We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
ARAB HEALTH - INFORMA

Download Mobile App





Novel Calculators Identify Hospitalized COVID-19 Patients at Greatest Risk of Requiring Mechanical Ventilation or of In-Hospital Death

By HospiMedica International staff writers
Posted on 01 Mar 2021
Print article
Illustration
Illustration
Two novel calculators for predicting which patients admitted to the hospital with COVID-19 are at greatest risk of requiring mechanical ventilation or of in-hospital death have been developed and validated by researchers.

In a new study, researchers at the Massachusetts General Hospital (MGH; Boston, MA, USA) have described how these models could enable clinicians to better stratify risk in COVID-infected patients to optimize care and resource utilization in hospitals faced with ICU capacity constraints. The research team compiled clinical information from 1,042 patients confirmed with COVID-19 who were admitted to five hospitals in the Mass General Brigham health care system during the first three months of the pandemic. Significant associations between clinical, hemodynamic, and laboratory data and the endpoints of in-hospital mortality and mechanical ventilation provided the building blocks for two separate risk stratification models known as the VICE (Ventilation in COVID Estimate) and DICE (Death in COVID Estimate) scores.

Predictive VICE factors uncovered by researchers were diabetes mellitus, oxygen saturation of the blood, and two inflammatory markers: C-reactive protein and lactate dehydrogenase. DICE factors predictive of mortality were age, male sex, coronary artery disease, diabetes mellitus, body mass index, platelet count, and a variety of inflammatory and infectious markers. Researchers were surprised to learn that age was not a significant predictor of whether a patient would require mechanical ventilation. Indeed, other than the youngest patients, the percentage of hospitalized COVID-19 patients requiring mechanical ventilation was similar in each decade of life, though there was a clear correlation between age and risk of in-hospital death, with only 15% survival in patients over 84 requiring mechanical ventilation. Nor was age a predictor of how long a patient would need ventilation. The study found that 59% of patients in the 25-to-34 age group required more than 14 days of ventilation, similar to older age groups.

Another significant finding from the study was that regular use of statins was associated with reduced in-hospital mortality, underscoring the strong links among COVID-19, cardiovascular disease, and inflammation. In another encouraging finding, researchers did not observe any relationship between minority ethnic background of COVID-19 patients and worse clinical outcomes after adjusting for clinical risk.

"By inputting clinical values into these online calculators, physicians can risk-stratify COVID-19 patients upon admission and determine which ones may need the most intensive care and management," says lead author Christopher Nicholson, PhD, a senior research fellow with the MGH Cardiovascular Research Center. "These risk scores allow them to predict with greater than 80% accuracy - higher than established models - patient outcomes, as well as demand for mechanical ventilators and ICU beds, which could impact end-of-life decisions involving COVID-19 patients."

Related Links:
Massachusetts General Hospital

Gold Member
12-Channel ECG
CM1200B
Gold Member
Real-Time Diagnostics Onscreen Viewer
GEMweb Live
New
Diagnostic Ultrasound System
MS1700C
New
Hospital Data Analytics Software
OR Companion

Print article

Channels

Surgical Techniques

view channel
Image: The surgical team and the Edge Multi-Port Endoscopic Surgical Robot MP1000 surgical system (Photo courtesy of Wei Zhang)

Endoscopic Surgical System Enables Remote Robot-Assisted Laparoscopic Hysterectomy

Telemedicine enables patients in remote areas to access consultations and treatments, overcoming challenges related to the uneven distribution and availability of medical resources. However, the execution... Read more

Patient Care

view channel
Image: The portable biosensor platform uses printed electrochemical sensors for the rapid, selective detection of Staphylococcus aureus (Photo courtesy of AIMPLAS)

Portable Biosensor Platform to Reduce Hospital-Acquired Infections

Approximately 4 million patients in the European Union acquire healthcare-associated infections (HAIs) or nosocomial infections each year, with around 37,000 deaths directly resulting from these infections,... Read more

Health IT

view channel
Image: First ever institution-specific model provides significant performance advantage over current population-derived models (Photo courtesy of Mount Sinai)

Machine Learning Model Improves Mortality Risk Prediction for Cardiac Surgery Patients

Machine learning algorithms have been deployed to create predictive models in various medical fields, with some demonstrating improved outcomes compared to their standard-of-care counterparts.... Read more

Point of Care

view channel
Image: The acoustic pipette uses sound waves to test for biomarkers in blood (Photo courtesy of Patrick Campbell/CU Boulder)

Handheld, Sound-Based Diagnostic System Delivers Bedside Blood Test Results in An Hour

Patients who go to a doctor for a blood test often have to contend with a needle and syringe, followed by a long wait—sometimes hours or even days—for lab results. Scientists have been working hard to... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.