Monitoring vital signs — heart rates, respiratory rates, blood pressure and temperature — can give nurses and doctors a pretty good idea of how unwell someone is. But researchers began noticing something was going wrong in UK hospital wards — crucial signs of patient deterioration were being missed.
Researchers at the University of Nottingham, UK, are developing an Artificial Intelligence (AI) algorithm that can take account of the vital signs history of a patient, including the trend over time and the degree of variability. Tools like these can help medical staff spot early signs of deteriorating patients and treat life-threatening conditions before it’s too late.
Reviewing the charts from patients who have suffered a cardiac arrest often reveals a pattern of worsening vital signs in the hours beforehand. It was soon recognised that combinations of abnormal vital signs were associated with a higher risk than a single abnormal sign. Which is why Early Warning Scores are largely used to assign a number to each vital sign and added together to give a total score. For example, one widely used score in the UK is the National Early Warning Score-2 (NEWS-2) — if you score five or more you should get an urgent medical review, seven or more and the medical team will come running.
