth AustraliaAustralia5006
- The University of AucklandLiggins InstitutePrivate Bag 9201985 Park RoadAucklandNew Zealand
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Al-Far HFM, Tjessem IH, Fuglsang J, Lauszus FF. Preeclampsia is associated with increased ambulatory arterial stiffness index in type 1 diabetes mellitus. Eur J Obstet Gynecol Reprod Biol 2017; 216:153-158. [PMID: 28768228 DOI: 10.1016/j.ejogrb.2017.07.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2017] [Revised: 07/22/2017] [Accepted: 07/24/2017] [Indexed: 10/19/2022]
Abstract
INTRODUCTION Treatment of mild to moderate hypertension might not benefit maternal or fetal outcome. This pessimistic point of view may have come about by using non-validated methods for measuring blood pressure in pregnancy combined with inadequate methodology for diagnosis, treatment, and monitoring effects. AIM To determine the association between AASI in women with type 1 diabetes mellitus (T1DM) and preeclampsia, and to assess the ability of AASI to diagnose preeclampsia. MATERIAL AND METHODS Repeated 24-h ambulatory blood pressure recordings were performed three times during pregnancy and once three months postpartum in 151 women with T1DM and 50 control women without diabetes. Circadian rhythm was evaluated as the night day ratio, night blood pressure divided by day blood pressure. RESULTS Of the T1DM women, 33 developed preeclampsia, which was associated with AASI in the 3rd trimester (p<0.05). The best predictor of preeclampsia in T1DM was an AASI of 0.35. The diurnal blood pressure was significantly higher in all trimesters in women who later had preeclampsia. A flattened circadian rhythm was present in T1DM women with preeclampsia compared to women without preeclampsia (night-day ratio: systole 2nd trimester: 0.94±0.07 vs. 0.91±0.05, women with and without preeclampsia, respectively, p=0.015; diastole 2nd trimester: 0.89±0.07 vs. 0.85±0.07, p=0.003). AASI was higher during pregnancy compared to postpartum in women with T1DM (0.31±0.16, 0.31±0.16 and 0.33±0.18 vs. 0.25±0.17; 1st, 2nd and 3rd trimester vs. postpartum). CONCLUSION Women with T1DM and preeclampsia demonstrate increased arterial stiffness and had early manifestations in the non-dipping of blood pressure.
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Affiliation(s)
| | | | - Jens Fuglsang
- Department of Obstetrics/Gynecology and Clinical Institute, Aarhus University Hospital, Denmark
| | - Finn F Lauszus
- Department of Obstetrics/Gynecology, Herning Hospital, Denmark; Department of Obstetrics/Gynecology and Clinical Institute, Aarhus University Hospital, Denmark
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Moy FM, Ray A, Buckley BS, West HM. Techniques of monitoring blood glucose during pregnancy for women with pre-existing diabetes. Cochrane Database Syst Rev 2017; 6:CD009613. [PMID: 28602020 PMCID: PMC6481528 DOI: 10.1002/14651858.cd009613.pub3] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
BACKGROUND Self-monitoring of blood glucose (SMBG) is recommended as a key component of the management plan for diabetes therapy during pregnancy. No existing systematic reviews consider the benefits/effectiveness of various techniques of blood glucose monitoring on maternal and infant outcomes among pregnant women with pre-existing diabetes. The effectiveness of the various monitoring techniques is unclear. OBJECTIVES To compare techniques of blood glucose monitoring and their impact on maternal and infant outcomes among pregnant women with pre-existing diabetes. SEARCH METHODS We searched the Cochrane Pregnancy and Childbirth Group's Trials Register (30 November 2016), searched reference lists of retrieved studies and contacted trial authors. SELECTION CRITERIA Randomised controlled trials (RCTs) and quasi-RCTs comparing techniques of blood glucose monitoring including SMBG, continuous glucose monitoring (CGM) or clinic monitoring among pregnant women with pre-existing diabetes mellitus (type 1 or type 2). Trials investigating timing and frequency of monitoring were also included. RCTs using a cluster-randomised design were eligible for inclusion but none were identified. DATA COLLECTION AND ANALYSIS Two review authors independently assessed study eligibility, extracted data and assessed the risk of bias of included studies. Data were checked for accuracy. The quality of the evidence was assessed using the GRADE approach. MAIN RESULTS This review update includes at total of 10 trials (538) women (468 women with type 1 diabetes and 70 women with type 2 diabetes). The trials took place in Europe and the USA. Five of the 10 included studies were at moderate risk of bias, four studies were at low to moderate risk of bias, and one study was at high risk of bias. The trials are too small to