Quick Sepsis-related Organ Failure Assessment Versus Systemic Inflammatory Response Syndrome Criteria for Predicting Organ Dysfunction and Mortality

Harimtepathip, Punnavit; Lee, James R; Griffith, Elliot; Williams, Gabriel J.; Patel, Ravi; Lebowitz, David; Koochakzadeh, Sina

doi:10.7759/cureus.3511

Cited by 3 publications

(2 citation statements)

References 10 publications

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“… 2 15 21 However, other studies have concluded that the qSOFA score is superior to the SIRS criteria because of better prognostic accuracy. 9 10 12 22 Until now, most of the studies have investigated the difference between the SIRS criteria and the qSOFA score in intensive care units (ICU) or in specific patients, such as elderly patients or those suffering from pneumonia. 2 3 6 12 The aim of our study is to compare the daily practice of two EDs in the Netherlands, where SIRS criteria and qSOFA score are used differently as screening tools for culture-positive sepsis.…”

Section: Introductionmentioning

confidence: 99%

Comparison of SIRS criteria and qSOFA score for identifying culture-positive sepsis in the emergency department: a prospective cross-sectional multicentre study

et al. 2021

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ObjectiveTo compare the daily practice of two emergency departments (ED) in the Netherlands, where systemic inflammatory response syndrome (SIRS) criteria and quick Sequential Organ Failure Assessment (qSOFA) score are used differently as screening tools for culture-positive sepsis.DesignA prospective cross-sectional multicentre study.SettingTwo EDs at two European clinical teaching hospitals in the Netherlands.Participants760 patients with suspected infection who met SIRS criteria or had a qualifying qSOFA score who were treated at two EDs in the Netherlands from 1 January to 1 March 2018 were included.MethodsSIRS criteria and qSOFA score were calculated for each patient. The first hospital treated the patients who met SIRS criteria following the worldwide Surviving Sepsis Campaign protocol. At the second hospital, only patients who met the qualifying qSOFA score received this treatment. Therefore, patients could be divided into five groups: (1) SIRS+, qSOFA−, not treated according to protocol (reference group); (2) SIRS+, qSOFA−, treated according to protocol; (3) SIRS+, qSOFA+, treated according to protocol; (4) SIRS−, qSOFA+, not treated according to protocol; (5) SIRS−, qSOFA+, treated according to protocol.Primary and secondary outcome measuresTo prove culture-positive sepsis was present, cultures were used as the primary outcome. Secondary outcomes were in-hospital mortality and intensive care unit (ICU) admission.Results98.9% met SIRS criteria and 11.7% met qSOFA score. Positive predictive values of SIRS criteria and qSOFA score were 41.2% (95% CI 37.4% to 45.2%) and 48.1% (95% CI 37.4% to 58.9%), respectively. HRs were 0.79 (95% CI 0.40 to 1.56, p=0.500), 3.42 (95% CI 1.82 to 6.44, p<0.001), 18.94 (95% CI 2.48 to 144.89, p=0.005) and 4.97 (95% CI 1.44 to 17.16, p=0.011) for groups 2–5, respectively.ConclusionqSOFA score performed as well as SIRS criteria for identifying culture-positive sepsis and performed significantly better for predicting in-hospital mortality and ICU admission. This study shows that SIRS criteria are no longer necessary and recommends qSOFA score as the standard for identifying culture-positive sepsis in the ED.Trial registration numberNL8315.

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Section: Introductionmentioning

confidence: 99%

Comparison of SIRS criteria and qSOFA score for identifying culture-positive sepsis in the emergency department: a prospective cross-sectional multicentre study

et al. 2021

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“…However, the adoption of qSOFA, the new screening tool for sepsis, was not conducive to early sepsis screening and remains controversial [13][14][15]. Many studies have shown that qSOFA has a relatively high specificity for early detection of sepsis-related organ dysfunction [16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Development and Validation of Deep-Learning-Based Sepsis and Septic Shock Early Prediction System (DeepSEPS) Using Real-World ICU Data

