Researchers at Oxford University have developed a tool that makes it easier and cheaper to diagnose pneumonia, according to new research. Health workers need to judge how severe the infection is to decide whether a child needs referral to a hospital and whether the infection is viral or bacterial to determine if antibiotics will have any effect, but the workers need a basic set of easily portable equipment in order to do so. For an automated system to be effective, it needs to be able to work with data from the basic equipment, so the researchers took in-depth data from a clinical study in the Gambia and used machine learning techniques to try and develop an algorithm that could diagnose pneumonia.

“With the nearest hospital hours away, generalist health workers depend on a set of guidelines known as IMCI. These can sometimes be good at identifying cases of pneumonia but not so good at screening out cases that are not pneumonia. There is also huge variability across users,” explains Elina Naydenova of Oxford University. “In settings, where there isn’t a clinical expert to set a conclusive diagnosis, the number of unnecessary antibiotic prescriptions has increased as a result…we wanted to apply smart engineering to develop a robust automated system that was consistently more accurate.”

Elina says the team found four features for identifying pneumonia that can be measured with two pieces of equipment: heart rate, respiratory rate, and oxygen saturation that can be measured with a pulse oximeter, and temperature, which requires a thermometer. “Using these four measures, we achieved 98.2% sensitivity and 97.5% specificity [ie — they could correctly identify 982 out of every 1000 pneumonia cases and only falsely identified pneumonia in 25 of every 1000 people without the disease], compared to IMCI, where the best performance is 94% sensitivity and 69% specificity,” says Elina.

According to Science Daily, by adding an assessment of two lung sounds, using a stethoscope, the team was able to work out the severity of an infection with 72.4% sensitivity and 82.2% specificity (IMCI achieves 79.3% and 67.7% respectively). Also, adding a test for the biomarker C Reactive Protein (CRP) delivered 89.1% sensitivity and 81.3% specificity, though the team points out this would involve additional cost.

In addition, by assessing heart and respiratory rates and oxygen saturation in tandem with a biomarker called Lipocalin-2, the researchers could identify whether pneumonia was bacterial or viral with 81.8% sensitivity and 90.6% specificity. When IMCI was applied, it was 100% sensitive to severe bacterial infection by 0% specific; all severe cases would have also been prescribed antibiotics. While low-cost tests for these biomarkers are not commercially available yet, research teams are looking into developing such tests for use in resource-constrained settings, according to Science Daily.

Elina says, “We have identified a set of features that could offer an alternative to the combination of X-rays and blood cultures only available in a well-equipped hospital. These will be used in a mobile application linked to a set low-cost diagnostic equipment, which we will be trialing in the next couple of years.”

Source: Science Daily