Aim

Mathematical optimization of automated external defibrillator (AED) placement has demonstrated potential to improve survival of out-of-hospital cardiac arrest (OHCA). Existing models mostly aim to improve accessibility based on coverage radius and do not account for detailed impact of delayed defibrillation on survival. We aimed to predict OHCA survival based on time to defibrillation and developed an AED placement model to directly maximize the expected survival rate.

Methods

We stratified OHCAs occurring in Singapore (2010 to 2017) based on time to defibrillation and developed a regression model to predict the Utstein survival rate. We then developed a novel AED placement model, the maximum expected survival rate (MESR) model. We compared the performance of MESR with a maximum coverage model developed for Canada that was shown to be generalizable to other settings (Denmark). The survival gain of MESR was assessed through 10-fold cross-validation for placement of 20 to 1000 new AEDs in Singapore. Statistical analysis was performed using ${\chi }^2$ and McNemar’s tests.

Results

During the study period, 15,345 OHCAs occurred. The power-law approximation with R² of 91.33% performed best among investigated models. It predicted a survival of 54.9% with defibrillation within the first two minutes after collapse that was reduced by more than 60% without defibrillation within the first 4 minutes. MESR outperformed the maximum coverage model with P-value <0.05 (<0.0001 in 22 of 30 experiments).

Conclusion

We developed a novel AED placement model based on the impact of time to defibrillation on OHCA outcomes. Mathematical optimization can improve OHCA survival.

中文翻译：

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公共访问除颤器放置的最大预期存活率模型

目的

自动体外除颤器 (AED) 放置的数学优化已证明有可能提高院外心脏骤停 (OHCA) 的存活率。现有模型主要旨在根据覆盖半径提高可访问性，并没有考虑延迟除颤对生存的详细影响。我们旨在根据除颤时间预测 OHCA 存活率，并开发了 AED 放置模型以直接最大化预期存活率。

方法

我们根据除颤时间对新加坡（2010 年至 2017 年）发生的 OHCA 进行分层，并开发了一个回归模型来预测 Utstein 存活率。然后，我们开发了一种新的 AED 放置模型，即最大预期存活率 (MESR) 模型。我们将 MESR 的性能与为加拿大开发的最大覆盖模型进行了比较，该模型被证明可推广到其他环境（丹麦）。通过在新加坡放置 20 至 1000 个新 AED 的 10 倍交叉验证评估 MESR 的生存增益。使用进行统计分析${\chi }^2$和 McNemar 的测试。

结果

在研究期间，发生了 15,345 次 OHCA。R ²为 91.33%的幂律近似在所研究的模型中表现最好。它预测在崩溃后的前两分钟内进行除颤的存活率为 54.9%，而在前 4 分钟内未进行除颤的存活率降低了 60% 以上。MESR 优于最大覆盖率模型，P值 <0.05（30 次实验中有 22 次小于 0.0001）。

结论

我们基于除颤时间对 OHCA 结果的影响开发了一种新的 AED 放置模型。数学优化可以提高 OHCA 的存活率。