• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

一种用于预测严重 COVID-19 病例的入院前分诊工具:ABCD 评分。

A pre-admission triaging tool to predict severe COVID-19 cases: ABCD score.

机构信息

Sarawak General Hospital, Department of Medicine, Infectious Disease Unit, Kuching, Sarawak, Malaysia.

Sarawak General Hospital, Clinical Research Centre, Kuching, Sarawak, Malaysia.

出版信息

Med J Malaysia. 2022 Mar;77(2):237-240.

PMID:35338633
Abstract

INTRODUCTION

Isolation of SARS-CoV-2-infected individuals is an important COVID-19 pandemic control measure. While most cases have uncomplicated infection, a small proportion of them has developed life-threatening disease. We set up a retrospective study to determine preadmission triaging tool to predict the development of severe COVID-19.

MATERIALS AND METHODS

A retrospective study was conducted from 1 October 2020 to 31 January 2021 with enrolment of all SARS-CoV-2 PCR-confirmed persons aged ≥13 years. The disease severity was assessed on admission and daily throughout the hospitalisation. Test-positive individuals were considered as having "severe COVID-19" if they had ≥1 of the following: room air oxygen saturation 30 breaths/minute, signs of severe respiratory distress, or received mechanical ventilation and/or vasopressor therapy. Uni- and multi-variate analyses using SPSS Statistics Ver. 26 were performed.

RESULTS

We showed that age ≥ 60 years, BMI ≥ 30.0, presentation on days 7-12 of illness, and ≥1 comorbidity were associated with development of severe COVID-19. A scoring system based on the four variables is a useful COVID-19 risk assessment tool. A total score ≥2 had a sensitivity of 60.9%, specificity of 88.2%, positive predictive value of 37.8% and negative predictive value of 95.0%.

CONCLUSION

Development of preadmission triaging tool can help health care providers (HCPs) decide on the placement of test-positive individuals to appropriate isolation facilities according to the risk of developing severe COVID-19.

摘要

简介

对 SARS-CoV-2 感染者进行隔离是 COVID-19 大流行控制的重要措施。虽然大多数病例感染较轻,但仍有一小部分患者会发展为危及生命的疾病。我们进行了一项回顾性研究,旨在确定入院前的分诊工具,以预测 COVID-19 的严重程度。

材料和方法

本回顾性研究于 2020 年 10 月 1 日至 2021 年 1 月 31 日进行,纳入所有年龄≥13 岁、SARS-CoV-2 PCR 检测阳性的患者。入院时及住院期间每日对疾病严重程度进行评估。若患者符合以下任意一项标准,即被认为患有“严重 COVID-19”:静息状态下血氧饱和度<93%、呼吸窘迫明显、需要机械通气和/或血管升压药物治疗。采用 SPSS Statistics Ver. 26 进行单变量和多变量分析。

结果

我们发现,年龄≥60 岁、BMI≥30.0、疾病第 7-12 天出现症状以及存在≥1 种合并症与发展为严重 COVID-19 相关。基于这四个变量的评分系统是一种有用的 COVID-19 风险评估工具。总分≥2 分的敏感性为 60.9%,特异性为 88.2%,阳性预测值为 37.8%,阴性预测值为 95.0%。

结论

入院前分诊工具的制定有助于医疗保健提供者根据发展为严重 COVID-19 的风险,将检测阳性患者安置到适当的隔离设施。

相似文献

1
A pre-admission triaging tool to predict severe COVID-19 cases: ABCD score.一种用于预测严重 COVID-19 病例的入院前分诊工具:ABCD 评分。
Med J Malaysia. 2022 Mar;77(2):237-240.
2
Evaluation of an adjusted MEWS (Modified Early Warning Score) for COVID-19 patients to identify risk of ICU admission or death in the Kingdom of Bahrain.评估针对巴林王国新冠肺炎患者的调整后MEWS(改良早期预警评分),以确定入住重症监护病房或死亡风险。
J Infect Public Health. 2023 Nov;16(11):1773-1777. doi: 10.1016/j.jiph.2023.09.002. Epub 2023 Sep 9.
3
Cohort of Four Thousand Four Hundred Four Persons Under Investigation for COVID-19 in a New York Hospital and Predictors of ICU Care and Ventilation.在纽约一家医院中对 4404 人进行的 COVID-19 调查队列研究,以及 ICU 护理和通气的预测因素。
Ann Emerg Med. 2020 Oct;76(4):394-404. doi: 10.1016/j.annemergmed.2020.05.011. Epub 2020 May 11.
4
The Development and Validation of Simplified Machine Learning Algorithms to Predict Prognosis of Hospitalized Patients With COVID-19: Multicenter, Retrospective Study.中文译文:简化机器学习算法预测 COVID-19 住院患者预后的开发和验证:多中心回顾性研究。
J Med Internet Res. 2022 Jan 21;24(1):e31549. doi: 10.2196/31549.
5
Atypical symptoms, SARS-CoV-2 test results and immunisation rates in 456 residents from eight nursing homes facing a COVID-19 outbreak.456 名来自面临 COVID-19 疫情的 8 家养老院居民的非典型症状、SARS-CoV-2 检测结果和免疫接种率。
Age Ageing. 2021 May 5;50(3):641-648. doi: 10.1093/ageing/afab050.
6
Accuracy of the Traditional COVID-19 Phone Triaging System and Phone Triage-Driven Deep Learning Model.传统 COVID-19 电话分诊系统和电话分诊驱动的深度学习模型的准确性。
J Prim Care Community Health. 2022 Jan-Dec;13:21501319221113544. doi: 10.1177/21501319221113544.
7
Application of the Sight Outcomes Research Collaborative Ophthalmology Data Repository for Triaging Patients With Glaucoma and Clinic Appointments During Pandemics Such as COVID-19.在 COVID-19 等大流行期间,Sight Outcomes Research Collaborative Ophthalmology Data Repository 在青光眼患者分诊和诊所预约中的应用。
JAMA Ophthalmol. 2020 Sep 1;138(9):974-980. doi: 10.1001/jamaophthalmol.2020.2974.
8
Risk-based stratification triaging system in pediatric urology: what COVID-19 pandemic has taught us.儿科泌尿外科的基于风险分层的分诊系统:新冠疫情教会了我们什么。
Pediatr Surg Int. 2021 Jun;37(6):827-833. doi: 10.1007/s00383-021-04868-4. Epub 2021 Feb 27.
9
Predictive value of National Early Warning Score 2 (NEWS2) for intensive care unit admission in patients with SARS-CoV-2 infection.国家早期预警评分 2(NEWS2)对 SARS-CoV-2 感染患者入住重症监护病房的预测价值。
Infect Dis (Lond). 2020 Oct;52(10):698-704. doi: 10.1080/23744235.2020.1784457. Epub 2020 Jun 25.
10
Characteristics and Outcomes of COVID-19 Infection from an Urban Ambulatory COVID-19 Clinic-Guidance for Outpatient Clinicians in Triaging Patients.城市门诊 COVID-19 诊所中 COVID-19 感染的特征和结果——为门诊临床医生分诊患者提供指导。
J Prim Care Community Health. 2021 Jan-Dec;12:21501327211017016. doi: 10.1177/21501327211017016.

引用本文的文献

1
An Elaboration on Sample Size Planning for Performing a One-Sample Sensitivity and Specificity Analysis by Basing on Calculations on a Specified 95% Confidence Interval Width.基于指定的95%置信区间宽度计算进行单样本灵敏度和特异性分析的样本量规划详述
Diagnostics (Basel). 2023 Apr 11;13(8):1390. doi: 10.3390/diagnostics13081390.