儿科重症监护中疼痛、镇静、谵妄和医源性戒断综合征算法的有效性、质量及实施情况：一项系统评价和荟萃分析
Effectiveness, quality and implementation of pain, sedation, delirium, and iatrogenic withdrawal syndrome algorithms in pediatric intensive care: a systematic review and meta-analysis.
作者信息
MacDonald Ibo, de Goumoëns Véronique, Marston Mark, Alvarado Silvia, Favre Eva, Trombert Alexia, Perez Maria-Helena, Ramelet Anne-Sylvie
机构信息
Institute of Higher Education and Research in Healthcare, University of Lausanne, Lausanne, Switzerland.
La Source School of Nursing, HES-SO University of Applied Sciences and Arts Western Switzerland, Lausanne, Switzerland.
出版信息
Front Pediatr. 2023 Jun 16;11:1204622. doi: 10.3389/fped.2023.1204622. eCollection 2023.
BACKGROUND
Pain, sedation, delirium, and iatrogenic withdrawal syndrome are conditions that often coexist, algorithms can be used to assist healthcare professionals in decision making. However, a comprehensive review is lacking. This systematic review aimed to assess the effectiveness, quality, and implementation of algorithms for the management of pain, sedation, delirium, and iatrogenic withdrawal syndrome in all pediatric intensive care settings.
METHODS
A literature search was conducted on November 29, 2022, in PubMed, Embase, CINAHL and Cochrane Library, ProQuest Dissertations & Theses, and Google Scholar to identify algorithms implemented in pediatric intensive care and published since 2005. Three reviewers independently screened the records for inclusion, verified and extracted data. Included studies were assessed for risk of bias using the JBI checklists, and algorithm quality was assessed using the PROFILE tool (higher % = higher quality). Meta-analyses were performed to compare algorithms to usual care on various outcomes (length of stay, duration and cumulative dose of analgesics and sedatives, length of mechanical ventilation, and incidence of withdrawal).
RESULTS
From 6,779 records, 32 studies, including 28 algorithms, were included. The majority of algorithms (68%) focused on sedation in combination with other conditions. Risk of bias was low in 28 studies. The average overall quality score of the algorithm was 54%, with 11 (39%) scoring as high quality. Four algorithms used clinical practice guidelines during development. The use of algorithms was found to be effective in reducing length of stay (intensive care and hospital), length of mechanical ventilation, duration of analgesic and sedative medications, cumulative dose of analgesics and sedatives, and incidence of withdrawal. Implementation strategies included education and distribution of materials (95%). Supportive determinants of algorithm implementation included leadership support and buy-in, staff training, and integration into electronic health records. The fidelity to algorithm varied from 8.2% to 100%.
CONCLUSIONS
The review suggests that algorithm-based management of pain, sedation and withdrawal is more effective than usual care in pediatric intensive care settings. There is a need for more rigorous use of evidence in the development of algorithms and the provision of details on the implementation process.
SYSTEMATIC REVIEW REGISTRATION
https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021276053, PROSPERO [CRD42021276053].
背景
疼痛、镇静、谵妄和医源性戒断综合征常同时存在，算法可用于协助医疗保健专业人员进行决策。然而，目前缺乏全面的综述。本系统综述旨在评估所有儿科重症监护环境中用于管理疼痛、镇静、谵妄和医源性戒断综合征的算法的有效性、质量和实施情况。
方法
于2022年11月29日在PubMed、Embase、CINAHL和Cochrane图书馆、ProQuest学位论文数据库以及谷歌学术上进行文献检索，以识别2005年以来在儿科重症监护中实施并发表的算法。三位评审员独立筛选纳入记录，核实并提取数据。使用JBI清单评估纳入研究的偏倚风险，使用PROFILE工具评估算法质量（百分比越高 = 质量越高）。进行荟萃分析以比较算法与常规护理在各种结局（住院时间、镇痛和镇静药物的持续时间和累积剂量、机械通气时间以及戒断发生率）方面的差异。
结果
从6779条记录中，纳入了32项研究，包括28种算法。大多数算法（68%）侧重于镇静并结合其他情况。28项研究的偏倚风险较低。算法的平均总体质量得分为54%，其中11项（39%）得分较高。4种算法在开发过程中使用了临床实践指南。研究发现，使用算法可有效缩短住院时间（重症监护和医院）、机械通气时间、镇痛和镇静药物的持续时间、镇痛和镇静药物的累积剂量以及戒断发生率。实施策略包括教育和材料分发（95%）。算法实施的支持性决定因素包括领导支持和认同、员工培训以及整合到电子健康记录中。算法的依从性从8.2%到100%不等。
结论
该综述表明，在儿科重症监护环境中，基于算法的疼痛、镇静和戒断管理比常规护理更有效。在算法开发过程中需要更严格地使用证据，并提供实施过程的详细信息。
系统综述注册
https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021276053，PROSPERO [CRD42021276053]。
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