Department of Surgery, Kushiro City General Hospital, 1-12, Shunko-Dai, Kushiro City, Hokkaido, 085-0822, Japan.
Department of Emergency Medicine, Hokkaido University Hospital, Sapporo, Hokkaido, Japan.
BMC Emerg Med. 2022 Nov 4;22(1):177. doi: 10.1186/s12873-022-00734-1.
A shortage of donor organs amid high demand for transplantable organs is a worldwide problem, and an increase in organ donation would be welcomed by the global healthcare system. Patients with brain death (BD) are potential organ donors, and early prediction of patients with BD may facilitate the process of organ procurement. Therefore, we developed a model for the early prediction of BD in patients who survived the initial phase of out-of-hospital cardiac arrest (OHCA).
We retrospectively analyzed data of patients aged < 80 years who experienced OHCA with a return of spontaneous circulation (ROSC) and were admitted to our hospital between 2006 and 2018. We categorized patients into either a non-BD or BD group. Demographic and laboratory data on ED admission were used for stepwise logistic regression analysis. Prediction scores of BD after OHCA were based on β-coefficients of prognostic factors identified in the multivariable logistic model.
Overall, 419 OHCA patients with ROSC were admitted to our hospital during the study period. Seventy-seven patients showed BD (18.3%). Age and etiology of OHCA were significantly different between the groups. Logistic regression analysis confirmed that age, low-flow time, pH, and etiology were independent predictors of BD. The area under the receiver operating characteristic curve for this model was 0.831 (95% confidence interval, 0.786-0.876).
We developed and internally validated a new prediction model for BD after OHCA, which could aid in the early identification of potential organ donors for early donor organ procurement.
在器官移植需求高的情况下，供体器官短缺是一个全球性问题，全球医疗体系都将欢迎增加器官捐赠。脑死亡（BD）患者是潜在的器官捐献者，早期预测 BD 患者可能有助于器官获取过程。因此，我们开发了一种模型，用于预测在院外心脏骤停（OHCA）初始阶段存活的患者的 BD。
我们回顾性分析了 2006 年至 2018 年间在我院接受治疗的年龄<80 岁、经历 OHCA 且自主循环恢复（ROSC）的患者的数据。我们将患者分为非 BD 或 BD 组。使用 ED 入院时的人口统计学和实验室数据进行逐步逻辑回归分析。BD 预测评分基于多变量逻辑模型中确定的预后因素的β系数。
在研究期间，共有 419 名 ROSC 的 OHCA 患者入住我院。77 例患者表现为 BD（18.3%）。两组患者的年龄和 OHCA 病因差异有统计学意义。逻辑回归分析证实，年龄、低血流时间、pH 值和病因是 BD 的独立预测因素。该模型的受试者工作特征曲线下面积为 0.831（95%置信区间，0.786-0.876）。
我们开发并内部验证了一种新的 OHCA 后 BD 预测模型，该模型有助于早期识别潜在的器官捐献者，以便进行早期供体器官获取。