show differences in important outcomes such as macrosomia, preterm birth, miscarriage or death of baby. Almost all the reported GRADE outcomes were assessed as being very low-quality evidence. This was due to design limitations in the studies, wide confidence intervals, small sample sizes, and few events. In addition, there was high heterogeneity for some outcomes.Various methods of glucose monitoring were compared in the trials. Neither pooled analyses nor individual trial analyses showed any clear advantages of one monitoring technique over another for primary and secondary outcomes. Many important outcomes were not reported.1. Self-monitoring versus standard care (two studies, 43 women): there was no clear difference for caesarean section (risk ratio (RR) 0.78, 95% confidence interval (CI) 0.40 to 1.49; one study, 28 women) or glycaemic control (both very low-quality), and not enough evidence to assess perinatal mortality and neonatal mortality and morbidity composite. Hypertensive disorders of pregnancy, large-for-gestational age, neurosensory disability, and preterm birth were not reported in either study.2. Self-monitoring versus hospitalisation (one study, 100 women): there was no clear difference for hypertensive disorders of pregnancy (pre-eclampsia and hypertension) (RR 4.26, 95% CI 0.52 to 35.16; very low-quality: RR 0.43, 95% CI 0.08 to 2.22; very low-quality). There was no clear difference in caesarean section or preterm birth less than 37 weeks' gestation (both very low quality), and the sample size was too small to assess perinatal mortality (very low-quality). Large-for-gestational age, mortality or morbidity composite, neurosensory disability and preterm birth less than 34 weeks were not reported.3. Pre-prandial versus post-prandial glucose monitoring (one study, 61 women): there was no clear difference between groups for caesarean section (RR 1.45, 95% CI 0.92 to 2.28; very low-quality), large-for-gestational age (RR 1.16, 95% CI 0.73 to 1.85; very low-quality) or glycaemic control (very low-quality). The results for hypertensive disorders of pregnancy: pre-eclampsia and perinatal mortality are not meaningful because these outcomes were too rare to show differences in a small sample (all very low-quality). The study did not report the outcomes mortality or morbidity composite, neurosensory disability or preterm birth.4. Automated telemedicine monitoring versus conventional system (three studies, 84 women): there was no clear difference for caesarean section (RR 0.96, 95% CI 0.62 to 1.48; one study, 32 women; very low-quality), and mortality or morbidity composite in the one study that reported these outcomes. There were no clear differences for glycaemic control (very low-quality). No studies reported hypertensive disorders of pregnancy, large-for-gestational age, perinatal mortality (stillbirth and neonatal mortality), neurosensory disability or preterm birth.5.CGM versus intermittent monitoring (two studies, 225 women): there was no clear difference for pre-eclampsia (RR 1.37, 95% CI 0.52 to 3.59; low-quality), caesarean section (average RR 1.00, 95% CI 0.65 to 1.54; I² = 62%; very low-quality) and large-for-gestational age (average RR 0.89, 95% CI 0.41 to 1.92; I² = 82%; very low-quality). Glycaemic control indicated by mean maternal HbA1c was lower for women in the continuous monitoring group (mean difference (MD) -0.60 %, 95% CI -0.91 to -0.29; one study, 71 women; moderate-quality). There was not enough evidence to assess perinatal mortality and there were no clear differences for preterm birth less than 37 weeks' gestation (low-quality). Mortality or morbidity composite, neurosensory disability and preterm birth less than 34 weeks were not reported.6. Constant CGM versus intermittent CGM (one study, 25 women): there was no clear difference between groups for caesarean section (RR 0.77, 95% CI 0.33 to 1.79; very low-quality), glycaemic control (mean blood glucose in the 3rd trimester) (MD -0.14 mmol/L, 95% CI -2.00 to 1.72; very low-quality) or preterm birth less than 37 weeks' gestation (RR 1.08, 95% CI 0.08 to 15.46; very low-quality). Other primary (hypertensive disorders of pregnancy, large-for-gestational age, perinatal mortality (stillbirth and neonatal mortality), mortality or morbidity composite, and neurosensory disability) or GRADE outcomes (preterm birth less than 34 weeks' gestation) were not reported. AUTHORS' CONCLUSIONS This review found no evidence that any glucose monitoring technique is superior to any other technique among pregnant women with pre-existing type 1 or type 2 diabetes. The evidence base for the effectiveness of monitoring techniques is weak and additional evidence from large well-designed randomised trials is required to inform choices of glucose monitoring techniques.
