Evidence map›Paper›PMID 37631595›Full record

ReviewSensors (Basel, Switzerland)2023

Noninvasive Glucose Sensing In Vivo.

Ho Man Colman Leung, Gregory P Forlenza, Temiloluwa O Prioleau, Xia Zhou

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. 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

4 authors.

Ho Man Colman LeungDepartment of Computer Science, Columbia University, New York, NY 10027, USA.ORCID 0000-0001-5703-0823
Gregory P ForlenzaBarbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.ORCID 0000-0003-3607-9788
Temiloluwa O PrioleauDepartment of Computer Science, Dartmouth College, Hanover, NH 03755, USA.ORCID 0000-0001-6750-202X
Xia ZhouDepartment of Computer Science, Columbia University, New York, NY 10027, USA.

Funding

Directorate for Engineering 2037267
6 · The paper itself

Abstract

Blood glucose monitoring is an essential aspect of disease management for individuals with diabetes. Unfortunately, traditional methods require collecting a blood sample and thus are invasive and inconvenient. Recent developments in minimally invasive continuous glucose monitors have provided a more convenient alternative for people with diabetes to track their glucose levels 24/7. Despite this progress, many challenges remain to establish a noninvasive monitoring technique that works accurately and reliably in the wild. This review encompasses the current advancements in noninvasive glucose sensing technology in vivo, delves into the common challenges faced by these systems, and offers an insightful outlook on existing and future solutions.

Indexed as

Blood GlucoseBlood Glucose Self-MonitoringDisease ManagementHumansBlood Glucosediabetesinterstitial fluidnoninvasive glucose sensing

Identifiers

PMID37631595
PMCPMC10458980

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.