ABSTRACT
Objective:To explore the relationship between the dynamic changes of lymphocytes in the early stage (within 72 hours of admission) and the severity of disease in patients with coronavirus disease 2019 (COVID-19).Methods:A retrospective study was conducted. The clinical data of COVID-19 patients admitted in Wenzhou Central Hospital from January 17, 2020 to February 14, 2020 were collected and analyzed. According to whether there was lymphopenia on the first day of admission [lymphocyte count (LYM) < 0.8×10 9/L], whether the difference between LYM on the third day and the first day of admission (ΔLYM) was less than 0, the patients were divided into four groups: the first group was LYM normal on the first day of admission, ΔLYM ≥ 0; the second group was LYM normal on the first day of admission, ΔLYM < 0; the third group was lymphopenia on the first day of admission, ΔLYM ≥ 0; the fourth group was lymphopenia on the first day of admission, ΔLYM < 0. The study endpoint was the development of severe/critically ill patients within 30 days after admission. Severe/critical standard referred to classification of Diagnosis and treatment protocol for coronavirus disease 2019 (trial version 5, revised edition). The differences in general information, laboratory results, and probability of developing severe/critical were compared among the four groups. Cox regression analysis was used to analyze the correlation between the early dynamic changes of lymphocytes and the probability of severe illness; and the Kaplan-Meier survival curve was drawn to assess the probability of severe illness in patients with different LYM groups. Results:A total of 104 patients with COVID-19 were enrolled, and 21 patients developed to severe/critical cases within 30 days of onset (accounting for 20.2%; 17 severe cases and 4 critical cases). There were significant differences in age ( F = 5.061, P = 0.003), white blood cell count (WBC) on the first day of admission ( Z = 10.850, P = 0.013), C-reactive protein (CRP) on the first day of admission ( Z = -4.449, P < 0.001), LYM on the first day of admission ( Z = 43.132, P < 0.001), LYM on the third day of admission ( Z = 40.340, P < 0.001), and the occurrence of severe/critical illness ( χ2 = 18.645, P < 0.001) among the four groups. Patients in groups 3 and 4 were older; patients in group 3 had the lowest WBC and LYM on the first day of admission; patients in group 4 had the highest CRP on the first day of admission, the lowest LYM on the third day of admission, and high proportion of severe/critical cases. Regarding the probability of severe/critically ill patients within 30 days of admission, univariate Cox regression analysis showed that the probability of severe/critical patients in group 4 was 12.7 times higher than that in group 1 [hazard ratio ( HR) = 12.732, 95% confidence interval (95% CI) was 3.951-41.025, P < 0.001]; age, CRP, albumin (ALB) and lymphocyte grouping were included in multivariate Cox regression analysis, the probability of severe/critically ill patients in group 4 was 6.4 times that of group 1 ( HR = 6.398, 95% CI was 1.757-23.301, P = 0.005); however, there was no difference in the probability among the group 1, 2 and 3. Kaplan-Meier survival curve showed that the probability of severe/critically ill patients in group 4 was significantly higher than that in groups 1, 2 and 3 (Log-Rank test: χ2 = 42.617, P < 0.001). Conclusions:Early lymphocyte dynamics change is related to the severity of patients with COVID-19. Patients with low LYM on the first day and continued decrease within 72 hours of admission have a higher probability to develop into severe/critically cases.
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Objective:To explore the correlation between early inflammation indicators and the severity of coronavirus disease 2019 (COVID-19).Methods:A retrospective study was conducted. Patients with COVID-19 admitted to Wenzhou Central Hospital from January 17 to February 14, 2020 were enrolled. The general information, chest CT before admission, the first laboratory parameters and chest CT within 24 hours after admission were collected. Patients were followed up for 30 days after the first onset of dyspnea or pulmonary imaging showed that the lesions progressed more than 50% within 24 to 48 hours (according to the criteria for severe cases) as the study endpoint. According to the endpoint, the patients were divided into two groups: mild type/common type group and severe/critical group, and the differences in general information and inflammation index of the two groups were compared. Logistic regression was used to analyze the inflammation index and the severity of COVID-19. Receiver operating characteristic (ROC) curve was draw to evaluate the predictive value of early inflammation indicators for severe/critical in patients with COVID-19.Results:A total of 140 patients with COVID-19 were included, 74 males and 66 females; the average age was (45±14) years old; 6 cases (4.3%) of mild type, 107 cases (76.4%) of common type, and 22 cases (15.7%) of severe type, 5 cases (3.6%) were critical. There were significantly differences in ages (years old: 43±13 vs. 57±13), the proportion of patients with one chronic disease (17.7% vs. 55.6%), C-reactive protein [CRP (mg/L): 7.3 (2.3, 21.0) vs. 40.1 (18.8, 62.6)], lymphocyte count [LYM (×10 9/L): 1.3 (1.0, 1.8) vs. 0.8 (0.7, 1.1)], the neutrophil/lymphocyte ratio [NLR: 2.1 (1.6, 3.0) vs. 3.1 (2.2, 8.8)] and multilobularinltration, hypo-lymphocytosis, bacterial coinfection, smoking history, hyper-tension and age [MuLBSTA score: 5.0 (3.0, 5.0) vs. 5.0 (5.0, 7.0)] between mild/common group and severe/critical group (all P < 0.05). Univariate Logistic regression analysis showed that CRP, NLR, MuLBSTA score, age, and whether chronic diseases were associated with the severity of COVID-19 [odds ratio ( OR) and 95% confidence interval (95% CI) were 1.037 (1.020-1.055), 1.374 (1.123-1.680), 1.574 (1.296-1.911), 1.082 (1.042-1.125), 6.393 (2.551-16.023), respectively, all P < 0.01]. Further multivariate Logistic regression analysis showed that CRP and MuLBSTA score were risk factors for the development of COVID-19 to severe/critical cases [OR and 95% CI were 1.024 (1.002-1.048) and 1.321 (1.027-1.699) respectively, both P < 0.05]. ROC curve analysis showed that the area under the curve for CRP and MuLBSTA score to predict severe/critical cases were both 0.818, and the best cut-off points were 27.4 mg/L and 6.0 points, respectively. Conclusion:CRP and MuLBSTA score are related to the severity of COVID-19, and may have good independent predictive ability for the development of severe/critical illness.
