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Predictive value of D-dimer to albumin ratio for severe illness and mortality in patients with COVID-19.
Xiao, Benjie; Yang, Zhangwei; Liang, Huazheng; Han, Yudi; Wu, Yinyan; Xiao, Jingjing; Bi, Yong.
Afiliación
  • Xiao B; Department of Neurology, Zhoupu Hospital Affiliated to Shanghai University of Medicine & Health Sciences, Shanghai, China.
  • Yang Z; Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
  • Liang H; Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
  • Han Y; Medical Department, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
  • Wu Y; Suzhou Industrial Park Monash Research Institute of Science and Technology, Suzhou, Jiangsu, China.
  • Xiao J; Department of Neurology, Shanghai Fourth People's Hospital Affiliated to Tongji University School of Medicine, Shanghai, China.
  • Bi Y; Department of Neurology, Shanghai Fourth People's Hospital Affiliated to Tongji University School of Medicine, Shanghai, China.
Front Med (Lausanne) ; 11: 1410179, 2024.
Article en En | MEDLINE | ID: mdl-39144651
ABSTRACT

Objective:

Although the impact of the variants of COVID-19 on the general population is diminishing, there is still a certain mortality rate for severe and critically ill patients, especially for the elderly with comorbidities. The present study investigated whether the D-dimer to albumin ratio (DAR) can predict the severity of illness and mortality in COVID-19 patients.

Methods:

A total of 1,993 patients with COVID-19 were retrospectively reviewed and the association of DAR with severe or critical illness or death during hospitalization was analyzed. The area under the ROC curve was used to screen the best indicators, Chi-square test, rank sum test, and univariate and multivariate binary logistic regression analysis were used to calculate the mean value of difference and adjusted odds ratio (aORs) with their 95% CI, and finally, survival was analyzed using Kaplan-Meier (KM) curves.

Results:

Among 1,993 patients with COVID-19, 13.4% were severely ill, and the mortality rate was 2.3%. The area under the curve (AUC) using DAR to predict severe and critically ill patients was higher than that using other parameters. The best cut-off value of DAR was 21 in the ROC with a sensitivity of 83.1% and a specificity of 68.7%. After adjusting age, gender, comorbidities, and treatment, the binary logistic regression analysis showed that elevated DAR was an independent risk factor for severely ill and mortality of COVID-19 patients. The KM curve suggested that patients with a higher DAR was associated with worse survival. The negative predictive value of DAR (21) for adverse prognosis and death was 95.98 and 99.84%, respectively, with a sensitivity of 80.9 and 95.65%, respectively.

Conclusion:

The DAR may be an important predictor for severe illness and mortality in COVID-19 patients.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Med (Lausanne) Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Med (Lausanne) Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza