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In Vitro Diagnostics in Diabetes: Meeting the Challenge

Turner, Anthony PF, Chen, Beining, Piletsky, Sergey A·1999·Clinical Chemistry

Abstract

Diabetes is one of the leading causes of death and disability in the world. There is a large population in the world suffering from this disease, and the healthcare costs increase every year. It is a chronic disorder resulting from insulin deficiency and hyperglycemia and has a high risk of development of complications for the eyes, kidneys, peripheral nerves, heart, and blood vessels. Quick diagnosis and early prevention are critical for the control of the disease status. Traditional biosensors such as glucose meters and glycohemoglobin test kits are widely used in vitro for this purpose because they are the two major indicators directly involved in diabetes diagnosis and long-term management. The market size and huge demand for these tests make it a model disease to develop new approaches to biosensors. In this review, we briefly summarize the principles of biosensors, the current commercial devices available for glucose and glycohemoglobin measurements, and the recent work in the area of artificial receptors and the potential for the development of new devices for diabetes specifically connected with in vitro monitoring of glucose and glycohemoglobin HbA1c.

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Metadata

Authors
Turner, A. P., Chen, B., & Piletsky, S. A.
Venue
Clinical Chemistry
Published
1999-09-01
Volume
45
Issue
9
Pages
1596-1601
ISSN
  • 0009-9147 (ISSN-L)
  • 1530-8561
OpenAlex
W2108225249
Cited by
161
References
0
FWCI
5.78
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: In Vitro Diagnostics in Diabetes: Meeting the Challenge. https://app.cochat.ai/papers/10.1093/clinchem/45.9.1596
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Turner, A. P., Chen, B., & Piletsky, S. A. (1999). In Vitro Diagnostics in Diabetes: Meeting the Challenge. Clinical Chemistry. https://doi.org/10.1093/clinchem/45.9.1596

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.