Urine odor in diabetes

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Urine Odor as a Diagnostic Indicator for Diabetes

Urine odor has long been associated with diabetes, particularly due to the presence of sweet or distinctive smells caused by metabolic changes. Recent research has focused on leveraging this characteristic for non-invasive diabetes detection.

Sweet-Smelling Urine and Volatile Organic Compounds (VOCs) in Diabetes

Diabetic patients often exhibit a sweet or unusual odor in their urine, primarily due to elevated glucose and the presence of specific volatile organic compounds (VOCs) such as acetone, ammonia, ethyl methyl ketone, and butyric acid. These compounds are more prevalent in the urine of diabetic individuals compared to healthy subjects, making them useful biomarkers for disease detection 2467.

Electronic Nose (E-Nose) Technology for Urine Odor Analysis

Several studies have developed and tested electronic nose (e-nose) devices equipped with gas sensors to detect and analyze urine odor patterns. These devices can distinguish between diabetic and non-diabetic urine samples by identifying unique odor profiles associated with diabetes. The e-nose systems utilize various sensor technologies, including metal oxide sensors, polymer/functionalized carbon nanotube composites, and surface acoustic wave sensors, to capture and process the odor signatures 1234567.

Accuracy and Effectiveness of Urine Odor-Based Diabetes Detection

Research has demonstrated high accuracy rates for urine odor-based diabetes detection. For example, some systems achieved success rates as high as 94% and 98.99% in correctly identifying diabetic urine samples, while others reported effective discrimination between diabetic and healthy individuals using principal component analysis and artificial neural networks 357. Both fasting and non-fasting urine samples have been shown to be effective for this type of analysis, increasing the flexibility and convenience of testing .

Advantages of Urine Odor Analysis for Diabetes Screening

Urine odor analysis offers several advantages over traditional blood-based diabetes tests. It is non-invasive, painless, and can be performed in real-time, making it suitable for self-monitoring and home use. The technology is also safe and convenient, potentially enabling broader access to early diabetes screening and ongoing health tracking 237.

Conclusion

Urine odor analysis, particularly using advanced e-nose technology, shows strong potential as a non-invasive, accurate, and user-friendly method for diabetes detection and monitoring. The identification of specific VOCs and sweet-smelling urine provides a reliable biomarker for diabetes, and ongoing research continues to improve the sensitivity and practicality of these diagnostic tools 1234567.

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Most relevant research papers on this topic

Diabetes diagnosis by direct measurement from urine odor using electronic nose

The electronic nose effectively detects diabetes by measuring urine odor, offering a potential tool for healthcare personnel and home users.

2012·

27citations

·S. Siyang et al.

Self-screening for diabetes by sniffing urine samples based on a hand-held electronic nose

The hand-held e-nose device effectively detects specific sweet-smelling urine odors, enabling real-time self-monitoring for diabetes patients and those at high risk of developing diabetes.

2016·

12citations

·T. Seesaard et al.

Recognition of Urine Smell Patterns in Diabetes Mellitus Patients Using an Artificial Neural Network Based on Semiconductor Sensors and Biosensors (Surface Acoustic Wave)

This research developed a non-invasive tool using e-nose equipment and artificial neural networks to accurately recognize urine odor patterns in diabetes mellitus patients, with a success rate of 94%.

2024·

0citations

·Muhammad Taufiqurrohman et al.

Volatile urine biomarkers detection in type II diabetes towards use as smart healthcare application

Chemiresistive gas sensors in e-noses can potentially detect type II diabetes by analyzing volatile urine odors, offering an alternative diagnostic tool.

2017·

8citations

·P. Choden et al.

Designing a Diabetes Mellitus Detection Tool Using the Backpropagation Method

The artificial neural network method using TGS 2610 and TGS 813 successfully detects diabetes mellitus in urine samples with a success rate of 75%.

2020·

1citation

·R. Alfita et al.

Developing diabetes ketoacidosis prediction using ANFIS model

The ANFIS model accurately predicts diabetic ketoacidosis using both fasting and non-fasting urine samples, enabling flexible diagnostic tests for diabetic patients.

2017·

5citations

·Galuh Wilujeng Saraswati et al.

Self-detection System for Type 2 Diabetes Mellitus by Aspiration of the Patient's Urinalysis

This research developed a self-detection system for type 2 diabetes mellitus by aspirating a patient's urine, detecting the disease through its sweet smell with a 98.99% efficiency.

2023·

0citations

·Brian Meneses-Claudio et al.

Rapid and non-invasive diagnosis of type 2 diabetes through sniffing urinary acetone by a proton transfer reaction mass spectrometry.

Sniffing urinary acetone using proton transfer reaction mass spectrometry is a rapid, non-invasive method for diagnosing type 2 diabetes with comparable accuracy to clinical methods.

Observational Study

2023·

12citations

·Wei Xu et al.

United States Patent Office 2 , 981 , 606 Patented Apr . 25 , 1961

The invention provides an improved, inexpensive, quick, convenient, and odor-free method for detecting glucose in urine for diabetic detection and treatment.

2017·

0citations

·E. Lilly

A history of diabetes mellitus or how a disease of the kidneys evolved into a kidney disease.

Diabetes mellitus has evolved from a kidney disease to a cause of chronic kidney disease, with its sweet taste in urine being due to sugar in the blood.

Highly Cited

2005·

91citations

·G. Eknoyan et al.

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