Department of Emergency Medicine, University of Ottawa, Ottawa, Ontario, Canada.
Acad Emerg Med. 2013 Jan;20(1):17-26. doi: 10.1111/acem.12056.
There are no validated guidelines to guide physicians with difficult disposition decisions for emergency department (ED) patients with heart failure (HF). The authors sought to develop a risk scoring system to identify HF patients at high risk for serious adverse events (SAEs).
This was a prospective cohort study at six large Canadian EDS that enrolled adult patients who presented with acute decompensated HF. Each patient was assessed for standardized clinical and laboratory variables as well as for SAEs defined as death, intubation, admission to a monitored unit, or relapse requiring admission. Adjusted odds ratios for predictors of SAEs were calculated by stepwise logistic regression.
In 559 visits, 38.1% resulted in patient admission. Of 65 (11.6%) SAE cases, 31 (47.7%) occurred in patients not initially admitted. The multivariate model and resultant Ottawa Heart Failure Risk Scale consists of 10 elements, and the risk of SAEs varied from 2.8% to 89.0%, with good calibration between observed and expected probabilities. Internal validation showed the risk scores to be very accurate across 1,000 replications using the bootstrap method. A threshold of 1, 2, or 3 total scores for admission would be associated with sensitivities of 95.2, 80.6, or 64.5%, respectively, all better than current practice.
Many HF patients are discharged home from the ED and then suffer SAEs or death. The authors have developed an accurate risk scoring system that could ultimately be used to stratify the risk of poor outcomes and to enable rational and safe disposition decisions.
目前尚无经过验证的指南来指导医生对急诊科（ED）心力衰竭（HF）患者进行困难处置决策。作者旨在开发一种风险评分系统，以识别 HF 患者发生严重不良事件（SAE）的高危人群。
这是一项在加拿大 6 家大型急诊科进行的前瞻性队列研究，纳入了因急性失代偿性 HF 就诊的成年患者。每位患者均接受了标准化的临床和实验室变量评估，以及定义为死亡、插管、入住监护病房或需要再次入院的 SAE。通过逐步逻辑回归计算预测 SAE 的预测因素的调整比值比。
在 559 次就诊中，38.1%的患者接受了入院治疗。在 65 例（11.6%）SAE 病例中，有 31 例（47.7%）最初未入院的患者发生了 SAE。多变量模型和由此产生的渥太华心力衰竭风险评分由 10 个要素组成，SAE 风险从 2.8%到 89.0%不等，观察到的和预期的概率之间具有良好的校准。内部验证表明，使用 bootstrap 方法在 1000 次重复中，风险评分非常准确。总分为 1、2 或 3 的入院阈值将分别与 95.2%、80.6%或 64.5%的敏感性相关，均优于目前的实践。
许多 HF 患者从 ED 出院后会发生 SAE 或死亡。作者开发了一种准确的风险评分系统，最终可用于分层不良结局的风险，并实现合理和安全的处置决策。
