The classification algorithm, published in the journal Analytical Chemistry, is based on infrared spectra of blood plasma, acquired on an Agilent Cary 630 FTIR Spectrometer
Agilent technologies announces that researchers at IIT Bombay in India and the QIMR Berghofer Medical Research Institute in Australia have developed a rapid method for differentiating COVID-19-positive patients expected to show severe symptoms from those likely to experience only mild symptoms. The classification algorithm, published in the journal Analytical Chemistry, is based on infrared spectra of blood plasma, acquired on an Agilent Cary 630 FTIR Spectrometer.
In the study, the researchers collected infrared spectra of blood plasma from 160 COVID-positive patients from Mumbai (130 as a training set for model development and 30 as a blind test set for model validation). The spectra, collected on a Cary 630 FTIR spectrometer equipped with a diamond-attenuated total reflectance (ATR) sampling module, revealed slight but observable differences between severe and non-severe COVID-19 patient samples.
Samir Vyas, Country Manager, Agilent India said, “2021 has opened new avenues for Agilent to work with industry and academia partners and contribute towards their research through the implementation of technological advancements, highly skilled applications, and expert support team utilization. This research highlights the potential of ATR-FTIR spectroscopy for further investigations into COVID-19 and other infectious diseases. It has been an honor to work with Dr Sanjeeva Srivastava and contribute towards the research endeavors of IIT, Mumbai, QIMR, and Kasturba hospital Mumbai researchers. We look forward to more innovation-based collaborations in future”.
Michelle Hill, Associate Professor, Head of QIMR Berghofer’s Precision and Systems Biomedicine Research Group, and one of the lead scientists of the study explained, “We found there were measurable differences in the infra-red spectra in the patients who became severely unwell. In particular, there were differences in two infra-red regions that correspond to sugar and phosphate chemical groups, as well as primary amines, which occur in specific types of proteins.”
Professor Dr Sanjeeva Srivastava from the Indian Institute of Technology Bombay added, “We also found that having diabetes was a key predictor of becoming severely unwell in this group of patients, so we included clinical parameters such as age, sex, diabetes mellitus, and hypertension into the algorithm. We then tested the algorithm on blood samples from a separate group of 30 patients from Mumbai and found it was 69.2% specific and 94.1% sensitive in predicting which patients would become severely ill.”
Professor Srivastava further explained, “It did however result in more ‘false positives’ than predictions that were based solely on the clinical risk factors of age, sex, hypertension, and diabetes. We hope that with more testing, we can reduce these false positives”.
The Agilent Cary 630 FTIR spectrometer is a versatile and reliable instrument used by researchers in high-impact studies throughout the world. Its ultra-compact form, simplicity, and ease of use make it ideal for seamless deployment in a multitude of settings and scenarios. It is particularly well suited for use in infectious disease research and the investigation of biological samples, where it can be paired with powerful multivariate statistical analysis to allow researchers to link spectral information with qualitative, macroscopic properties.