Infra-Red Technology Based Test Can Rapidly Predict Severe COVID-19

The researchers hope that the test could in future be used to triage patients in areas with large outbreaks of the disease.

The test was developed through an international collaboration between academia and industry using blood samples from 128 COVID-19 patients in Mumbai, India. Infra-red spectra measure the levels of different chemical groups in a sample. The team then used artificial intelligence to develop an algorithm to work out which chemical groups, or ‘signatures’, were correlated with patients who became severely unwell.

“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,” said Associate Professor Michelle Hill, head of QIMR Berghofer’s Precision and Systems Biomedicine Research Group.

“We also found that having diabetes was a predictor of becoming severely unwell in this group of patients, so we fed this information into the algorithm. We then tested the algorithm on blood samples from a separate group of 30 patients from Mumbai and found it was 85 per cent accurate in predicting which patients would become severely ill,” Associate Professor Hill said. “However, it did 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.”

“From our study, we can say that there is a correlation between blood chemical signature and becoming severely unwell with COVID-19,” said Professor Sanjeeva Srivastava, head of the Proteomics Facility at the Indian Institute of Technology. She added that the finding that there were chemical differences in more severe COVID-19 cases was consistent with published studies conducted in other countries.

Related Links:
QIMR Berghofer Medical Research Institute
Indian Institute of Technology