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预测并预防急诊科外周静脉留置针穿刺失败:临床医生的“直觉”再获成功。

Predicting and preventing peripheral intravenous cannula insertion failure in the emergency department: Clinician 'gestalt' wins again.

作者信息

Rippey James Cr, Carr Peter J, Cooke Marie, Higgins Niall, Rickard Claire M

机构信息

Emergency Medicine, School of Primary, Aboriginal and Rural Health Care, Faculty of Medicine, Dentistry and Health Services, The University of Western Australia, Perth, Western Australia, Australia.

Emergency Department, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia.

出版信息

Emerg Med Australas. 2016 Dec;28(6):658-665. doi: 10.1111/1742-6723.12695. Epub 2016 Nov 14.

Abstract

OBJECTIVE

Failed attempts at peripheral i.v. cannula (PIVC) insertion in the ED are common. The psychological, physical and economic impact of these failures is significant. We sought to explore whether clinicians of differing experience levels can predict their own likelihood (clinician 'gestalt') of first-time cannula insertion success on any given patient.

METHODS

Data analyses from a prospective self-reported study assessing risk factors for first-time insertion success in a tertiary adult ED. We constructed and compared two simple theoretical clinical decision algorithms in an attempt to improve first-time PIVC insertion success rates.

RESULTS

This best algorithm identified a subgroup of 18% of the total PIVC population at higher risk of failure. This 18% comprised 57% of all PIVC failures, and implementation would result in a relative risk reduction of PIVC failure by 31%.

CONCLUSIONS

When applied to our sample population, an algorithm relying on clinician gestalt to identify patients at high risk of PIVC failure had the greatest potential impact. These patients would be referred to expert PIVC inserters prior to, rather than after, failed attempts.

摘要

目的

在急诊科,外周静脉留置针(PIVC)穿刺失败很常见。这些失败所带来的心理、身体和经济影响颇为显著。我们试图探究不同经验水平的临床医生是否能够预测他们在任何给定患者身上首次穿刺成功的可能性(临床医生的“整体判断”)。

方法

对一项前瞻性自我报告研究进行数据分析,该研究评估了三级成人急诊科首次穿刺成功的风险因素。我们构建并比较了两种简单的理论临床决策算法,以试图提高首次PIVC穿刺成功率。

结果

这种最佳算法在整个PIVC人群中识别出了一个占比18%的高失败风险亚组。这18%的人群占所有PIVC穿刺失败病例的57%,采用该算法将使PIVC穿刺失败的相对风险降低31%。

结论

当应用于我们的样本人群时,一种依靠临床医生整体判断来识别PIVC穿刺高失败风险患者的算法具有最大的潜在影响。这些患者应在穿刺尝试失败之前而非之后被转介给专业的PIVC穿刺人员。

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