Kim,

Tae,

Yeo

et al. 2023

JCM

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Background: Successful sepsis treatment depends on early diagnosis. We aimed to develop and validate a system to predict sepsis and septic shock in real time using deep learning. Methods: Clinical data were retrospectively collected from electronic medical records (EMRs). Data from 2010 to 2019 were used as development data, and data from 2020 to 2021 were used as validation data. The collected EMRs consisted of eight vital signs, 13 laboratory data points, and three demographic information items. We validated the deep-learning-based sepsis and septic shock early prediction system (DeepSEPS) using the validation datasets and compared our system with other traditional early warning scoring systems, such as the national early warning score, sequential organ failure assessment (SOFA), and quick sequential organ failure assessment. Results: DeepSEPS achieved even higher area under receiver operating characteristic curve (AUROC) values (0.7888 and 0.8494 for sepsis and septic shock, respectively) than SOFA. The prediction performance of traditional scoring systems was enhanced because the early prediction time point was close to the onset time of sepsis; however, the DeepSEPS scoring system consistently outperformed all conventional scoring systems at all time points. Furthermore, at the time of onset of sepsis and septic shock, DeepSEPS showed the highest AUROC (0.9346). Conclusions: The sepsis and septic shock early warning system developed in this study exhibited a performance that is worth considering when predicting sepsis and septic shock compared to other traditional early warning scoring systems. DeepSEPS showed better performance than existing sepsis prediction programs. This novel real-time system that simultaneously predicts sepsis and septic shock requires further validation.

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<p>Presepsin level in predicting patients’ in-hospital mortality from sepsis under sepsis-3 criteria</p>

Wen

Huang

Yang

et al. 2019

TCRM

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Background: Early recognition of septic patients with poor prognosis is important for clinicians to prescribe personalized therapies which include timely fluid resuscitation therapy and appropriate antimicrobial therapy. We aimed to evaluate the effect of the presepsin level on predicting the prognosis of patients with sepsis under the sepsis-3 criteria. Methods: Patients who were diagnosed as sepsis under the sepsis-3 criteria were recruited and assigned to the survivor group and the non-survivor group according to their in-hospital mortality. The two groups' baseline characteristics were analyzed with Pearson's chi-square (χ 2) test or Kruskal-Wallis test. Binary logistic regression analysis was performed to determine the independent predictors of in-hospital mortality from sepsis. Receiver operating characteristic analysis was conducted to evaluate the efficacy of presepsin in predicting patients' in-hospital mortality from sepsis. The correlation between presepsin and the Sequential Organ Failure Assessment (SOFA) score was measured with Spearman's rank correlation coefficient. P-values of less than 0.05 were considered to indicate statistical significance. Results: Overall, 138 patients were included in this study. The presepsin level of the non-survivor group was significantly higher than that of the other group (P=0.000). Binary logistic regression showed that the presepsin level was an independent risk factor of patients' in-hospital mortality from sepsis (OR =1.221 P=0.026). The presepsin level was positively associated with the SOFA score (ρ=0.396, P=0.000). ROC curve analysis revealed the presepsin level was highly accurate in predicting patients' in-hospital mortality from sepsis (AUC =0.703, P=0.000). The AUC value of a combination of presepsin and the SOFA score was significantly larger than that of the SOFA score alone (AUC: 0.817 vs 0.793, P=0.041). Conclusions: Presepsin is a prognostic biomarker with high accuracy in predicting the prognosis of sepsis under the sepsis-3 criteria.

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Quick Sepsis-related Organ Failure Assessment Versus Systemic Inflammatory Response Syndrome Criteria for Predicting Organ Dysfunction and Mortality

Cited by 3 publications

References 10 publications

Comparison of SIRS criteria and qSOFA score for identifying culture-positive sepsis in the emergency department: a prospective cross-sectional multicentre study

Comparison of SIRS criteria and qSOFA score for identifying culture-positive sepsis in the emergency department: a prospective cross-sectional multicentre study

Development and Validation of Deep-Learning-Based Sepsis and Septic Shock Early Prediction System (DeepSEPS) Using Real-World ICU Data

<p>Presepsin level in predicting patients’ in-hospital mortality from sepsis under sepsis-3 criteria</p>

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