Risk stratification tool for COVID-19 patients developed

By Dr. Ananya Mandal, MDSep 9 2020

Researchers have worked on the development of a protocol that could stratify COVID-19 patients based on a scoring system. This new study describing the scoring system for risk stratification is titled, “Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: development and validation of the 4C Mortality Score,” and is published in the latest issue of the British Medical Journal.

Colorized scanning electron micrograph of an apoptotic cell (green) heavily infected with SARS-CoV-2 virus particles (purple), isolated from a patient sample. Image captured at the NIAID Integrated Research Facility (IRF) in Fort Detrick, Maryland. Credit: NIAID

What was the study about?

To date, over 27 million people around the world have been infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which has taken over 900,000 globally since its emergence in late December 2019. At the same time, over 18.6 million individuals are reported as recovered.

Researchers wrote that the infection with SARS-CoV-2 that causes COVID-19 disease is known to have a high mortality rate among the aging and vulnerable population, mainly due to respiratory failure. Around the world, there is a rapid influx of patients admitted to the hospitals with respiratory symptoms caused by the infection, and there is thus a need for a tool that could stratify the risk of death and the need for intensive care among those admitted into the hospitals. If the high-risk individuals are identified early, their management could be tailored accordingly, and this could bring down the number of deaths, wrote the researchers.

Writing on the course of the disease, the team explained that it is different from other conditions such as pneumonia, influenza, and sepsis. They added that most patients with severe covid-19 develop a picture of “pneumonitis, profound hypoxia, and systemic inflammation affecting multiple organs.”

Prognostic tools

Over the last several months researchers around the world have shared their experiences with COVID-19 patients and thus have also developed treatment protocols and tools to assess which of the patients could worsen and need intensive care or ventilation. The authors of this study wrote that these tools, however, have been developed in a small number of patients. Therefore there is a need for a tool that would classify patients according to their risks, which was developed in a large population of patients.

This study aimed at developing and validating such a prognostic and risk stratification tool that could predict the risk of death in the hospital for the patients admitted with COVID-19.

What was done in this study?

This was a prospective observational study performed on a cohort of COVID-19 patients. This was part of the International Severe Acute Respiratory and Emerging Infections Consortium (ISARIC) World Health Organization (WHO) Clinical Characterisation Protocol UK (CCP-UK) study (performed by the ISARIC Coronavirus Clinical Characterisation Consortium—ISARIC-4C). A total of 260 acute care hospitals across England, Scotland, and Wales were part of this study.

Patients with COVID-19 were included between 6 February and 20 May 2020 for the initial model training for the development of the tool. Validation of the model, which was developed initially, was conducted on the next set of COVID-19 patients admitted between 21 May and 29 June 2020. The participants in the cohorts were aged over 18 years and admitted to the hospitals included in the study at least four weeks before the final data collection. The main parameter tested was the mortality of the patients during their stay in the hospital. The authors developed a “pragmatic 4C Mortality Score (where 4C stands for Coronavirus Clinical Characterisation Consortium).”

What was found?

For this study, a total of 35,463 patients (median age 74 years age) were included. Here the mortality rate was 32.2 percent. In the next cohort that was used for validation of the developed tool, 22,361 patients were included. Here the mortality rate was 30.1 percent.

The team wrote that the final 4C Mortality Score comprised of eight variables. These were available for all the patients included in the cohorts. The score range for the participants in the study was between 0 and 21 points. They were as follows:

• Age
• Gender
• Number of comorbidities
• Respiratory rate
• Peripheral oxygen saturation
• Level of consciousness/Glasgow coma scale
• Urea level, and
• C reactive protein

This scoring system was significantly effective in predicting mortality. They wrote that patients who had a score of at least 15 (seen in 19 percent of the participants or 4,158 patients) had 62 percent mortality. Those with a score of 3 or less had a mortality rate of 1 percent. Such low scores were seen in 1,650 patients or 7 percent of participants. The team identified four risk classes.

Conclusions and implications

The researchers thus have developed and validated an easy-to-use risk stratification score based on the commonly available parameters from admitted patients to stratify the patients admitted to hospital with covid-19 into different management groups. The team wrote, “The score should be further validated to determine its applicability in other populations.”