Predictors of progression from moderate to severe coronavirus disease 2019: a retrospective cohort.
ABSTRACT: OBJECTIVE:Most cases of coronavirus disease 2019 (COVID-19) are identified as moderate, which is defined as having a fever or dry cough and lung imaging with ground-glass opacities. The risk factors and predictors of prognosis in such cohorts remain uncertain. METHODS:All adults with COVID-19 of moderate severity diagnosed using quantitative RT-PCR and hospitalized at the Central Hospital of Wuhan, China, from 1 January to 20 March 2020 were enrolled in this retrospective study. The main outcomes were progression from moderate to severe or critical condition or death. RESULTS:Among the 456 enrolled patients with moderate COVID-19, 251/456 (55.0%) had poor prognosis. Multivariate logistic regression analysis identified higher neutrophil count: lymphocyte count ratio (NLR) on admission (OR 1.032, 95% CI 1.042-1.230, p 0.004) and higher C-reactive protein (CRP) on admission (OR 3.017, 95% CI 1.941-4.690, p < 0.001) were associated with increased OR of poor prognosis. The area under the receiver operating characteristic curve (AUC) for NLR and CRP in predicting progression to critical condition was 0.77 (95% CI 0.694-0.846, p < 0.001) and 0.84 (95% CI 0.780-0.905, p < 0.001), with a cut-off value of 2.79 and 25.95 mg/L, respectively. The AUC of NLR and CRP in predicting death was 0.81 (95% CI 0.732-0.878, p < 0.001) and 0.89 (95% CI 0.825-0.946, p < 0.001), with a cut-off value of 3.19 and 33.4 mg/L, respectively. CONCLUSIONS:Higher levels of NLR and CRP at admission were associated with poor prognosis of individuals with moderate COVID-19. NLR and CRP were good predictors of progression to critical condition and death.
Project description:Background:Coronavirus disease 2019 (COVID-19) has spread rapidly worldwide from Wuhan. An easy-to-use index capable of the early identification of inpatients who are at risk of becoming critically ill is urgently needed in clinical practice. Hence, the aim of this study was to explore an easy-to-use nomogram and a model to triage patients into risk categories to determine the likelihood of developing a critical illness. Methods:A retrospective cohort study was conducted. We extracted data from 84 patients with laboratory-confirmed COVID-19 from one designated hospital. The primary endpoint was the development of severe/critical illness within 7 days after admission. Predictive factors of this endpoint were selected by LASSO Cox regression model. A nomogram was developed based on selected variables. The predictive performance of the derived nomogram was evaluated by calibration curves and decision curves. Additionally, the predictive performances of individual and combined variables under study were evaluated by receiver operating characteristic curves. The developed model was also tested in a separate validation set with 71 laboratory-confirmed COVID-19 patients. Results:None of the 84 inpatients were lost to follow-up in this retrospective study. The primary endpoint occurred in 23 inpatients (27.4%). The neutrophil-to-lymphocyte ratio (NLR) and C-reactive protein (CRP) were selected as the final prognostic factors. A nomogram was developed based on the NLR and CRP. The calibration curve and decision curve indicated that the constructed nomogram model was clinically useful. The AUCs for the NLR, CRP and Combined Index in both training set and validation sets were 0.685 (95% CI: 0.574-0.783), 0.764 (95% CI: 0.659-0.850), 0.804 (95% CI: 0.702-0.883), and 0.881 (95% CI: 0.782-0.946), respectively. Conclusions:Our results demonstrated that the nomogram and Combined Index calculated from the NLR and CRP are potential and reliable predictors of COVID-19 prognosis and can triage patients at the time of admission.
