Evidence map›Paper›PMID 31863200›Full record

ReviewCurrent diabetes reports2019

Technological Advancements in the Management of Type 2 Diabetes.

Abigail Kennedy Grant, Lauren Golden

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current diabetes reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Observational
  9. Review
  10. Flash Glucose Monitoring and Patient Satisfaction: A Meta-Review of Systematic Reviews.International journal of environmental research and public health · 2021
    Review
  11. Article
  12. Four-microRNA signature for detection of type 2 diabetes.World journal of clinical cases · 2020
    Article
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Abigail Kennedy GrantNYU Langone Medical Center, New York, NY, USA.
Lauren GoldenNYU Langone Medical Center, New York, NY, USA. Lauren.Golden@nyulangone.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewThe increasing prevalence of type 2 diabetes is driving the boundaries of clinical diabetes care outside of the traditional office setting. The purpose of this paper will be to review recent technological advances in the medical management of people with type 2 diabetes, spanning the spectrum of care from access to healthcare providers/educators, to continual virtual support methods, on-line management tools, and technologically integrated medication delivery systems. RECENT

findingsRecent findings support a potential positive impact of technology on access to care, clinical outcomes, convenience, patient well-being, and patient acceptance. This includes the use of Bluetooth-enabled glucose meters, continuous glucose monitors, mHealth apps, smartpens, and insulin pumps. However, there are impediments to the implementation of some technologies due to cost and lack of insurance coverage. There is evidence to support the use of technology to improve the management and treatment of people with type 2 diabetes. Further research is required to demonstrate the long-term clinical benefit and financial viability of technology in the management of type 2 diabetes.

Indexed as

Diabetes Mellitus, Type 1Biomedical TechnologyBlood GlucoseBlood Glucose Self-MonitoringDiabetes Mellitus, Type 2HumansInsulin Infusion SystemsTelemedicineBlood GlucoseGlucose sensorInsulin pumpLifestyle modificationSmartpenTechnologyType 2 diabetes

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.