| Autor: |
Jeppson MA, Rasmussen Z, Castro R, Nalugwa T, Kisakye E, Mangeni W, Andama A, Jaganath D, Cattamanchi A, Mohanty SK |
| Jazyk: |
angličtina |
| Zdroj: |
MedRxiv : the preprint server for health sciences [medRxiv] 2024 Jun 14. Date of Electronic Publication: 2024 Jun 14. |
| DOI: |
10.1101/2024.05.23.24307746 |
| Abstrakt: |
Tuberculosis (TB) remains a significant global health issue; making early, accurate, and inexpensive point-of-care detection critical for effective treatment. This paper presents a clinical demonstration of an electrochemical sensor that detects methyl-nicotinate (MN), a volatile organic biomarker associated with active pulmonary tuberculosis. The sensor was initially tested on a patient cohort comprised of 57 adults in Kampala, Uganda, of whom 42 were microbiologically confirmed TB-positive and 15 TB-negative. The sensor employed a copper(II) liquid metal salt solution with a square wave voltammetry method tailored for MN detection using commercially available screen-printed electrodes. An exploratory machine learning analysis was performed using XGBOOST. Utilizing this approach, the sensor was 78% accurate with 71% sensitivity and 100% specificity. These initial results suggest the sensing methodology is effective in identifying TB from complex breath samples, providing a promising tool for non-invasive and rapid TB detection in clinical settings. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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