Related Experiment Video
Updated: Dec 8, 2025
Trajectory Data Analyses for Pedestrian Space-time Activity Study
Published on: February 25, 2013
Patient Trajectories Among Persons Hospitalized for COVID-19 : A Cohort Study
Brian T Garibaldi1, Jacob Fiksel2, John Muschelli2
1Johns Hopkins University School of Medicine, Baltimore, Maryland (B.T.G., M.L.R., P.N., J.H.G., H.M., T.M.N., B.S.K., P.M.H., R.B., D.R.T., M.G.B., A.R., A.G.).
Insights
Predicting severe coronavirus disease 2019 (COVID-19) progression is crucial. Demographic and clinical factors at admission can identify high-risk patients early, aiding clinical decisions and resource allocation.
Area of Science:
- Infectious Diseases
- Public Health
- Clinical Medicine
Background:
- Risk factors for severe coronavirus disease 2019 (COVID-19) progression in U.S. patient cohorts remain underexplored.
- Identifying predictors of severe COVID-19 or death is essential for timely intervention.
Purpose of the Study:
- To identify factors present at hospital admission that predict severe COVID-19 disease or death.
- To develop a predictive model for in-hospital disease progression.
Main Methods:
- Retrospective cohort analysis of 832 COVID-19 admissions across five hospitals.
- Patient outcomes were categorized using the World Health Organization COVID-19 disease severity scale.
- Analysis included demographic and clinical variables, laboratory results, and vital signs.
Main Results:
- A significant proportion of patients admitted with mild to moderate COVID-19 progressed to severe disease or death within days.
- Factors including age, nursing home residence, comorbidities, obesity, respiratory symptoms, vital signs, and specific laboratory values (lymphocyte count, albumin, troponin, CRP) were associated with progression.
- A predictive model using admission data demonstrated strong performance (AUC 0.79-0.85) for forecasting in-hospital disease progression.
Conclusions:
- A combination of demographic and clinical factors at admission strongly predicts severe COVID-19 outcomes and early onset.
- The COVID-19 Inpatient Risk Calculator (CIRC) can inform clinical management and resource allocation decisions for hospitalized patients.
Background:
Risk factors for progression of coronavirus disease 2019 (COVID-19) to severe disease or death are underexplored in U.S. cohorts.
Objective:
To determine the factors on hospital admission that are predictive of severe disease or death from COVID-19.
Design:
Retrospective cohort analysis.
Setting:
Five hospitals in the Maryland and Washington, DC, area.
Patients:
832 consecutive COVID-19 admissions from 4 March to 24 April 2020, with follow-up through 27 June 2020.
Measurements:
Patient trajectories and outcomes, categorized by using the World Health Organization COVID-19 disease severity scale. Primary outcomes were death and a composite of severe disease or death.
Results:
Median patient age was 64 years (range, 1 to 108 years); 47% were women, 40% were Black, 16% were Latinx, and 21% were nursing home residents. Among all patients, 131 (16%) died and 694 (83%) were discharged (523 [63%] had mild to moderate disease and 171 [20%] had severe disease). Of deaths, 66 (50%) were nursing home residents. Of 787 patients admitted with mild to moderate disease, 302 (38%) progressed to severe disease or death: 181 (60%) by day 2 and 238 (79%) by day 4. Patients had markedly different probabilities of disease progression on the basis of age, nursing home residence, comorbid conditions, obesity, respiratory symptoms, respiratory rate, fever, absolute lymphocyte count, hypoalbuminemia, troponin level, and C-reactive protein level and the interactions among these factors. Using only factors present on admission, a model to predict in-hospital disease progression had an area under the curve of 0.85, 0.79, and 0.79 at days 2, 4, and 7, respectively.
Limitation:
The study was done in a single health care system.
Conclusion:
A combination of demographic and clinical variables is strongly associated with severe COVID-19 disease or death and their early onset. The COVID-19 Inpatient Risk Calculator (CIRC), using factors present on admission, can inform clinical and resource allocation decisions.
Primary Funding Source:
Hopkins inHealth and COVID-19 Administrative Supplement for the HHS Region 3 Treatment Center from the Office of the Assistant Secretary for Preparedness and Response.
Related Concept Videos
01:15Bioavailability Study Design: Healthy Subjects Versus Patients
01:26Healthcare Associated Infections I: Iatrogenic, Exogenic and Endogenic
HAIs significantly increase the cost of health care. Extended stays in healthcare institutions, increased disability, increased costs of medications, including specialized antibiotics, and prolonged recovery times add to the patient's expenses and the healthcare institution and funding bodies.
01:30Pneumonia I: Introduction
Risk Factors
Various factors influence the likelihood of developing pneumonia. Age plays a crucial role, with infants, children under two, and individuals over 65 at increased risk due to their...
01:30Pneumonia III: Complications and Assessment
00:59Hospitals-II
Nurses that work in...
01:15Methods of Documentation VI: Case Management Model
For example, a patient with a chronic...