Clinical Evidence for Use of a Noninvasive Biosensor for Tear Glucose as an Alternative to Painful Finger-Prick for Diabetes Management Utilizing a Biopolymer Coating

Diabetes is a metabolic condition that is exponentially increasing worldwide. Current monitoring methods for diabetes are invasive, painful, and expensive. Herein, we present the first multipatient clinical trial that demonstrates clearly that tear fluid may be a valuable marker for systemic glucose...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Biomacromolecules 2018-11, Vol.19 (11), p.4504-4511
Hauptverfasser: Kownacka, Alicja E, Vegelyte, Dovile, Joosse, Maurits, Anton, Nicoleta, Toebes, B. Jelle, Lauko, Jan, Buzzacchera, Irene, Lipinska, Katarzyna, Wilson, Daniela A, Geelhoed-Duijvestijn, Nel, Wilson, Christopher J
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Diabetes is a metabolic condition that is exponentially increasing worldwide. Current monitoring methods for diabetes are invasive, painful, and expensive. Herein, we present the first multipatient clinical trial that demonstrates clearly that tear fluid may be a valuable marker for systemic glucose measurements. The NovioSense Glucose Sensor, worn under the lower eye lid (inferior conjunctival fornix), is reported to continuously measure glucose levels in the basal tear fluid with good correlation to blood glucose values, showing clear clinical feasibility in both animals and humans. Furthermore, the polysaccharide coated device previously reported by our laboratory when worn, does not induce pain or irritation. In a phase II clinical trial, six patients with type 1 Diabetes Mellitus were enrolled and the capability of the device to measure glucose in the tear fluid was evaluated. The NovioSense Glucose Sensor gives a stable signal and the results correlate well to blood glucose values obtained from finger-prick measurements determined by consensus error grid analysis.
ISSN:1525-7797
1526-4602
DOI:10.1021/acs.biomac.8b01429