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Affiliation(s)
- Foong Ming Moy
- Faculty of Medicine, University of MalayaJulius Centre University of Malaya, Department of Social and Preventive MedicineKuala LumpurMalaysia50603
| | - Amita Ray
- DM Wayanad Institute of Medical SciencesDepartment of Obstetrics and GynaecologyNaseera Nagar ,Meppadi (PO)WayanadWayanadIndia673577
| | - Brian S Buckley
- University of PhillipinesDepartment of SurgeryManilaPhilippines
| | - Helen M West
- The University of LiverpoolInstitute of Psychology, Health and SocietyLiverpoolUK
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10
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Abstract
The glycemic goals of pregnancy are very narrow to reduce excess risks for numerous maternal and fetal complications. Continuous glucose monitors (CGMs) may help women achieve glucose goals and reduce hypoglycemia. CGM use has been found to be safe and effective in pregnancies associated with diabetes. CGM use can accurately identify glycemic patterns among women with and without diabetes in pregnancy. The data on the effects of CGM use on maternal and fetal outcomes are conflicting. Using CGMs in conjunction with continuous subcutaneous insulin infusion therapy in pregnancies complicated by diabetes may improve outcomes. There are limitations of CGM use that affect patients in and outside of pregnancy, as well as specific barriers that only affect pregnant women. Of importance, CGM use does not replace standard clinical care, but may be used an adjunctive tool in pregnancy. CGM remote monitoring in pregnancy is an understudied field. In this study, we review the studies on CGM use in pregnancy.
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Affiliation(s)
- Sarit Polsky
- Barbara Davis Center for Diabetes, University of Colorado Denver , Aurora, Colorado
| | - Rachel Garcetti
- Barbara Davis Center for Diabetes, University of Colorado Denver , Aurora, Colorado
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11
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The efficacy and effectiveness of continuous glucose monitoring during pregnancy: a systematic review. Obstet Gynecol Surv 2014; 68:811-24. [PMID: 24193194 DOI: 10.1097/ogx.0000000000000002] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
OBJECTIVE Diabetic pregnancies carry a high risk for both mother and child, especially when glycemic control is poor. A novel technique that aims to improve glycemic control is the continuous glucose monitor (CGM). This tool is already in use to improve pregnancy outcome. This review presents the available evidence on the efficacy of CGM use in pregnancy and the effectiveness on pregnancy outcome. METHODS A systematic search was conducted using PubMed, EMBASE, and the Cochrane Libraries for articles on CGM in pregnancy. We evaluated the selected articles with particular attention for clinical and cost-effectiveness of CGM to improve pregnancy outcome. RESULTS We retrieved 5032 articles, 11 of which remained as relevant after selection according to predefined criteria. Most studies were limited to the evaluation of the role of CGM on clinical decision making. Only 2 studies were randomized controlled trials (RCTs) evaluating the effect on pregnancy outcome. One small RCT on retrospective CGM showed a significant reduction in third-trimester HbA1c and a significant reduction in neonatal macrosomia. A second RCT on real-time CGM did not show any effect on either glycemic control or on pregnancy outcome. CONCLUSIONS Current evidence on the efficacy of CGM on improving glycemic control during pregnancy as well as on the effectiveness on pregnancy outcome is limited to 2 RCTs with contradicting results. Evidence on the cost-effectiveness is lacking. Further proper RCTs on the effectiveness and cost-effectiveness of CGM in pregnancy are required before wide implementation in practice.
