Comparing the Efficacy of a Mobile Phone-Based Blood Glucose Management System With Standard Clinic Care in Women With Gestational Diabetes: Randomized Controlled Trial
Treatment of hyperglycemia in women with gestational diabetes mellitus (GDM) is associated with improved maternal and neonatal outcomes and requires intensive clinical input. This is currently achieved by hospital clinic attendance every 2 to 4 weeks with limited opportunity for intervention between...
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Published in | JMIR mHealth and uHealth Vol. 6; no. 3; p. e71 |
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Main Authors | , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Canada
JMIR Publications
20.03.2018
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Abstract | Treatment of hyperglycemia in women with gestational diabetes mellitus (GDM) is associated with improved maternal and neonatal outcomes and requires intensive clinical input. This is currently achieved by hospital clinic attendance every 2 to 4 weeks with limited opportunity for intervention between these visits.
We conducted a randomized controlled trial to determine whether the use of a mobile phone-based real-time blood glucose management system to manage women with GDM remotely was as effective in controlling blood glucose as standard care through clinic attendance.
Women with an abnormal oral glucose tolerance test before 34 completed weeks of gestation were individually randomized to a mobile phone-based blood glucose management solution (GDm-health, the intervention) or routine clinic care. The primary outcome was change in mean blood glucose in each group from recruitment to delivery, calculated with adjustments made for number of blood glucose measurements, proportion of preprandial and postprandial readings, baseline characteristics, and length of time in the study.
A total of 203 women were randomized. Blood glucose data were available for 98 intervention and 85 control women. There was no significant difference in rate of change of blood glucose (-0.16 mmol/L in the intervention and -0.14 mmol/L in the control group per 28 days, P=.78). Women using the intervention had higher satisfaction with care (P=.049). Preterm birth was less common in the intervention group (5/101, 5.0% vs 13/102, 12.7%; OR 0.36, 95% CI 0.12-1.01). There were fewer cesarean deliveries compared with vaginal deliveries in the intervention group (27/101, 26.7% vs 47/102, 46.1%, P=.005). Other glycemic, maternal, and neonatal outcomes were similar in both groups. The median time from recruitment to delivery was similar (intervention: 54 days; control: 49 days; P=.23). However, there were significantly more blood glucose readings in the intervention group (mean 3.80 [SD 1.80] and mean 2.63 [SD 1.71] readings per day in the intervention and control groups, respectively; P<.001). There was no significant difference in direct health care costs between the two groups, with a mean cost difference of the intervention group compared to control of -£1044 (95% CI -£2186 to £99). There were no unexpected adverse outcomes.
Remote blood glucocse monitoring in women with GDM is safe. We demonstrated superior data capture using GDm-health. Although glycemic control and maternal and neonatal outcomes were similar, women preferred this model of care. Further studies are required to explore whether digital health solutions can promote desired self-management lifestyle behaviors and dietetic adherence, and influence maternal and neonatal outcomes. Digital blood glucose monitoring may provide a scalable, practical method to address the growing burden of GDM around the world.
ClinicalTrials.gov NCT01916694; https://clinicaltrials.gov/ct2/show/NCT01916694 (Archived by WebCite at http://www.webcitation.org/6y3lh2BOQ). |
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AbstractList | Treatment of hyperglycemia in women with gestational diabetes mellitus (GDM) is associated with improved maternal and neonatal outcomes and requires intensive clinical input. This is currently achieved by hospital clinic attendance every 2 to 4 weeks with limited opportunity for intervention between these visits.
We conducted a randomized controlled trial to determine whether the use of a mobile phone-based real-time blood glucose management system to manage women with GDM remotely was as effective in controlling blood glucose as standard care through clinic attendance.
Women with an abnormal oral glucose tolerance test before 34 completed weeks of gestation were individually randomized to a mobile phone-based blood glucose management solution (GDm-health, the intervention) or routine clinic care. The primary outcome was change in mean blood glucose in each group from recruitment to delivery, calculated with adjustments made for number of blood glucose measurements, proportion of preprandial and postprandial readings, baseline characteristics, and length of time in the study.
