Comparison of Prognostic Accuracy of the quick Sepsis-Related Organ Failure Assessment between Short- &amp; Long-term Mortality in Patients Presenting Outside of the Intensive Care Unit – A Systematic Review &amp; Meta-analysis

Tan, Toh Leong; Tang, Ying; Ching, Ling Jing; Abdullah, Nor Azizan; Neoh, Hui Min

doi:10.1038/s41598-018-35144-6

Cited by 19 publications

(12 citation statements)

References 65 publications

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“…The Sequential Organ Failure Assessment (SOFA) score, used to codify the degree of organ dysfunction, is a simple and effective method to monitor patient condition and disease progression, and is widely used in ICUs to evaluate the severity and prognosis of patients with sepsis (Ferreira et al, 2001;Tan et al, 2018;Lambden et al, 2019). SOFA score is a total score including six domains: respiratory system (PaO 2 /FiO 2 ), renal system (creatinine), central nervous system (Glasgow Coma Score), coagulation system (platelet counts), hepatic (bilirubin), and cardiovascular system (systolic blood pressure).…”

Section: Introductionmentioning

confidence: 99%

Exposure-Response Modeling to Support Dosing Selection for Phase IIb Development of Kukoamine B in Sepsis Patients

Wang

et al. 2021

Front. Pharmacol.

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Aim: Kukoamine B, a small molecule compound, is being developed for the treatment of sepsis in a Phase II clinical trial. The objective of this study was to optimize dosing selection for a Phase IIb clinical trial using an exposure-response model.Methods: Data of 34 sepsis patients from a Phase IIa clinical trial were used in the model: 10 sepsis patients from the placebo group and a total of 24 sepsis patients from the 0.06 mg/kg, 0.12 mg/kg, and 0.24 mg/kg drug groups. Exposure-response relationship was constructed to model the impact of the standard care therapy and area under curve (AUC) of kukoamine B to the disease biomarker (SOFA score). The model was evaluated by goodness of fit and visual predictive check. The simulation was performed 1,000 times based on the built model.Results: The data of the placebo and the drug groups were pooled and modeled by a nonlinear mixed-effect modeling approach in sepsis. A latent-variable approach in conjunction with an inhibitory indirect response model was used to link the standard care therapy effect and drug exposure to SOFA score. The maximum fraction of the standard care therapy was estimated to 0.792. The eliminate rate constant of the SOFA score was 0.263/day for the standard care therapy. The production rate of SOFA score (Kin) was estimated at 0.0569/day and the AUC at half the maximal drug effect (EAUC50) was estimated at 1,320 h*ng/mL. Model evaluation showed that the built model could well describe the observed SOFA score. Model-based simulations showed that the SOFA score on day 7 decreased to a plateau when AUC increased to 1,500 h*ng/mL.Conclusion: We built an exposure-response model characterizing the pharmacological effect of kukoamine B from the standard care therapy in sepsis patients. A dose regimen of 0.24 mg/kg was finally recommended for the Phase IIb clinical trial of kukoamine B based on modeling and simulation results.

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Section: Introductionmentioning

confidence: 99%

Exposure-Response Modeling to Support Dosing Selection for Phase IIb Development of Kukoamine B in Sepsis Patients

Wang

et al. 2021

Front. Pharmacol.

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“…The qSOFA scores can be used outside of the intensive care unit (ICU) for predicting mortality or ICU stay [4][5][6][7][8][9]. However, several meta-analyses of qSOFA scores have shown that these scores had a poor sensitivity for predicting in-hospital mortality [10][11][12][13][14]. Early warning scores [15,16], a tool for identifying hospitalized patients at risk of deterioration, have been proposed for predicting hospital mortality in those with suspected sepsis in the ED [7,[17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Development and Validation of a Quick Sepsis-Related Organ Failure Assessment-Based Machine-Learning Model for Mortality Prediction in Patients with Suspected Infection in the Emergency Department

