Sepsis, especially septic shock, is a major cause of death affecting millions of individuals around the world (1). As example, one study from two independent cohorts found that nearly 50 percent of all hospital deaths in the United States (US) are related to sepsis (2). Another important study in the US confirmed that sepsis has become the top-ranked diagnosis related to intensive care units (ICUs) admissions among older patients, and this is an impressive fact, considering the US and worldwide population aging (3). Furthermore, an international database analysis showed a global mortality for severe sepsis of 270 per 100,000 person-years between the years 1995 and 2015, with 5.3 million potentially preventable deaths annually (4). Nevertheless, it is important to point out that the term severe sepsis should not be used, since the 2016 definitions of sepsis and septic shock originated from the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) were established (5).
The early implementation of evidence-based therapies, such as fluid resuscitation, source control and appropriate antibiotic therapy, is the cornerstone of sepsis care (1). Therefore, reducing the time to the diagnosis of sepsis and early identification of patients at higher risk of developing septic shock and organ dysfunction are thought to be a critical component to reduce sepsis-related mortality (1,6,7). However, the routinely available tools do not accurately predict who will develop sepsis or, especially, septic shock. Therefore, researchers recently have been searching for tools based on health information technology, such as automated systems of real-time computerized alerts, with promising results (8-10).
Thus, Henry et al. proposed a new algorithm for predicting patients at risk of septic shock, called “Targeted Real-time Early Warning Score” (TREWScore) (11). This score was derived from the analysis of the Multiparameter Intelligent Monitoring in Intensive Care-II Clinical Database (MIMIC-II Clinical Database), containing electronic health records of 16,234 adult patients admitted to medical, surgical or cardiac ICU (12). The TREWScore showed a sensitivity of 85% and specificity of 67% and identified patients with a median lead time of 28.2 hours before septic shock onset, which is enough time for health professionals to implement appropriate therapies and probably improve patient outcome (11,13). It is necessary to emphasize that this score can be programmed into the hospital electronic health records systems, automatically alerting doctors and nurses about ICU patients with high risk for septic shock onset (11).
However, it should be highlighted that having an early warning system and using it to alter clinical practice are two different things. In this aspect, the TREWscore has only been validated as a warning system (11) and, consequently, the researchers will need to determine if it has an impact on clinical care and patient outcome. Another important aspect of this score is that it was built using an electronic health record of patients admitted to the ICU (11); therefore, its clinical use in non-ICU patients (ward or emergency department) also needs to be evaluated.
In summary, the TREWScore can become a very useful tool to alert health professionals about ICU patients at high risk of developing septic shock with an advance of 28 hours before septic shock onset. Thus, health professionals will have enough time to reevaluate patients and their exams to intensify or readdress treatment, very probably improving outcome.
Conflicts of Interest: The authors have no conflicts of interest to declare.
- Dellinger RP, Levy MM, Rhodes A, et al. Surviving Sepsis Campaign: international guidelines for management of severe sepsis and septic shock, 2012. Intensive Care Med 2013;39:165-228. [Crossref] [PubMed]
- Liu V, Escobar GJ, Greene JD, et al. Hospital deaths in patients with sepsis from 2 independent cohorts. JAMA 2014;312:90-2. [Crossref] [PubMed]
- Sjoding MW, Prescott HC, Wunsch H, et al. Longitudinal Changes in ICU Admissions Among Elderly Patients in the United States. Crit Care Med 2016;44:1353-60. [Crossref] [PubMed]
- Fleischmann C, Scherag A, Adhikari NK, et al. Assessment of Global Incidence and Mortality of Hospital-treated Sepsis. Current Estimates and Limitations. Am J Respir Crit Care Med 2016;193:259-72. [Crossref] [PubMed]
- Singer M, Deutschman CS, Seymour CW, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA 2016;315:801-10. [Crossref] [PubMed]
- Cortés-Puch I, Hartog CS. Opening the Debate on the New Sepsis Definition Change Is Not Necessarily Progress: Revision of the Sepsis Definition Should Be Based on New Scientific Insights. Am J Respir Crit Care Med 2016;194:16-8. [Crossref] [PubMed]
- Angus DC. Opening the Debate on the New Sepsis Definition Defining Sepsis: A Case of Bounded Rationality and Fuzzy Thinking? Am J Respir Crit Care Med 2016;194:14-5. [Crossref] [PubMed]
- Sawyer AM, Deal EN, Labelle AJ, et al. Implementation of a real-time computerized sepsis alert in nonintensive care unit patients. Crit Care Med 2011;39:469-73. [Crossref] [PubMed]
- Umscheid CA, Betesh J, VanZandbergen C, et al. Development, implementation, and impact of an automated early warning and response system for sepsis. J Hosp Med 2015;10:26-31. [Crossref] [PubMed]
- Westphal GA, Lino AS. Systematic screening is essential for early diagnosis of severe sepsis and septic shock. Rev Bras Ter Intensiva 2015;27:96-101. [Crossref] [PubMed]
- Henry KE, Hager DN, Pronovost PJ, et al. A targeted real-time early warning score (TREWScore) for septic shock. Sci Transl Med 2015;7:299ra122. [Crossref] [PubMed]
- Saeed M, Villarroel M, Reisner AT, et al. Multiparameter Intelligent Monitoring in Intensive Care II: a public-access intensive care unit database. Crit Care Med 2011;39:952-60. [Crossref] [PubMed]
- Vorwerk C, Loryman B, Coats TJ, et al. Prediction of mortality in adult emergency department patients with sepsis. Emerg Med J 2009;26:254-8. [Crossref] [PubMed]