Investigators at the University of Pittsburgh identified 4 sepsis phenotypes that could help pave the way to targeted treatment options for the disease.
Investigators at the University of Pittsburgh Medical Center used machine learning to identify 4 sepsis phenotypes in research aimed at developing targeted therapies for the condition.
The retrospective study, published in the Journal of the American Medication Association, involved more than 60,000 patients, and examined clinical outcomes and frequency of 4 distinct sepsis subtypes—α, β, γ, and δ.
“For over a decade, there have been no major breakthroughs in the treatment of sepsis; the largest improvements we’ve seen involve the enforcing of ‘one-size fits all’ protocols for prompt treatment,” lead author Christopher Seymour, MD, MSc, an associate professor in University of Pittsburgh’s Department of Critical Care Medicine, said in a statement. “But these protocols ignore that sepsis patients are not all the same. For a condition that kills more than 6 million people annually, that’s unacceptable. Hopefully, by seeing sepsis as several distinct conditions with varying clinical characteristics, we can discover and test therapies precisely tailored to the type of sepsis each patient has.”
The results of the study were presented at the American Thoracic Society’s Annual Meeting.
Investigators on the study, dubbed the “Sepsis Endotyping in Emergency Care” (SENECA) project, which was funded by the National Institutes of Health, analyzed 29 clinical variables among patients for whom sepsis was identified within 6 hours of hospital arrival with a computer algorithm determining 4 distinct types of sepsis. These phenotypes, determined with routinely available data, can be identified at the time patients arrive at the emergency department and could help inform treatment, according to the study.
Using data from 3 observational cohorts and 3 randomized clinical trials, the research involved determining phenotypes, understanding the correlation of clinical phenotypes and biological markers with clinical outcomes, and exploring the role phenotypes play in clinical trial outcomes.
The α subtype was the most common and least deadly in the study, affecting 33% of patients and producing a 2% death rate. The β subgroup was seen more among older patients with chronic illnesses and kidney dysfunction and affected less than a third of patients in the study. Also affecting less than a third of patients, the γ phenotype was associated with the δ group, seen among 13% of patients, and was the deadliest with a 32% mortality rate, often involving cardiovascular and liver dysfunction and shock.
In applying their findings to previous clinical trials, the investigators found that therapies targeting treatments to specific sepsis types could affect outcomes of treatment. They noted that early goal-directed therapy was found to be beneficial among α sepsis patients but detrimental to those in the δ group.
“The next step is to do the same for sepsis that we have for cancer—find therapies that apply to the specific types of sepsis and then design new clinical trials to test them,” senior author Derek Angus, MD, MPH, professor and chair of the Department of Critical Care Medicine, said in the statement.