A total of 203 women were randomized. Blood glucose data were available for 98 intervention and 85 control women. There was no significant difference in rate of change of blood glucose (-0.16 mmol/L in the intervention and -0.14 mmol/L in the control group per 28 days, P=.78). Women using the intervention had higher satisfaction with care (P=.049). Preterm birth was less common in the intervention group (5/101, 5.0% vs 13/102, 12.7%; OR 0.36, 95% CI 0.12-1.01). There were fewer cesarean deliveries compared with vaginal deliveries in the intervention group (27/101, 26.7% vs 47/102, 46.1%, P=.005). Other glycemic, maternal, and neonatal outcomes were similar in both groups. The median time from recruitment to delivery was similar (intervention: 54 days; control: 49 days; P=.23). However, there were significantly more blood glucose readings in the intervention group (mean 3.80 [SD 1.80] and mean 2.63 [SD 1.71] readings per day in the intervention and control groups, respectively; P<.001). There was no significant difference in direct health care costs between the two groups, with a mean cost difference of the intervention group compared to control of -£1044 (95% CI -£2186 to £99). There were no unexpected adverse outcomes.
Remote blood glucocse monitoring in women with GDM is safe. We demonstrated superior data capture using GDm-health. Although glycemic control and maternal and neonatal outcomes were similar, women preferred this model of care. Further studies are required to explore whether digital health solutions can promote desired self-management lifestyle behaviors and dietetic adherence, and influence maternal and neonatal outcomes. Digital blood glucose monitoring may provide a scalable, practical method to address the growing burden of GDM around the world.
ClinicalTrials.gov NCT01916694; https://clinicaltrials.gov/ct2/show/NCT01916694 (Archived by WebCite at http://www.webcitation.org/6y3lh2BOQ). BackgroundTreatment of hyperglycemia in women with gestational diabetes mellitus (GDM) is associated with improved maternal and neonatal outcomes and requires intensive clinical input. This is currently achieved by hospital clinic attendance every 2 to 4 weeks with limited opportunity for intervention between these visits. ObjectiveWe conducted a randomized controlled trial to determine whether the use of a mobile phone-based real-time blood glucose management system to manage women with GDM remotely was as effective in controlling blood glucose as standard care through clinic attendance. MethodsWomen with an abnormal oral glucose tolerance test before 34 completed weeks of gestation were individually randomized to a mobile phone-based blood glucose management solution (GDm-health, the intervention) or routine clinic care. The primary outcome was change in mean blood glucose in each group from recruitment to delivery, calculated with adjustments made for number of blood glucose measurements, proportion of preprandial and postprandial readings, baseline characteristics, and length of time in the study. ResultsA total of 203 women were randomized. Blood glucose data were available for 98 intervention and 85 control women. There was no significant difference in rate of change of blood glucose (–0.16 mmol/L in the intervention and –0.14 mmol/L in the control group per 28 days, P=.78). Women using the intervention had higher satisfaction with care (P=.049). Preterm birth was less common in the intervention group (5/101, 5.0% vs 13/102, 12.7%; OR 0.36, 95% CI 0.12-1.01). There were fewer cesarean deliveries compared with vaginal deliveries in the intervention group (27/101, 26.7% vs 47/102, 46.1%, P=.005). Other glycemic, maternal, and neonatal outcomes were similar in both groups. The median time from recruitment to delivery was similar (intervention: 54 days; control: 49 days; P=.23). However, there were significantly more blood glucose readings in the intervention group (mean 3.80 [SD 1.80] and mean 2.63 [SD 1.71] readings per day in the intervention and control groups, respectively; P<.001). There was no significant difference in direct health care costs between the two groups, with a mean cost difference of the intervention group compared to control of –£1044 (95% CI –£2186 to £99). There were no unexpected adverse outcomes. ConclusionsRemote blood glucocse monitoring in women with GDM is safe. We demonstrated superior data capture using GDm-health. Although glycemic control and maternal and neonatal outcomes were similar, women preferred this model of care. Further studies are required to explore whether digital health solutions can promote desired self-management lifestyle behaviors and dietetic adherence, and influence maternal and neonatal outcomes. Digital blood glucose monitoring may provide a scalable, practical method to address the growing burden of GDM around the world. Trial