Department of Clinical Laboratory, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, China.
Department of Cardiovascular Medicine, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, China.
Am J Emerg Med. 2024 Dec;86:87-93. doi: 10.1016/j.ajem.2024.10.010. Epub 2024 Oct 5.
To determine the predictive value of brain natriuretic peptide (BNP) levels for 30-day mortality after return of spontaneous circulation (ROSC) in patients with cardiac arrest (CA) of presumed cardiac etiology.
This retrospective study included 260 patients with CA of presumed cardiac etiology who regained ROSC and was conducted between November 2013 and June 2022 at two tertiary comprehensive hospitals. Cox regression and nomogram models were used to demonstrate the value of BNP level in predicting 30-day mortality rates. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were used to compare the ability of the two models to predict 30-day mortality risk.
BNP level was a predictive factor for 30-day mortality (hazard ratio [HR] = 1.441; 95 % confidence interval [CI] = 1.198-1.734). The area under curves (AUCs) of BNP level alone and model 2 (male sex, age, non-shockable rhythm, epinephrine, and time to ROSC >30 min) for predicting 30-day mortality were similar(0.813 versus 0.834). Model 1 that included the variables in model 2 and BNP level showed good predictive value (area under curve = 0.887; 95 % CI = 0.836-0.939). Compared to Model 2, Model 1 showed improved comprehensive differentiation and net weight classification of mortality prediction, further demonstrating the predictive value of BNP for 30-day mortality (NRI = 0.451, 95 % CI = 0.267-0.577; IDI = 0.109, 95 % CI = 0.035-0.191).
BNP level was a predictive factor for 30-day mortality after ROSC in patients with CA of presumed cardiac etiology who regained ROSC. The nomogram model included BNP may provide a reference for predicting 30-day mortality.
确定脑利钠肽（BNP）水平对推定心源性心搏骤停（CA）患者自主循环恢复（ROSC）后 30 天死亡率的预测价值。
本回顾性研究纳入了 2013 年 11 月至 2022 年 6 月在两家三级综合医院接受治疗的 260 例推定心源性 CA 并恢复 ROSC 的患者。采用 Cox 回归和列线图模型来证明 BNP 水平在预测 30 天死亡率方面的价值。净重新分类改善（NRI）和综合判别改善（IDI）用于比较两种模型预测 30 天死亡风险的能力。
BNP 水平是 30 天死亡率的预测因素（危险比 [HR] = 1.441；95%置信区间 [CI] = 1.198-1.734）。BNP 水平单独以及模型 2（男性、年龄、非可除颤节律、肾上腺素和 ROSC 时间>30 分钟）预测 30 天死亡率的曲线下面积（AUCs）相似（0.813 与 0.834）。包含模型 2 中变量和 BNP 水平的模型 1 显示出良好的预测价值（AUC = 0.887；95%CI = 0.836-0.939）。与模型 2 相比，模型 1 显示出对死亡率预测的综合区分度和净分类权重的改善，进一步证明了 BNP 对 30 天死亡率的预测价值（NRI = 0.451，95%CI = 0.267-0.577；IDI = 0.109，95%CI = 0.035-0.191）。
BNP 水平是推定心源性 CA 患者 ROSC 后 30 天死亡率的预测因素。纳入 BNP 的列线图模型可为预测 30 天死亡率提供参考。
