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A New Prediction System of Sepsis: A Retrospective, Clinical Study

A New Prediction System of Sepsis: A Retrospective, Clinical Study
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摘要 Objective: Analyzing 6 biomarkers, such as procalcitonin (PCT), C-reactive protein (CRP), fibrinogen (Fib), lactate concentration (Lac), D-dimer (D-d), neutrophil ratio (NEUT%) to figure out several sensitive indicators and establish a new prediction system of sepsis, which could achieve a higher sensitivity and specificity to predict sepsis. Methods: We collected 113 SIRS patients in ICU. According to their prognosis, all the patients were divided into two groups named sepsis and non-sepsis group according to the diagnostic criteria of sepsis. We recorded the general information and detected the plasma levels of the 6 biomarkers. Results: The plasma levels of NEUT% and Fib between the two groups had no significant difference. PCT had the highest prediction accuracy of sepsis compared with other biomarkers. A predictive model was established, in which Lac, PCT, CRP were enrolled. The final prediction model was: logit(P) = 0.314 + 0.105 × Lac(mmol/l) + 0.099 × PCT(ng/mL) + 0.012 × CRP(mg/L). The area under the curve of the prediction model was 0.893, which was higher than every single biomarker involved in this study. Conclusion: The three serum biomarkers of Lac, PCT, CRP are used to establish a prediction model of sepsis: logit(P) = 0.314 + 0.105 × Lac(mmol/l) + 0.099 × PCT(ng/mL) + 0.012 × CRP(mg/L), which can better predict the occurrence of sepsis compared with other biomarkers. Objective: Analyzing 6 biomarkers, such as procalcitonin (PCT), C-reactive protein (CRP), fibrinogen (Fib), lactate concentration (Lac), D-dimer (D-d), neutrophil ratio (NEUT%) to figure out several sensitive indicators and establish a new prediction system of sepsis, which could achieve a higher sensitivity and specificity to predict sepsis. Methods: We collected 113 SIRS patients in ICU. According to their prognosis, all the patients were divided into two groups named sepsis and non-sepsis group according to the diagnostic criteria of sepsis. We recorded the general information and detected the plasma levels of the 6 biomarkers. Results: The plasma levels of NEUT% and Fib between the two groups had no significant difference. PCT had the highest prediction accuracy of sepsis compared with other biomarkers. A predictive model was established, in which Lac, PCT, CRP were enrolled. The final prediction model was: logit(P) = 0.314 + 0.105 × Lac(mmol/l) + 0.099 × PCT(ng/mL) + 0.012 × CRP(mg/L). The area under the curve of the prediction model was 0.893, which was higher than every single biomarker involved in this study. Conclusion: The three serum biomarkers of Lac, PCT, CRP are used to establish a prediction model of sepsis: logit(P) = 0.314 + 0.105 × Lac(mmol/l) + 0.099 × PCT(ng/mL) + 0.012 × CRP(mg/L), which can better predict the occurrence of sepsis compared with other biomarkers.
作者 Enhe Liu Zhinan Zheng Qiuye Kou Enhe Liu;Zhinan Zheng;Qiuye Kou(Department of Intensive care Unit, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China;Department of Anesthesia, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China)
出处 《Modern Research in Inflammation》 2016年第4期63-76,共14页 炎症(英文)
关键词 SEPSIS Biomarkers Prediction System Sepsis Biomarkers Prediction System
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