Young People Hospitalized With COVID-19 Face Substantial Adverse Outcomes
More than 1 in 5 hospitalized patients between ages 18 and 34 required intensive care
While older age is widely recognized as a risk factor for increased morbidity and mortality due to COVID-19, younger patients have received less attention as a population vulnerable to adverse clinical outcomes. Researchers from Brigham and Women’s Hospital analyzed records from 419 hospitals using the Premier Healthcare Database to study the clinical trajectories of 3,222 hospitalized COVID-19 patients aged 18-34. Findings were published as a research letter in JAMA Internal Medicine. Researchers found that over one-fifth of the patients (21 percent) required intensive care, 10 percent required mechanical ventilation and 2.7 percent died. For comparison, the team wrote, the death rate of those in the same age group hospitalized with heart attacks is approximately half of that figure.
“There was a significant rate of adverse outcomes,” said Jonathan Cunningham, MD, a Cardiovascular Medicine fellow at the Brigham and first author on the letter. “Even though a 2.7 percent death rate is lower than for older patients, it’s high for young people who typically do well even when hospitalized for other conditions.”
Another striking observation for the researchers was that 57 percent of the young people hospitalized for COVID-19 were Black or Hispanic, a finding consistent with other reports about the disproportionate burden the disease has had on these demographics.
Individuals with cardiovascular risk factors were also over-represented among the young people hospitalized: 36.8 percent and 24.5 percent of patients had obesity and morbid obesity, respectively; 18.2 percent of patients had diabetes and 16.1 percent had hypertension. The researchers found that patients who presented these comorbidities were also more likely to experience adverse outcomes. Patients with morbid obesity, for example, comprised 41 percent of the hospitalized young adults who died or required mechanical ventilation. For individuals with more than one of these conditions, risks for adverse outcomes were comparable to the risks faced by middle-aged adults, aged 35-64, who had none of these conditions, as observed in a study of 8,862 members of this population.
The researchers stress that the dataset, which relies on hospital administrative claims, only lends insight into the adverse outcomes of hospitalized young people.
“We know nothing about the total denominator of patients who got an infection,” said corresponding author Scott Solomon, MD, director of noninvasive cardiology in the Division of Cardiovascular Medicine at the Brigham. “We think the vast majority of people in this age range have self-limited disease and don’t require hospitalization. But if you do, the risks are really substantial.”
There was no funding organization for this study. Cunningham reported grants from the National Heart, Lung, and Blood Institute (T32HL094301) during the conduct of the study. Solomon reported grants from industry outside of the submitted work. A full list of disclosures are available in the paper.
Paper cited: Cunningham, JW et al. “Clinical Outcomes in Young US Adults Hospitalized With COVID-19” The Journal of the American Medical Association Internal Medicine DOI: 10.1001/jamainternmed.2020.5313
Study Provides Additional Support for Use of New Class of Diabetes Drugs
Clinical trial finds that ertugliflozin, an SGLT2 inhibitor for patients with diabetes, demonstrated non-inferiority on the rate of cardiovascular death, heart attack or stroke compared to placebo
A new study led by a cardiologist from Brigham and Women’s Hospital has assessed the cardiovascular and renal outcomes for ertugliflozin, an SGLT2 inhibitor prescribed for patients with type 2 diabetes to help them control blood sugar levels. The Evaluation of Ertugliflozin Efficacy and Safety Cardiovascular Outcomes Trial (VERTIS CV) found that the drug had a safety profile similar to that of other SGLT2 inhibitors and did not increase risk of major adverse events compared to the placebo. The results did not show a statistically significant benefit, but, taken together with other recent studies of SGLT2 inhibitors, the study results add to a growing body of evidence that supports guidelines for using this class of drugs to help prevent adverse cardiovascular outcomes. The findings of their study were published in the New England Journal of Medicine.
“This class of medications has turned out to be a huge win for patients with benefits beyond blood glucose control,” said Christopher Cannon, MD, a cardiologist at the Brigham. “Originally, the Food and Drug Administration had requested analyses of the safety of these medications, but studies have found that rather than causing harm, SGLT2 inhibitors show beneficial effects, lowering risk of adverse cardiovascular and renal outcomes.”
Type 2 diabetes can lead to heart failure hospitalization and renal disease progression, with adult type 2 diabetic patients and their clinicians often navigating cardiovascular and renal concerns while working to control blood sugar levels. Recent studies of other SGLT2 inhibitors have found that they may provide a benefit to both renal and cardiovascular health.
