Systemic inflammatory response syndrome, sepsis, severe sepsis and septic shock: Incidence, morbidities and outcomes in surgical ICU patients

Pittet, Didier; Rangel-Frausto, Sigfrido; Li, Ning; Tarara, Debra T; Costigan, Michele; Rempe, Lynn; Jebson, Peter; Wenzel, Richard P.

doi:10.1007/bf01705408

Cited by 303 publications

(178 citation statements)

References 17 publications

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“…[17][18][19][20][21][22][23][24] Previously published data on the test characteristics of SIRS have largely focused on the SIRS score at the time of presentation to the emergency department or upon admission to the medical floor or ICU. Since our patients are often admitted for prolonged hospital stays (30 day planned admissions) …”

Section: Discussionmentioning

confidence: 99%

Utility of the systemic inflammatory response syndrome (SIRS) criteria in predicting the onset of septic shock in hospitalized patients with hematologic malignancies

Mato¹,

Fuchs²,

Heitjan³

et al. 2009

Cancer Biology & Therapy

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Section: Discussionmentioning

confidence: 99%

Utility of the systemic inflammatory response syndrome (SIRS) criteria in predicting the onset of septic shock in hospitalized patients with hematologic malignancies

Mato¹,

Fuchs²,

Heitjan³

et al. 2009

Cancer Biology & Therapy

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“…This likely represents the independent association between SIRS and organ dysfunction with the risk for mortality (27,31,32).…”

Section: Discussionmentioning

confidence: 95%

“…One review of 39 EWSs reported PPVs ranging from 13.5-26.1% (34), and another review of 25 systems reported a median PPV of 36.7% with interquartile range 29.3-43.8% (34). PPV was not reported for several of the most elegant and well-studied EWSs (22,23,25,32). From the perspective of bedside clinicians and rapid response team members, the efficiency of an alert system is strongly influenced by the PPV, because a poor PPV translates to frequent false alerts.…”

Section: * Our Data Indicate That Rrt Activation Would Occur About Twmentioning

confidence: 99%

Clinical performance of an interactive clinical decision support system for assessment of plasma lactate in hospitalized patients with organ dysfunction

Raschke¹,

Khurana²,

Owen-Reece³

et al. 2017

Southwest J Pulm Crit Care

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Purpose: Elevated plasma lactate concentration can be a useful measure of tissue hypo-perfusion in acutely deteriorating patients, focusing attention on the need for urgent resuscitation. But lactate is not always assessed in a timely fashion in patients who have deteriorating vital signs. We hypothesized that an electronic medical record (EMR)-based decision support system could interact with clinicians to prompt assessment of plasma lactate in appropriate clinical situations in order to risk stratify a population of inpatients and identify those who are acutely deteriorating in real-time. Methods: All adult patients admitted to our hospital over a three month period were monitored by an EMR-based lactate decision support system (lactate DSS) programmed to detect patients exhibiting acute organ dysfunction and engage the clinician in the decision to order a plasma lactate concentration. Inpatient mortality was determined for the five risk categories that this system generated, and chart review was performed on a high-risk subgroup to describe the spectrum of bedside events that triggered the system logic. Results: The lactate DSS segregated inpatients into five strata with mortality rates of 0.8% (95%CI:0.6-1.0%); 2.7% (95%CI:1.0-4.4%); 7.9% (95%CI: 6.0-10.1%), 13.0% (95%CI: 9.0-17.8%) and 42.1% (95%CI: 32.0-52.4%), achieving a discriminant accuracy of 80% (95%CI:76-84%) by AUROC for predicting inpatient mortality. Classification into the two highest risk strata had a positive predictive value for detecting acute lifethreatening clinical events of 54% (95%CI: 41.5-66.5%). Conclusions: Our lactate decision support system is different than previouslydescribed computerized "early warning systems", because it engages the clinician in decision-making and incorporates clinical judgment in risk stratification. Our system has favorable operating characteristics for the prediction of inpatient mortality and real-time detection of acute life-threatening deterioration.

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“…Different studies have shown that the incidence of SIRS is quite high in critical patients in general. For example, Pittet et al [44] presented a SIRS incidence of up to 93% in critical care patients, while Rangel et al showed an incidence of 68% [43]. The latter study also shows that 25% of patients with SIRS developed a Sepsis, 18% presented Severe Sepsis, and 4% of them, Septic Shock.…”

Section: Quantitative Analysis Of the Prognosis Of Sepsismentioning

confidence: 92%

Intelligent Management of Sepsis in the Intensive Care Unit

Ripoll

Rodríguez

Vellido

2012

Medical Applications of Intelligent Data Analysis

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Sepsis is a transversal pathology and one of the main causes of death in the Intensive Care Unit (ICU). It has in fact become the tenth most common cause of death in western societies. Its mortality rates can reach up to 60% for Septic Shock, its most acute manifestation. For these reasons, the prediction of the mortality caused by Sepsis is an open and relevant medical research challenge. This problem requires prediction methods that are robust and accurate, but also readily interpretable. This is paramount if they are to be used in the demanding context of real-time decision making at the ICU. In this brief contribution, three different methods are presented. One is based on a variant of the well-known support vector machine (SVM) model and provides and automated ranking of relevance of the mortality predictors while the other two are based on logistic-regression and logistic regression over latent Factors. The reported results show that the methods presented outperform in terms of accuracy alternative techniques currently in use in clinical settings, while simultaneously assessing the relative impact of individual pathology indicators.

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Systemic inflammatory response syndrome, sepsis, severe sepsis and septic shock: Incidence, morbidities and outcomes in surgical ICU patients

Cited by 303 publications

References 17 publications

Utility of the systemic inflammatory response syndrome (SIRS) criteria in predicting the onset of septic shock in hospitalized patients with hematologic malignancies

Utility of the systemic inflammatory response syndrome (SIRS) criteria in predicting the onset of septic shock in hospitalized patients with hematologic malignancies

Clinical performance of an interactive clinical decision support system for assessment of plasma lactate in hospitalized patients with organ dysfunction

Intelligent Management of Sepsis in the Intensive Care Unit

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