Ilczak Tomasz, Skoczynski Szymon, Oclon Ewa, Kucharski Mirosław, Strejczyk Tomasz, Jagosz Marta, Jedynak Antonina, Wita Michał, Ćwiertnia Michał, Jędrzejek Marek, Dutka Mieczysław, Waksmańska Wioletta, Bobiński Rafał, Pakuła Roch, Kawecki Marek, Kukla Paweł, Białka Szymon
Department of Emergency Medicine, Faculty of Health Sciences, University of Bielsko-Biala, 43-309 Bielsko-Biała, Poland.
Department of Lung Diseases and Tuberculosis, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, 40-752 Katowice, Poland.
Healthcare (Basel). 2024 Jul 18;12(14):1436. doi: 10.3390/healthcare12141436.
From the moment the SARS-CoV-2 virus was identified in December 2019, the COVID-19 disease spread around the world, causing an increase in hospitalisations and deaths. From the beginning of the pandemic, scientists tried to determine the major cause that led to patient deaths. In this paper, the background to creating a research model was diagnostic problems related to early assessment of the degree of damage to the lungs in patients with COVID-19. The study group comprised patients hospitalised in one of the temporary COVID hospitals. Patients admitted to the hospital had confirmed infection with SARS-CoV-2. At the moment of admittance, arterial blood was taken and the relevant parameters noted. The results of physical examinations, the use of oxygen therapy and later test results were compared with the condition of the patients in later computed tomography images and descriptions. The point of reference for determining the severity of the patient's condition in the computer imagery was set for a mild condition as consisting of a percentage of total lung parenchyma surface area affected no greater than 30%, an average condition of between 30% and 70%, and a severe condition as greater than 70% of the lung parenchyma surface area affected. Patients in a mild clinical condition most frequently had mild lung damage on the CT image, similarly to patients in an average clinical condition. Patients in a serious clinical condition most often had average levels of damage on the CT image. On the basis of the collected data, it can be said that at the moment of admittance, BNP, PE and HCO levels, selected due to the form of lung damage, on computed tomography differed from one another in a statistically significant manner ( < 0.05). Patients can qualify for an appropriate group according to the severity of COVID-19 on the basis of a physical examination and applied oxygen therapy. Patients can qualify for an appropriate group according to the severity of COVID-19 on the basis of BNP, HCO and BE parameters obtained from arterial blood.
自2019年12月首次发现严重急性呼吸综合征冠状病毒2（SARS-CoV-2）以来，新型冠状病毒肺炎（COVID-19）在全球范围内迅速传播，导致住院人数和死亡人数不断增加。自疫情爆发之初，科学家们就试图确定导致患者死亡的主要原因。本文中，创建研究模型的背景是与COVID-19患者肺部损伤程度早期评估相关的诊断问题。研究组由在一家临时COVID医院住院的患者组成。入院患者确诊感染SARS-CoV-2。入院时采集动脉血并记录相关参数。将体格检查结果、氧疗使用情况及后续检查结果与患者后续计算机断层扫描（CT）图像及描述中的病情进行比较。在计算机图像中，确定患者病情严重程度的参考点设定为：轻度病情为肺实质总面积受累百分比不超过30%，中度病情为介于30%至70%之间，重度病情为肺实质表面积受累超过70%。临床症状较轻的患者在CT图像上最常出现轻度肺损伤，临床症状中等的患者情况类似。临床症状严重的患者在CT图像上最常出现中度损伤水平。根据收集的数据可以说，入院时，由于肺部损伤形式而选择的脑钠肽（BNP）、动脉血氧分压（PE）和碳酸氢根（HCO）水平在计算机断层扫描中彼此存在统计学显著差异（<0.05）。根据体格检查和应用的氧疗，患者可根据COVID-19的严重程度归入相应组别。根据从动脉血中获得的BNP、HCO和碱剩余（BE）参数，患者可根据COVID-19的严重程度归入相应组别。
