Department of Emergency Medicine, College of Medicine, Korea University, Goryeodae-ro 73, Seongbuk-gu, Seoul, 02841, Republic of Korea.
Clinical Research Center, Asan Institute for Life Sciences, Asan Medical Center, 88 Olympic-ro 43gil, Songpa-gu, Seoul, 05505, Republic of Korea.
Crit Care. 2021 Jan 18;25(1):29. doi: 10.1186/s13054-020-03408-1.
A prediction model of mortality for patients with acute poisoning has to consider both poisoning-related characteristics and patients' physiological conditions; moreover, it must be applicable to patients of all ages. This study aimed to develop a scoring system for predicting in-hospital mortality of patients with acute poisoning at the emergency department (ED).
This was a retrospective analysis of the Injury Surveillance Cohort generated by the Korea Center for Disease Control and Prevention (KCDC) during 2011-2018. We developed the new-Poisoning Mortality Scoring system (new-PMS) to generate a prediction model using the derivation group (2011-2017 KCDC cohort). Points were computed for categories of each variable. The sum of these points was the new-PMS. The validation group (2018 KCDC cohort) was subjected to external temporal validation. The performance of new-PMS in predicting mortality was evaluated using area under the receiver operating characteristic curve (AUROC) for both the groups.
Of 57,326 poisoning cases, 42,568 were selected. Of these, 34,352 (80.7%) and 8216 (19.3%) were enrolled in the derivation and validation groups, respectively. The new-PMS was the sum of the points for each category of 10 predictors. The possible range of the new-PMS was 0-137 points. Hosmer-Lemeshow goodness-of-fit test showed adequate calibration for the new-PMS with p values of 0.093 and 0.768 in the derivation and validation groups, respectively. AUROCs of the new-PMS were 0.941 (95% CI 0.934-0.949, p < 0.001) and 0.946 (95% CI 0.929-0.964, p < 0.001) in the derivation and validation groups, respectively. The sensitivity, specificity, and accuracy of the new-PMS (cutoff value: 49 points) were 86.4%, 87.2%, and 87.2% and 85.9%, 89.5%, and 89.4% in the derivation and validation groups, respectively.
We developed a new-PMS system based on demographic, poisoning-related variables, and vital signs observed among patients at the ED. The new-PMS showed good performance for predicting in-hospital mortality in both the derivation and validation groups. The probability of death increased according to the increase in the new-PMS. The new-PMS accurately predicted the probability of death for patients with acute poisoning. This could contribute to clinical decision making for patients with acute poisoning at the ED.
急性中毒患者的死亡率预测模型必须同时考虑中毒相关特征和患者的生理状况;此外,它必须适用于所有年龄段的患者。本研究旨在开发一种用于预测急诊科(ED)急性中毒患者住院死亡率的评分系统。
这是对韩国疾病控制和预防中心(KCDC)在 2011-2018 年期间生成的伤害监测队列进行的回顾性分析。我们使用推导组(2011-2017 KCDC 队列)开发了新的中毒死亡率评分系统(new-PMS)来生成预测模型。为每个变量类别的类别计算分数。这些分数的总和即为 new-PMS。验证组(2018 KCDC 队列)进行了外部时间验证。使用两组的接收者操作特征曲线(AUROC)评估 new-PMS 在预测死亡率方面的性能。
在 57326 例中毒病例中,选择了 42568 例。其中,推导组和验证组分别纳入 34352 例(80.7%)和 8216 例(19.3%)。new-PMS 是 10 个预测因子的每个类别分数的总和。new-PMS 的可能范围为 0-137 分。Hosmer-Lemeshow 拟合优度检验显示 new-PMS 在推导组和验证组中的拟合度良好,p 值分别为 0.093 和 0.768。new-PMS 的 AUROCs 在推导组和验证组中分别为 0.941(95%CI 0.934-0.949,p<0.001)和 0.946(95%CI 0.929-0.964,p<0.001)。new-PMS(截断值:49 分)在推导组和验证组中的灵敏度、特异性和准确度分别为 86.4%、87.2%和 87.2%和 85.9%、89.5%和 89.4%。
我们基于急诊科患者的人口统计学、中毒相关变量和生命体征开发了一种新的 PMS 系统。new-PMS 在推导组和验证组中均具有良好的预测住院死亡率的性能。根据 new-PMS 的增加,死亡的概率增加。new-PMS 准确预测了急性中毒患者的死亡概率。这有助于急诊科急性中毒患者的临床决策。