Kwon

Baek

2020

JCM

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The quick sepsis-related organ failure assessment (qSOFA) score has been introduced to predict the likelihood of organ dysfunction in patients with suspected infection. We hypothesized that machine-learning models using qSOFA variables for predicting three-day mortality would provide better accuracy than the qSOFA score in the emergency department (ED). Between January 2016 and December 2018, the medical records of patients aged over 18 years with suspected infection were retrospectively obtained from four EDs in Korea. Data from three hospitals (n = 19,353) were used as training-validation datasets and data from one (n = 4234) as the test dataset. Machine-learning algorithms including extreme gradient boosting, light gradient boosting machine, and random forest were used. We assessed the prediction ability of machine-learning models using the area under the receiver operating characteristic (AUROC) curve, and DeLong’s test was used to compare AUROCs between the qSOFA scores and qSOFA-based machine-learning models. A total of 447,926 patients visited EDs during the study period. We analyzed 23,587 patients with suspected infection who were admitted to the EDs. The median age of the patients was 63 years (interquartile range: 43–78 years) and in-hospital mortality was 4.0% (n = 941). For predicting three-day mortality among patients with suspected infection in the ED, the AUROC of the qSOFA-based machine-learning model (0.86 [95% CI 0.85–0.87]) for three -day mortality was higher than that of the qSOFA scores (0.78 [95% CI 0.77–0.79], p < 0.001). For predicting three-day mortality in patients with suspected infection in the ED, the qSOFA-based machine-learning model was found to be superior to the conventional qSOFA scores.

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“…It appears that the qSOFA score may have low sensitivity but high specificity as a prognosticator of mortality. [5][6][7][8][9][10][11][12] Age, sex and HIV status have been shown to independently predict mortality in patients with infection in the US and have been used in prior qSOFA validation studies in resource-limited settings. [13] There is limited research on the prognostic value of qSOFA in resourcelimited settings -initial results from developing countries [13] and African countries are encouraging.…”

mentioning

confidence: 99%

Prognostic value of the Quick Sepsis-related Organ Failure Assessment (qSOFA) score among critically ill medical and surgical patients with suspected infection in a resourcelimited setting

Bischop

Wilson

Wise

et al. 2021

AJTCCM

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Background. The Quick Sequential Organ Failure Assessment (qSOFA) score is a simple bedside tool validated outside of the intensive care unit (ICU) to identify patients with suspected infection who are at risk for poor outcomes. Objectives. To assess qSOFA at the time of ICU referral as a mortality prognosticator in adult medical v. surgical patients with suspected infection admitted to an ICU in a resource-limited regional hospital in South Africa (SA). Methods. We conducted a retrospective cohort study on adult medical or surgical patients that were admitted to an ICU in a resource-limited hospital in SA. We performed univariate and multivariable logistic regression and compared nested models using likelihood ratio test, and we calculated the area under the receiver operating characteristic curve (AUROC). Results. We recruited a total of 1 162 (medical n=283 and surgical n=875) participants in the study who were admitted to the ICU with suspected infection. qSOFA at the time of ICU referral was highly associated with but poorly discriminant of in-ICU mortality among medical (odds ratio (OR) 2.60, 95% confidence interval (CI) 1.19 - 5.71; p=0.02; AUROC 0.60; 95% CI 0.53 - 0.67; p=0.02) and surgical (OR 2.74; 95% CI 1.73-4.36; p<0.001; AUROC 0.60; 95% CI 0.55 - 0.65; p=0.04) patients. qSOFA model performance was similar between medical and surgical subgroups (p≥0.26). Addition of qSOFA to a baseline risk factor model including age, sex, and HIV status improved the model discrimination in both subgroups (medical AUROC 0.64; 95% CI 0.56 - 0.71; p=0.049; surgical AUROC 0.69; 95% CI 0.64 - 0.74; p<0.0001). Conclusion. qSOFA was highly associated with, but poorly discriminant for, poor outcomes among medical and surgical patients with suspected infection admitted to the ICU in a resource-limited setting. These findings suggest that qSOFA may be useful as a tool to identify patients at increased risk of mortality in these populations and in this context.

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Comparison of Prognostic Accuracy of the quick Sepsis-Related Organ Failure Assessment between Short- & Long-term Mortality in Patients Presenting Outside of the Intensive Care Unit – A Systematic Review & Meta-analysis

Cited by 19 publications

References 65 publications

Exposure-Response Modeling to Support Dosing Selection for Phase IIb Development of Kukoamine B in Sepsis Patients

Exposure-Response Modeling to Support Dosing Selection for Phase IIb Development of Kukoamine B in Sepsis Patients

Development and Validation of a Quick Sepsis-Related Organ Failure Assessment-Based Machine-Learning Model for Mortality Prediction in Patients with Suspected Infection in the Emergency Department

Prognostic value of the Quick Sepsis-related Organ Failure Assessment (qSOFA) score among critically ill medical and surgical patients with suspected infection in a resourcelimited setting

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