According to the results of our study, four easily available and low-cost laboratory characteristics appear to be import predictors of classification in critical patients after hospital admission. The new classification model based on four laboratory characteristics was demonstrated to had better discriminative ability than other 3 current popular systems. The results of AUC, NRI and DCA analysis also demonstrated that it was the best classifier. The discriminative ability of it was also externally validated.
CRP level were positively correlated with the severity of COVID-19. It was consistent with some previous studies. CRP can activate the complement system to enhance the regulation of lymphocytes and promote the phagocytosis of macrophages to eliminate the invading pathogens [18, 19]. Some studies of COVID-19 showed that CRP level was significantly increased specifically in patients with severe disease [20, 21]. The reason might be some inflammatory factors such as interleukin 6, interleukin 1, tumor necrosis α could promote the synthesis of CRP by hepatocytes [18]. Ko et al. found that CRP ≥ 2 mg/dl was one of the predictive factors for pneumonia development of Middle East respiratory syndrome (MERS), while CRP ≥ 4 mg/dl, low albumin level, male, hypertension, thrombocytopenia, lymphopenia were regarded as the predictive factors for respiratory failure [22]. A recent retrospective study also showed that CRP levels of patients with COVID-19 were also significantly higher in the death group on admission [23]. Liu et al. reported that IL-6 and CRP could be used as independent factors to predict the severity of COVID-19, and those patients were more likely to have severe complications while their CRP level larger 41.8 mg/L [24]. Wang also suggested that CRP level can be regarded as an important biomarker in the early stage of COVID-19 because CRP could reflect lung lesions and disease severity [25]. Albumin was the second potential biomarker found in our study. It could be detected in the blood and was a protein made in the liver. Albumin could prevent leakage of the fluids from the blood into other organs [26]. Increasing number of studies showed that low albumin levels were associated with poorer outcomes of patients with COVID-19 [27]. Albumin concentration was suggested as an independent risk factor for mortality in patients with pneumonia and also found associated with COVID-19 [28, 29]. A systematic reviewed and meta-analysis showed that hypoalbuminemia status increased risk of severe COVID-19 [30]. Our study also described that lower sodium was a risk factor for severe COVID-19 infection. Sodium was considered a predicator in several scoring systems for assessing pneumonia, including the PSI and Acute Physiology and Chronic Health Evaluation II. Hyponatremia was the most common electrolyte disorder in clinical practice and severe hyponatremia was associated with increased mortality [31]. Berni et al. found that sodium was inversely correlated with IL-6 in COVID-19 patients, directly correlated with PaO2/FiO2 ratio [32]. Stephan J.L Bakker gave a hypothesis about that low sodium balance may augment cellular damage at a certain virus load and increase the risk of developing severe and fatal COVID-19 infection by their experimental and epidemiological data [33]. Finally, globulin was suggested to be positively relative with the severity of COVID-19. Yafei Zhang demonstrated that the globulin level in severe COVID-19 patients is significantly increased while comparing to the mild patients because the promoted immunoglobulin synthesis [27].
In addition, the CPIS, a diagnostic algorithm, is mainly applied for ventilator-associated pneumonia and community-acquired pneumonia. Most studies indicated that CPIS had inaccurate sensitivity and specificity [34–37]. The CPIS was suggested to have high inter-observer variability and is not available for multiple centers study [37, 38]. The CURB-65 score consists of 5 separate elements: confusion, uremia, respiratory rate, blood pressure, and age ≥ 65. The CURB-65 is relatively simple to use. The PSI involves 20 clinical variables defining 5 classes of increasing risk of mortality. It has been extensively validated. However, the inappropriate weights of age or inappropriate threshold values for both the PSI and CURB-65 result in a potential underestimation of severe pneumonia, especially in young people [39, 40].
A major limitation of the current study is the insufficient sample size. As more raw data will be collected in the future, we would have the ability to optimize our new model. Another limitation of our study was that we had to combine patients with critical presentation to severe presentation because there were only 6 patients with a critical clinical presentation in our study.
In conclusion, four easily available and low-cost laboratory characteristics appear to be import predictors of classification in critical patients after hospital admission. They guide therapeutic options and help clinicians make clinical decisions. Hence, we believe that such classification is essential for a more rational allocation scarce medical resource.