Evidence map›Paper›PMID 23294791›Full record

ArticleJournal of diabetes science and technology2012

Continuous monitoring of glucose in subcutaneous tissue using microfabricated differential affinity sensors.

Xian Huang, Charles Leduc, Yann Ravussin, Siqi Li, Erin Davis, Bing Song, Qian Wang, Domenico Accili, Rudolph Leibel, Qiao Lin

Open access · bronzeAbstract read
In one paragraph

Article in Journal of diabetes science and technology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 30% of its field
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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Article
  3. A MEMS differential viscometric sensor for affinity glucose detection in continuous glucose monitoring.Journal of micromechanics and microengineering : structures, devices, and systems · 2013
    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

10 authors at 3 institutions in 1 country.

Xian HuangDepartment of Mechanical Engineering, Columbia University, New York, NY 10027, USA. xh2123@columbia.edu
Charles Leduc
Yann Ravussin
Siqi Li
Erin Davis
Bing Song
Qian Wang
Domenico Accili
Rudolph Leibel
Qiao Lin
Columbia University Irving Medical Center · USUniversity of South Carolina · USColumbia University · US

Funding

Translational Biomarker Analytical Core (TBAC)P30DK063608 · NIDDK · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI DOMENICO ACCILI · 2003 to 2026
$36.7M
NIDDK NIH HHS DK63068-05NIDDK NIH HHS P30 DK063608NIDDK NIH HHS P30 DK63608-10
6 · The paper itself

Abstract

objectiveWe describe miniaturized differential glucose sensors based on affinity binding between glucose and a synthetic polymer. The sensors possess excellent resistance to environmental disturbances and can potentially allow wireless measurements of glucose concentrations within interstitial fluid in subcutaneous tissue for long-term, stable continuous glucose monitoring (CGM).

methodsThe sensors are constructed using microelectromechanical systems (MEMS) technology and exploit poly(N-hydroxy-ethyl acrylamide-ran-3-acrylamidophenylboronic acid) (PHEAA-ran-PAAPBA), a glucose-binding polymer with excellent specificity, reversibility, and stability. Two sensing approaches have been investigated, which respectively, use a pair of magnetically actuated diaphragms and perforated electrodes to differentially measure the glucose-binding-induced changes in the viscosity and permittivity of the PHEAA-ran-PAAPBA solution with respect to a reference, glucose-unresponsive polymer solution.

resultsIn vivo characterization of the MEMS affinity sensors were performed by controlling blood glucose concentrations of laboratory mice by exogenous glucose and insulin administration. The sensors experienced an 8-30 min initialization period after implantation and then closely tracked commercial capillary glucose meter readings with time lags ranging from 0-15 min during rapid glucose concentration changes. Clarke error grid plots obtained from sensor calibration suggest that, for the viscometric and dielectric sensors, respectively, approximately 95% (in the hyperglycemic range) and 84% (ranging from hypoglycemic to hyperglycemic glucose concentrations) of measurement points were clinically accurate, while 5% and 16% of the points were clinically acceptable.

conclusionsThe miniaturized MEMS sensors explore differential measurements of affinity glucose recognition. In vivo testing demonstrated excellent accuracy and stability, suggesting that the devices hold the potential to enable long-term and reliable CGM in clinical applications.

Indexed as

AnimalsBiosensing TechniquesBlood GlucoseBlood Glucose Self-MonitoringMiceMice, Inbred C57BLMicrotechnologyMonitoring, PhysiologicSubcutaneous TissueBlood Glucose

Identifiers

PMID23294791
PMCPMC3570886
OpenAlexW2055882479

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.