New Model to Predict the Progression of Covid-19 Could Ease Healthcare System Burden
A new mathematical model aims at reliably identifying patients who are at a lower risk of deterioration due to Covid-19.
A mathematical model aimed at reliably identifying patients at lower risk of deterioration due to Covid-19 was developed as part of a collaboration effort between the MedUni Vienna, the Favoriten Clinic, the Innsbruck Medical University, the Johannes Kepler University Linz, and the Karolinska Institute in Stockholm. This means certain patients could be discharged from hospitals earlier than is currently the case, resulting in alleviating the burden on the healthcare system until a majority of the population can be vaccinated.
A key issue during the Covid-19 pandemic is to be able to provide high-quality, individual patient care while simultaneously preventing the healthcare system from collapsing under the strain of high patient numbers. Sars-Cov-2 is unique in that patients can deteriorate drastically only after seven to ten days of coming down with the virus. In order to take this phase into account, patients are kept in the hospital longer, even if experiencing a comparatively mild form of the illness. Treating Covid-19 patients in this way not only ties up resources and raises the risk of infection to the staff, hospital beds urgently needed for other patients are occupied. Alice Assinger, MedUni Vienna's Institute of Vascular Biology and Thrombosis Research, remarked: "Although we are continually learning more about the virus every day, we still don’t have reliable decision-making tools to allow us to discharge some patients earlier."
A team of scientists at the MedUni Vienna/Center for Physiology and Pharmacology led by Alice Assinger has now developed a model that has a high degree of accuracy when it comes to predicting the illness’ progression in regard to patients hospitalized with the Covid-19 virus. The model’s special feature is that it is based exclusively on parameters that have already been collected during clinical routines, meaning additional, technically complex laboratory determinations are not needed.
By entering collected parameter values into an openly accessible online calculator, hospital physicians now have an important tool at their disposal that can play a key role in discharging patients. Developed by Stefan Heber (Institute of Physiology at the MedUni in Vienna), the mathematical model is based on repeated measurements of the inflammation "C-reactive protein" marker which reflects kidney functions, and the "creatinine" marker, which reflects the number of blood platelets.
Based on the way these parameters develop during the first four days of hospitalization and together with additional factors that include the patient's age and the patient’s body temperature at the time of hospital admission, physicians can predict the progression of the illness with a high degree of accuracy. According to Heber, "This works regardless of how long symptoms lasted before being admitted to the hospital." Data from 441 patients at three different centers was used to develop this ACCP tool (Age+C-reactive protein+Creatinine+Platelet) and the developed model was validated using data provided by 553 patients in three other independent cohorts.
Stefan Heber, the study’s first author, added: "It was important for us to make the ACCP tool available for routine clinical use as soon as possible. This tool will hopefully help alleviate strains on the Austrian healthcare system until the majority of the population can be vaccinated."
This paper is part of the ACOVACT Study at the Medical University of Vienna and is financially supported by the Austrian Federal Ministry of Education, Science and Research, the Medical-Scientific Fund by the Mayor of Vienna (COVID024), and the Austrian Science Fund (P32064).