Evaluation of hypotension prediction index software in patients undergoing orthotopic liver transplantation: retrospective observational study

IF 1.7 4区 医学 Q2 ANESTHESIOLOGY
Jacek B. Cywinski , Yufei Li , Lusine Israelyan , Roshni Sreedharan , Silvia Perez-Protto , Kamal Maheshwari
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引用次数: 0

Abstract

Background

Extreme hemodynamic changes, especially intraoperative hypotension (IOH), are common and often prolonged during Liver Transplant (LT) surgery and during initial hours of recovery. Hypotension Prediction Index (HPI) software is one of the tools which can help in proactive hemodynamic management. The accuracy of the advanced hemodynamic parameters such as Cardiac Output (CO) and Systemic Vascular Resistance (SVR) obtained from HPI software and prediction performance of the HPI in LT surgery remains unknown.

Methods

This was a retrospective observational study conducted in a tertiary academic center with a large liver transplant program. We enrolled 23 adult LT patients who received both Pulmonary Artery Catheter (PAC) and HPI software monitoring. Primarily, we evaluated agreement between PAC and HPI software measured CO and SVR. A priori, we defined a relative difference of less than 20% between measurements as an adequate agreement for a pair of measurements and estimated the Lin's Concordance Correlation Coefficient and Bland-Altman Limits of Agreement (LOA). Clinically acceptable LOA was defined as ± 1 L.min-1 for CO and ± 200 dynes s.cm-5 for SVR. Secondary outcome was the ability of the HPI to predict future hypotension, defined as Mean Arterial Pressure (MAP) less than 65 mmHg lasting at least one minute. We estimated sensitivity, positive predictive value, and time from alert to hypotensive events for HPI software.

Results

Overall, 125 pairs of CO and 122 pairs of SVR records were obtained from 23 patients. Based on our predefined criteria, only 42% (95% CI 30%, 55%) of CO records and 53% (95% CI 28%, 72%) of SVR records from HPI software were considered to agree with those from PAC. Across all patients, there were a total of 1860 HPI alerts (HPI ≥ 85) and 642 hypotensive events (MAP < 65 mmHg). Out of the 642 hypotensive events, 618 events were predicted by HPI alert with sensitivity of 0.96 (95% CI: 0.95). Many times, the HPI value remained above alert level and was followed by multiple hypotensive events. Thus, to evaluate PPV and time to hypotension metric, we considered only the first HPI alert followed by a hypotensive event (“true alerts”). The “true alert” was the first alert when there were several alerts before a hypotension. There were 614 “true alerts” and the PPV for HPI was 0.33 (95% CI 0.31, 0.35). The median time from HPI alert to hypotension was 3.3 [Q1, Q3: 1, 9.3] mins.

Conclusion

There was poor agreement between the pulmonary artery catheter and HPI software calculated advanced hemodynamic parameters (CO and SVR), in the patients undergoing LT surgery. HPI software had high sensitivity but poor specificity for hypotension prediction, resulting in a high burden of false alarms.
原位肝移植患者低血压预测指数软件的评价:回顾性观察研究。
背景:极端的血流动力学变化,特别是术中低血压(IOH),在肝移植(LT)手术和恢复的最初几个小时内是常见的,并且经常延长。低血压预测指数(HPI)软件是主动进行血流动力学管理的工具之一。HPI软件获得的心输出量(CO)和全身血管阻力(SVR)等高级血流动力学参数的准确性以及HPI在LT手术中的预测性能尚不清楚。方法:这是一项回顾性观察性研究,在一个大型肝移植项目的三级学术中心进行。我们招募了23名接受肺动脉导管(PAC)和HPI软件监测的成年LT患者。首先,我们评估了PAC和HPI软件测量CO和SVR之间的一致性。先验地,我们将测量值之间的相对差异小于20%定义为一对测量值的足够一致性,并估计了Lin’s一致性相关系数和Bland-Altman一致性极限(LOA)。临床上可接受的LOA定义为CO为±1 L.min-1, SVR为±200 dynes s.cm-5。次要结果是HPI预测未来低血压的能力,定义为平均动脉压(MAP)低于65 mmHg持续至少一分钟。我们估计了HPI软件的敏感性、阳性预测值和从警报到低血压事件的时间。结果:23例患者共获得125对CO和122对SVR记录。根据我们的预定义标准,HPI软件中只有42% (95% CI 30%, 55%)的CO记录和53% (95% CI 28%, 72%)的SVR记录被认为与PAC的记录一致。在所有患者中,共有1860次HPI警报(HPI≥85)和642次低血压事件(MAP< 65 mmHg)。在642例低血压事件中,HPI预警预测618例事件,敏感性为0.96 (95% CI: 0.95)。许多时候,HPI值保持在警戒水平以上,随后发生多次低血压事件。因此,为了评估PPV和降压时间指标,我们只考虑了第一次HPI警报之后的低血压事件(“真实警报”)。“真正的警报”是在低血压之前有几个警报时的第一个警报。有614例“真实警报”,HPI的PPV为0.33 (95% CI 0.31, 0.35)。从HPI警报到低血压的中位时间为3.3分钟[Q1, Q3: 1,9.3]分钟。结论:在接受LT手术的患者中,肺动脉导管与HPI软件计算的晚期血流动力学参数(CO和SVR)之间的一致性较差。HPI软件对低血压的预测敏感性高,但特异性差,导致虚警负担高。
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
CiteScore
2.10
自引率
0.00%
发文量
88
审稿时长
68 days
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