The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Design, Development, and Evaluation of a Novel Microneedle Array-based Continuous Glucose Monitor
Open accessAbstract
Background: The development of accurate, minimally invasive continuous glucose monitoring (CGM) devices has been the subject of much work by several groups, as it is believed that a less invasive and more user-friendly device will result in greater adoption of CGM by persons with insulin-dependent diabetes. Methods: This article presents the results of preliminary clinical studies in subjects with diabetes of a novel prototype microneedle-based continuous glucose monitor. In this device, an array of tiny hollow microneedles is applied into the epidermis from where glucose in interstitial fluid (ISF) is transported via passive diffusion to an amperometric glucose sensor external to the body. Results: Comparison of 1396 paired device glucose measurements and fingerstick blood glucose readings for up to 72-hour wear in 10 diabetic subjects shows the device to be accurate and well tolerated by the subjects. Overall mean absolute relative difference (MARD) is 15% with 98.4% of paired points in the A+B region of the Clarke error grid. Conclusions: The prototype device has demonstrated clinically accurate glucose readings over 72 hours, the first time a microneedle-based device has achieved such performance.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Continuous glucose monitoring and intensive treatment of type 1 diabetes
(2008) · New England Journal of Medicine · doi:10.1056/nejmoa0805017 · Cited by 1,559
Technologies for Continuous Glucose Monitoring: Current Problems and Future Promises
Vaddiraju, S., Burgess, D. J., Tomazos, I., Jain, F. C., & Papadimitrakopoulos, F. (2010) · Journal of Diabetes Science and Technology · doi:10.1177/193229681000400632 · Cited by 285
Cited by
Accessing analytes in biofluids for peripheral biochemical monitoring
Heikenfeld, J., Jajack, A., Feldman, B., Granger, S. W., Gaitonde, S., Begtrup, G., & Katchman, B. A. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0040-3 · Cited by 758
Flexible Hybrid Electronics for Digital Healthcare
Ma, Y., Zhang, Y., Cai, S., Han, Z., Liu, X., Wang, F., Cao, Y., Wang, Z., Li, H., Chen, Y., et al. (2020) · Advanced Materials · doi:10.1002/adma.201902062 · Cited by 620
From pre-diabetes to diabetes: diagnosis, treatments and translational research
Khan, R., Chua, Z., Tan, J., Yang, Y., Liao, Z., & Zhao, Y. (2019) · Medicina · doi:10.3390/medicina55090546 · Cited by 484
Wearable Electrochemical Glucose Sensors in Diabetes Management: A Comprehensive Review
Saha, T., Del Caño, R., Mahato, K., De la Paz, E., Chen, C., Ding, S., Yin, L., & Wang, J. (2023) · Chemical Reviews · doi:10.1021/acs.chemrev.3c00078 · Cited by 442
Lab under the Skin: Microneedle Based Wearable Devices
Teymourian, H., Tehrani, F., Mahato, K., & Wang, J. (2021) · Advanced Healthcare Materials · doi:10.1002/adhm.202002255 · Cited by 310
Metadata
- Authors
- Jina, A., Tierney, M. J., Tamada, J. A., McGill, S., Desai, S., Chua, B., Chang, A., & Christiansen, M.
- Venue
- Journal of Diabetes Science and Technology
- Publisher
- SAGE Publications
- Published
- 2014-03-06
- Volume
- 8
- Issue
- 3
- Pages
- 483-487
- ISSN
- 1932-2968 (ISSN-L)
- OpenAlex
- W2138418310
- Cited by
- 176
- References
- 2
- FWCI
- 4.55
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Design, Development, and Evaluation of a Novel Microneedle Array-based Continuous Glucose Monitor. https://app.cochat.ai/papers/10.1177/1932296814526191
- The paper
- Jina, A., Tierney, M. J., Tamada, J. A., McGill, S., Desai, S., Chua, B., Chang, A., & Christiansen, M. (2014). Design, Development, and Evaluation of a Novel Microneedle Array-based Continuous Glucose Monitor. Journal of Diabetes Science and Technology. https://doi.org/10.1177/1932296814526191
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.