A medical worker places a swab in a vial while testing the homeless for COVID-19 through the Miami-Dade County Homeless Trust in Miami in April 2020.

A medical worker places a swab in a vial while testing the homeless for COVID-19 through the Miami-Dade County Homeless Trust in Miami in April 2020. Lynne Sladky/AP file photo

Machine Learning System Predicts Severe COVID-19

An advanced machine learning system can accurately predict the risk of a patient's COVID-19 advancing to severe disease or death, say researchers.

An advanced machine-learning system can accurately predict if a patient’s bout with COVID-19 will become severe or fatal and relay its findings to clinicians.

Clinicians often learn how to recognize patterns in COVID-19 cases after they treat many patients with it. Machine-learning systems promise to enhance that ability, recognizing more complex patterns in large numbers of people with COVID-19 and using that insight to predict the course of an individual patient’s case.

However, physicians sworn to “do no harm” may be reluctant to base treatment and care strategies for their most seriously ill patients on difficult-to-use or hard-to-interpret machine-learning algorithms. The new system offers findings in an easily understandable form.

The prognostic tool, known as the Severe COVID-19 Adaptive Risk Predictor (SCARP), offers findings in an easily understandable form and can help define the one-day and seven-day risk of a patient hospitalized with COVID-19 developing a more severe form of the disease or dying from it.

As reported in a paper in the Annals of Internal Medicine, SCARP asks for a minimal amount of input to give an accurate prediction, making it fast, simple to use, and reliable for basing treatment and care decisions.

“SCARP was designed to provide clinicians with a predictive tool that is interactive and adaptive, enabling real-time clinical variables to be entered at a patient’s bedside,” says senior author Matthew Robinson, assistant professor of medicine at the Johns Hopkins University School of Medicine.

“By yielding a personalized clinical prediction of developing severe disease or death in the next day and week, and at any point in the first two weeks of hospitalization, SCARP will enable a medical team to make more informed decisions about how best to treat each patient with COVID-19.”

The brains of SCARP is a predictive algorithm called Random Forests for Survival, Longitudinal and Multivariate Data (RF-SLAM), described in a 2019 paper by its creators, Johns Hopkins Medicine researchers Shannon Wongvibulsin, Katherine Wu, and Scott Zeger.

Unlike past clinical prediction methods that base a patient’s risk score on their condition at the time they enter the hospital, RF-SLAM adapts to the latest available patient information and considers the changes in those measurements over time.

To make this dynamic analysis possible, RF-SLAM divides a patient’s hospital stay into six-hour windows. Data collected during those time spans are then evaluated by the algorithm’s “random forests” of approximately 1,000 “decision trees” that operate as an ensemble. This enables SCARP to give a more accurate prediction of an outcome than each individual decision tree could do on its own.

“The same way that individual stocks and bonds perform better as a portfolio—with the overall value staying strong as individual items balance each other’s rises and falls in price—the trees as a group create a flexible and adaptable forest that protect each other from individual errors,” Robinson says. “So, even if some trees predict incorrectly, many others will get it right and move the group in the correct direction.”

Most machine-learning systems used to make clinical prediction can only consider static data at a single point in time. “RF-SLAM enables us to be nimble and predict the future at any point,” Robinson says.

To demonstrate SCARP’s ability to predict severe COVID-19 cases or deaths from the disease, Robinson and his colleagues used a clinical registry with data about patients hospitalized with COVID-19 between March and December 2020, at five centers within the Johns Hopkins Health System.

The patient information available included demographics, other medical conditions, and behavioral risk factors, along more than 100 variables over time, such as vital signs, blood counts, metabolic profiles, respiratory rates, and the amount of supplemental oxygen needed.

Among 3,163 patients admitted with moderate COVID-19 during this time, 228 (7%) became severely ill or died within 24 hours; an additional 355 (11%) became severely ill or died within the first week. Data also were collected on the numbers who developed severe COVID-19 or died on any day within the 14 days following admission.

Overall, SCARP’s one-day risk predictions for progression to severe COVID-19 or death were 89% accurate, while the seven-day risk predictions for both outcomes were 83% accurate.

Robinson says he plans further SCARP trials to validate its performance on a large scale using national patient databases. Based on the results of the first study, Johns Hopkins Medicine has already incorporated a version of SCARP into the electronic medical record system at all five of its hospitals in the Maryland and Washington, DC, area.

“Our successful demonstration shows that SCARP has the potential to be an easy-to-use, highly accurate, and clinically meaningful risk calculator for patients hospitalized with COVID-19,” says Robinson.

“Having a solid grasp of a patient’s real-time risk of progressing to severe disease or death within the next 24 hours and next week could help health care providers make more informed choices and treatment decisions for their patients with COVID-19 as they get sicker.”

Source: Johns Hopkins University

This article was originally published in Futurity. Edits have been made to this republication. It has been republished under the Attribution 4.0 International license.

X
This website uses cookies to enhance user experience and to analyze performance and traffic on our website. We also share information about your use of our site with our social media, advertising and analytics partners. Learn More / Do Not Sell My Personal Information
Accept Cookies
X
Cookie Preferences Cookie List

Do Not Sell My Personal Information

When you visit our website, we store cookies on your browser to collect information. The information collected might relate to you, your preferences or your device, and is mostly used to make the site work as you expect it to and to provide a more personalized web experience. However, you can choose not to allow certain types of cookies, which may impact your experience of the site and the services we are able to offer. Click on the different category headings to find out more and change our default settings according to your preference. You cannot opt-out of our First Party Strictly Necessary Cookies as they are deployed in order to ensure the proper functioning of our website (such as prompting the cookie banner and remembering your settings, to log into your account, to redirect you when you log out, etc.). For more information about the First and Third Party Cookies used please follow this link.

