Sepsis is a huge problem worldwide: There are about 20 million cases of sepsis, leading to more than 5 million deaths annually, with much of the burden in low- and middle-income countries (LMICs) such as Vietnam.
There is currently no reference standard that allows easy, accurate diagnosis of sepsis. Louise Thwaites, Duong Bich Thuy and other researchers from OUCRU have been contributing to a collaborative project across 10 countries to test the predictability of a clinical scoring method which could be used to identify patients with sepsis. The study, the Sepsis Assessment and Identification in Low Resource Settings (SAILORS) collaboration, was led by Dr. Kristina E. Rudd, MD, MPH, at the University of Washington (Seattle, Washington, USA). The results of this study have been published in an article in JAMA this week which is available as an open-access publication.
In 2016, the Sepsis-3 Task Force proposed that, for patients with suspected infection outside of the intensive care unit (ICU), a combination of respiratory rate, mental status, and systolic blood pressure, named ‘quick’ Sequential (Sepsis-related) Organ Failure Assessment (qSOFA), could be used to help identify patients with sepsis. This study was a test of the predictive validity of qSOFA, which is one of the main ways to identify patients with sepsis. Identification of patients with sepsis in an accurate and rapid manner is important, as studies show that prompt and appropriate treatment (with antibiotics, organ support, etc) within the first hour is critical to improve outcomes and reduce mortality.
This study is the largest and most robust study of the performance of the qSOFA in LMICs to date. This is extremely important, as the patients, pathogens, and clinical capacity to manage sepsis differ considerably between high-income and LMIC settings and, as pointed out above, the majority of sepsis cases occur in LMICs. The study found that for hospitalized adults with suspected infection, a qSOFA score greater than or equal to 2 was significantly associated with increased likelihood of excess hospital death compared with a lower score. The study also found that a moderate qSOFA score of just one point also is associated with increased risk of excess mortality compared to a score of zero. This means that the aSOFA score may help identify patients at higher risk for excess hospital mortality among adults with suspected infection in LMICs.
The 10 countries represented in the 9 data sets in this study are: Bangladesh, Haiti, India, Indonesia, Myanmar, Rwanda, Sierra Leone, Sri Lanka, Thailand, and Vietnam. The success of this project is the result of incredible international collaboration between the researchers who performed the original 9 studies and contributed their data for analysis in the study.
