Resuscitation · 2020
Neuroprognostic accuracy of blood biomarkers for post-cardiac arrest patients: A systematic review and meta-analysis.
СтатьяМетаанализСистематический обзорНазвание и аннотация: Перевод в очереди
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Wang Chih-Hung, Chang Wei-Tien, Su Ke-Ing, Huang Chien-Hua, Tsai Min-Shan, Chou Eric, Lu Tsung-Chien, Chen Wen-Jone, Lee Chien-Chang, Chen Shyr-Chyr
Аннотация
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.
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.