RegistrationClinicalTrials.gov NCT01916694; https://clinicaltrials.gov/ct2/show/NCT01916694 (Archived by WebCite at http://www.webcitation.org/6y3lh2BOQ) Background: Treatment of hyperglycemia in women with gestational diabetes mellitus (GDM) is associated with improved maternal and neonatal outcomes and requires intensive clinical input. This is currently achieved by hospital clinic attendance every 2 to 4 weeks with limited opportunity for intervention between these visits. Objective: We conducted a randomized controlled trial to determine whether the use of a mobile phone-based real-time blood glucose management system to manage women with GDM remotely was as effective in controlling blood glucose as standard care through clinic attendance. Methods: Women with an abnormal oral glucose tolerance test before 34 completed weeks of gestation were individually randomized to a mobile phone-based blood glucose management solution (GDm-health, the intervention) or routine clinic care. The primary outcome was change in mean blood glucose in each group from recruitment to delivery, calculated with adjustments made for number of blood glucose measurements, proportion of preprandial and postprandial readings, baseline characteristics, and length of time in the study. Results: A total of 203 women were randomized. Blood glucose data were available for 98 intervention and 85 control women. There was no significant difference in rate of change of blood glucose (–0.16 mmol/L in the intervention and –0.14 mmol/L in the control group per 28 days, P=.78). Women using the intervention had higher satisfaction with care (P=.049). Preterm birth was less common in the intervention group (5/101, 5.0% vs 13/102, 12.7%; OR 0.36, 95% CI 0.12-1.01). There were fewer cesarean deliveries compared with vaginal deliveries in the intervention group (27/101, 26.7% vs 47/102, 46.1%, P=.005). Other glycemic, maternal, and neonatal outcomes were similar in both groups. The median time from recruitment to delivery was similar (intervention: 54 days; control: 49 days; P=.23). However, there were significantly more blood glucose readings in the intervention group (mean 3.80 [SD 1.80] and mean 2.63 [SD 1.71] readings per day in the intervention and control groups, respectively; P<.001). There was no significant difference in direct health care costs between the two groups, with a mean cost difference of the intervention group compared to control of –£1044 (95% CI –£2186 to £99). There were no unexpected adverse outcomes. Conclusions: Remote blood glucocse monitoring in women with GDM is safe. We demonstrated superior data capture using GDm-health. Although glycemic control and maternal and neonatal outcomes were similar, women preferred this model of care. Further studies are required to explore whether digital health solutions can promote desired self-management lifestyle behaviors and dietetic adherence, and influence maternal and neonatal outcomes. Digital blood glucose monitoring may provide a scalable, practical method to address the growing burden of GDM around the world. Trial Registration: ClinicalTrials.gov NCT01916694; https://clinicaltrials.gov/ct2/show/NCT01916694 (Archived by WebCite at http://www.webcitation.org/6y3lh2BOQ) Treatment of hyperglycemia in women with gestational diabetes mellitus (GDM) is associated with improved maternal and neonatal outcomes and requires intensive clinical input. This is currently achieved by hospital clinic attendance every 2 to 4 weeks with limited opportunity for intervention between these visits.BACKGROUNDTreatment of hyperglycemia in women with gestational diabetes mellitus (GDM) is associated with improved maternal and neonatal outcomes and requires intensive clinical input. This is currently achieved by hospital clinic attendance every 2 to 4 weeks with limited opportunity for intervention between these visits.We conducted a randomized controlled trial to determine whether the use of a mobile phone-based real-time blood glucose management system to manage women with GDM remotely was as effective in controlling blood glucose as standard care through clinic attendance.OBJECTIVEWe conducted a randomized controlled trial to determine whether the use of a mobile phone-based real-time blood glucose management system to manage women with GDM remotely was as effective in controlling blood glucose as standard care through clinic attendance.Women with an abnormal oral glucose tolerance test before 34 completed weeks of gestation were individually randomized to a mobile phone-based blood glucose management solution (GDm-health, the intervention) or routine clinic care. The primary outcome was change in mean blood glucose in each group from recruitment to delivery, calculated with adjustments made for number of blood glucose measurements, proportion of preprandial and postprandial