Levine Cardiac Intensive Care Unit, TIMI Study Group, Cardiovascular Division, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 60 Fenwood Rd, Suite 7022, Boston, MA 02115, USA.
Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
Eur Heart J Acute Cardiovasc Care. 2022 Mar 16;11(3):252-257. doi: 10.1093/ehjacc/zuac012.
Contemporary cardiac intensive care unit (CICU) outcomes remain highly heterogeneous. As such, a risk-stratification tool using readily available lab data at time of CICU admission may help inform clinical decision-making.
The primary derivation cohort included 4352 consecutive CICU admissions across 25 tertiary care CICUs included in the Critical Care Cardiology Trials Network (CCCTN) Registry. Candidate lab indicators were assessed using multivariable logistic regression. An integer risk score incorporating the top independent lab indicators associated with in-hospital mortality was developed. External validation was performed in a separate CICU cohort of 9716 patients from the Mayo Clinic (Rochester, MN, USA). On multivariable analysis, lower pH [odds ratio (OR) 1.96, 95% confidence interval (CI) 1.72-2.24], higher lactate (OR 1.40, 95% CI 1.22-1.62), lower estimated glomerular filtration rate (OR 1.26, 95% CI 1.10-1.45), and lower platelets (OR 1.18, 95% CI 1.05-1.32) were the top four independent lab indicators associated with higher in-hospital mortality. Incorporated into the CCCTN Lab-Based Risk Score, these four lab indicators identified a 20-fold gradient in mortality risk with very good discrimination (C-index 0.82, 95% CI 0.80-0.84) in the derivation cohort. Validation of the risk score in a separate cohort of 3888 patients from the Registry demonstrated good performance (C-index of 0.82; 95% CI 0.80-0.84). Performance remained consistent in the external validation cohort (C-index 0.79, 95% CI 0.77-0.80). Calibration was very good in both validation cohorts (r = 0.99).
A simple integer risk score utilizing readily available lab indicators at time of CICU admission may accurately stratify in-hospital mortality risk.
当代心脏重症监护病房(CICU)的预后仍然高度异质。因此,一种使用 CICU 入院时可获得的实验室数据进行风险分层的工具可能有助于指导临床决策。
主要的推导队列包括 25 个三级心脏重症监护病房中连续的 4352 例 CICU 入院患者,这些患者都包含在心脏重症监护临床试验网络(CCCTN)注册中心。使用多变量逻辑回归评估候选实验室指标。开发了一个整数风险评分,纳入了与住院死亡率相关的最重要的独立实验室指标。在来自美国明尼苏达州罗彻斯特市梅奥诊所的 9716 例单独的 CICU 队列中进行了外部验证。在多变量分析中,较低的 pH 值(比值比 [OR] 1.96,95%置信区间 [CI] 1.72-2.24)、较高的乳酸(OR 1.40,95% CI 1.22-1.62)、较低的估计肾小球滤过率(OR 1.26,95% CI 1.10-1.45)和较低的血小板计数(OR 1.18,95% CI 1.05-1.32)是与更高的住院死亡率相关的四个最重要的独立实验室指标。将这四个实验室指标纳入 CCCTN 基于实验室的风险评分中,可以识别出死亡率风险呈 20 倍梯度,且在推导队列中具有很好的区分度(C 指数为 0.82,95%CI 0.80-0.84)。在来自该注册中心的另外 3888 例患者的队列中验证风险评分的性能良好(C 指数为 0.82;95%CI 0.80-0.84)。在外部验证队列中,性能仍然一致(C 指数为 0.79,95%CI 0.77-0.80)。在两个验证队列中,校准都非常好(r=0.99)。
一种利用 CICU 入院时可获得的实验室指标的简单整数风险评分,可以准确分层住院死亡率风险。