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比较新型临床评分与预测残余神经肌肉阻滞的残留神经肌肉阻滞预测评分和电子麻醉记录中最后一个四串计数:电子文件中存档的电子数据回顾性队列研究。

Comparison of a novel clinical score to estimate the risk of REsidual neuromuscular block Prediction Score and the last train-of-four count documented in the electronic anaesthesia record: A retrospective cohort study of electronic data on file.

机构信息

From the Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital (MIR, PYN, HD, FTS, SDG, TTH), Harvard Medical School, Boston, Massachusetts (MIR, PYN, HD, FTS, SDG, TTH, ME), Department of Adult Intensive Care, Queen Mary Hospital and The University of Hong Kong, Pok Fu Lam, Hong Kong (PYN), Department of Anesthesiology, Vanderbilt University School of Medicine, Nashville, Tennessee (JPW), Department of Anesthesia, Critical Care, and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA (ME) and Universitätsklinikum Essen, Essen, Germany (ME).

出版信息

Eur J Anaesthesiol. 2018 Nov;35(11):883-892. doi: 10.1097/EJA.0000000000000861.

Abstract

BACKGROUND

Residual neuromuscular block (rNMB) after surgery is not difficult to identify if proper neuromuscular monitoring is used, but many clinicians do not use quantitative neuromuscular monitoring.

OBJECTIVE

The aim of this study was to develop a REsidual neuromuscular block Prediction Score (REPS) to predict postoperative rNMB and compare the predictive accuracy of the prediction score with train-of-four count (TOFC) measurement at the end of a surgical case.

DESIGN

Retrospective cohort study of data on file.

DATA SOURCE

Electronic patient data and peri-operative data on vital signs, administered medications, and train-of-four ratio (TOFR) obtained in the postoperative recovery rooms [postanaesthesia care unit (PACU)] at Massachusetts General Hospital in Boston, Massachusetts, USA.

PATIENTS

Quantitative TOFR measurements obtained on admission to the PACU were available from 2144 adult noncardiac surgical patients.

MAIN OUTCOME MEASURE

Presence of rNMB at PACU admission, defined as a TOFR of less than 0.9.

RESULTS

In the score development cohort (n=2144), rNMB occurred in 432 cases (20.2%). Ten independent predictors for residual paralysis were identified and used for the score development. The final model included: hepatic failure, neurological disease, high-neostigmine dose, metastatic tumour, female sex, short time between neuromuscular blocking agent administration and extubation, aminosteroidal neuromuscular blocking agent, BMI more than 35, absence of nurse anaesthetist and having an experienced surgeon. The model discrimination by C statistics was 0.63, 95% confidence interval (0.60 to 0.66), and risk categories derived from the REPS had a higher accuracy than the last documented intra-operative TOFC for predicting rNMB (net reclassification improvement score 0.26, standard error 0.03, P < 0.001).

CONCLUSION

The REPS can be used to identify patients at greater risk of rNMB. This tool may inform anaesthetists better than an intra-operative TOFC and thus enable peri-operative anaesthetic practices to be tailored to the patient and minimise the undesirable effects of rNMB.

TRIAL REGISTRY NUMBER

Approved by Partners Human Research Committee (protocol number 2016P000940) at MGH in Boston, Massachusetts, USA on 25 April 2016.

摘要

背景

如果使用适当的神经肌肉监测,术后残余神经肌肉阻滞(rNMB)并不难识别,但许多临床医生不使用定量神经肌肉监测。

目的

本研究旨在开发一种残余神经肌肉阻滞预测评分(REPS),以预测术后 rNMB,并比较预测评分与手术结束时的四个成串刺激计数(TOFC)测量的预测准确性。

设计

回顾性队列研究,对文件中的数据进行分析。

数据来源

美国马萨诸塞州波士顿市马萨诸塞州综合医院(MGH)术后恢复室(PACU)中电子患者数据和围手术期生命体征、给予的药物以及四个成串刺激比(TOFR)的监测数据。

患者

纳入 2144 例非心脏手术成年患者,其 PACU 入院时获得定量 TOFR 测量值。

主要观察指标

PACU 入院时存在 rNMB,定义为 TOFR 小于 0.9。

结果

在评分开发队列(n=2144)中,432 例(20.2%)发生 rNMB。确定了 10 个独立的预测残余瘫痪的因素,并用于评分开发。最终模型包括:肝衰竭、神经疾病、高新斯的明剂量、转移性肿瘤、女性、神经肌肉阻滞剂给药与拔管之间时间短、氨基甾醇类神经肌肉阻滞剂、BMI 大于 35、无护士麻醉师和有经验的外科医生。C 统计的模型区分度为 0.63,95%置信区间(0.60 至 0.66),并且源自 REPS 的风险类别比最后记录的术中 TOFC 更能准确预测 rNMB(净重新分类改善评分 0.26,标准误 0.03,P<0.001)。

结论

REPS 可用于识别发生 rNMB 风险较高的患者。该工具可能比术中 TOFC 更能为麻醉师提供信息,从而使围手术期麻醉实践能够根据患者情况进行调整,并将 rNMB 的不良影响降到最低。

试验注册编号

2016 年 4 月 25 日在美国马萨诸塞州波士顿市 MGH 经合作伙伴人类研究委员会批准(协议编号 2016P000940)。

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