New forecasting device predicts the necessity for intensive care items for COVID-19 sufferers
Researchers in the UK have developed a forecasting tool that accurately predicts whether patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) – the pathogen causing 2019 coronavirus disease (COVID-19) – will need to be admitted to the intensive care unit ( ICU), die or survive without escalating to the ICU.
"We developed a dynamic risk score to predict an escalation to the ICU or death within the next 24 hours," says Timothy Card and colleagues from the NHS Trust at Nottingham University Hospitals and the University of Nottingham.
The researchers say the tool differentiated well between patients who would or would not need to be admitted to the intensive care unit (or would die), and that it was better at predicting those needs than current forecasting tools.
The risk assessments currently in use generally do not take into account the dynamic changes in disease severity daily during the hospital admission period, the researchers say.
"We have shown that including daily measurements of clinical observations and blood tests improves the accuracy of predicting both prognosis and resource needs in secondary care patients with SARS-CoV-2," they write.
When validated in other populations, the results suggest that such a tool could act as a warning that an escalation of care and certain resources in the ICU will be required.
A pre-print version of the paper is available on the medRxiv * server while the article is being peer-reviewed.
The challenges of health care
Throughout 2020, the COVID-19 pandemic put an unprecedented burden on health services and nearly collapsed some systems.
The need to divert resources has likely increased the risk of death from other diseases, says Card and the team. As the pandemic continues to spread, limited resources need to be re-focused on the seriously ill while trying to maintain care for patients with other health problems.
A number of forecast and prioritization values were developed during the first wave of the pandemic.
"Ideal grading systems would allow safe and early discharge of people who are unlikely to require ongoing hospital care, while allowing immediate escalation of care for those with worsening diseases," say the researchers.
The scores currently in use are generally based on clinical and laboratory parameters measured at a single point in time (usually hospitalization). However, clinical decisions regarding escalation of care need to be made throughout the course of the disease.
Some scores are designed for more dynamic use as the disease progresses, but they are not disease-specific, say Elliott and colleagues.
"However, it is to be expected that a simple assessment, which should be both dynamic and optimized for SARS-CoV-2, will perform better, and such a rating system would be of great value as the degree of disease rises again," they write.
What did the researchers do?
The team conducted a retrospective observational study of all patients with confirmed SARS-CoV-2 infection who were enrolled in the NHS Trust of Nottingham University Hospitals (NUH) between February 1 and November 30 of this year (2020).
The patients (n = 2,964) were divided into a first wave group (those who were admitted by June 30; n = 1,374) and a second wave validation group (those who were admitted afterwards; n = 1,590).
Daily status of patients from the day the COVID diagnosis was suspected
The NUH's electronic records contain comprehensive socio-demographic, clinical and laboratory variables, including any measurements recorded throughout the licensing period. Complete information was also available for care escalation, death, or for 30 days after discharge from hospital.
By linking this information with the basic data at the presentation, the researchers were able to retrospectively analyze the performance of the scores over the entire approval period.
"We have therefore decided to develop a really dynamic and SARS-CoV-2-specific score," they write.
The model accurately predicted the need for intensive care units
In the first wave group, 593 patients were eligible for escalation in the ICU, and in the validation group, 958 were eligible for ICU admission.
The model was able to predict with good precision the daily need for admission, death, or survival in the ICU without escalating care during the admission period. In addition, the tool predicted this daily forecast better than previously set values.
In the validation group, the score showed excellent discrimination but had to be recalibrated as it overestimated escalation and death.
"This will likely reflect the change in demographics and clinical practice between the first and second waves in the UK as escalation practice changed and the use of steroids in patient care introduced," the team explains.
What did the researchers conclude from this?
The researchers say the study showed that including daily measurements of clinical observations and blood tests improved the accuracy of predicting prognosis and resource needs in secondary care patients with SARS-CoV-2.
"The clinical application of such a dynamic score could be used to prompt a clinical review to ensure timely escalation of care and to predict the need to increase or re-use critical care capacity at the operational level in hospitals," concludes the team.
* Important NOTE
medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be considered conclusive, guide clinical practice / health-related behavior, or treated as established information.