ABSTRACT
Rationale COVID-19 pandemic has imposed tremendous stress and burden on the economy and society worldwide. There is an urgent demand to find a new model to estimate the deterioration of patients inflicted by Omicron variants. Objective This study aims to develop a model to predict the deterioration of elderly patients inflicted by Omicron Sub-variant BA.2. Methods COVID-19 patients were randomly divided into the training and the validation cohorts. Both Lasso and Logistic regression analyses were performed to identify prediction factors, which were then selected to build a deterioration model in the training cohort. This model was validated in the validation cohort. Measurements and main results The deterioration model of COVID-19 was constructed with five indices, including C-reactive protein, neutrophil count/lymphocyte count (NLR), albumin/globulin ratio (A/G), international normalized ratio (INR), and blood urea nitrogen (BUN). The area under the ROC curve (AUC) showed that this model displayed a high accuracy in predicting deterioration, which was 0.85 in the training cohort and 0.85 in the validation cohort. The nomogram provided an easy way to calculate the possibility of deterioration, and the decision curve analysis (DCA) and clinical impact curve analysis (CICA)showed good clinical net profit using this model. Conclusion The model we constructed can identify and predict the risk of deterioration (requirement for ventilatory support or death) in elderly patients and it is clinically practical, which will facilitate medical decision making and allocating medical resources to those with critical conditions.
ABSTRACT
Objective: The aim of the present study is to assess the utility of C-reactive protein to Lymphocyte Ratio (CLR) in predicting short-term clinical outcomes of patients infected by SARS-CoV-2 BA.2.2. Methods: This retrospective study was performed on 1,219 patients with laboratory-confirmed SARS-CoV-2 BA.2.2 to determine the association of CLR with short-term clinical outcomes. Independent Chi square test, Rank sum test, and binary logistic regression analysis were performed to calculate mean differences and adjusted odds ratios (aORs) with their 95% CI, respectively. Results: Over 8% of patients admitted due to SARS-CoV-2 BA.2.2. were critically ill. The best cut-off value of CLR was 21.25 in the ROC with a sensitivity of 72.3% and a specificity of 86%. After adjusting age, gender, and comorbidities, binary logistic regression analysis showed that elevated CLR was an independent risk factor for poor short-term clinical outcomes of COVID-19 patients. Conclusion: C-reactive protein to Lymphocyte Ratio is a significant predictive factor for poor short-term clinical outcomes of SARS-CoV-2 BA.2.2 inflicted patients.
Subject(s)
COVID-19 , Humans , C-Reactive Protein/analysis , SARS-CoV-2 , Retrospective Studies , ROC Curve , LymphocytesABSTRACT
BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) has been an almost global pandemic with significant public health impacts. The increasing prevalence of malignancy has become a leading cause of human mortality. However, conflicting findings have been published on the association between malignancy and COVID-19 severity. This study aims to assess the pooled proportion of malignancy amongst 2019-nCov patients and to investigate the association between malignancy and COVID-19 severity. METHODS: Correlative studies were identi?ed by systematically searching electronic databases (PubMed, Web of Sciences and Embase) up to September 2, 2020. All data analyses were carried out using Stata 15.0. RESULTS: Twenty-nine studies consisting of 9475 confirmed COVID-19 patients (median age 54.4 years [IQR 49-62], 54.0% men) were included. The overall proportion of malignancy was 2.5% (95% CI 1.6%-3.4%). The proportion of malignancy was higher in patients with severe/critical 2019-nCoV than those in non-severe/non-critical group (3.9% [95% CI 2.0-6.3] vs 1.4% [95% CI 0.8-2.2]). Furthermore, pre-existing malignancy was associated with more than twofold higher risk of severe/critical patients with COVID-19 (OR 2.25, 95% CI 1.65-3.06 I2 = 0.0%). CONCLUSION: Malignancy was associated with up to 2.3-fold higher risk of severe/critical COVID-19 and may serve as a clinical predictor for adverse outcomes.