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用于儿科、新生儿和孕产妇住院患者脓毒症早期检测的计算机化临床决策支持系统:范围综述

Computerized Clinical Decision Support Systems for the Early Detection of Sepsis Among Pediatric, Neonatal, and Maternal Inpatients: Scoping Review.

作者信息

Ackermann Khalia, Baker Jannah, Festa Marino, McMullan Brendan, Westbrook Johanna, Li Ling

机构信息

Centre for Health Systems and Safety Research, Australian Institute of Health Innovation, Macquarie University, Australia.

Kids Critical Care Research, Department of Paediatric Intensive Care, Children's Hospital at Westmead, Sydney, Australia.

出版信息

JMIR Med Inform. 2022 May 6;10(5):e35061. doi: 10.2196/35061.

Abstract

BACKGROUND

Sepsis is a severe condition associated with extensive morbidity and mortality worldwide. Pediatric, neonatal, and maternal patients represent a considerable proportion of the sepsis burden. Identifying sepsis cases as early as possible is a key pillar of sepsis management and has prompted the development of sepsis identification rules and algorithms that are embedded in computerized clinical decision support (CCDS) systems.

OBJECTIVE

This scoping review aimed to systematically describe studies reporting on the use and evaluation of CCDS systems for the early detection of pediatric, neonatal, and maternal inpatients at risk of sepsis.

METHODS

MEDLINE, Embase, CINAHL, Cochrane, Latin American and Caribbean Health Sciences Literature (LILACS), Scopus, Web of Science, OpenGrey, ClinicalTrials.gov, and ProQuest Dissertations and Theses Global (PQDT) were searched by using a search strategy that incorporated terms for sepsis, clinical decision support, and early detection. Title, abstract, and full-text screening was performed by 2 independent reviewers, who consulted a third reviewer as needed. One reviewer performed data charting with a sample of data. This was checked by a second reviewer and via discussions with the review team, as necessary.

RESULTS

A total of 33 studies were included in this review-13 (39%) pediatric studies, 18 (55%) neonatal studies, and 2 (6%) maternal studies. All studies were published after 2011, and 27 (82%) were published from 2017 onward. The most common outcome investigated in pediatric studies was the accuracy of sepsis identification (9/13, 69%). Pediatric CCDS systems used different combinations of 18 diverse clinical criteria to detect sepsis across the 13 identified studies. In neonatal studies, 78% (14/18) of the studies investigated the Kaiser Permanente early-onset sepsis risk calculator. All studies investigated sepsis treatment and management outcomes, with 83% (15/18) reporting on antibiotics-related outcomes. Usability and cost-related outcomes were each reported in only 2 (6%) of the 31 pediatric or neonatal studies. Both studies on maternal populations were short abstracts.

CONCLUSIONS

This review found limited research investigating CCDS systems to support the early detection of sepsis among pediatric, neonatal, and maternal patients, despite the high burden of sepsis in these vulnerable populations. We have highlighted the need for a consensus definition for pediatric and neonatal sepsis and the study of usability and cost-related outcomes as critical areas for future research.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/24899.

摘要

背景

脓毒症是一种在全球范围内与高发病率和死亡率相关的严重病症。儿科、新生儿和孕产妇患者在脓毒症负担中占相当大的比例。尽早识别脓毒症病例是脓毒症管理的关键支柱,并促使了嵌入计算机化临床决策支持(CCDS)系统中的脓毒症识别规则和算法的发展。

目的

本范围综述旨在系统描述关于使用和评估CCDS系统以早期检测有脓毒症风险的儿科、新生儿和孕产妇住院患者的研究。

方法

通过使用包含脓毒症、临床决策支持和早期检测术语的检索策略,对MEDLINE、Embase、CINAHL、Cochrane、拉丁美洲和加勒比卫生科学文献数据库(LILACS)、Scopus、科学引文索引、OpenGrey、临床试验.gov以及ProQuest全球学位论文和论文数据库(PQDT)进行检索。由2名独立评审员进行标题、摘要和全文筛选,必要时咨询第三名评审员。一名评审员对一部分数据进行数据制表。必要时由第二名评审员并通过与评审团队讨论进行核对。

结果

本综述共纳入33项研究——13项(39%)儿科研究、18项(55%)新生儿研究和2项(6%)孕产妇研究。所有研究均在2011年后发表,27项(82%)于2017年及以后发表。儿科研究中调查的最常见结果是脓毒症识别的准确性(9/13,69%)。在13项已确定的研究中,儿科CCDS系统使用了18种不同临床标准的不同组合来检测脓毒症。在新生儿研究中,78%(即14/18)的研究调查了凯撒医疗机构早发型脓毒症风险计算器。所有研究均调查了脓毒症治疗和管理结果,83%(15/18)报告了与抗生素相关的结果。在31项儿科或新生儿研究中,仅有2项(6%)报告了可用性和成本相关结果。两项关于孕产妇人群的研究均为简短摘要。

结论

本综述发现,尽管这些弱势群体中脓毒症负担很高,但针对支持儿科、新生儿和孕产妇患者脓毒症早期检测的CCDS系统的研究有限。我们强调需要为儿科和新生儿脓毒症制定共识定义,并将可用性和成本相关结果的研究作为未来研究的关键领域。

国际注册报告识别号(IRRID):RR2-10.2196/24899 。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b02/9123549/3b47b0f20a9a/medinform_v10i5e35061_fig1.jpg

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