Abstract
Rapid diagnosis of the etiology of infection is highly important for an effective treatment of the infected patients. Bacterial and viral infections are serious diseases that can cause death in many cases. The human immune system deals with many viral and bacterial infections that cause no symptoms and pass quietly without treatment. However, oncology patients undergoing chemotherapy have a very weak immune system caused by leukopenia, and even minor pathogen infection threatens their lives. For this reason, physicians tend to prescribe immediately several types of antibiotics for febrile pediatric oncology patients (FPOPs). Uncontrolled use of antibiotics is one of the major contributors to the development of resistant bacteria. Therefore, for oncology patients, a rapid and objective diagnosis of the etiology of the infection is extremely critical. Current identification methods are time-consuming (>24 h). In this study, the potential of midinfrared spectroscopy in tandem with machine learning algorithms is evaluated for rapid and objective diagnosis of the etiology of infections in FPOPs using simple peripheral blood samples. Our results show that infrared spectroscopy enables the diagnosis of the etiology of infection as bacterial or viral within 70 minutes after the collection of the blood sample with 93% sensitivity and 88% specificity.
Original language | American English |
---|---|
Article number | e201900215 |
Journal | Journal of Biophotonics |
Volume | 13 |
Issue number | 2 |
DOIs | |
State | Published - 1 Feb 2020 |
Keywords
- FTIR microscopy
- infection etiology
- leukocytes
- machine learning
All Science Journal Classification (ASJC) codes
- General Chemistry
- General Materials Science
- General Biochemistry,Genetics and Molecular Biology
- General Engineering
- General Physics and Astronomy