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通过电子护理记录识别 COVID-19 患者临床恶化的预测因素:回顾性观察研究。

Identification of Predictors for Clinical Deterioration in Patients With COVID-19 via Electronic Nursing Records: Retrospective Observational Study.

机构信息

Department of Nursing Science, Research Institute of Nursing Science, Chungbuk National University, Cheongju, Chungcheongbuk-do, Republic of Korea.

Department of Radiation Oncology, College of Medicine, Seoul National University, Seoul, Republic of Korea.

出版信息

J Med Internet Res. 2024 Mar 29;26:e53343. doi: 10.2196/53343.

Abstract

BACKGROUND

Few studies have used standardized nursing records with Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) to identify predictors of clinical deterioration.

OBJECTIVE

This study aims to standardize the nursing documentation records of patients with COVID-19 using SNOMED CT and identify predictive factors of clinical deterioration in patients with COVID-19 via standardized nursing records.

METHODS

In this study, 57,558 nursing statements from 226 patients with COVID-19 were analyzed. Among these, 45,852 statements were from 207 patients in the stable (control) group and 11,706 from 19 patients in the exacerbated (case) group who were transferred to the intensive care unit within 7 days. The data were collected between December 2019 and June 2022. These nursing statements were standardized using the SNOMED CT International Edition released on November 30, 2022. The 260 unique nursing statements that accounted for the top 90% of 57,558 statements were selected as the mapping source and mapped into SNOMED CT concepts based on their meaning by 2 experts with more than 5 years of SNOMED CT mapping experience. To identify the main features of nursing statements associated with the exacerbation of patient condition, random forest algorithms were used, and optimal hyperparameters were selected for nursing problems or outcomes and nursing procedure-related statements. Additionally, logistic regression analysis was conducted to identify features that determine clinical deterioration in patients with COVID-19.

RESULTS

All nursing statements were semantically mapped to SNOMED CT concepts for "clinical finding," "situation with explicit context," and "procedure" hierarchies. The interrater reliability of the mapping results was 87.7%. The most important features calculated by random forest were "oxygen saturation below reference range," "dyspnea," "tachypnea," and "cough" in "clinical finding," and "oxygen therapy," "pulse oximetry monitoring," "temperature taking," "notification of physician," and "education about isolation for infection control" in "procedure." Among these, "dyspnea" and "inadequate food diet" in "clinical finding" increased clinical deterioration risk (dyspnea: odds ratio [OR] 5.99, 95% CI 2.25-20.29; inadequate food diet: OR 10.0, 95% CI 2.71-40.84), and "oxygen therapy" and "notification of physician" in "procedure" also increased the risk of clinical deterioration in patients with COVID-19 (oxygen therapy: OR 1.89, 95% CI 1.25-3.05; notification of physician: OR 1.72, 95% CI 1.02-2.97).

CONCLUSIONS

The study used SNOMED CT to express and standardize nursing statements. Further, it revealed the importance of standardized nursing records as predictive variables for clinical deterioration in patients.

摘要

背景

很少有研究使用具有《系统医学术语》(SNOMED CT)的标准化护理记录来识别临床恶化的预测因素。

目的

本研究旨在使用 SNOMED CT 对 COVID-19 患者的护理文件记录进行标准化,并通过标准化护理记录识别 COVID-19 患者临床恶化的预测因素。

方法

本研究分析了 226 例 COVID-19 患者的 57558 条护理记录。其中,45852 条来自 207 例稳定(对照组)患者,11706 条来自 19 例在 7 天内转入重症监护病房的恶化(病例)患者。数据采集于 2019 年 12 月至 2022 年 6 月。这些护理记录使用 2022 年 11 月 30 日发布的 SNOMED CT 国际版进行标准化。选择占 57558 条记录的前 90%的 260 条独特护理记录作为映射源,并由 2 名具有超过 5 年 SNOMED CT 映射经验的专家根据其含义映射到 SNOMED CT 概念中。为了确定与患者病情恶化相关的护理记录的主要特征,使用随机森林算法,并针对护理问题或结果和护理程序相关的记录选择最佳超参数。此外,还进行了逻辑回归分析,以确定决定 COVID-19 患者临床恶化的特征。

结果

所有护理记录都按照语义映射到“临床发现”、“具有明确上下文的情况”和“程序”层次结构的 SNOMED CT 概念。映射结果的组内一致性为 87.7%。随机森林计算出的最重要特征是“临床发现”中的“氧饱和度低于参考范围”、“呼吸困难”、“呼吸急促”和“咳嗽”,以及“程序”中的“氧疗”、“脉搏血氧监测”、“体温测量”、“通知医生”和“感染控制隔离教育”。其中,“呼吸困难”和“临床发现”中的“饮食不足”增加了临床恶化的风险(呼吸困难:比值比 [OR] 5.99,95%CI 2.25-20.29;饮食不足:OR 10.0,95%CI 2.71-40.84),而“氧疗”和“程序”中的“通知医生”也增加了 COVID-19 患者临床恶化的风险(氧疗:OR 1.89,95%CI 1.25-3.05;通知医生:OR 1.72,95%CI 1.02-2.97)。

结论

本研究使用 SNOMED CT 来表达和标准化护理记录。此外,它揭示了标准化护理记录作为 COVID-19 患者临床恶化预测变量的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9700/10984341/1e97a00a372d/jmir_v26i1e53343_fig1.jpg

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