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Moy FM, Ray A, Buckley BS. Techniques of monitoring blood glucose during pregnancy for women with pre-existing diabetes. Cochrane Database Syst Rev 2014:CD009613. [PMID: 24782359 DOI: 10.1002/14651858.cd009613.pub2] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
BACKGROUND Self-monitoring of blood glucose is recommended as a key component of the management plan for diabetes therapy during pregnancy. No existing systematic reviews consider the benefits/effectiveness of various techniques of blood glucose monitoring on maternal and infant outcomes among pregnant women with pre-existing diabetes. The effectiveness of the various monitoring techniques is unclear. OBJECTIVES To compare techniques of blood glucose monitoring and their impact on maternal and infant outcomes among pregnant women with pre-existing diabetes. SEARCH METHODS We searched the Cochrane Pregnancy and Childbirth Group's Trials Register (6 August 2013), searched reference lists of retrieved studies and contacted trial authors. SELECTION CRITERIA Randomised controlled trials (RCTs) comparing techniques of blood glucose monitoring including self blood glucose monitoring, continuous glucose monitoring (CGM) or clinic monitoring among pregnant women with pre-existing diabetes mellitus (Type 1 or Type 2). Trials investigating timing and frequency of monitoring were also included. Quasi-RCTs and RCTs using a cluster-randomised design were eligible for inclusion but none were identified. DATA COLLECTION AND ANALYSIS Two review authors independently assessed study eligibility, extracted data and assessed the risk of bias of included studies. Data were checked for accuracy. MAIN RESULTS The search of the Pregnancy and Childbirth Group's Trials Register identified 21 trial reports. Following application of eligibility criteria, nine trials were included in this review. The included trials involved a total of 506 women (436 women with Type 1 diabetes and 70 women with Type 2 diabetes). All trials originated from European countries and the USA. None of the studies included women with gestational diabetes. Five of the nine included studies were at moderate risk of bias and four studies were at low to moderate risk of bias. Primary outcomes were maternal glycaemic control (fasting blood glucose and HbA1c) and infant birthweight or macrosomia.Various methods of glucose monitoring were compared in the trials. The following comparisons were included in the review: (1) self-monitoring versus standard care, (2) self-monitoring versus hospitalisation, (3) pre-prandial versus post-prandial glucose monitoring, (4) automated telemedicine monitoring versus conventional system, (5) CGM versus intermittent monitoring and (6) constant CGM versus intermittent CGM.Neither pooled analyses nor individual trial analyses showed any significant advantages of one monitoring technique over another for primary outcomes (maternal glycaemic control and infant birthweight) and secondary outcomes such as gestational age at birth or preterm birth, frequency of neonatal hypoglycaemia, death of baby including stillbirth, and neonatal intensive care admission. Primary outcome data on macrosomia were reported by one trial but at a different cut-off value than that pre-specified for the review. Secondary outcomes such as shoulder dystocia, major and minor anomalies were not reported by any of the trials. AUTHORS' CONCLUSIONS This review found no evidence that any glucose monitoring technique is superior to any other technique among pregnant women with pre-existing Type 1 or Type 2 diabetes. The evidence base for the effectiveness of monitoring techniques is weak and additional evidence from large well-designed randomised trials is required to inform choices of glucose monitoring techniques.
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Affiliation(s)
- Foong Ming Moy
- Julius Centre University of Malaya, Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Wilayah Persekutuan, Malaysia, 50603
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Scuffi C. Interstitium versus Blood Equilibrium in Glucose Concentration and its Impact on Subcutaneous Continuous Glucose Monitoring Systems. EUROPEAN ENDOCRINOLOGY 2014; 10:36-42. [PMID: 29872462 PMCID: PMC5983095 DOI: 10.17925/ee.2014.10.01.36] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2013] [Accepted: 02/13/2014] [Indexed: 12/18/2022]
Abstract
The relationship between both interstitial and blood glucose remains a debated topic, on which there is still no consensus. The experimental evidence suggests that blood and interstitial fluid glucose levels are correlated by a kinetic equilibrium, which as a consequence has a time and magnitude gradient in glucose concentration between blood and interstitium. Furthermore, this equilibrium can be perturbed by several physiological effects (such as foreign body response, wound-healing effect, etc.), with a consequent reduction of interstitial fluid glucose versus blood glucose correlation. In the present study, the impact of operating in the interstitium on continuous glucose monitoring systems (CGMs) will be discussed in depth, both for the application of CGMs in the management of diabetes and in other critical areas, such as tight glycaemic control in critically ill patients.
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Affiliation(s)
- Cosimo Scuffi
- Scientist, Scientific and Technology Affairs Department, A. Menarini Diagnostics, Florence, Italy
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