| BackgroundPrevious studies have shown that up to one-third of patients in the ICU are in a circulatory shock state and have a high mortality rate,mainly due to tissue organs ischemia and hypoxia.Early blood flow distribution guarantees the irrigation of cerebral blood flow,but if the circulating blood capacity is insufficient,it will cause secondary brain dysfunction.This type of brain dysfunction is often manifested in delirium,which is related to the decline in cognitive function in the later period.Therefore,early identification of brain dysfunction is particularly important.In recent years,brain-derived biomarkers are widely used in the recognition of central nervous system disease due to its rapid testing and convenience.At present,there are rare patients with shock as the research crowd.Therefore,this study explores the correlation of brain functional disorders and prognosis through dynamic monitoring of patients brain-derived biomarkers expression levels.MethodsIn this study,blood samples from patients who treated in the intensive care unit of our hospital and diagnosed with shock were prospectively collected from December 1,2020 to December 30,2022.The expression of brain-derived biomarkers(GFAP,PGP9.5,NSE,S100β)was detected by ELISA.The area under curve(AUC)was obtained by plotting the receiver operating characteristic curve(ROC),which was used to evaluate the predictive efficacy of biomarkers and the prediction performance of different baseline biomarker level groups.Finally,the risk predictors and clinical application value of outcome events were evaluated by multivariate analysis.In this study,blood samples were prospectively collected from patients who were diagnosed with shock and treated in the intensive care unit of Guangdong Provincial People’s Hospital between December 1,2020 and December 30,2022.Blood samples were collected at enrollment,6 hours after enrollment,24 hours after enrollment,3 days after enrollment,and 5 days after enrollment.The expression levels of brain-derived biomarkers(GFAP,PGP9.5,NSE,S100β)were detected by ELISA.Consciousness is assessed daily using the CAM-ICU Score Scale after enrollment.If the CAM-ICU screening is positive at one time point,the patient is defined as positive for the CAM-ICU assessment,and then defined as acute brain injury.According to the patient’s prognosis when patients transferred out of the ICU,and divided into poor outcome group and good outcome group.The area under the curve(AUC)was obtained by plotting the receiver operating characteristic curve(ROC),which was used to evaluate the predictive power of biomarkers and groups with different baseline biomarker levels.Finally,the risk prediction power and clinical application value of biomarkers for the occurrence and poor outcome of acute brain injury were evaluated by multivariate analysis.ResultsA total of 156 patients were enrolled in this study and 106 patients were eventually included.The results showed that the expression levels of the four markers(GFAP,PGP9.5,S100β,NSE)were significantly increased in both the acute brain injury group and the poor outcome group.The AUC for the prediction of acute brain injury by GFAP on admission was 0.694(95%CI:0.589-0.798).The AUC for S100βon day 3 for predicting poor outcome was 0.734(95%CI:0.599-0.870).The optimal cutoff value for the marker was calculated and the patients were divided into high-level groups(GFAP+,PGP9.5+,S100β+)and low-level groups(GFAP-,PGP9.5-,S100β-)according to their expression level.The ad GFAP+was used to predict acute brain injury with an AUC of 0.662(95%CI:0.554-0.770).The AUC of 3d S100β+ for predicting poor outcome was 0.747(95%CI:0.618-0.876).In the prediction of acute brain injury cohort,the AUC of combination of ad GFAP+、ad PGP9.5+and ad S100β+was 0.744(95%CI:0.648-0.839),which was increased compared with individual markers.In the poor outcome cohort,3d GFAP+combined with 3d S100β+had the largest AUC,which was 0.802(95%CI:0.686-0.917).Multivariate logistic regression analysis showed that GFAP>14.96 pg/mL at admission(OR:3.78(95%CI:(1.167-12.243,p=0.027))and GCS score decreased were independent risk factors for acute brain injury.Elevated CRP at day 3(OR:1.017(95%CI:1.001-1.032,p=0.037)),GFAP>24.71 pg/mL at day 3(OR:17.54(95%CI:1.561-197.089,p=0.02))and receibing CRRT treatment(OR:9.742(95%CI:1.424-66.637,p=0.02))were independent risk factors for poor outcome.ConclusionsBrain-derived biomarker could be used to predict acute brain dysfunction and poor outcome.The predictive efficiency of GFAP were higher compared with other three biomarker in acute brain injury.The predictive efficiency of S100β were higher compared with other three biomarker in poor outcome.And co-prediction with markers can significantly improve the predictive efficiency compared with single biomarker. |
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