Red Blood Cell Distribution Width Is Not a Predictor of Hospital Mortality in Elderly and Nonelderly COVID-19-Infected Patients: A Prospective Study at a Brazilian Quaternary University Hospital.

IF 2.6 4区 医学 Q3 INFECTIOUS DISEASES
Helena Duani, Máderson Alvares de Souza Cabral, Carla Jorge Machado, Thalyta Nogueira Fonseca, Milena Soriano Marcolino, Vandack Alencar Nobre, Cecilia Gómez Ravetti, Paula Frizera Vassallo, Unaí Tupinambás
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引用次数: 0

Abstract

Objective: To investigate if red blood cell distribution width (RDW) is a risk factor for hospital mortality in patients admitted to a public university hospital in Belo Horizonte, Minas Gerais, Brazil. Methods: This observational prospective study included patients over 16 years who had been hospitalized for COVID-19 between May and October 2020. A descriptive and time-to-death analysis was performed using the Cox proportional hazards model. Results: Of the 161 patients included, 39 (24.2%) died during hospitalization. A total of 2227 blood counts were performed, an average of 13.8 tests per patient (standard deviation, SD 2.9). Upon admission, the RDW was normal (11.5% to 14.6%) in 115 patients (71.4%), elevated in 45 (28%), and low in 1 (0.6%). The mean RDW value at admission was 14.5 (SD 2.4), which falls within the normal reference range. Of the patients with normal RDW at admission, 82 (71.3%) maintained normal levels throughout their stay, while 33 (28.7%) showed increased RDW levels over time. Among those with elevated RDW at admission, 40 (88.9%) remained elevated, while 5 (11.1%) returned to normal levels. There was no significant difference in the mean RDW value at admission between survivors and nonsurvivors (14.4 [SD 2.4] for survivors vs. 14.9 [SD 2.4] for nonsurvivors; p=0.2081). The risk for mortality in the group with high RDW upon admission was higher than in the group with normal RDW, but without statistical significance (31.1% vs. 21.7%; RR = 1.43; p=0.413). When performing a multivariate analysis, the following continue to be risk factors for lower survival: age > 70 years, HR 4.8 (95% CI: 2.3; 10.3), p < 0.001; white race, HR 3.2 (95% CI: 1.2; 8.61), p=0.018; and need for invasive MV, HR 3.8 (1.7; 8.7), p=0.001. The presence of a chest X-ray suggestive of COVID-19, HR 3.5 (95% CI: 1.0; 11.5), p=0.044, also appears to be a risk factor in this analysis. Conclusion: Alterations on RDW values on admission were not associated with higher mortality, and further increases in RDW during hospitalization were not linked to a higher risk of mortality across all age groups. Our findings suggest that while RDW may indicate disease severity, it may not serve as a reliable independent predictor of mortality when other factors are accounted for in this cohort.

红细胞分布宽度不是老年和非老年covid -19感染患者住院死亡率的预测因素:巴西第四大学医院的一项前瞻性研究
目的:探讨巴西米纳斯吉拉斯州贝洛奥里藏特市某公立大学医院患者红细胞分布宽度(RDW)是否为住院死亡的危险因素。方法:这项观察性前瞻性研究纳入了2020年5月至10月期间因COVID-19住院的16岁以上患者。使用Cox比例风险模型进行描述性和死亡时间分析。结果:161例患者中,39例(24.2%)在住院期间死亡。总共进行了2227次血球计数,平均每位患者13.8次(标准差,SD 2.9)。入院时,RDW正常(11.5% ~ 14.6%)115例(71.4%),增高45例(28%),低1例(0.6%)。入院时的平均RDW值为14.5 (SD 2.4),在正常参考范围内。入院时RDW正常的患者中,82例(71.3%)在整个住院期间保持正常水平,而33例(28.7%)随着时间的推移显示RDW水平升高。入院时RDW升高的患者中,40例(88.9%)保持升高,5例(11.1%)恢复正常。入院时幸存者和非幸存者的平均RDW值无显著差异(幸存者为14.4 [SD 2.4],非幸存者为14.9 [SD 2.4], p=0.2081)。RDW高组入院时死亡风险高于RDW正常组,但差异无统计学意义(31.1% vs. 21.7%; RR = 1.43; p=0.413)。当进行多变量分析时,以下因素仍然是降低生存率的危险因素:年龄100 - 70岁,风险比4.8 (95% CI: 2.3; 10.3), p < 0.001;白种人,HR 3.2 (95% CI: 1.2; 8.61), p=0.018;有创MV的必要性,HR 3.8 (1.7; 8.7), p=0.001。胸片提示COVID-19, HR 3.5 (95% CI: 1.0; 11.5), p=0.044,在本分析中似乎也是一个危险因素。结论:入院时RDW值的改变与更高的死亡率无关,住院期间RDW的进一步增加与所有年龄组的更高死亡率无关。我们的研究结果表明,虽然RDW可能表明疾病的严重程度,但当在该队列中考虑其他因素时,它可能不能作为死亡率的可靠独立预测因子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.30
自引率
0.00%
发文量
108
审稿时长
>12 weeks
期刊介绍: Canadian Journal of Infectious Diseases and Medical Microbiology is a peer-reviewed, Open Access journal that publishes original research articles, review articles, and clinical studies related to infectious diseases of bacterial, viral and parasitic origin. The journal welcomes articles describing research on pathogenesis, epidemiology of infection, diagnosis and treatment, antibiotics and resistance, and immunology.
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