Izmir Democracy University, School of Medicine, Department of Anesthesiology, Turkey.
University of Health Sciences, Izmir Dr. Suat Seren Chest Diseases and Chest Surgery Training and Research Hospital, Anesthesiology Department, Turkey.
Clin Imaging. 2022 Aug;88:4-8. doi: 10.1016/j.clinimag.2022.04.017. Epub 2022 May 4.
COVID-19 is a disease with high mortality worldwide, and which parameters that affect mortality in intensive care are still being investigated. This study aimed to show the factors affecting mortality in COVID-19 intensive care patients and write a model that can predict mortality.
The data of 229 patients in the COVID-19 intensive care unit were scanned. Laboratory tests, APACHE, SOFA, and GCS values were recorded. CT scores were calculated with chest CTs. The effects of these data on mortality were examined. The effects of the variables were modeled using the stepwise regression method.
While the mean age of female (30.14%) patients was 69.1 ± 12.2, the mean age of male (69.86%) patients was 66.9 ± 11.5. The mortality rate was 69.86%. Age, CRP, D-dimer, creatinine, procalcitonin, APACHE, SOFA, GCS, and CT score were significantly different in the deceased patients than the survival group. When we attempted to create a model using stepwise linear regression analysis, the appropriate model was achieved at the fourth step. Age, CRP, APACHE, and CT score were included in the model, which has the power to predict mortality with 89.9% accuracy.
Although, when viewed individually, there is a significant difference in parameters such as creatinine, procalcitonin, D-dimer, GCS, and SOFA score, the probability of mortality can be estimated by knowing only the age, CRP, APACHE, and CT scores. These four simple parameters will help clinicians effectively use resources in treatment.
COVID-19 是一种全球死亡率较高的疾病，目前仍在研究影响重症监护死亡率的参数。本研究旨在展示 COVID-19 重症监护患者的死亡率的影响因素，并建立一个可以预测死亡率的模型。
扫描了 229 名 COVID-19 重症监护病房患者的数据。记录了实验室检查、APACHE、SOFA 和 GCS 值。用胸部 CT 计算 CT 评分。检查这些数据对死亡率的影响。使用逐步回归方法对变量的影响进行建模。
女性（30.14%）患者的平均年龄为 69.1±12.2，而男性（69.86%）患者的平均年龄为 66.9±11.5。死亡率为 69.86%。在死亡患者中，年龄、CRP、D-二聚体、肌酐、降钙素原、APACHE、SOFA、GCS 和 CT 评分与存活组相比差异有统计学意义。当我们试图使用逐步线性回归分析创建模型时，在第四步达到了合适的模型。年龄、CRP、APACHE 和 CT 评分被纳入模型，该模型可以以 89.9%的准确率预测死亡率。
虽然单独观察时，肌酐、降钙素原、D-二聚体、GCS 和 SOFA 评分等参数存在显著差异，但仅了解年龄、CRP、APACHE 和 CT 评分就可以估计死亡率。这四个简单的参数将帮助临床医生在治疗中有效利用资源。