VERTIS-CV relied on an event-driven, noninferiority structure, which was revised in the wake of a positive trial involving another drug in the class. In light of the positive outcomes of that EMPA-REG trial, the VERTIS-CV team doubled its sample size and reduced the time left in the trial from five years to an average of three years. Of the 8,238 patients enrolled in the trial, the average age was 64.4 and average length of type 2 diabetes diagnosis was 13 years.
Previous studies have established ertugliflozin as an effective medication for controlling blood sugar levels. VERTIS-CV assessed the drug’s cardiovascular safety. Among patients with type 2 diabetes and atherosclerotic cardiovascular disease, ertugliflozin was non-inferior to placebo for the composite of cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke — an endpoint known as MACE. Overall, major adverse cardiovascular outcomes occurred in about 12 percent of patients in both the ertugliflozin and placebo groups. A combination of both cardiovascular death or hospitalization for heart failure occurred in about 8 percent and 9 percent in the ertugliflozin and placebo groups, respectively. A secondary endpoint of hospitalization for heart failure showed a 30 percent lower rate with ertugliflozin.
Ertugliflozin is the fourth drug in this class to be tested on such a large scale and demonstrate noninferiority against a placebo. The three other major SGLT2 drug trials — testing dapagliflozin, canagliflozin, and empagliflozin — produced significant benefits across different endpoints.
The American Diabetes Association guidelines established in 2019 recommend the use of SGLT2 inhibitors such as ertugliflozin in type 2 diabetes patients as an additional agent for lowering blood sugar and for lowering risk of cardiovascular and renal events in patients predisposed to these complications. Cannon describes his team’s results as supportive of these guidelines.
“The guidelines, if anything, were a little bit ahead of their time and are spot on,” said Cannon.
“These data reaffirm the guidelines, and now it’s on us as clinicians to more completely follow the guidelines.”
Cannon, C.P. et al. “Ertugliflozin and Cardiovascular Outcomes in Type 2 Diabetes” New England Journal of Medicine DOI: 10.1056/NEJMoa2004967
Artificial Intelligence System Developed to Help Better Select Embryos for Implantation
System trained to detect highest quality in-vitro fertilization embryos outperformed trained embryologists
For many people who are struggling to conceive, in-vitro fertilization (IVF) can offer a life-changing solution. But the average success rate for IVF is only about 30 percent. Investigators from Brigham and Women’s Hospital and Massachusetts General Hospital are developing an artificial intelligence system with the goal of improving IVF success by helping embryologists objectively select embryos most likely to result in a healthy birth. Using thousands of embryo image examples and deep-learning artificial intelligence (AI), the team developed a system that was able to differentiate and identify embryos with the highest potential for success significantly better than 15 experienced embryologists from five different fertility centers across the United States. Results of their study are published in eLife.
“We believe that these systems will benefit clinical embryologists and patients,” said corresponding author Hadi Shafiee, PhD, of the Division of Engineering in Medicine at the Brigham. “A major challenge in the field is deciding on the embryos that need to be transferred during IVF. Our system has tremendous potential to improve clinical decision making and access to care.”
Currently, the tools available to embryologists are limited and expensive, and most embryologists must rely on their observational skills and expertise. Shafiee and colleagues are developing an assistive tool that can evaluate images captured using microscopes traditionally available at fertility centers.
“There is so much at stake for our patients with each IVF cycle. Embryologists make dozens of critical decisions that impact the success of a patient cycle. With assistance from our AI system, embryologists will be able to select the embryo that will result in a successful pregnancy better than ever before,” said co-lead author Charles Bormann, PhD, MGH IVF Laboratory director.
The team trained the AI system using images of embryos captured at 113 hours post-insemination. Among 742 embryos, the AI system was 90 percent accurate in choosing the most high-quality embryos.
The investigators further assessed the AI system’s ability to distinguish among high-quality embryos with the normal number of human chromosomes and compared the system’s performance to that of trained embryologists. The system performed with an accuracy of approximately 75 percent while the embryologists performed with an average accuracy of 67 percent.
The authors note that in its current stage, this system is intended to act only as an assistive tool for embryologists to make judgments during embryo selection.
“Our approach has shown the potential of AI systems to be used in aiding embryologists to select the embryo with the highest implantation potential, especially amongst high-quality embryos,” said Manoj Kumar Kanakasabapathy, one of the co-lead authors.
Funding for this work was provided by Brigham and Women’s Hospital and Partners Healthcare (Precision Medicine Developmental Grant and Innovation Discovery Grant), and National Institutes of Health (R01AI138800).
Paper cited: Bormann, CL et al. “Performance of a deep learning based neural network in the selection of human blastocysts for implantation” eLife DOI: 10.7554/e.life.55301