Abstract
Background The design of computerized systems able to support automated detection of threatening
conditions in critically ill patients such as systemic inflammatory response syndrome
(SIRS) and sepsis has been fostered recently. The increase of research work in this
area is due to both the growing digitalization in health care and the increased appreciation
of the importance of early sepsis detection and intervention. To be able to understand
the variety of systems and their characteristics as well as performances, a systematic
literature review is required. Existing reviews on this topic follow a rather restrictive
searching methodology or they are outdated. As much progress has been made during
the last 5 years, an updated review is needed to be able to keep track of current
developments in this area of research.
Objectives To provide an overview about current approaches for the design of clinical decision-support
systems (CDSS) in the context of SIRS, sepsis, and septic shock, and to categorize
and compare existing approaches.
Methods A systematic literature review was performed in accordance with the preferred reporting
items for systematic reviews and meta-analyses (PRISMA) statement. Searches for eligible
articles were conducted on five electronic bibliographic databases, including PubMed/MEDLINE,
IEEE Xplore, Embase, Scopus, and ScienceDirect. Initial results were screened independently
by two reviewers based on clearly defined eligibility criteria. A backward as well
as an updated search enriched the initial results. Data were extracted from included
articles and presented in a standardized way. Articles were classified into predefined
categories according to characteristics extracted previously. The classification was
performed according to the following categories: clinical setting including patient
population and mono- or multicentric study, support type of the system such as prediction
or detection, systems characteristics such as knowledge- or data-driven algorithms
used, evaluation of methodology, and results including ground truth definition, sensitivity,
and specificity. All results were assessed qualitatively by two reviewers.
Results The search resulted in 2,373 articles out of which 55 results were identified as
eligible. Over 80% of the articles describe monocentric studies. More than 50% include
adult patients, and only four articles explicitly report the inclusion of pediatric
patients. Patient recruitment often is very selective, which can be observed from
highly varying inclusion and exclusion criteria. The task of disease detection is
covered in 62% of the articles; prediction of upcoming conditions in 33%. Sepsis is
covered in 67% of the articles, SIRS as sole entity in only 4%, whereas 27% focus
on severe sepsis and/or septic shock. The most common combinations of categories “algorithm
used” and “support type” are knowledge-based detection of sepsis and data-driven prediction
of sepsis. In evaluations, manual chart review (38%) and diagnosis coding (29%) represent
the most frequently used ground truth definitions; most studies present a sample size
between 10,001 and 100,000 cases (31%) and performances highly differ with only five
articles presenting sensitivities and specificities above 90%; four of them using
knowledge-based rather than machine learning algorithms. The presentations of holistic
CDSS approaches, including technical implementation details, system interfaces, and
data and interoperability aspects enabling the use of CDSS in routine settings are
missing in nearly all articles.
Conclusions The review demonstrated the high variety of research in this context successfully.
A clear trend is observable toward the use of data-driven algorithms, and a lack of
research could be identified in covering the pediatric population as well as acknowledging
SIRS as an independent and threatening condition. The quality as well as the significance
of the presented evaluations for assessing the performances of the algorithms in clinical
routine settings are often not meeting the current standard of scientific work. Our
future interest will be concentrated on these realistic settings by implementing and
evaluating SIRS detection approaches as well as considering factors to make the CDSS
useable in clinical routine from both technical and medical perspectives.
Keywords clinical decision-support systems - sepsis - SIRS - critical care - systematic review
