Esteban Cristóbal, Villanueva Ane, García-Gutierrez Susana, Aramburu Amaia, Gorordo Inmaculada, Quintana Jose María, Working Group The Covid-Osakidetza
Respiratory Department, Hospital Galdakao, Galdakao, Spain.
Health Services Research on Chronic Patients Network (REDISSEC), Galdakao, Spain.
Expert Rev Respir Med. 2022 Apr;16(4):477-484. doi: 10.1080/17476348.2022.2031985. Epub 2022 Apr 6.
To develop a predictive model for COPD patients admitted for COVID-19 to support clinical decision-making.
Retrospective cohort study of 1313 COPD patients with microbiological confirmation of SARS-CoV-2 infection. The sample was randomly divided into two subsamples, for the purposes of derivation and validation of the prediction rule (60% and 40%,respectively). Data collected for this study included sociodemographic characteristics, baseline comorbidities, baseline treatments, and other background data. Multivariable logistic regression analysis was used to develop the predictive model.
Male sex, older age, hospital admissions in the previous year, flu vaccination in the previous season, a Charlson Index>3 and a prescription of renin-angiotensin aldosterone system inhibitors at baseline were the main risk factors for hospital admission. The AUC of the categorized risk score was 0.72 and 0.69 in the derivation and validation samples, respectively. Based on the risk score, four groups were identified with a risk of hospital admission ranging from 21% to 80%.
We propose a classification system to identify COPD people with COVID-19 with a higher risk of hospitalization, and indirectly, more severe disease, that is easy to use in primary care, as well as hospital emergency room settings to help clinical decision-making.
CLINICALTRIALS.GOV IDENTIFIER: NCT04463706.
为因新型冠状病毒肺炎(COVID-19)入院的慢性阻塞性肺疾病(COPD)患者开发一种预测模型,以支持临床决策。
对1313例经微生物学确诊感染严重急性呼吸综合征冠状病毒2(SARS-CoV-2)的COPD患者进行回顾性队列研究。为了推导和验证预测规则,样本被随机分为两个子样本(分别为60%和40%)。本研究收集的数据包括社会人口学特征、基线合并症、基线治疗及其他背景数据。采用多变量逻辑回归分析来开发预测模型。
男性、年龄较大、前一年曾住院、前一季接种过流感疫苗、Charlson指数>3以及基线时使用肾素-血管紧张素-醛固酮系统抑制剂是入院的主要危险因素。在推导样本和验证样本中,分类风险评分的曲线下面积(AUC)分别为0.72和0.69。根据风险评分,确定了四组患者,其入院风险范围为21%至80%。
我们提出了一种分类系统,用于识别因COVID-19住院风险较高且间接提示疾病更严重的COPD患者,该系统易于在基层医疗以及医院急诊室环境中使用,以帮助临床决策。
NCT04463706。