readings, baseline characteristics, and length of time in the study.METHODSWomen with an abnormal oral glucose tolerance test before 34 completed weeks of gestation were individually randomized to a mobile phone-based blood glucose management solution (GDm-health, the intervention) or routine clinic care. The primary outcome was change in mean blood glucose in each group from recruitment to delivery, calculated with adjustments made for number of blood glucose measurements, proportion of preprandial and postprandial readings, baseline characteristics, and length of time in the study.A total of 203 women were randomized. Blood glucose data were available for 98 intervention and 85 control women. There was no significant difference in rate of change of blood glucose (-0.16 mmol/L in the intervention and -0.14 mmol/L in the control group per 28 days, P=.78). Women using the intervention had higher satisfaction with care (P=.049). Preterm birth was less common in the intervention group (5/101, 5.0% vs 13/102, 12.7%; OR 0.36, 95% CI 0.12-1.01). There were fewer cesarean deliveries compared with vaginal deliveries in the intervention group (27/101, 26.7% vs 47/102, 46.1%, P=.005). Other glycemic, maternal, and neonatal outcomes were similar in both groups. The median time from recruitment to delivery was similar (intervention: 54 days; control: 49 days; P=.23). However, there were significantly more blood glucose readings in the intervention group (mean 3.80 [SD 1.80] and mean 2.63 [SD 1.71] readings per day in the intervention and control groups, respectively; P<.001). There was no significant difference in direct health care costs between the two groups, with a mean cost difference of the intervention group compared to control of -£1044 (95% CI -£2186 to £99). There were no unexpected adverse outcomes.RESULTSA total of 203 women were randomized. Blood glucose data were available for 98 intervention and 85 control women. There was no significant difference in rate of change of blood glucose (-0.16 mmol/L in the intervention and -0.14 mmol/L in the control group per 28 days, P=.78). Women using the intervention had higher satisfaction with care (P=.049). Preterm birth was less common in the intervention group (5/101, 5.0% vs 13/102, 12.7%; OR 0.36, 95% CI 0.12-1.01). There were fewer cesarean deliveries compared with vaginal deliveries in the intervention group (27/101, 26.7% vs 47/102, 46.1%, P=.005). Other glycemic, maternal, and neonatal outcomes were similar in both groups. The median time from recruitment to delivery was similar (intervention: 54 days; control: 49 days; P=.23). However, there were significantly more blood glucose readings in the intervention group (mean 3.80 [SD 1.80] and mean 2.63 [SD 1.71] readings per day in the intervention and control groups, respectively; P<.001). There was no significant difference in direct health care costs between the two groups, with a mean cost difference of the intervention group compared to control of -£1044 (95% CI -£2186 to £99). There were no unexpected adverse outcomes.Remote blood glucocse monitoring in women with GDM is safe. We demonstrated superior data capture using GDm-health. Although glycemic control and maternal and neonatal outcomes were similar, women preferred this model of care. Further studies are required to explore whether digital health solutions can promote desired self-management lifestyle behaviors and dietetic adherence, and influence maternal and neonatal outcomes. Digital blood glucose monitoring may provide a scalable, practical method to address the growing burden of GDM around the world.CONCLUSIONSRemote blood glucocse monitoring in women with GDM is safe. We demonstrated superior data capture using GDm-health. Although glycemic control and maternal and neonatal outcomes were similar, women preferred this model of care. Further studies are required to explore whether digital health solutions can promote desired self-management lifestyle behaviors and dietetic adherence, and influence maternal and neonatal outcomes. Digital blood glucose monitoring may provide a scalable, practical method to address the growing burden of GDM around the world.ClinicalTrials.gov NCT01916694; https://clinicaltrials.gov/ct2/show/NCT01916694 (Archived by WebCite at http://www.webcitation.org/6y3lh2BOQ).TRIAL REGISTRATIONClinicalTrials.gov NCT01916694; https://clinicaltrials.gov/ct2/show/NCT01916694 (Archived by WebCite at http://www.webcitation.org/6y3lh2BOQ). |
Author | Clifton, Lei Levy, Jonathan Cummings Bartlett, Katy Jane Hirst, Jane Elizabeth Farmer, Andrew J Tarassenko, Lionel Mackillop, Lucy Birks, Jacqueline Susan Gibson, Oliver Loerup, Lise Rivero-Arias, Oliver Velardo, Carmelo Ming, Wai-Kit Kenworthy, Yvonne |
