International study of the prevalence and outcomes of infection in intensive care units

Background: The diagnosis and management of sepsis remain a global health care challenge. Digital technologies have the potential to improve sepsis care.
Objective: The aim of this paper was to systematically review the evidence on the impact of digital alerting systems on sepsis related outcomes.
Methods: The following databases were searched for studies published from April 1964 to February 12, 2019, with no language restriction: EMBASE, MEDLINE, HMIC, PsycINFO, and Cochrane. All full-text reports of studies identified as potentially eligible after title and abstract reviews were obtained for further review. The search was limited to adult inpatients. Relevant articles were hand searched for other studies. Only studies with clear pre- and postalerting phases were included. Primary outcomes were hospital length of stay (LOS) and intensive care LOS, whereas secondary outcomes were time to antibiotics and mortality. Studies based solely on intensive care, case reports, narrative reviews, editorials, and commentaries were excluded. All other trial designs were included. A qualitative assessment and meta-analysis were performed.
Results: This review identified 72 full-text articles. From these, 16 studies met the inclusion criteria and were included in the final analysis. Of these, 8 studies reviewed hospital LOS, 12 reviewed mortality outcomes, 5 studies explored time to antibiotics, and 5 studies investigated intensive care unit (ICU) LOS. Both quantitative and qualitative assessments of the studies were performed. There was evidence of a significant benefit of digital alerting in hospital LOS, which reduced by 1.31 days (P=.014), and ICU LOS, which reduced by 0.766 days (P=.007). There was no significant association between digital alerts and mortality (mean decrease 11.4%; P=.77) or time to antibiotics (mean decrease 126 min; P=.13).
Conclusions: This review highlights that digital alerts can considerably reduce hospital and ICU stay for patients with sepsis. Further studies including randomized controlled trials are necessary to confirm these findings and identify the choice of alerting system according to the patient status and pathological cohort.

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Digital Alerting and Outcomes in Patients With Sepsis: Systematic Review and Meta-Analysis.

The identification of patients with possible sepsis is vitally important because timely recognition and appropriate, effective treatment substantially improves survival. Unlike some other life-threatening conditions (such as myocardial infarction), for which highly accurate diagnostic tests are available, no rapid diagnostic tests are currently available to accurately identify patients with sepsis (or those at high risk of developing sepsis) to help clinicians determine the best course of action. Development of such tests for sepsis will involve consideration of a number of key issues, such as whether sepsis is just one or, rather, multiple entities; whether degrees of having sepsis exist; which test is the gold standard (an accepted benchmark against which similar tests can be compared and diagnostic accuracy assessed); what levels of accuracy are sufficient for use in clinical practice; and which tests based on what markers are the most cost-effective. In the meantime, however, clinicians must rely on clinical judgment, potentially augmented by clinical criteria validated to identify sepsis among patients with infection. In 2016, sepsis was redefined as a life-threatening organ dysfunction caused by a dysregulated host response to infection.1 Along with this new conceptual definition for sepsis, members of the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) task force proposed qSOFA (quick Sequential [Sepsis-related] Organ Failure Assessment)—an empirically derived score using simple clinical criteria—to potentially assist bedside clinicians in identifying, among patients with infection, those with sepsis or those likely to develop it.2 To develop this score, Seymour et al2 and the Sepsis-3 Task Force analyzed several, very large, hospital databases, selecting patients with suspected infection (defined by a combination of use of antibiotics and body fluid culture within a specific time-window). Based on routinely available, clinical data, the authors identified the most parsimonious model, over and above baseline risk, that could distinguish a suspected infection likely to be, or lead to, sepsis from one that likely was not or would not. When a gold standard exists for a disease or condition, it is possible to assign true-positives, false-positives, and falsenegatives and calculate traditional metrics such as sensitivity and specificity. However, when there is no gold standard, true vs false assignment cannot be determined. Instead, the value of a test must be assessed on its performance across different aspects of validity, reliability, and usefulness. The principal domain used to assess qSOFA was predictive validity. Specifically, Seymour et al explored the extent to which qSOFA and other more complex measures predicted excess deaths or prolonged intensive care unit (ICU) stay beyond that explained by baseline risk. These outcomes were used because, if sepsis differs from a simple infection because of organ dysfunction and increased threat to life, then death or prolonged ICU stay should be more common among patients with sepsis than among those with simple infection. After validation in 4 external data sets and multiple sensitivity analyses, the final qSOFA model included 3 parameters: Glasgow Coma Scale score of less than 15 (1 point), systolic blood pressure of 100 mm Hg or less (1 point), and respiratory rate of 22/min or more (1 point). Among patients with infection outside the ICU, qSOFA had similar or better predictive validity for the selected outcomes expected to be more common following sepsis than the more complex measures tested—SOFA3 and the Logistic Organ Dysfunction System4—that require a greater number of clinical and laboratory variables. However, among patients with infection in the ICU, qSOFA had statistically worse predictive validity. Both the new definition of sepsis and qSOFA have been discussed and debated.5-10 qSOFA and, more specifically, its measurement properties appear to have generated and attracted the most concern. Two studies in this issue of JAMA, despite apparently focusing on prognosis (predicting outcome, regardless of the cause of the outcome) rather than diagnosis (identifying a disease or condition−the original intention of qSOFA), provide an opportunity to revisit qSOFA and its measurement properties both outside and inside the ICU.11,12 Because so many patients worldwide are at risk of sepsis and because evaluation for sepsis may occur in the ambulatory setting, emergency department (ED), or during hospitalization, understanding whether qSOFA is a good measure is an enormously important question. Freund et al11 evaluated the predictive validity of qSOFA in a prospective study of patients presenting to EDs in France, Switzerland, Spain, and Belgium.11 Among 879 patients (median age 67 years, 379 with respiratory tract infection, in-hospital mortality of 8%) presenting with suspected infection to 30 EDs over a 4-week period, the investigators confirmed that the predictive validity of qSOFA in the ED setting was similar to that of the full SOFA score and that the addition of lactate did not improve predictive validity. The in-hospital mortality was 3% for patients with a qSOFA score of less than 2 and 24% for qSOFA score of 2 or more. qSOFA performed better than systemic inflammatory response syndrome (SIRS) criteria and severe sepsis to predict in-hospital mortality. The study does have some limitations. Patients who were initially suspected to have infection but subsequently adjudicated not to have infection Related articles pages 290 and 301 Opinion

