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心脏手术后高敏肌钙蛋白T检测用于预测死亡率的时机和阈值:一项回顾性队列分析

Timing and threshold of high sensitive troponin T measurement for the prediction of mortality after cardiac surgery: a retrospective cohort analysis.

作者信息

Koköfer Andreas, Cozowicz Crispiana, Wernly Bernhard, Rodemund Niklas

机构信息

Department of Anaesthesiology, Perioperative Medicine and Intensive Care Medicine, Paracelsus Medical University of Salzburg, Salzburg, Austria.

Center for Public Health and Healthcare Research, Paracelsus Medical University of Salzburg, Salzburg, Austria.

出版信息

Intensive Care Med Exp. 2023 Sep 1;11(1):58. doi: 10.1186/s40635-023-00545-z.

DOI:10.1186/s40635-023-00545-z
PMID:37656268
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10473995/
Abstract

BACKGROUND

High sensitive cardiac troponin T (hsTnT) is a widely used biomarker of myocardial injury. Along with other high sensitive troponins, HsTnT can predict mortality in both cardiac and non-cardiac surgery. The aim of this study was to determine the association between hsTnT serum elevations in the immediate postoperative period until 120 h after cardiac surgery and the occurrence of in-hospital mortality compared to the Simplified Acute Physiology Score 3 (SAPS3). Additionally, we identified an ideal hsTnT serum threshold to predict in-hospital mortality.

METHODS

We performed a retrospective single-institutional cohort analysis of 2179 patients undergoing cardiac surgery with cardiopulmonary bypass from 2013 to 2021. Logistic regression analysis was used to investigate an association of hsTnT at various time points and in-hospital mortality. The model was adjusted for relevant covariates including SAPS3, lactate and administered norepinephrine dosage. ROC analysis was performed to estimate the accuracy to predict mortality by serum hsTnT concentrations. This prediction was compared to the SAPS3 score. An ideal cutoff of hsTnT concentration was calculated by means of Youden index.

RESULTS

In total 7576 troponins were measured at the predefined timepoints. 100 (4.59%) patients died during the hospital stay. The fourth hsTnT on d3 (at 96-120 h postoperatively) showed the highest association with in-hospital death (OR 1.56; 95% CI (1.39-1.76); p < 0.001). This finding persisted after multivariable adjustment (aOR 1.34; 95% CI (1.18-1.53); p < 0.001). In contrast, the third hsTnT on d2 (at 48-72 h postoperatively) showed the best discrimination for in-hospital mortality (AUC 82.75%; 95% CI (0.77-0.89). The prediction by the third hsTnT was comparable to the in-hospital mortality prediction by SAPS3 (AUC 79.36%; 95% CI (0.73-0.85); p = 0.056). The optimal cutoff for the third hsTnT was calculated to be 1264 ng/L (Sensitivity 0.62; Specificity 0.88).

CONCLUSION

Elevated hsTnT after cardiac surgery was associated with an increased risk of in-hospital mortality. HsTnT measured on postoperative day 2 and 3 were most accurate to predict in-hospital mortality. The prediction of in-hospital mortality using hsTNT is comparable to mortality prediction using the SAPS3 score. HsTnT serum levels currently recommended to establish clinically important periprocedural myocardial injury are lower than thresholds identified in this study.

摘要

背景

高敏心肌肌钙蛋白T(hsTnT)是一种广泛应用的心肌损伤生物标志物。与其他高敏肌钙蛋白一样,HsTnT可预测心脏手术和非心脏手术的死亡率。本研究的目的是确定心脏手术后直至术后120小时即刻术后期间hsTnT血清升高与院内死亡率之间的关联,并与简化急性生理学评分3(SAPS3)进行比较。此外,我们确定了一个预测院内死亡率的理想hsTnT血清阈值。

方法

我们对2013年至2021年接受体外循环心脏手术的2179例患者进行了回顾性单机构队列分析。采用逻辑回归分析来研究不同时间点的hsTnT与院内死亡率之间的关联。该模型针对包括SAPS3、乳酸和去甲肾上腺素给药剂量在内的相关协变量进行了调整。进行ROC分析以评估血清hsTnT浓度预测死亡率的准确性。将该预测结果与SAPS3评分进行比较。通过约登指数计算hsTnT浓度的理想临界值。

结果

在预定时间点共检测了7576次肌钙蛋白。100例(4.59%)患者在住院期间死亡。术后第3天(术后96 - 120小时)的第四次hsTnT与院内死亡的关联最强(OR 1.56;95% CI(1.39 - 1.76);p < 0.001)。经过多变量调整后,这一发现仍然存在(校正OR 1.34;95% CI(1.18 - 1.53);p < 0.001)。相比之下,术后第2天(术后48 - 72小时)的第三次hsTnT对院内死亡率的区分能力最佳(AUC 82.75%;95% CI(0.77 - 0.89)。第三次hsTnT的预测与SAPS3对院内死亡率的预测相当(AUC 79.36%;95% CI(0.73 - 0.85);p = 0.056)。第三次hsTnT的最佳临界值经计算为1264 ng/L(敏感性0.62;特异性0.88)。

结论

心脏手术后hsTnT升高与院内死亡风险增加相关。术后第2天和第3天测量的HsTnT对预测院内死亡率最为准确。使用hsTNT预测院内死亡率与使用SAPS3评分预测死亡率相当。目前推荐用于确定临床上重要的围手术期心肌损伤的hsTnT血清水平低于本研究中确定的阈值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce27/10473995/3b63e7b3c57b/40635_2023_545_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce27/10473995/ec9999225245/40635_2023_545_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce27/10473995/6f0e080e0b69/40635_2023_545_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce27/10473995/3b63e7b3c57b/40635_2023_545_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce27/10473995/ec9999225245/40635_2023_545_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce27/10473995/6f0e080e0b69/40635_2023_545_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce27/10473995/3b63e7b3c57b/40635_2023_545_Fig3_HTML.jpg

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