Recent Developments in Personal Glucose Meters as Point-of-Care Testing Devices (2020-2024)

Abstract

Point-of-care testing (POCT) is a contemporary diagnostic approach characterized by its user-friendly nature, cost efficiency, environmental compatibility, and lack of reliance on professional experts. Therefore, it is widely used in clinical diagnosis and other analytical testing fields to meet the demand for rapid and convenient testing. The application of POCT technology not only improves testing efficiency, but also brings convenience and benefits to the healthcare industry. The personal glucose meter (PGM) is a highly successful commercial POCT tool that has been widely used not only for glucose analysis, but also for non-glucose target detection. In this review, the recent advances from 2020 to 2024 in non-glucose target analysis for PGMs as POCT devices are summarized. The signal transduction strategies for non-glucose target analysis based on PGMs, including enzymatic transduction, nanocarrier transduction (enzyme or glucose), and glucose consumption transduction are briefly introduced. Meanwhile, the applications of PGMs in non-glucose target analysis are outlined, encompassing biomedical, environmental, and food analysis, along with other diverse applications. Finally, the prospects of and obstacles to employing PGMs as POCT tools for non-glucose target analysis are discussed.

Keywords: enzymatic transduction; glucose consumption transduction; nanocarrier transduction; non-glucose target; personal glucose meters.

Figure 3

Schematic diagram of the enzymatic transduction technology for detecting analytes other than glucose using the PGM method. (A) Diagram illustration of the principle of the PGM method based on β-Glucosidase-mediated cascade enzymatic reaction. Reprinted with permission from Ref. [13]. (B) Diagram illustration of the design of H₂O₂ detection based on the inhibition of H₂O₂ on AAO and the PGM readout triggered by AA. Reprinted with permission from Ref. [17]. (C) Diagram illustration of the PGM strategy to detect H₂O₂ based on the target-induced oxidation of [Fe(CN)₆]⁴⁻ to [Fe(CN)₆]³⁻. Reprinted with permission from Ref. [18].

Figure 1

Number of published articles on PGM-based methods from 2020 to 2024. Data obtained from Web of Science. Search condition: Topic: personal glucose meter; Document types: Article; Total: 83 published articles up to August 2024.

Figure 2

Visual overview of the review on PGM-based sensing strategies to detect analytes other than glucose. Reprinted with permission from Refs. [13,14,15].

Figure 4

Schematic diagram of the nanocarrier-immobilized enzyme transduction technology for detecting analytes other than glucose using the PGM method. (A) Diagram illustration of the principle of a biosensing platform for pathogen DNA based on the CRISPR Cas12a system and PGM method. Reprinted with permission from Ref. [26]. (B) Diagram illustration of the principle of the Fe₃O₄@Au-Apt/DMSNs-I-cDNA aptamer sensor for the detection of aflatoxin B1 and bisphenol A by PGM. Reprinted with permission from Ref. [27]. (C) Diagram illustration of the principle of the enzyme@ZIF-90 platform for ATP detection by PGM. Reprinted with permission from Ref. [14].

Figure 5

Schematic diagram of nanocarrier-encapsulated glucose transduction technology for detecting analytes other than glucose using the PGM method. (A) Diagram illustration of the principle of a PEM-based MSN-PEI@Au NPs-Ab platform for CYFRA21-1 detection. Reprinted with permission from Ref. [28]. (B) Diagram illustration of the preparation of aptamer-grafted liposomes with glucose encapsulation (G-Lip-Apt), single-strand DNA-attached magnetic Fe₃O₄@SiO₂/NH₂-DNA nanocomposites, and the principle of AβO detection by PGM. Reprinted with permission from Ref. [30].

Figure 6

Schematic diagram of the glucose consumption transduction technology for detecting analytes other than glucose using the PGM method. (A) Diagram illustration of PGM-CeO₂ NP-based TdT detection. Reprinted with permission from Ref. [31]. (B) Diagram illustration of PGM-AuNP-based biothiol detection. Reprinted with permission from Ref. [15].

Figure 7

Application of PGM in non-glucose target quantitative biomedical analysis. (A) Preparation of streptavidin-invertase-Ca₃(PO₄)₂ hybrid nanoflowers by one-pot method. (B) Overview of the proposed SICa-based N protein detection method. Reprinted with permission from Ref. [75].

Figure 8

Applications of PGMs in non-glucose target quantitative food analysis. Schematic of the mechanism of the proposed portable ELISA for the detection of CBD. Reprinted with permission from Ref. [90].

Figure 9

Applications of PGMs in non-glucose target quantitative environmental analysis. Schematic of the mechanism of the proposed two-mode Hg²⁺ sensing platforms based on the tunable cobalt metal–organic framework (Co-MOF) active site strategy for the detection of Hg²⁺. Reprinted with permission from Ref. [84].