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Objective To establish a visualized nomogram with early predictive value for the severity of first-onset acute pancreatitis ( AP ) . Methods 706 cases of first-onset AP patients admitted to the First Affiliated Hospital of Wenzhou Medical University within 72 hours from January 2013 to January 2016 were collected. According to the revised Atlanta classification of AP in 2012, AP patients was divided into non-severe pancreatitis ( NSAP, also called mild acute pancreatitis and moderately severe acute pancreatitis) group and severe acute pancreatitis ( SAP) group. The demographic data ( age, body mass index and admission time, etc) and laboratory tests (serum amylase, blood sugar, albumin, white blood cells, creatinine, urea nitrogen) were collected and statistically analyzed. Logistic univariate and multivariant regression analysis were performed based on the relevant clinical indicators. The statistically significant indicators were used to obtain regression equations. The R-language software was used to obtain the visualized nomogram via LR model, which was further validated by ROC curve analysis. Results In univariate logistic regression analysis, the OR ( 95％CI) values of blood glucose, creatinine at admission and 24 h after admission, urea nitrogen at admission and 24 h after admission, white blood cell, albumin in NSAP group and SAP group were 1. 132(1. 080-1. 186), 1. 019(1. 013-1. 025), 1. 026(1. 020-1. 033), 1. 066(1. 035-1. 099), 1. 333(1. 241-1. 432), 1. 083 (1.032-1.136), and 0.853(0.811-0.889), and all the differences were statistically significant (all P values <0. 05). Multivariate logistic regression analysis showed that the regression equation of the LR model was Y= -2. 657-0. 116 × albumin(g/L) +0. 082 × white blood cell( × 109/L) +0. 118 × glycemia(mmol/L) +0. 022 × 24 h after admission creatinine (μmol/L). A total score of more than 60 points on the nomogram predicted the possibility of SAP. If the total score exceeded 130, the possibility of SAP may be up to 14％ or more. Furthermore, the ROC curve analysis confirmed that the sensitivity and specificity of LR model established in this study for predicting of SAP were superior to those of urea nitrogen, creatinine and BISAP score alone by AUC, respectively. Conclusions This nomogram may be a useful clinical tool for predicting the severity of the first-onset acute pancreatitis.
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Objective@#To establish a visualized nomogram with early predictive value for the severity of first-onset acute pancreatitis (AP).@*Methods@#706 cases of first-onset AP patients admitted to the First Affiliated Hospital of Wenzhou Medical University within 72 hours from January 2013 to January 2016 were collected. According to the revised Atlanta classification of AP in 2012, AP patients was divided into non-severe pancreatitis (NSAP, also called mild acute pancreatitis and moderately severe acute pancreatitis) group and severe acute pancreatitis (SAP) group. The demographic data (age, body mass index and admission time, etc) and laboratory tests (serum amylase, blood sugar, albumin, white blood cells, creatinine, urea nitrogen) were collected and statistically analyzed. Logistic univariate and multivariant regression analysis were performed based on the relevant clinical indicators. The statistically significant indicators were used to obtain regression equations. The R-language software was used to obtain the visualized nomogram via LR model, which was further validated by ROC curve analysis.@*Results@#In univariate logistic regression analysis, the OR (95% CI) values of blood glucose, creatinine at admission and 24 h after admission, urea nitrogen at admission and 24 h after admission, white blood cell, albumin in NSAP group and SAP group were 1.132(1.080-1.186), 1.019(1.013-1.025), 1.026(1.020-1.033), 1.066(1.035-1.099), 1.333(1.241-1.432), 1.083(1.032-1.136), and 0.853(0.811-0.889), and all the differences were statistically significant (all P values <0.05). Multivariate logistic regression analysis showed that the regression equation of the LR model was Y=-2.657-0.116×albumin(g/L)+ 0.082×white blood cell(×109/L)+ 0.118× glycemia(mmol/L)+ 0.022× 24 h after admission creatinine (μmol/L). A total score of more than 60 points on the nomogram predicted the possibility of SAP. If the total score exceeded 130, the possibility of SAP may be up to 14% or more. Furthermore, the ROC curve analysis confirmed that the sensitivity and specificity of LR model established in this study for predicting of SAP were superior to those of urea nitrogen, creatinine and BISAP score alone by AUC, respectively.@*Conclusions@#This nomogram may be a useful clinical tool for predicting the severity of the first-onset acute pancreatitis.