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Scand J Trauma Resusc Emerg Med. 2020 Jul 13;28(1):66. doi: 10.1186/s13049-020-00764-3.
2
A Novel Scoring System for Prediction of Disease Severity in COVID-19.一种用于预测 COVID-19 疾病严重程度的新型评分系统。
Front Cell Infect Microbiol. 2020 Jun 5;10:318. doi: 10.3389/fcimb.2020.00318. eCollection 2020.
3
Prevalence and severity of corona virus disease 2019 (COVID-19): A systematic review and meta-analysis.新型冠状病毒病 2019(COVID-19)的患病率和严重程度:系统评价和荟萃分析。
J Clin Virol. 2020 Jun;127:104371. doi: 10.1016/j.jcv.2020.104371. Epub 2020 Apr 14.
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A Tool for Early Prediction of Severe Coronavirus Disease 2019 (COVID-19): A Multicenter Study Using the Risk Nomogram in Wuhan and Guangdong, China.一种用于早期预测严重 2019 冠状病毒病(COVID-19)的工具:来自中国武汉和广东的多中心研究使用风险列线图。
Clin Infect Dis. 2020 Jul 28;71(15):833-840. doi: 10.1093/cid/ciaa443.
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Lymphopenia predicts disease severity of COVID-19: a descriptive and predictive study.淋巴细胞减少症可预测新型冠状病毒肺炎的疾病严重程度:一项描述性和预测性研究。
Signal Transduct Target Ther. 2020 Mar 27;5(1):33. doi: 10.1038/s41392-020-0148-4.
6
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J Allergy Clin Immunol. 2020 Jul;146(1):110-118. doi: 10.1016/j.jaci.2020.04.006. Epub 2020 Apr 12.
7
Prediction for Progression Risk in Patients With COVID-19 Pneumonia: The CALL Score.COVID-19 肺炎患者进展风险预测:CALL 评分。
Clin Infect Dis. 2020 Sep 12;71(6):1393-1399. doi: 10.1093/cid/ciaa414.
8
Predictors of mortality for patients with COVID-19 pneumonia caused by SARS-CoV-2: a prospective cohort study.预测 SARS-CoV-2 引起的 COVID-19 肺炎患者死亡率的前瞻性队列研究。
Eur Respir J. 2020 May 7;55(5). doi: 10.1183/13993003.00524-2020. Print 2020 May.
9
Clinical Characteristics of Coronavirus Disease 2019 in China.《中国 2019 年冠状病毒病临床特征》
N Engl J Med. 2020 Apr 30;382(18):1708-1720. doi: 10.1056/NEJMoa2002032. Epub 2020 Feb 28.
10
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.

新冠肺炎病死率的新型Charlson 合并症指数:CoLACD。

The impact of charlson comorbidity index on mortality from SARS-CoV-2 virus infection and A novel COVID-19 mortality index: CoLACD.

机构信息

Suat Seren Chest Diseases and Surgery Education and Training Hospital, University of Health Sciences, Izmir, Turkey.

出版信息

Int J Clin Pract. 2021 Apr;75(4):e13858. doi: 10.1111/ijcp.13858. Epub 2020 Dec 7.

DOI:10.1111/ijcp.13858
PMID:33237615
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7744887/
Abstract

OBJECTIVE

The aim of this study is to find out the potential risk factors including charlson comorbidity index (CCI) score associated with death in COVID-19 patients hospitalised because of pneumonia and try to find a novel COVID-19 mortality score for daily use.

METHODS

All patients diagnosed as confirmed or probable COVID-19 pneumonia whom hospitalised in our Chest Diseases Education and Research Hospital between March 11, 2020 and May 15, 2020 were enrolled. The optimal cut-off values, sensitivity and specificity values and odds ratios to be used in mortality prediction of the novel scoring system created from these parameters were calculated by ROC analysis according to the area under the curve and Youden index.

RESULTS

Over 383 patients (n: 33 deceased, n: 350 survivors) univariate and multivariate regression analysis showed that CCI and lymphocyte ratio were prognostic factors for COVID-19-related mortality. Using this analysis, a novel scoring model CoLACD (CoVID-19 Lymphocyte ratio, Age, CCI score, Dyspnoea) was established. The cut-off value of this scoring system, which determines the mortality risk in patients, was 2.5 points with 82% sensitivity and 73% specificity (AUC = 0.802, 95% CI 0.777-0.886, P < .001). The risk of mortality was 11.8 times higher in patients with a CoLACD mortality score higher than 2.5 points than patients with a score lower than 2.5 (OR = 11.8 95% CI 4.7-29.3 P < .001).

CONCLUSION

This study showed that by using the CoLACD mortality score, clinicians may achieve a prediction of mortality in COVID-19 patients hospitalised for pneumonia.

摘要

目的

本研究旨在找出与因肺炎住院的 COVID-19 患者死亡相关的潜在风险因素,包括 Charlson 合并症指数(CCI)评分,并尝试寻找一种新的 COVID-19 死亡率评分,以便日常使用。

方法

纳入 2020 年 3 月 11 日至 2020 年 5 月 15 日期间在我院胸部疾病教育和研究医院住院的确诊或疑似 COVID-19 肺炎患者。根据曲线下面积和约登指数,通过 ROC 分析计算从这些参数创建的新型评分系统进行死亡率预测的最佳截断值、敏感性和特异性值以及比值比。

结果

超过 383 例患者(n:33 例死亡,n:350 例存活)进行单因素和多因素回归分析显示,CCI 和淋巴细胞比率是 COVID-19 相关死亡率的预后因素。利用该分析,建立了一种新的评分模型 CoLACD(COVID-19 淋巴细胞比率、年龄、CCI 评分、呼吸困难)。该评分系统的截断值为 2.5 分,敏感性为 82%,特异性为 73%(AUC=0.802,95%CI 0.777-0.886,P<.001)。CoLACD 死亡率评分高于 2.5 分的患者死亡风险是评分低于 2.5 分的患者的 11.8 倍(OR=11.8,95%CI 4.7-29.3,P<.001)。

结论

本研究表明,通过使用 CoLACD 死亡率评分,临床医生可能能够预测因肺炎住院的 COVID-19 患者的死亡率。