Project description:BACKGROUND:Coronavirus disease 2019 (COVID-19) emerged first in December 2019 in Wuhan, China and quickly spread throughout the world. Clinical and laboratory data are of importance to increase the success in the management of COVID-19 patients. METHODS:Data were obtained retrospectively from medical records of 191 hospitalized patients diagnosed with COVID-19 from a tertiary single-center hospital between March and April 2020. Prognostic effects of variables on admission among patients who received intensive care unit (ICU) support and those who didn't require ICU care were compared. RESULTS:Patients required ICU care (n = 46) were older (median, 71 vs. 43 years), with more underlying comorbidities (76.1% vs. 33.1%). ICU patients had lower lymphocytes, percentage of large unstained cell (%LUC), hemoglobin, total protein, and albumin, but higher leucocytes, neutrophils, neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), platelet-lymphocytes ratio (PLR), urea, creatinine, aspartate amino transferase (AST), lactate dehydrogenase (LDH), and D-dimer when compared with non-critically ill patients (p < 0.001). A logistic regression model was created to include ferritin, %LUC, NLR, and D-dimer. %LUC decrease and D-dimer increase had the highest odds ratios (0.093 vs 5.597, respectively) to predict severe prognosis. D-dimer, CRP, and NLR had the highest AUC in the ROC analysis (0.896, 0.874, 0.861, respectively). CONCLUSIONS:The comprehensive analysis of clinical and admission laboratory parameters to identify patients with severe prognosis is important not only for the follow-up of the patients but also to identify the pathophysiology of the disease. %LUC decrease and D-dimer, NLR, and CRP increases seem to be the most powerful laboratory predictors of severe prognosis.
Project description:<h4>Background</h4>The neutrophil-to-lymphocyte ratio (NLR), an inflammatory marker, was suggested to be predictive of severity and mortality in COVID-19 patients. Here, we investigated whether NLR levels on admission could predict the severity and mortality of COVID-19 patients.<h4>Methods</h4>A literature search was conducted on 23 July 2020 to retrieve all published articles, including grey literature and preprints, investigating the association between on-admission NLR values and severity or mortality in COVID-19 patients. A meta-analysis was performed to determine the overall standardized mean difference (SMD) in NLR values and the pooled risk ratio (RR) for severity and mortality with the 95% Confidence Interval (95%CI).<h4>Results</h4>A total of 38 articles, including 5699 patients with severity outcomes and 6033 patients with mortality outcomes, were included. The meta-analysis showed that severe and non-survivors of COVID-19 had higher on-admission NLR levels than non-severe and survivors (SMD 0.88; 95%CI 0.72-1.04; I<sup>2</sup> = 75.52% and 1.87; 95%CI 1.25-2.49; I<sup>2</sup> = 97.81%, respectively). Regardless of the different NLR cut-off values, the pooled mortality RR in patients with elevated vs. normal NLR levels was 2.74 (95%CI 0.98-7.66).<h4>Conclusion</h4>High NLR levels on admission were associated with severe COVID-19 and mortality. Further studies need to focus on determining the optimal cut-off value for NLR before clinical use.
Project description:BACKGROUND:Since December 2019, the outbreak of COVID-19 caused a large number of hospital admissions in China. Many patients with COVID-19 have symptoms of acute respiratory distress syndrome, even are in danger of death. This is the first study to evaluate dynamic changes of D-Dimer and Neutrophil-Lymphocyte Count Ratio (NLR) as a prognostic utility in patients with COVID-19 for clinical use. METHODS:In a retrospective study, we collected data from 349 hospitalized patients who diagnosed as the infection of the COVID-19 in Wuhan Pulmonary Hospital. We used ROC curves and Cox regression analysis to explore critical value (optimal cut-off point associated with Youden index) and prognostic role of dynamic changes of D-Dimer and NLR. RESULTS:Three hundred forty-nine participants were enrolled in this study and the mortality rate of the patients with laboratory diagnosed COVID-19 was 14.9%. The initial and peak value of D-Dimer and NLR in deceased patients were higher statistically compared with survivors (P?<?0.001). There was a more significant upward trend of D-Dimer and NLR during hospitalization in the deceased patients, initial D-Dimer and NLR were lower than the peak tests (MD) -25.23, 95% CI: -?31.81- -18.64, P?<?0.001; (MD) -43.73, 95% CI:-59.28- -31.17, P?<?0.001. The test showed a stronger correlation between hospitalization days, PCT and peak D-Dimer than initial D-Dimer. The areas under the ROC curves of peak D-Dimer and peak NLR tests were higher than the initial tests (0.94(95%CI: 0.90-0.98) vs. 0.80 (95% CI: 0.73-0.87); 0.93 (95%CI:0.90-0.96) vs. 0.86 (95%CI:0.82-0.91). The critical value of initial D-Dimer, peak D-Dimer, initial NLR and peak NLR was 0.73?mg/L, 3.78?mg/L,7.13 and 14.31 respectively. 35 (10.03%) patients were intubated. In the intubated patients, initial and peak D-Dimer and NLR were much higher than non-intubated patients (P <?0.001). The critical value of initial D-Dimer, peak D-Dimer, initial NLR and peak NLR in prognosticate of intubation was 0.73?mg/L, 12.75?mg/L,7.28 and 27.55. The multivariable Cox regression analysis showed that age (HR 1.04, 95% CI 1.00-1.07, P?=?0.01), the peak D-Dimer (HR 1.03, 95% CI 1.01-1.04, P?<?0.001) were prognostic factors for COVID-19 patients' death. CONCLUSIONS:To dynamically observe the ratio of D-Dimer and NLR was more valuable during the prognosis of COVID-19. The rising trend in D-Dimer and NLR, or the test results higher than the critical values may indicate a risk of death for participants with COVID-19.
