Effect of predictive nursing based on risk early warning system on patients with acute respiratory failure in Intensive Care Unit.

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2024-09-01 DOI:10.12669/pjms.40.8.9506

Mimi Pan, Lizhong Zhang

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Abstract

Background & objective: Acute respiratory failure (ARF) is a life-threatening condition that necessitates intensive care and often results in high morbidity and mortality. Predictive nursing, combined with a risk early warning system, offers a proactive approach to patient care that could potentially improve outcomes in patients with ARF. However, the efficiency of this approach in intensive care settings is still unclear. This study aimed to analyze the effect of predictive nursing based on risk early warning system in patients with acute respiratory failure in intensive care unit (ICU) setting.

Methods: A retrospective cohort study included records of 368 patients admitted to ICU of a tertiary care hospital due to ARF from January 2021 to January 2023. Patients were divided into two groups based on the received care: standard care (control group, n=197) and predictive nursing care based on a risk early warning system (observation group, n=171). Data on demographics, clinical characteristics, complications, Acute Physiology, Age and Chronic Health Evaluation-II (APACHE-II) and Sequential Organ Failure Assessment (SOFA) scores, and duration of hospitalization were collected and analyzed.

Results: The observation group exhibited significantly lower incidence of complications related to ventilator use and shorter durations of mechanical ventilation, ICU stay, and total hospitalization compared to the control group (p<0.001). Furthermore, patients in the observation group had significantly lower APACHE-II and SOFA scores and blood lactate levels at both one week and two weeks post-intervention.

Conclusion: Predictive nursing care based on a risk early warning system significantly improved clinical outcomes and reduced mortality rates in ICU patients with ARF. The results underscore the potential of integrating predictive nursing care into routine practice, thereby transforming the care paradigm for ICU patients with ARF. Future research should explore the applicability of predictive nursing for other clinical conditions and in various healthcare settings.

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基于风险预警系统的预测性护理对重症监护病房急性呼吸衰竭患者的影响。

背景与目的：急性呼吸衰竭（ARF）是一种危及生命的疾病，需要进行重症监护，通常会导致较高的发病率和死亡率。预测性护理与风险预警系统相结合，为患者护理提供了一种积极主动的方法，有可能改善 ARF 患者的预后。然而，这种方法在重症监护环境中的效率尚不明确。本研究旨在分析基于风险预警系统的预测性护理对重症监护病房（ICU）急性呼吸衰竭患者的影响：一项回顾性队列研究纳入了 2021 年 1 月至 2023 年 1 月期间因急性呼吸衰竭入住某三甲医院 ICU 的 368 名患者的记录。根据所接受的护理将患者分为两组：标准护理（对照组，n=197）和基于风险预警系统的预测性护理（观察组，n=171）。收集并分析了人口统计学、临床特征、并发症、急性生理学、年龄和慢性健康评估-II（APACHE-II）和序贯器官衰竭评估（SOFA）评分以及住院时间等数据：结果：与对照组相比，观察组使用呼吸机相关并发症的发生率明显降低，机械通气时间、重症监护室住院时间和总住院时间也明显缩短（p 结论：观察组与对照组相比，使用呼吸机相关并发症的发生率明显降低，机械通气时间、重症监护室住院时间和总住院时间也明显缩短：基于风险预警系统的预测性护理能明显改善重症监护病房 ARF 患者的临床疗效并降低死亡率。研究结果强调了将预测性护理纳入常规实践的潜力，从而改变了对重症监护室 ARF 患者的护理模式。未来的研究应探索预测性护理在其他临床病症和各种医疗环境中的适用性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.