Researchers in India, Australia Develop Rapid Screening Method to Predict Severity of COVID-19


Researchers at the Indian Institute of Technology in Bombay, India and the QIMR Berghofer Medical Research Institute in Australia have created a rapid method to determine whether a COVID-19 patient is likely to have severe symptoms.


The classification algorithm that was developed is based on infrared spectra of blood plasma acquired using the FTIR Agilent Cary 630 spectrometer from the Californian biotechnology company Agilent Technologies.

In their study, of which the results were published in the journal Analytical Chemistry, the researchers collected infrared spectra of blood plasma from 160 COVID-positive patients from Mumbai – 130 as a training set for the development of the multivariate statistical model and another 30 as as a blind test set for the validation model.

The Agilent spectrometer showed “slight but observable” differences in sample blood plasma spectra between severe and non-severe COVID-19 patients.

“In particular, there were differences in two infrared regions that correspond to the chemical groups of sugar and phosphate, as well as primary amines, which occur in specific types of proteins,” said Michelle Hill, group leader. Precision and Systems Biomedicine research team at QIMR. Berghofer.

According to Sanjeeva Srivastava, a professor at the Indian Institute of Technology in Bombay, the study also found that diabetes is a “key predictor” of severe COVID-19.

Following this, the algorithm was fed with other clinical parameters, such as age, gender, diabetes mellitus, and hypertension, and then tested on 30 samples for blind testing. It was later revealed that he obtained a specificity of 69.2% and a sensitivity of 94.1% to predict who among the COVID-19 patients would become seriously ill.

However, this resulted in more false positives than predictions, Professor Srivastava noted. “We hope that with more testing we can reduce these false positives,” he said.


Health systems around the world have been overwhelmed by persistent outbreaks of COVID-19, leading to shortages of hospital resources such as beds and ventilators.

The The World Health Organization has stressed the importance of early identification and triage of patients based on severity to help free up resources.

Agilent said in a statement that the latest research has the potential to provide support for healthcare facilities making critical decisions about hospital resources.


An AI tool has recently been developed that can indicate the likelihood of a COVID-19 patient surviving after hospitalization. The Web Hong Kong-based AI systems developer Deep Longevity’s COVID risk calculator provides a patient’s COVID-19 risk score, expected time to death, and probability of survival curve. The company stressed that assigning risk to admitted patients is still a “critical, albeit grim necessity” as hospitals around the world continue to be inundated with new cases of COVID-19.


“We are very excited about this study and were pleased to support the researchers in their fight against COVID-19 by placing the Cary 630 FTIR spectrometer for this study. Their work highlights the potential of ATR-FTIR spectroscopy for research on COVID-19 and infectious diseases. , and we will continue to support research in this area, ”said Andrew Hind, assistant vice president of research and development for the Molecular Spectroscopy division at Agilent.

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