ReviewDiagnostics (Basel, Switzerland)2014
Trends in Nanomaterial-Based Non-Invasive Diabetes Sensing Technologies.
Review in Diagnostics (Basel, Switzerland), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
36 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Concise and Systematic Review on Non-Invasive Glucose Monitoring for Potential Diabetes Management.Biosensors · 2022Pooled it
- Integration of substrate-specific enzymes and a peroxide biosensor for detection of glucose, uric acid, and cholesterol.Applied and environmental microbiology · 2026Article
- Flexible and Stretchable Microneedle Electrode Arrays by Soft Lithography for Continuous Monitoring of Glucose.Biosensors · 2025Article
- Advanced Wearable Devices for Monitoring Sweat Biochemical Markers in Athletic Performance: A Comprehensive Review.Biosensors · 2024Review
- Control of sensitivity in metal oxide electrolyte gated field-effect transistor-based glucose sensor by electronegativity modulation.Scientific reports · 2024Article
- Multilayer patch functionalized microfibrillated cellulosic paper sensor for sweat glucose monitoring.Scientific reports · 2024Article
- DiaNet v2 deep learning based method for diabetes diagnosis using retinal images.Scientific reports · 2024Article
- Genetic perspectives on childhood monogenic diabetes: Diagnosis, management, and future directions.World journal of diabetes · 2023Review
- Improving the Accuracy of Continuous Blood Glucose Measurement Using Personalized Calibration and Machine Learning.Diagnostics (Basel, Switzerland) · 2023Article
- Screen-Printed Textile-Based Electrochemical Biosensor for Noninvasive Monitoring of Glucose in Sweat.Biosensors · 2023Article
- A Nanotechnology-Based Approach to Biosensor Application in Current Diabetes Management Practices.Nanomaterials (Basel, Switzerland) · 2023Review
- Fluorescence Sensing Technologies for Ophthalmic Diagnosis.ACS sensors · 2022Review
- Colorimetric and Electrochemical Screening for Early Detection of Diabetes Mellitus and Diabetic Retinopathy-Application of Sensor Arrays and Machine Learning.Sensors (Basel, Switzerland) · 2022Review
- Comprehensive Review on Wearable Sweat-Glucose Sensors for Continuous Glucose Monitoring.Sensors (Basel, Switzerland) · 2022Review
- Biosensing on a Plasmonic Dual-Band Perfect Absorber Using Intersection Nanostructure.ACS omega · 2022Article
- Commercial and Scientific Solutions for Blood Glucose Monitoring-A Review.Sensors (Basel, Switzerland) · 2022Review
- Glucose biosensors in clinical practice: principles, limits and perspectives of currently used devices.Theranostics · 2022Review
- Nanosensors for Visual Detection of Glucose in Biofluids: Are We Ready for Instrument-Free Home-Testing?Materials (Basel, Switzerland) · 2021Review
- The Application of Wearable Glucose Sensors in Point-of-Care Testing.Frontiers in bioengineering and biotechnology · 2021Review
- Advances in Biosensors for Continuous Glucose Monitoring Towards Wearables.Frontiers in bioengineering and biotechnology · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Blood glucose monitoring is considered the gold standard for diabetes diagnostics and self-monitoring. However, the underlying process is invasive and highly uncomfortable for patients. Furthermore, the process must be completed several times a day to successfully manage the disease, which greatly contributes to the massive need for non-invasive monitoring options. Human serums, such as saliva, sweat, breath, urine and tears, contain traces of glucose and are easily accessible. Therefore, they allow minimal to non-invasive glucose monitoring, making them attractive alternatives to blood measurements. Numerous developments regarding noninvasive glucose detection techniques have taken place over the years, but recently, they have gained recognition as viable alternatives, due to the advent of nanotechnology-based sensors. Such sensors are optimal for testing the amount of glucose in serums other than blood thanks to their enhanced sensitivity and selectivity ranges, in addition to their size and compatibility with electronic circuitry. These nanotechnology approaches are rapidly evolving, and new techniques are constantly emerging. Hence, this manuscript aims to review current and future nanomaterial-based technologies utilizing saliva, sweat, breath and tears as a diagnostic medium for diabetes monitoring.
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What OpenQuestion holds
Registered trials
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.