Project description:Background: The recent outbreak of coronavirus disease 2019 (COVID-19) has been rapidly spreading on a global scale and poses a great threat to human health. Acute respiratory distress syndrome, characterized by a rapid onset of generalized inflammation, is the leading cause of mortality in patients with COVID-19. We thus aimed to explore the effect of risk factors on the severity of the disease, focusing on immune-inflammatory parameters, which represent the immune status of patients. Methods: A comprehensive systematic search for relevant studies published up to April 2020 was performed by using the PubMed, Web of Science, EMBASE, and China National Knowledge Internet (CNKI) databases. After extracting all available data of immune-inflammatory indicators, we statistically analyzed the risk factors of severe and non-severe COVID-19 patients with a meta-analysis. Results: A total of 4,911 patients from 29 studies were included in the final meta-analysis. The results demonstrated that severe patients tend to present with increased white blood cell (WBC) and neutrophil counts, neutrophil-lymphocyte ratio (NLR), procalcitonin (PCT), C-reaction protein (CRP), erythrocyte sedimentation rate (ESR), and Interleukin-6 (IL-6) and a decreased number of total lymphocyte and lymphocyte subtypes, such as CD4+ T lymphocyte and CD8+ T lymphocyte, compared to the non-severe patients. In addition, the WBC count>10 × 109/L, lymphocyte count<1 × 109/L, PCT>0.5 ng/mL, and CRP>10 mg/L were risk factors for disease progression in patients with COVID-19 (WBC count>10 × 109/L: OR = 2.92, 95% CI: 1.96-4.35; lymphocyte count<1 × 109/L: OR = 4.97, 95% CI: 3.53-6.99; PCT>0.5 ng/mL: OR = 6.33, 95% CI: 3.97-10.10; CRP>10 mg/L: OR = 3.51, 95% CI: 2.38-5.16). Furthermore, we found that NLR, as a novel marker of systemic inflammatory response, can also help predict clinical severity in patients with COVID-19 (OR = 2.50, 95% CI: 2.04-3.06). Conclusions: Immune-inflammatory parameters, such as WBC, lymphocyte, PCT, CRP, and NLR, could imply the progression of COVID-19. NLR has taken both the levels of neutrophil and lymphocyte into account, indicating a more complete, accurate, and reliable inspection efficiency; surveillance of NLR may help clinicians identify high-risk COVID-19 patients at an early stage.
