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CALL Score and RAS Score as Predictive Models for Coronavirus Disease 2019

机译:呼叫得分和RAS分数作为冠状病毒疾病预测模型2019

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Background:?Coronavirus disease 2019 (COVID-19) is a novel infectious disease of multi-system involvement with significant pulmonary manifestations. So far, many prognostic models have been introduced to guide treatment and resource management. However, data on the impact of measurable respiratory parameters associated with the disease are scarce. Objective:?To demonstrate the role of Comorbidity-Age-Lymphocyte count-Lactate dehydrogenase (CALL) score and to introduce Respiratory Assessment Scoring (RAS) model in predicting disease progression and mortality in COVID-19. Methodology:?Data of 252 confirmed COVID-19 patients were collected at Pak Emirates Military Hospital (PEMH) from 10th?April 2020 to 31st?August 2020. The CALL score and proposed factors of RAS model, namely?respiratory rate, oxygen saturation at rest, alveolar arterial gradient and minimal exercise desaturation test, were calculated on the day of admission. Progression of disease was defined and correlated with measured variables. Univariate and multivariate Cox regression analysis for each variable, its hazard ratio (HR) and 95% confidence interval (CI) were calculated, and a nomogram was made using the high-risk respiratory parameters to establish the RAS model. Results:?Progression of disease and death was observed in 124 (49.2%) and 49 (19.4%) patients, respectively. Presence of more than 50% of chest infiltrates was significantly associated with worsening disease and death (p-value 0.001). Death was observed in 100% of patients who had critical disease category on presentation. Regression analysis showed that the presence of comorbidity (n: 180), in contrast to other variables of CALL score, was not a good prognosticator of disease severity (p-value: 0.565). Nonetheless, the CALL model itself was validated to be a reliable prognostic indicator of disease progression and mortality. Some 10 feet oxygen desaturation test (HR: 0.99, 95%CI: 0.95-1.04, p-value: 0.706) was not a powerful predictor of the progression of disease. However, respiratory rate of more than 30 breaths/minute (b/m) (HR: 3.03, 95%CI: 1.77-5.19), resting oxygen saturation of less than 90% (HR: 2.41, 95%CI: 1.15-5.06), and an elevated alveolar-arterial oxygen gradient (HR: 2.14, 95%CI: 1.04-4.39) were considered statistically significant high-risk predictors of disease progression and death, in the formed RAS model. The model resulted in 85% (95%CI: 80%-89%) of area under the receiver operating characteristic curve (AUROC), with substantial positive (76%, 95%CI: 68%-83%) and negative predictive values (80%, 95%CI: 73%-87%) for a cutoff value of seven. Patients with higher CALL and RAS scores also resulted in higher mortality. Conclusion:?CALL and RAS scores were strongly associated with progression and mortality in patients with COVID-19.
机译:背景:冠状病毒2019(Covid-19)是一种新型传染病,具有显着肺部表现的多系统累容。到目前为止,已经引入了许多预后模型来指导治疗和资源管理。然而,关于与疾病相关的可测量呼吸参数的影响的数据是稀缺的。目的:展示合并症型淋巴细胞计数乳酸脱氢酶(呼叫)评分的作用,并引入呼吸评估评分(RAS)模型预测Covid-19中的疾病进展和死亡率。方法论:252确认的Covid-19患者的数据在Pak Emirates军事医院(PEMH)从10日起收集(PEMH)从10月20日至31日至31日?呼叫得分和RAS模型的提出因素,即呼吸速率,氧气饱和度休息,肺泡动脉梯度和最小的运动去饱和试验在入院日计算。疾病的进展定义和与测量变量相关。计算每个变量的单变量和多变量Cox回归分析,其危害比(HR)和95%置信区间(CI)进行了计算,并使用高风险呼吸参数制造ROM图以建立RAS模型。结果:24(49.2%)和49名(19.4%)患者分别观察到疾病和死亡的进展。超过50%的胸部渗透性与恶化和死亡显着相关(p值<0.001)。在100%的患者中观察到在介绍中有批判性疾病类别的患者中观察到死亡。回归分析表明,与其他呼叫评分的其他变量相比,合并率(N:180)的存在不是疾病严重程度的良好预后剂(p值:0.565)。尽管如此,呼叫模型本身被验证为疾病进展和死亡率的可靠预后指标。约10英尺的氧去饱和试验(HR:0.99,95%CI:0.95-1.04,P值:0.706)不是疾病进展的强大预测因子。然而,呼吸速率超过30呼吸/分钟(B / M)(HR:3.03,95%CI:1.77-5.19),静氧饱和度小于90%(HR:2.41,95%CI:1.15-5.06 )和升高的肺泡 - 动脉氧梯度(HR:2.14,95%CI:1.04-4.39)被认为是在成立的RAS模型中的疾病进展和死亡的统计学显着的高风险预测因子。该模型在接收器操作特征曲线(Auroc)下导致85%(95%CI:80%-89%)面积,具有大量阳性(76%,95%Ci:68%-83%)和负预测值(80%,95%CI:73%-87%),截止值为7。患有较高电话和RAS分数的患者也导致了更高的死亡率。结论:?呼叫和RAS分数与Covid-19患者的进展和死亡率密切相关。

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