Timely ketone detection in patients with type 1 diabetes mellitus (T1DM) is critical for the effective management of diabetic ketoacidosis (DKA). This systematic review evaluates the current literature on breath-based analysis for ketone detection in T1DM, highlighting nanotechnology as a potential for a non-invasive alternative to blood-based ketone measurements. A comprehensive search across 5 databases identified 11 studies meeting inclusion criteria, showcasing various breath analysis techniques, such as semiconducting gas sensors, colorimetry, and nanoparticle-based chemo-resistive sensors. These studies report high sensitivity and correlation between breath acetone (BrAce) levels and blood ketones, with some demonstrating accuracies up to 94.7% and correlations reaching R values as high as 0.98. However, significant heterogeneity in methodologies and cut-off values limits device comparability and precludes meta-analysis. Despite these challenges, the findings indicate that BrAce monitoring could offer significant clinical benefits by enabling the earlier detection of ketone buildup, reducing DKA-related hospitalisations and healthcare costs. Standardising BrAce measurement techniques and sensitivity thresholds is essential to broaden clinical adoption. This review underscores the promise of nanotechnology-based breath analysis as a transformative tool for DKA management, with potential utility across varied ketotic conditions.
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http://dx.doi.org/10.3390/bios15010062 | DOI Listing |
Microorganisms
January 2025
Department of Clinical Biochemistry, Pediatric Institute, Faculty of Medicine, Jagiellonian University Medical College, 30-663 Krakow, Poland.
Small intestinal bacterial overgrowth (SIBO) is a disorder characterized by the excessive growth of bacteria in the small intestine. Bacterial overgrowth disrupts the bacterial balance and can lead to abdominal pain, weight loss, and gastrointestinal symptoms, including bloating, diarrhea, and malabsorption. SIBO is widespread in the population.
View Article and Find Full Text PDFCancers (Basel)
January 2025
Department of Radiation Oncology, Miami Cancer Institute, Miami, FL 33176, USA.
: Over the past decade, significant advances have been made in image-guided radiotherapy (RT) particularly with the introduction of magnetic resonance (MR)-guided radiotherapy (MRgRT). However, the optimal clinical applications of MRgRT are still evolving. The intent of this analysis was to describe our institutional MRgRT utilization patterns and evolution therein, specifically as an early adopter within a center endowed with multiple other technology platforms.
View Article and Find Full Text PDFHealthcare (Basel)
January 2025
Jiann-Ping-Hsu College of Public Health, Georgia Southern University, Statesboro, GA 30460, USA.
Chronic kidney disease (CKD) is a severe health problem with dire consequences for the quality of life of millions of individuals and their families around the globe. This quantitative study analyzes the factors associated with hemodialysis patients' quality of life (QoL) in Lahore City, Pakistan. Primary data from a sample of 384 patients were collected through regular visits to the hospital.
View Article and Find Full Text PDFJ Health Popul Nutr
January 2025
Department of Gastroenterology, The Affiliated Hospital of Xuzhou Medical University, Huaihai West Road, Xuzhou, Jiang Su, 221004, China.
Aims: This study aims to assess the serum levels of pepsinogen (PG)I, PG II, and gastrin (G17) in patients with gastric intestinal metaplasia (GIM) and evaluate their correlation with demographic characteristics.
Methods: A total of 247 normal controls (NC) and 240 patients diagnosed with GIM were enrolled in this study. All participants underwent a gastroscopy procedure followed by pathological examination for diagnosis confirmation.
Sci Rep
January 2025
Hospital Tuanku Ja'afar, Jalan Rasah, 70300, Seremban, Negeri Sembilan, Malaysia.
The COVID-19 pandemic has burdened healthcare systems globally. To curb high hospital admission rates, only patients with genuine medical needs are admitted. However, machine learning (ML) models to predict COVID-19 hospitalization in Asian children are lacking.
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