AuthorAffiliation | 3 Centre for Statistics in Medicine University of Oxford Oxford United Kingdom 6 Oxford Centre for Diabetes, Endocrinology and Metabolism Oxford University Hospitals NHS Foundation Trust Oxford United Kingdom 2 Nuffield Department of Women's and Reproductive Health University of Oxford Oxford United Kingdom 7 National Perinatal Epidemiology Unit University Of Oxford Oxford United Kingdom 8 Department of Obstetrics and Gynaecology Sun Yat-Sen University Guangzhou China 4 Nuffield Department of Primary Care Health Sciences University of Oxford Oxford United Kingdom 1 Oxford University Hospitals NHS Foundation Trust Headington United Kingdom 5 Institute of Biomedical Engineering University of Oxford Oxford United Kingdom |
AuthorAffiliation_xml | – name: 1 Oxford University Hospitals NHS Foundation Trust Headington United Kingdom – name: 4 Nuffield Department of Primary Care Health Sciences University of Oxford Oxford United Kingdom – name: 6 Oxford Centre for Diabetes, Endocrinology and Metabolism Oxford University Hospitals NHS Foundation Trust Oxford United Kingdom – name: 5 Institute of Biomedical Engineering University of Oxford Oxford United Kingdom – name: 2 Nuffield Department of Women's and Reproductive Health University of Oxford Oxford United Kingdom – name: 8 Department of Obstetrics and Gynaecology Sun Yat-Sen University Guangzhou China – name: 3 Centre for Statistics in Medicine University of Oxford Oxford United Kingdom – name: 7 National Perinatal Epidemiology Unit University Of Oxford Oxford United Kingdom |
Author_xml | – sequence: 1 givenname: Lucy orcidid: 0000-0002-1927-1594 surname: Mackillop fullname: Mackillop, Lucy – sequence: 2 givenname: Jane Elizabeth orcidid: 0000-0002-0176-2651 surname: Hirst fullname: Hirst, Jane Elizabeth – sequence: 3 givenname: Katy Jane orcidid: 0000-0002-2323-2141 surname: Bartlett fullname: Bartlett, Katy Jane – sequence: 4 givenname: Jacqueline Susan orcidid: 0000-0002-8310-9911 surname: Birks fullname: Birks, Jacqueline Susan – sequence: 5 givenname: Lei orcidid: 0000-0001-5595-8468 surname: Clifton fullname: Clifton, Lei – sequence: 6 givenname: Andrew J orcidid: 0000-0002-6170-4402 surname: Farmer fullname: Farmer, Andrew J – sequence: 7 givenname: Oliver orcidid: 0000-0002-9227-306X surname: Gibson fullname: Gibson, Oliver – sequence: 8 givenname: Yvonne orcidid: 0000-0002-2037-9244 surname: Kenworthy fullname: Kenworthy, Yvonne – sequence: 9 givenname: Jonathan Cummings orcidid: 0000-0002-9486-1885 surname: Levy fullname: Levy, Jonathan Cummings – sequence: 10 givenname: Lise orcidid: 0000-0002-1141-6680 surname: Loerup fullname: Loerup, Lise – sequence: 11 givenname: Oliver orcidid: 0000-0003-2233-6544 surname: Rivero-Arias fullname: Rivero-Arias, Oliver – sequence: 12 givenname: Wai-Kit orcidid: 0000-0002-8846-7515 surname: Ming fullname: Ming, Wai-Kit – sequence: 13 givenname: Carmelo orcidid: 0000-0003-4836-3743 surname: Velardo fullname: Velardo, Carmelo – sequence: 14 givenname: Lionel orcidid: 0000-0002-0118-1646 surname: Tarassenko fullname: Tarassenko, Lionel |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/29559428$$D View this record in MEDLINE/PubMed |
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ContentType | Journal Article |
Copyright | Lucy Mackillop, Jane Elizabeth Hirst, Katy Jane Bartlett, Jacqueline Susan Birks, Lei Clifton, Andrew J Farmer, Oliver Gibson, Yvonne Kenworthy, Jonathan Cummings Levy, Lise Loerup, Oliver Rivero-Arias, Wai-Kit Ming, Carmelo Velardo, Lionel Tarassenko. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 20.03.2018. 2018. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. Lucy Mackillop, Jane Elizabeth Hirst, Katy Jane Bartlett, Jacqueline Susan Birks, Lei Clifton, Andrew J Farmer, Oliver Gibson, Yvonne Kenworthy, Jonathan Cummings Levy, Lise Loerup, Oliver Rivero-Arias, Wai-Kit Ming, Carmelo Velardo, Lionel Tarassenko. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 20.03.2018. 2018 |
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References | ref13 ref12 ref15 ref14 ref11 ref10 Farmer, AJ (ref4) 2005; 28 Turner, J (ref3) 2009; 17 ref2 ref1 Schroeder, E (ref19) 2012; 344 ref16 ref18 Curtis, L (ref17) 2015 ref24 ref23 ref26 ref25 ref20 ref22 ref21 ref28 ref27 ref8 ref7 ref9 ref6 ref5 |
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SubjectTerms | Cellular telephones Clinical outcomes Clinical trials Cost analysis Cost control Fasting Gestational age Gestational diabetes Glucose monitoring Hypoglycemia Midwifery Monitoring systems Multimedia Original Paper Outpatient care facilities Patient satisfaction Pregnancy Questionnaires Standard deviation Trauma Womens health |
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Title | Comparing the Efficacy of a Mobile Phone-Based Blood Glucose Management System With Standard Clinic Care in Women With Gestational Diabetes: Randomized Controlled Trial |
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