Batmunkh Munkh-Undrakh, Ravjir Oyungerel, Lkhagvasuren Enkhsaikhan, Dambaa Naranzul, Boldoo Tsolmon, Ganbold Sarangua, Ganbaatar Khorolgarav, Tserendorj Chinbayar, Togoo Khongorzul, Bat-Erdene Ariunzaya, Narmandakh Zolmunkh, Soodoi Chimidtseren, Damdinbazar Otgonbayar, Tsolmon Bilegtsaikhan, Gunchin Batbaatar, Sandag Tsogtsaikhan
Mongolian National University of Medical Sciences, Jamyan Street 3, Sukhbaatar District, Ulaanbaatar, 14210, Mongolia.
National Centre for Communicable Diseases, Horoo 14, 13th Horoolol, Nam Yan Ju Street, Bayanzurkh District, Ulaanbaata, 13335, Mongolia.
Inform Med Unlocked. 2022;31:100982. doi: 10.1016/j.imu.2022.100982. Epub 2022 Jun 10.
The study was focused on comparing crude and sex-adjusted hazard ratio calculated by the baseline variables which may have contributed to the severity of the disease course and fatal outcomes in Coronavirus Disease-19 (COVID-19) patients.
The study enrolled 150 eligible adult patients with confirmed SARS-CoV-2 infection. There were 61 (40.7%) male patients, and 89 (59.3%) female patients. Baseline information of patients was collected from patient medical records and surveys that the patients had completed on admission to the hospital.
Considerable number of baseline variables stratified according to disease severity and outcomes showed different optimal cut-points (OCP) in men and women. Sex-adjusted baseline data categories such as age; BMI; systolic and diastolic blood pressure; peripheral RBC and platelet counts; haematocrit; percentage of neutrophils, lymphocytes, monocytes, and their ratio; percentage of eosinophils; titre of plasma IL-6, IL-8, IL-10, and IL-17; and CXCL10; and ratio of pro- and anti-inflammatory cytokines demonstrated significant impacts on the development of the severe stage and fatal outcomes by the mean hazard ratio in the Kaplan-Meier and Cox regression models.
This study confirmed some improved predictive capabilities of the sex-adjusted approach in the analysis of the baseline predictive variables for severity and outcome of the COVID-19.
本研究聚焦于比较由基线变量计算得出的粗风险比和性别调整风险比,这些基线变量可能对冠状病毒病19(COVID-19)患者的疾病进程严重程度和致命结局产生影响。
该研究纳入了150例确诊感染严重急性呼吸综合征冠状病毒2(SARS-CoV-2)的合格成年患者。其中男性患者61例(40.7%),女性患者89例(59.3%)。患者的基线信息从患者病历以及患者入院时完成的调查中收集。
根据疾病严重程度和结局分层的大量基线变量在男性和女性中显示出不同的最佳切点(OCP)。性别调整后的基线数据类别,如年龄;体重指数;收缩压和舒张压;外周红细胞和血小板计数;血细胞比容;中性粒细胞、淋巴细胞、单核细胞及其比例的百分比;嗜酸性粒细胞百分比;血浆白细胞介素-6、白细胞介素-8、白细胞介素-10和白细胞介素-17的滴度;以及CXC趋化因子配体10(CXCL10);促炎细胞因子与抗炎细胞因子的比例,在Kaplan-Meier和Cox回归模型中通过平均风险比显示出对重症阶段发展和致命结局有显著影响。
本研究证实了性别调整方法在分析COVID-19严重程度和结局的基线预测变量方面具有一些改进的预测能力。