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The CB index predicts prognosis of critically ill COVID-19 patients
Liang Cao1, Sha Zhang2, Enxin Wang3
1Department of Traditional Chinese Medicine, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Insights
A new CB index, combining blood urea nitrogen (BUN) and high-sensitivity C-reactive protein (hs-CRP), effectively predicts mortality risk in critically ill COVID-19 patients. This tool aids clinicians in identifying high-risk individuals for timely interventions.
Area of Science:
- Critical Care Medicine
- Infectious Diseases
- Biomarkers
Background:
- COVID-19 poses a significant global health threat, with critically ill patients experiencing high in-hospital mortality rates.
- Identifying prognostic factors is crucial for guiding clinical decisions and therapeutic interventions in severe COVID-19 cases.
Purpose of the Study:
- To identify independent prognostic factors for mortality in critically ill COVID-19 patients.
- To develop and validate a predictive model for assessing survival outcomes.
Main Methods:
- Retrospective analysis of 171 critically ill COVID-19 patients from two medical centers.
- Univariate and multivariate logistic regression to identify prognostic factors.
- Development and external validation of a linear prediction index (CB index).
Main Results:
- Blood urea nitrogen (BUN) and high-sensitivity C-reactive protein (hs-CRP) were independent negative predictors of survival.
- The CB index (hs-CRP + BUN) demonstrated high sensitivity (86.7%) and specificity (89.7%) for predicting death.
- A high-risk group (CB index >32) exhibited a 56.3-fold increased risk of mortality compared to the low-risk group.
Conclusions:
- The CB index serves as a valuable prognostic factor for critically ill COVID-19 patients.
- This index can assist clinicians in stratifying patient risk and informing treatment strategies.
Background:
The global outbreak of COVID-19 is a significant threat to public health. Among COVID-19 cases, critically ill patients account for most in-hospital deaths. Given the pressing clinical needs, identification of potential prognostic factors that would assist clinicians to determine appropriate therapeutic interventions is urgently needed.
Methods:
A retrospective analysis of 171 critically ill COVID-19 patients from two medical centers in Wuhan was conducted. The training and validation cohorts were comprised of 77 and 94 patients, respectively. Univariate and multivariate Logistic regression analyses were used to identify independent prognostic factors, and the linear prediction index was established and externally validated.
Results:
Blood urine nitrogen (BUN) and high-sensitive C-reactive protein (hs-CRP) were independent factors negatively correlated with patient survival in the training cohort. A linear prediction model, named as the CB index (hs-CRP combined with BUN), was established and logistic regression analysis showed that this was associated with a 13% increase in death rate, with high sensitivity (86.7%) and specificity (89.7%). Patients were then divided into a high-risk group (CB index >32) and low-risk group (CB index <32) and the high-risk group showed a 56.3-fold risk of death compared with the low-risk group. Importantly, these findings were readily recaptured in the validation cohort. The efficacy of the CB index in predicting prognosis in real-world patients was then determined, which showed that patients with a higher CB index had an increased risk of death in comparison to those with a lower CB index.
Conclusions:
The CB index may be an important prognostic factor in critically ill COVID-19 patients.
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