ArticleACS omega2022
Breath Analysis for the In Vivo Detection of Diabetic Ketoacidosis.
Article in ACS omega, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
What it found
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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
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.
- Is Breath Best? A Systematic Review on the Accuracy and Utility of Nanotechnology Based Breath Analysis of Ketones in Type 1 Diabetes.Biosensors · 2025Pooled it
- Headset-Type Biofluorometric Gas Sensor with CMOS for Transcutaneous Ethanol from the Ear Canal.Sensors (Basel, Switzerland) · 2026Article
- Breathomics in Diabetes Management: A Noninvasive Approach for Precision Health Monitoring.Journal of diabetes research · 2026Review
- An Insight Into Unveiling Nano Luminescence for Industrial Dye Detection.Journal of fluorescence · 2025Article
- Design and Development of Inexpensive Paper-Based Chemosensors for Detection of Divalent Copper.Journal of fluorescence · 2023Article
- An efficient transition metal chalcogenide sensor for monitoring respiratory alkalosis.3 Biotech · 2023Article
- Highly sensitive and selective colorimetric sensing of CO3 Biotech · 2022Article
- Review
- A smartphone-interfaced, low-cost colorimetry biosensor for selective detection of bronchiectasisRSC advances · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Human breath analysis of volatile organic compounds has gained significant attention recently because of its rapid and noninvasive potential to detect various metabolic diseases. The detection of ketones in the breath and blood is key to diagnosing and managing diabetic ketoacidosis (DKA) in patients with type 1 diabetes. It may also be of increasing importance to detect euglycemic ketoacidosis in patients with type 1 or type 2 diabetes or heart failure, treated with sodium-glucose transporter-2 inhibitors (SGLT2-i). The present research evaluates the efficiency of colorimetry for detecting acetone and ethanol in exhaled human breath with the response time, pH effect, temperature effect, concentration effect, and selectivity of dyes. Using the proposed multidye system, we obtained a detection limit of 0.0217 ppm for acetone and 0.029 ppm for ethanol in the detection range of 0.05-50 ppm. A smartphone-assisted unit consisting of a portable colorimetric device was used to detect relative red/green/blue values within 60 s of the interface for practical and real-time application. The developed method could be used for rapid, low-cost detection of ketones in patients with type 1 diabetes and DKA and patients with type 1 or type 2 diabetes or heart failure treated with SGLT2-I and euglycemic ketoacidosis.
Identifiers
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.