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追踪危重症患儿脓毒症的进展:用于检测血液功能障碍的临床决策支持。

Tracing the Progression of Sepsis in Critically Ill Children: Clinical Decision Support for Detection of Hematologic Dysfunction.

机构信息

Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, Hannover, Germany.

Department of Pediatric Cardiology and Intensive Care Medicine, Hannover Medical School, Germany.

出版信息

Appl Clin Inform. 2022 Oct;13(5):1002-1014. doi: 10.1055/a-1950-9637. Epub 2022 Sep 26.

Abstract

BACKGROUND

One of the major challenges in pediatric intensive care is the detection of life-threatening health conditions under acute time constraints and performance pressure. This includes the assessment of pediatric organ dysfunction (OD) that demands extraordinary clinical expertise and the clinician's ability to derive a decision based on multiple information and data sources. Clinical decision support systems (CDSS) offer a solution to support medical staff in stressful routine work. Simultaneously, detection of OD by using computerized decision support approaches has been scarcely investigated, especially not in pediatrics.

OBJECTIVES

The aim of the study is to enhance an existing, interoperable, and rule-based CDSS prototype for tracing the progression of sepsis in critically ill children by augmenting it with the capability to detect SIRS/sepsis-associated hematologic OD, and to determine its diagnostic accuracy.

METHODS

We reproduced an interoperable CDSS approach previously introduced by our working group: (1) a knowledge model was designed by following the commonKADS methodology, (2) routine care data was semantically standardized and harmonized using openEHR as clinical information standard, (3) rules were formulated and implemented in a business rule management system. Data from a prospective diagnostic study, including 168 patients, was used to estimate the diagnostic accuracy of the rule-based CDSS using the clinicians' diagnoses as reference.

RESULTS

We successfully enhanced an existing interoperable CDSS concept with the new task of detecting SIRS/sepsis-associated hematologic OD. We modeled openEHR templates, integrated and standardized routine data, developed a rule-based, interoperable model, and demonstrated its accuracy. The CDSS detected hematologic OD with a sensitivity of 0.821 (95% CI: 0.708-0.904) and a specificity of 0.970 (95% CI: 0.942-0.987).

CONCLUSION

We could confirm our approach for designing an interoperable CDSS as reproducible and transferable to other critical diseases. Our findings are of direct practical relevance, as they present one of the first interoperable CDSS modules that detect pediatric SIRS/sepsis-associated hematologic OD.

摘要

背景

儿科重症监护的主要挑战之一是在急性时间限制和绩效压力下检测危及生命的健康状况。这包括评估儿科器官功能障碍(OD),这需要非凡的临床专业知识和临床医生根据多个信息和数据源做出决策的能力。临床决策支持系统(CDSS)为支持医务人员在紧张的日常工作中提供了一种解决方案。同时,使用计算机化决策支持方法检测 OD 的研究很少,特别是在儿科领域。

目的

本研究旨在通过增强现有可互操作的基于规则的 CDSS 原型,跟踪危重病儿童脓毒症的进展,该原型通过增加检测 SIRS/脓毒症相关血液学 OD 的能力,来提高其诊断准确性。

方法

我们复制了我们工作组之前引入的一种可互操作的 CDSS 方法:(1)通过遵循 commonKADS 方法设计了一个知识模型,(2)使用 openEHR 作为临床信息标准对常规护理数据进行语义标准化和协调,(3)在业务规则管理系统中制定和实施规则。使用前瞻性诊断研究的数据,包括 168 名患者,使用临床医生的诊断作为参考来估计基于规则的 CDSS 的诊断准确性。

结果

我们成功地使用新的检测 SIRS/脓毒症相关血液学 OD 的任务增强了现有的可互操作的 CDSS 概念。我们对 openEHR 模板进行了建模,集成和标准化了常规数据,开发了基于规则的可互操作模型,并证明了其准确性。该 CDSS 检测血液学 OD 的灵敏度为 0.821(95%CI:0.708-0.904),特异性为 0.970(95%CI:0.942-0.987)。

结论

我们可以确认我们设计可互操作 CDSS 的方法是可复制和可转移到其他危重病的。我们的发现具有直接的实际意义,因为它们提供了第一个可互操作的 CDSS 模块之一,用于检测儿科 SIRS/脓毒症相关血液学 OD。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c9ee/9605821/2268ce91b59b/10-1055-a-1950-9637-i202203ra0079-1.jpg

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