| Title |
Emerging Technologies for the Management of Type 1 Diabetes in Pregnancy
|
|---|---|
| Published in |
Current Diabetes Reports, January 2018
|
| DOI | 10.1007/s11892-018-0973-9 |
| Pubmed ID | |
| Authors |
Jennifer M. Yamamoto, Helen R. Murphy |
| Abstract |
The purpose of the study is to discuss emerging technologies available in the management of type 1 diabetes in pregnancy. 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. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 67 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 14 | 21% |
| Student > Bachelor | 10 | 15% |
| Researcher | 5 | 7% |
| Student > Postgraduate | 5 | 7% |
| Other | 4 | 6% |
| Other | 10 | 15% |
| Unknown | 19 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 28 | 42% |
| Nursing and Health Professions | 10 | 15% |
| Computer Science | 3 | 4% |
| Biochemistry, Genetics and Molecular Biology | 2 | 3% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 3% |
| Other | 3 | 4% |
| Unknown | 19 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 May 2018.
All research outputs
#19,020,456
of 23,576,969 outputs
Outputs from Current Diabetes Reports
#794
of 1,024 outputs
Outputs of similar age
#332,876
of 442,660 outputs
Outputs of similar age from Current Diabetes Reports
#13
of 15 outputs
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We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.