Project description:<b>Background:</b> Since December 2019, Coronavirus disease 2019 (COVID-19) has emerged as an international pandemic. COVID-19 patients with myocardial injury might need special attention. However, understanding on this aspect remains unclear. This study aimed to illustrate clinical characteristics and the prognostic value of myocardial injury to COVID-19 patients. <b>Methods:</b> This retrospective, single-center study finally included 304 hospitalized COVID-19 cases confirmed by real-time RT-PCR from January 11 to March 25, 2020. Myocardial injury was determined by serum high-sensitivity troponin I (Hs-TnI). The primary endpoint was COVID-19 associated mortality. <b>Results:</b> Of 304 COVID-19 patients (median age, 65 years; 52.6% males), 88 patients (27.3%) died (61 patients with myocardial injury, 27 patients without myocardial injury on admission). COVID-19 patients with myocardial injury had more comorbidities (hypertension, chronic obstructive pulmonary disease, cardiovascular disease, and cerebrovascular disease); lower lymphocyte counts, higher C-reactive protein (CRP, median, 84.9 vs 28.5 mg/L, p<0.001), procalcitonin levels (median, 0.29 vs 0.06 ng/ml, p<0.001), inflammatory and immune response markers; more frequent need for noninvasive ventilation, invasive mechanical ventilation; and was associated with higher mortality incidence (hazard ratio, HR=7.02, 95% confidence interval, CI, 4.45-11.08, p<0.001) than those without myocardial injury. Myocardial injury (HR=4.55, 95% CI, 2.49-8.31, p<0.001), senior age, CRP levels, and novel coronavirus pneumonia (NCP) types on admission were independent predictors to mortality in COVID-19 patients. <b>Conclusions:</b> COVID patients with myocardial injury on admission is associated with more severe clinical presentation and biomarkers. Myocardial injury and higher HsTNI are both strongest independent predictors to COVID related mortality after adjusting confounding factors. In addition, senior age, CRP levels and NCP types are also associated with mortality. <b>Trial registration:</b> Not applicable.
Project description:<h4>Background and aims</h4>Emerging data have linked the presence of cardiac injury with a worse prognosis in novel coronavirus disease 2019 (COVID-19) patients. However, available data cannot clearly characterize the correlation between cardiac injury and COVID-19. Thus, we conducted a meta-analysis of recent studies to 1) explore the prevalence of cardiac injury in different types of COVID-19 patients and 2) evaluate the association between cardiac injury and worse prognosis (severe disease, admission to ICU, and mortality) in patients with COVID-19.<h4>Methods and results</h4>Literature search was conducted through PubMed, the Cochrane Library, Embase, and MedRxiv databases. A meta-analysis was performed with Stata 14.0. A fixed-effects model was used if the I<sup>2</sup> values ? 50%, otherwise the random-effects model was performed. The prevalence of cardiac injury was 19% (95% CI: 0.15-0.22, and p < 0.001) in total COVID-19 patients, 36% (95% CI: 0.25-0.47, and p < 0.001) in severe COVID-19 patients, and 48% (95% CI: 0.30-0.66, and p < 0.001) in non-survivors. Furthermore, cardiac injury was found to be associated with a significant increase in the risk of poor outcomes with a pooled effect size (ES) of 8.46 (95% CI: 3.76-19.06, and p = 0.062), severe disease with an ES of 3.54 (95% CI: 2.25-5.58, and p < 0.001), admission to ICU with an ES of 5.03 (95% CI: 2.69-9.39, and p < 0.001), and mortality with an ES of 4.99 (95% CI: 3.38-7.37, and p < 0.001).<h4>Conclusions</h4>The prevalence of cardiac injury was greatly increased in COVID-19 patients, particularly in patients with severe disease and non-survivors. COVID-19 patients with cardiac injury are more likely to be associated with poor outcomes, severity of disease, admission to ICU, and mortality.
Project description:<h4>Aims</h4>To investigate the prognostic value of admission blood glucose (BG) in predicting COVID-19 outcomes, including poor composite outcomes (mortality/severity), mortality, and severity.<h4>Methods</h4>Eligible studies evaluating the association between admission fasting BG (FBG) and random BG (RBG) levels with COVID-19 outcomes were included and assessed for risk of bias with the Quality in Prognosis Studies tool. Random-effects dose-response meta-analysis was conducted to investigate potential linear or non-linear exposure-response gradient.<h4>Results</h4>The search yielded 35 studies involving a total of 14,502 patients. We discovered independent association between admission FBG and poor COVID-19 prognosis. Furthermore, we demonstrated non-linear relationship between admission FBG and severity (P<sub>non-linearity</sub> < 0.001), where each 1 mmol/L increase augmented the risk of severity by 33% (risk ratio 1.33 [95% CI: 1.26-1.40]). Albeit exhibiting similar trends, study scarcity limited the evidence strength on the independent prognostic value of admission RBG. GRADE assessment yielded high-quality evidence for the association between admission FBG and COVID-19 severity, and moderate-quality evidence for its association with mortality and poor outcomes.<h4>Conclusion</h4>High admission FBG level independently predicted poor COVID-19 prognosis. Further research to confirm the prognostic value of admission RBG and to ascertain the estimated dose-response risk between admission FBG and COVID-19 severity are required.