Allow All Cookies

Manage Consent Preferences

Strictly Necessary Cookies - Always Active

We do not allow you to opt-out of our certain cookies, as they are necessary to ensure the proper functioning of our website (such as prompting our cookie banner and remembering your privacy choices) and/or to monitor site performance. These cookies are not used in a way that constitutes a “sale” of your data under the CCPA. You can set your browser to block or alert you about these cookies, but some parts of the site will not work as intended if you do so. You can usually find these settings in the Options or Preferences menu of your browser. Visit www.allaboutcookies.org to learn more.

Sale of Personal Data, Targeting & Social Media Cookies

Under the California Consumer Privacy Act, you have the right to opt-out of the sale of your personal information to third parties. These cookies collect information for analytics and to personalize your experience with targeted ads. You may exercise your right to opt out of the sale of personal information by using this toggle switch. If you opt out we will not be able to offer you personalised ads and will not hand over your personal information to any third parties. Additionally, you may contact our legal department for further clarification about your rights as a California consumer by using this Exercise My Rights link

If you have enabled privacy controls on your browser (such as a plugin), we have to take that as a valid request to opt-out. Therefore we would not be able to track your activity through the web. This may affect our ability to personalize ads according to your preferences.

Targeting cookies may be set through our site by our advertising partners. They may be used by those companies to build a profile of your interests and show you relevant adverts on other sites. They do not store directly personal information, but are based on uniquely identifying your browser and internet device. If you do not allow these cookies, you will experience less targeted advertising.

Social media cookies are set by a range of social media services that we have added to the site to enable you to share our content with your friends and networks. They are capable of tracking your browser across other sites and building up a profile of your interests. This may impact the content and messages you see on other websites you visit. If you do not allow these cookies you may not be able to use or see these sharing tools.

If you want to opt out of all of our lead reports and lists, please submit a privacy request at our Do Not Sell page.

Save Settings
Cookie Preferences Cookie List

Cookie List

A cookie is a small piece of data (text file) that a website – when visited by a user – asks your browser to store on your device in order to remember information about you, such as your language preference or login information. Those cookies are set by us and called first-party cookies. We also use third-party cookies – which are cookies from a domain different than the domain of the website you are visiting – for our advertising and marketing efforts. More specifically, we use cookies and other tracking technologies for the following purposes:

Strictly Necessary Cookies

We do not allow you to opt-out of our certain cookies, as they are necessary to ensure the proper functioning of our website (such as prompting our cookie banner and remembering your privacy choices) and/or to monitor site performance. These cookies are not used in a way that constitutes a “sale” of your data under the CCPA. You can set your browser to block or alert you about these cookies, but some parts of the site will not work as intended if you do so. You can usually find these settings in the Options or Preferences menu of your browser. Visit www.allaboutcookies.org to learn more.

Functional Cookies

We do not allow you to opt-out of our certain cookies, as they are necessary to ensure the proper functioning of our website (such as prompting our cookie banner and remembering your privacy choices) and/or to monitor site performance. These cookies are not used in a way that constitutes a “sale” of your data under the CCPA. You can set your browser to block or alert you about these cookies, but some parts of the site will not work as intended if you do so. You can usually find these settings in the Options or Preferences menu of your browser. Visit www.allaboutcookies.org to learn more.

Performance Cookies

We do not allow you to opt-out of our certain cookies, as they are necessary to ensure the proper functioning of our website (such as prompting our cookie banner and remembering your privacy choices) and/or to monitor site performance. These cookies are not used in a way that constitutes a “sale” of your data under the CCPA. You can set your browser to block or alert you about these cookies, but some parts of the site will not work as intended if you do so. You can usually find these settings in the Options or Preferences menu of your browser. Visit www.allaboutcookies.org to learn more.

Sale of Personal Data

We also use cookies to personalize your experience on our websites, including by determining the most relevant content and advertisements to show you, and to monitor site traffic and performance, so that we may improve our websites and your experience. You may opt out of our use of such cookies (and the associated “sale” of your Personal Information) by using this toggle switch. You will still see some advertising, regardless of your selection. Because we do not track you across different devices, browsers and GEMG properties, your selection will take effect only on this browser, this device and this website.

Social Media Cookies

We also use cookies to personalize your experience on our websites, including by determining the most relevant content and advertisements to show you, and to monitor site traffic and performance, so that we may improve our websites and your experience. You may opt out of our use of such cookies (and the associated “sale” of your Personal Information) by using this toggle switch. You will still see some advertising, regardless of your selection. Because we do not track you across different devices, browsers and GEMG properties, your selection will take effect only on this browser, this device and this website.

Targeting Cookies

We also use cookies to personalize your experience on our websites, including by determining the most relevant content and advertisements to show you, and to monitor site traffic and performance, so that we may improve our websites and your experience. You may opt out of our use of such cookies (and the associated “sale” of your Personal Information) by using this toggle switch. You will still see some advertising, regardless of your selection. Because we do not track you across different devices, browsers and GEMG properties, your selection will take effect only on this browser, this device and this website.