The 6-hour lactate clearance rate in predicting 30-day mortality in cardiogenic shock

Junfeng Wang, Mingxia Ji
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引用次数: 0

Abstract

Background

Early evaluation of prognosis in cardiogenic shock (CS) is crucial for tailored treatment selection. Both lactate clearance and lactate levels are considered useful prognostic biomarkers in patients with CS. However, there is yet no literature comparing the 6-hour lactate clearance rate (Δ6Lac) with lactate levels measured at admission (L1) and after 6 h (L2) to predict 30-day mortality in CS.

Methods

In this observational cohort study, 95 patients with CS were treated at Department of Intensive Care Unit, Yiwu Central Hospital between January 2020 and December 2022. Of these, 88 patients met the eligibility criteria. The lactate levels were measured after admission (L1) as the baseline lactate value, and were measured after 6 h (L2) following admission. The primary endpoint of the study was survival rate at 30 days. A receiver operating characteristic curve was used for data analysis. Univariate and multivariate Cox regression analyses were performed based on Δ6Lac. Kaplan–Meier (KM) survival curves were generated to compare the 30-day survival rates among L1, L2, and Δ6Lac.

Results

The Δ6Lac model showed the highest area under the curve value (0.839), followed by the L2 (0.805) and L1 (0.668) models. The Δ6Lac model showed a sensitivity of 84.2% and specificity of 75.4%. The L1 and L2 models had sensitivities of 57.9% each and specificities of 89.9% and 98.6%, respectively. The cut-off values for Δ6Lac, L1, and L2 were 18.2%, 6.7 mmol/L, and 6.1 mmol/L, respectively. Univariate Cox regression analysis revealed a significant association between Δ6Lac and 30-day mortality. After adjusting for five models in multivariate Cox regression, Δ6Lac remained a significant risk factor for 30-day mortality in patients with CS. In our fifth multivariate Cox regression model, Δ6Lac remained a risk factor associated with 30-day mortality (hazard ratio [HR]=5.14, 95% confidence interval [CI]: 1.48 to 17.89, P=0.010) as well as L2 (HR=8.42, 95% CI: 1.26 to 56.22, P=0.028). The KM survival curve analysis revealed that L1 >6.7 mmol/L (HR=8.08, 95% CI: 3.23 to 20.20, P <0.001), L2 >6.1 mmol/L (HR=25.97, 95% CI: 9.76 to 69.15, P <0.001), and Δ6Lac ≤18.2% (HR=8.92, 95% CI: 2.95 to 26.95, P <0.001) were associated with a higher risk of 30-day mortality.

Conclusions

Δ6Lac is a better predictor for 30-day mortality in CS than lactate levels at admission. It has a predictive value equivalent to that of lactate level at 6 h after admission, making it an important surrogate indicator for evaluating the suitability as well as poor prognosis after CS treatment. We found that a cut-off value of 18.2% for Δ6Lac provided the most accurate assessment of early prognosis in CS.

预测心源性休克患者 30 天死亡率的 6 小时乳酸清除率
背景早期评估心源性休克(CS)的预后对于选择有针对性的治疗至关重要。乳酸清除率和乳酸水平都被认为是预测心源性休克患者预后的有用生物标志物。然而,目前还没有文献将6小时乳酸清除率(Δ6Lac)与入院时(L1)和6小时后(L2)测量的乳酸水平进行比较,以预测CS患者30天的死亡率。方法在这项观察性队列研究中,义乌市中心医院重症医学科在2020年1月至2022年12月期间收治了95例CS患者。其中,88 名患者符合资格标准。入院后测量的乳酸水平(L1)为基线乳酸值,入院后 6 小时后测量的乳酸水平(L2)为基线乳酸值。研究的主要终点是 30 天的存活率。数据分析采用接收器操作特征曲线。根据Δ6Lac进行了单变量和多变量Cox回归分析。结果 Δ6Lac模型的曲线下面积值最高(0.839),其次是L2模型(0.805)和L1模型(0.668)。Δ6Lac模型的灵敏度为84.2%,特异性为75.4%。L1 和 L2 模型的灵敏度分别为 57.9%,特异性分别为 89.9% 和 98.6%。Δ6Lac、L1 和 L2 的临界值分别为 18.2%、6.7 mmol/L 和 6.1 mmol/L。单变量 Cox 回归分析显示,Δ6Lac 与 30 天死亡率之间存在显著关联。在多变量 Cox 回归中对五个模型进行调整后,Δ6Lac 仍是 CS 患者 30 天死亡率的重要风险因素。在我们的第五个多变量 Cox 回归模型中,Δ6Lac 仍然是与 30 天死亡率相关的风险因素(危险比 [HR]=5.14, 95% 置信区间 [CI]:1.48至17.89,P=0.010)以及L2(HR=8.42,95% CI:1.26至56.22,P=0.028)。KM 生存曲线分析显示,L1 >6.7 mmol/L (HR=8.08, 95% CI: 3.23 to 20.20, P <0.001)、L2 >6.1 mmol/L (HR=25.97, 95% CI: 9.76 to 69.15, P <0.001)、Δ6Lac ≤18.2%(HR=8.结论与入院时的乳酸水平相比,Δ6Lac能更好地预测CS患者30天内的死亡率。结论Δ6Lac比入院时的乳酸水平更能预测CS患者的30天死亡率,其预测价值与入院后6小时的乳酸水平相当,因此它是评估CS治疗是否合适以及预后是否不良的重要替代指标。我们发现,Δ6Lac 的临界值为 18.2%,能最准确地评估 CS 的早期预后。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of intensive medicine
Journal of intensive medicine Critical Care and Intensive Care Medicine
CiteScore
1.90
自引率
0.00%
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审稿时长
58 days
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