qSOFA for Identifying Sepsis Among Patients With Infection

INTRODUCTION: For early detection of sepsis, automated systems within the electronic health record have evolved to alert emergency department (ED) personnel to the possibility of sepsis, and in some cases link them to suggested care pathways. We conducted a systematic review of automated sepsis-alert detection systems in the ED. METHODS: We searched multiple health literature databases from the earliest available dates to August 2018. Articles were screened based on abstract, again via manuscript, and further narrowed with set inclusion criteria: 1) adult patients in the ED diagnosed with sepsis, severe sepsis, or septic shock; 2) an electronic system that alerts a healthcare provider of sepsis in real or near-real time; and 3) measures of diagnostic accuracy or quality of sepsis alerts. The final, detailed review was guided by QUADAS-2 and GRADE criteria. We tracked all articles using an online tool (Covidence), and the review was registered with PROSPERO registry of reviews. A two-author consensus was reached at the article choice stage and final review stage. Due to the variation in alert criteria and methods of sepsis diagnosis confirmation, the data were not combined for meta-analysis. RESULTS: We screened 693 articles by title and abstract and 20 by full text; we then selected 10 for the study. The articles were published between 2009-2018. Two studies had algorithm-based alert systems, while eight had rule-based alert systems. All systems used different criteria based on systemic inflammatory response syndrome (SIRS) to define sepsis. Sensitivities ranged from 10-100%, specificities from 78-99%, and positive predictive value from 5.8-54%. Negative predictive value was consistently high at 99-100%. Studies showed some evidence for improved process-of-care markers, including improved time to antibiotics. Length of stay improved in two studies. One low quality study showed improved mortality. CONCLUSION: The limited evidence available suggests that sepsis alerts in the ED setting can be set to high sensitivity. No high-quality studies showed a difference in mortality, but evidence exists for improvements in process of care. Significant further work is needed to understand the consequences of alert fatigue and sensitivity set points.

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Sepsis Alerts in Emergency Departments: A Systematic Review of Accuracy and Quality Measure Impact.

Objective To identify priorities for administrative, epidemiologic and diagnostic research in sepsis. Design As a follow-up to a previous consensus statement about sepsis research, members of the Surviving Sepsis Campaign Research Committee, representing the European Society of Intensive Care Medicine and the Society of Critical Care Medicine addressed six questions regarding care delivery, epidemiology, organ dysfunction, screening, identification of septic shock, and information that can predict outcomes in sepsis. Methods Six questions from the Scoring/Identification and Administration sections of the original Research Priorities publication were explored in greater detail to better examine the knowledge gaps and rationales for questions that were previously identified through a consensus process. Results The document provides a framework for priorities in research to address the following questions: (1) What is the optimal model of delivering sepsis care?; (2) What is the epidemiology of sepsis susceptibility and response to treatment?; (3) What information identifies organ dysfunction?; (4) How can we screen for sepsis in various settings?; (5) How do we identify septic shock?; and (6) What in-hospital clinical information is associated with important outcomes in patients with sepsis? Conclusions There is substantial knowledge of sepsis epidemiology and ways to identify and treat sepsis patients, but many gaps remain. Areas of uncertainty identified in this manuscript can help prioritize initiatives to improve an understanding of individual patient and demographic heterogeneity with sepsis and septic shock, biomarkers and accurate patient identification, organ dysfunction, and ways to improve sepsis care.

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The Surviving Sepsis Campaign: research priorities for the administration, epidemiology, scoring and identification of sepsis.

Objective To describe the improvements of an early warning system for the identification of septic patients on the time to diagnosis, antibiotic delivery, and mortality. Methods This was an observational cohort study that describes the successive improvements made over a period of 10 years using an early warning system to detect sepsis, including systematic active manual surveillance, electronic alerts via a telephonist, and alerts sent directly to the mobile devices of nurses. For all periods, after an alert was triggered, early treatment was instituted according to the institutional sepsis guidelines. Results In total, 637 patients with sepsis were detected over the study period. The median triage-to-diagnosis time was reduced from 19:20 (9:10 - 38:15) hours to 12:40 (2:50 - 23:45) hours when the manual surveillance method was used (p = 0.14), to 2:10 (1:25 - 2:20) hours when the alert was sent automatically to the hospital telephone service (p = 0.014), and to 1:00 (0:30 - 1:10) hour when the alert was sent directly to the nurse's mobile phone (p = 0.016). The diagnosis-to-antibiotic time was reduced to 1:00 (0:55 - 1:30) hours when the alert was sent to the telephonist and to 0:45 (0:30 - 1:00) minutes when the alert was sent directly to the nurse's mobile phone (p = 0.02), with the maintenance of similar values over the following years. There was no difference in the time of treatment between survivors and non-survivors. Conclusion Electronic systems help reduce the triage-to-diagnosis time and diagnosis-to-antibiotic time in patients with sepsis.

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Lucimeri Albino

Papers

An electronic warning system helps reduce the time to diagnosis of sepsis