Project description:BACKGROUND:Determining the factors affecting the mortality and clinical conditions of the patients with Covid-19 are indispensable needs in developing patient treatment algorithms. We aimed to determine the parameters that can predict the mortality of moderate to severely ill patients with laboratory confirmed Covid-19. METHODS:Moderate to severely ill, Covid-19 patients older than 18 years were included. Mild Covid-19 patients and the ones with negative polymerase chain reaction test results were excluded from the study. The primary outcome of the study was 30-day mortality rate and we aimed to determine the factors affecting mortality in moderate to severely ill Covid-19 patients. RESULTS:168 patient results were analyzed. Median age of the patients was 59.5 (48.3 to 76) and 90 (53.6%) were male. According to multivariate regression analysis results, the presence of any comorbid disease (p = 0.027, HR = 26.11 (95%CI: 1.45 to 471.31)), elevated C-reactive protein levels (CRP) (p < 0.001, HR = 1.24 (95%CI: 1.11 to 1.38)) and presence of dyspnea (p = 0.026, HR = 4.26 ((95%CI: 1.19 to 15.28)) were found to significantly increase the mortality, while high pulse O 2 saturation level (p < 0.001, HR = 0.90 (95%CI: 0.82 to 0.99) was found to decrease. When receiver operating characteristic curve was created for laboratory tests, it was determined that white blood cell counts, neutrophil counts, CRP levels and neutrophil/lymphocyte ratio predicted mortality while Lymphocyte levels did not. CONCLUSION:Dyspnea, the presence of any comorbid disease, elevated CRP levels, and low pulse O 2 saturation levels predict mortality in moderate to severely ill Covid-19 patients.
Project description:<h4>Background & aims</h4>Adipose tissue is a biologically active organ with pro-immunogenic properties. We aimed to evaluate the prognostic value of epicardial adipose tissue (EAT) in COVID-19 and its correlation with other inflammatory biomarkers.<h4>Material and methods</h4>One-hundred patients with COVID-19 were enrolled. C-reactive protein (CRP), lactate dehydrogenase (LDH), neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-CRP ratio (LCR), and platelet-to-lymphocyte ratio (PLR) were evaluated on admission. EAT volume and density were measured by computed tomography. Patients were followed until death or discharge. Univariate and multivariate analysis was performed and ROC curve analysis was used to assess the ability of inflammatory markers in predicting survival. The relationship between EAT and other inflammatory markers was also investigated.<h4>Results</h4>The mean ± SD age of patients was 55.5 ± 15.2 years old; 68% were male. Univariate analysis revealed that increased lung involvement, blood urea nitrogen, LDH and NLR, and decreased platelet count were significantly associated with death. After adjustment, LDH was independently predictive of death (OR = 1.013, p-value = 0.03). Among inflammatory markers, LCR had the best ability for predicting survival with 79.7% sensitivity and 64.3% specificity at an optimal cut-off value of 20.8 (AUC = 0.744, 95% CI = 0.612-0.876, p-value = 0.004). EAT volume demonstrated positive correlation with NLR and PLR (p = 0.001 and 0.01), and a negative correlation with LCR (p = 0.02). EAT density was significantly different between decedents and survivors (p = 0.008).<h4>Conclusion</h4>Routine laboratory tests that represent status of inflammation can be used as cost-effective prognostic markers of COVID-19. Also, the significant association between EAT volume and other inflammatory biomarkers might explain the more severe disease in obese patients.