COVID-19 Risk Score Predicts Mortality

By using readily available patient data, like blood pressure and patient demographics at admission a new scoring system was able to predict the likelihood of death in over 57,000 COVID-19 patients.

The Coronavirus Clinical Characterization Consortium (4C) Mortality Score was published online on the 9^th Sep 2020 (https://www.bmj.com/content/370/bmj.m3339). The score classifies patients has having either a low (0-3), intermediate (4-8), high (9-14) or very high (15+) likelihood of death on the basis of a point system from 0 to 21.

The hope is this score could help manage COVID-19 cases. This with a low score could be managed in the community. Those with an intermediate risk could be monitored in hospital whereas those with a high or very high risk could be directed to more aggressive treatment quickly. For example, if there are 3 high risk patients on a ward, the ICU could be made aware and prepare for their arrival in advance if necessary.

The score was developed in the UK and now has an online interactive tool for clinicians to use (https://isaric4c.net/risk/). The Score only requires eight factors: age, sex, number of comorbidities, respiratory rate, peripheral oxygen saturation, Glasgow coma scale score, urea level and C reactive protein concentration.

This new scoring system was compared against 15 other risk stratification methods and outperformed them in predicting COVID-19 specific mortality. Despite differences in the non-white population, the 4C score also remains valid for ethnic minority groups. However, some caution may be needed when applying the score to lower risk of death populations and in other countries than the UK.

The 4C score is an easy to use predictor of mortality, using readily available patient data, and can help guide clinical decisions. This study has laid the foundation for future prospective studies using deep-learning artificial intelligence that can further understand the nuances of the disease.