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基于 Charlson 和 Elixhauser 合并症指数的严重和危重新冠肺炎预后模型。

Prognosis models for severe and critical COVID-19 based on the Charlson and Elixhauser comorbidity indices.

机构信息

Department of Intensive Care Unit, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.

Department of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.

出版信息

Int J Med Sci. 2020 Aug 25;17(15):2257-2263. doi: 10.7150/ijms.50007. eCollection 2020.

DOI:10.7150/ijms.50007
PMID:32922189
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7484649/
Abstract

: Corona Virus Disease 2019 (COVID-19) has become a global pandemic. This study established prognostic scoring models based on comorbidities and other clinical information for severe and critical patients with COVID-19. : We retrospectively collected data from 51 patients diagnosed as severe or critical COVID-19 who were admitted between January 29, 2020, and February 18, 2020. The Charlson (CCI), Elixhauser (ECI), and age- and smoking-adjusted Charlson (ASCCI) and Elixhauser (ASECI) comorbidity indices were used to evaluate the patient outcomes. : The mean hospital length of stay (LOS) of the COVID-19 patients was 22.82 ± 12.32 days; 19 patients (37.3%) were hospitalized for more than 24 days. Multivariate analysis identified older age (OR 1.064, = 0.018, 95%CI 1.011-1.121) and smoking (OR 3.696, = 0.080, 95%CI 0.856-15.955) as positive predictors of a long LOS. There were significant trends for increasing hospital LOS with increasing CCI, ASCCI, and ASECI scores (OR 57.500, = 0.001, 95%CI 5.687-581.399; OR 71.500, = 0.001, 95%CI 5.689-898.642; and OR 19.556, = 0.001, 95%CI 3.315-115.372, respectively). The result was similar for the outcome of critical illness (OR 21.333, = 0.001, 95%CI 3.565-127.672; OR 13.000, = 0.009, 95%CI 1.921-87.990; OR 11.333, = 0.008, 95%CI 1.859-69.080, respectively). : This study established prognostic scoring models based on comorbidities and clinical information, which may help with the graded management of patients according to prognosis score and remind physicians to pay more attention to patients with high scores.

摘要

新冠病毒病 2019(COVID-19)已成为全球大流行疾病。本研究基于合并症和其他临床信息为 COVID-19 重症和危重症患者建立了预后评分模型。

我们回顾性收集了 2020 年 1 月 29 日至 2 月 18 日期间收治的 51 例确诊为重症或危重症 COVID-19 患者的数据。使用 Charlson(CCI)、Elixhauser(ECI)、年龄和吸烟调整的 Charlson(ASCCI)和 Elixhauser(ASECI)合并症指数评估患者结局。

COVID-19 患者的平均住院时间(LOS)为 22.82±12.32 天;19 例(37.3%)患者的住院时间超过 24 天。多变量分析确定年龄较大(OR 1.064, = 0.018,95%CI 1.011-1.121)和吸烟(OR 3.696, = 0.080,95%CI 0.856-15.955)是 LOS 延长的阳性预测因子。CCI、ASCCI 和 ASECI 评分越高,住院 LOS 越长,呈显著趋势(OR 57.500, = 0.001,95%CI 5.687-581.399;OR 71.500, = 0.001,95%CI 5.689-898.642;OR 19.556, = 0.001,95%CI 3.315-115.372)。危重症结局的结果也相似(OR 21.333, = 0.001,95%CI 3.565-127.672;OR 13.000, = 0.009,95%CI 1.921-87.990;OR 11.333, = 0.008,95%CI 1.859-69.080)。

本研究基于合并症和临床信息建立了预后评分模型,有助于根据预后评分对患者进行分级管理,并提醒医生注意评分较高的患者。

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本文引用的文献

1
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2
Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis.中国 COVID-19 患者 1590 例的合并症及其影响:一项全国性分析。
Eur Respir J. 2020 May 14;55(5). doi: 10.1183/13993003.00547-2020. Print 2020 May.
3
COVID-19 and smoking: A systematic review of the evidence.2019冠状病毒病与吸烟:证据的系统评价
利用行政数据进行机器学习,预测持续护理设施中的死亡风险。
Sci Rep. 2023 Oct 18;13(1):17708. doi: 10.1038/s41598-023-43943-9.
4
Associations between underlying diseases with COVID-19 and its symptoms among adults: a cross-sectional study.成年人中 COVID-19 及其症状与基础疾病之间的关联:一项横断面研究。
Front Public Health. 2023 Jun 13;11:1210800. doi: 10.3389/fpubh.2023.1210800. eCollection 2023.
5
Hematology profile analysis in coronavirus disease 2019 (COVID-19) patients.2019冠状病毒病(COVID-19)患者的血液学特征分析
Adv Lab Med. 2022 Oct 13;3(4):383-396. doi: 10.1515/almed-2022-0053. eCollection 2022 Dec.
6
Healthcare utilization and adverse outcomes stratified by sex, age and long-term care residency using the Alberta COVID-19 Analytics and Research Database (ACARD): a population-based descriptive study.利用艾伯塔省 COVID-19 分析和研究数据库(ACARD)按性别、年龄和长期护理居住情况分层的医疗保健利用和不良结局:一项基于人群的描述性研究。
BMC Infect Dis. 2023 May 19;23(1):337. doi: 10.1186/s12879-023-08326-5.
7
Risk factors associated with COVID-19 severity among patients on maintenance haemodialysis: a retrospective multicentre cross-sectional study in the UK.维持性血液透析患者 COVID-19 严重程度相关的危险因素:英国一项回顾性多中心横断面研究。
BMJ Open. 2022 May 30;12(5):e054869. doi: 10.1136/bmjopen-2021-054869.
8
The Effectiveness of National Early Warning Score, Quick Sequential Organ Failure Assessment, Charlson Comorbidity Index, and Elixhauser Comorbidity Index Scores in Predicting Mortality Due to COVID-19 in Elderly Patients.国家早期预警评分、快速序贯器官衰竭评估、查尔森合并症指数和埃利克斯豪泽合并症指数评分在预测老年患者因 COVID-19 导致的死亡率方面的有效性。
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9
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Turk Thorac J. 2022 Mar;23(2):145-153. doi: 10.5152/TurkThoracJ.2022.21076.
Tob Induc Dis. 2020 Mar 20;18:20. doi: 10.18332/tid/119324. eCollection 2020.
4
Diagnostic utility of clinical laboratory data determinations for patients with the severe COVID-19.严重 COVID-19 患者临床实验室数据测定的诊断效用。
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5
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7
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8
Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China.新型冠状病毒肺炎(SARS-CoV-2)感染的癌症患者:一项中国全国性分析。
Lancet Oncol. 2020 Mar;21(3):335-337. doi: 10.1016/S1470-2045(20)30096-6. Epub 2020 Feb 14.
9
Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China.《武汉 2019 年新型冠状病毒感染的肺炎 138 例住院患者临床特征分析》
JAMA. 2020 Mar 17;323(11):1061-1069. doi: 10.1001/jama.2020.1585.
10
Identification of a novel coronavirus causing severe pneumonia in human: a descriptive study.鉴定一种导致人类严重肺炎的新型冠状病毒:一项描述性研究。
Chin Med J (Engl). 2020 May 5;133(9):1015-1024. doi: 10.1097/CM9.0000000000000722.