Chih-Hung Wang1, Wei-Tien Chang1, Ke-Ing Su2, Chien-Hua Huang1, Min-Shan Tsai1, Eric Chou3, Tsung-Chien Lu1, Wen-Jone Chen4, Chien-Chang Lee5, Shyr-Chyr Chen6. 1. Department of Emergency Medicine, National Taiwan University Hospital, Taipei, Taiwan; Department of Emergency Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan. 2. Department of Emergency Medicine, National Taiwan University Hospital, Taipei, Taiwan. 3. Department of Emergency Medicine, Baylor Scott & White All Saints Medical Center, Fort Worth, Texas, USA. 4. Department of Emergency Medicine, National Taiwan University Hospital, Taipei, Taiwan; Department of Emergency Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan; Division of Cardiology, Department of Internal Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan. 5. Department of Emergency Medicine, National Taiwan University Hospital, Taipei, Taiwan; Department of Emergency Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan. Electronic address: hit3transparency@gmail.com. 6. Department of Emergency Medicine, National Taiwan University Hospital, Taipei, Taiwan; Department of Emergency Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan. Electronic address: scchen@ntu.edu.tw.
Abstract
AIM: To summarise and compare the prognostic accuracy of the blood biomarkers of brain injury, including NSE and S-100B, for neurological outcomes in adult post-cardiac arrest patients. METHODS: We systematically searched PubMed and Embase databases from their inception to March 2019. We selected studies providing sufficient data of prognostic values of NSE or S-100B to predict neurological outcomes in adult post-cardiac arrest patients. We adopted QUADAS-2 to assess risk of bias and a Bayesian bivariate random-effects meta-analysis model to synthesise the prognostic data. The study protocol was registered with PROSPERO (CRD42018084933). RESULTS: We included 42 studies involving 4806 patients in the meta-analysis. The NSE was associated with a pooled sensitivity of 0.56 (95% credible interval [CrI], 0.47-0.65) and pooled specificity of 0.99 (95% CrI, 0.98-1.00). The S-100B was associated with a pooled sensitivity of 0.63 (95% CrI, 0.46-0.78) and pooled specificity of 0.97 (95% CrI, 0.92-1.00). The heterogeneity for NSE (I2, 22.4%) and S-100B (I2, 16.1%) was low and publication bias was not significant. In subgroup analyses, both biomarkers were associated with high specificity across all subgroups with regard to different populations (i.e. whether patients were out-of-hospital cardiac arrest or whether patients received targeted temperature management), different timings of measurement, and different timings of outcome assessment. CONCLUSIONS: The prognostic performance was comparable between NSE and S-100B. Both biomarkers may be integrated into a multimodal neuroprognostication algorithm for post-cardiac arrest patients and institution-specific cut-off points for both biomarkers should be established.
AIM: To summarise and compare the prognostic accuracy of the blood biomarkers of brain injury, including NSE and S-100B, for neurological outcomes in adult post-cardiac arrestpatients. METHODS: We systematically searched PubMed and Embase databases from their inception to March 2019. We selected studies providing sufficient data of prognostic values of NSE or S-100B to predict neurological outcomes in adult post-cardiac arrestpatients. We adopted QUADAS-2 to assess risk of bias and a Bayesian bivariate random-effects meta-analysis model to synthesise the prognostic data. The study protocol was registered with PROSPERO (CRD42018084933). RESULTS: We included 42 studies involving 4806 patients in the meta-analysis. The NSE was associated with a pooled sensitivity of 0.56 (95% credible interval [CrI], 0.47-0.65) and pooled specificity of 0.99 (95% CrI, 0.98-1.00). The S-100B was associated with a pooled sensitivity of 0.63 (95% CrI, 0.46-0.78) and pooled specificity of 0.97 (95% CrI, 0.92-1.00). The heterogeneity for NSE (I2, 22.4%) and S-100B (I2, 16.1%) was low and publication bias was not significant. In subgroup analyses, both biomarkers were associated with high specificity across all subgroups with regard to different populations (i.e. whether patients were out-of-hospital cardiac arrest or whether patients received targeted temperature management), different timings of measurement, and different timings of outcome assessment. CONCLUSIONS: The prognostic performance was comparable between NSE and S-100B. Both biomarkers may be integrated into a multimodal neuroprognostication algorithm for post-cardiac arrestpatients and institution-specific cut-off points for both biomarkers should be established.
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