scholarly journals Early prognostication of COVID-19 to guide hospitalisation versus outpatient monitoring using a point-of-test risk prediction score

2020 ◽  
Author(s):  
Felix Chua ◽  
Rama Vancheeswaran ◽  
Adrian Draper ◽  
Tejal Vaghela ◽  
Matthew Knight ◽  
...  
Keyword(s):  
Predictive Accuracy ◽  
Fatal Outcome ◽  
Individual Characteristics ◽  
Adverse Outcomes ◽  
Hospital Death ◽  
Derivation Cohort ◽  
Outpatient Monitoring ◽  
Characteristic Values ◽  
Large Random Sample ◽  
Mortality Predictors

ABSTRACTIntroductionRisk factors of adverse outcomes in COVID-19 are defined but stratification of mortality using non-laboratory measured scores, particularly at the time of pre-hospital SARS-CoV-2 testing, is lacking.MethodsMultivariate regression with bootstrapping was used to identify independent mortality predictors in a derivation cohort of COVID-19 patients. Predictions were externally validated in a large random sample of the ISARIC cohort (N=14,231) and a smaller cohort from Aintree (N=290).Results983 patients (median age 70, IQR 53-83; in-hospital mortality 29.9%) were recruited over an 11-week study period. Through sequential modelling, a 5-predictor score termed SOARS (SpO2, Obesity, Age, Respiratory rate, Stroke history) was developed to correlate COVID-19 severity across low, moderate and high strata of mortality risk. The score discriminated well for in-hospital death, with area under the receiver operating characteristic values of 0.82, 0.80 and 0.74 in the derivation, Aintree and ISARIC validation cohorts respectively. Its predictive accuracy (calibration) in both external cohorts was consistently higher in patients with milder disease (SOARS 0-1), the same individuals who could be identified for safe outpatient monitoring. Prediction of a non-fatal outcome in this group was accompanied by high score sensitivity (99.2%) and negative predictive value (95.9%).ConclusionThe SOARS score uses constitutive and readily assessed individual characteristics to predict the risk of COVID-19 death. Deployment of the score could potentially inform clinical triage in pre-admission settings where expedient and reliable decision-making is key. The resurgence of SARS-CoV-2 transmission provides an opportunity to further validate and update its performance.

scholarly journals Early prognostication of COVID-19 to guide hospitalisation versus outpatient monitoring using a point-of-test risk prediction score

Thorax ◽  
2021 ◽  
pp. thoraxjnl-2020-216425
Author(s):  
Felix Chua ◽  
Rama Vancheeswaran ◽  
Adrian Draper ◽  
Tejal Vaghela ◽  
Matthew Knight ◽  
...  
Keyword(s):  
Operating Characteristic ◽  
Predictive Accuracy ◽  
Fatal Outcome ◽  
Individual Characteristics ◽  
Adverse Outcomes ◽  
Hospital Death ◽  
Outpatient Monitoring ◽  
Characteristic Values ◽  
Large Random Sample ◽  
Mortality Predictors

IntroductionRisk factors of adverse outcomes in COVID-19 are defined but stratification of mortality using non-laboratory measured scores, particularly at the time of prehospital SARS-CoV-2 testing, is lacking.MethodsMultivariate regression with bootstrapping was used to identify independent mortality predictors in patients admitted to an acute hospital with a confirmed diagnosis of COVID-19. Predictions were externally validated in a large random sample of the ISARIC cohort (N=14 231) and a smaller cohort from Aintree (N=290).Results983 patients (median age 70, IQR 53–83; in-hospital mortality 29.9%) were recruited over an 11-week study period. Through sequential modelling, a five-predictor score termed SOARS (SpO2, Obesity, Age, Respiratory rate, Stroke history) was developed to correlate COVID-19 severity across low, moderate and high strata of mortality risk. The score discriminated well for in-hospital death, with area under the receiver operating characteristic values of 0.82, 0.80 and 0.74 in the derivation, Aintree and ISARIC validation cohorts, respectively. Its predictive accuracy (calibration) in both external cohorts was consistently higher in patients with milder disease (SOARS 0–1), the same individuals who could be identified for safe outpatient monitoring. Prediction of a non-fatal outcome in this group was accompanied by high score sensitivity (99.2%) and negative predictive value (95.9%).ConclusionThe SOARS score uses constitutive and readily assessed individual characteristics to predict the risk of COVID-19 death. Deployment of the score could potentially inform clinical triage in preadmission settings where expedient and reliable decision-making is key. The resurgence of SARS-CoV-2 transmission provides an opportunity to further validate and update its performance.

scholarly journals Size-adjusted aortic valve area: refining the definition of severe aortic stenosis

2020 ◽  
Author(s):  
Branka Vulesevic ◽  
Naozumi Kubota ◽  
Ian G Burwash ◽  
Claire Cimadevilla ◽  
Sarah Tubiana ◽  
...  
Keyword(s):  
Aortic Valve ◽  
Predictive Accuracy ◽  
Severe Aortic Stenosis ◽  
Aortic Valve Area ◽  
Obese Patients ◽  
Derivation Cohort ◽  
Wide Range ◽  
Definition Of ◽  
Diagnostic And Prognostic Value ◽  
Valve Area

Abstract Aims Severe aortic valve stenosis (AS) is defined by an aortic valve area (AVA) <1 cm2 or an AVA indexed to body surface area (BSA) <0.6 cm/m2, despite little evidence supporting the latter approach and important intrinsic limitations of BSA indexation. We hypothesized that AVA indexed to height (H) might be more applicable to a wide range of populations and body morphologies and might provide a better predictive accuracy. Methods and results In 1298 patients with degenerative AS and preserved ejection fraction from three different countries and continents (derivation cohort), we aimed to establish an AVA/H threshold that would be equivalent to 1.0 cm2 for defining severe AS. In a distinct prospective validation cohort of 395 patients, we compared the predictive accuracy of AVA/BSA and AVA/H. Correlations between AVA and AVA/BSA or AVA/H were excellent (all R2 > 0.79) but greater with AVA/H. Regressions lines were markedly different in obese and non-obese patients with AVA/BSA (P < 0.0001) but almost identical with AVA/H (P = 0.16). AVA/BSA values that corresponded to an AVA of 1.0 cm2 were markedly different in obese and non-obese patients (0.48 and 0.59 cm2/m2) but not with AVA/H (0.61 cm2/m for both). Agreement for the diagnosis of severe AS (AVA < 1 cm2) was significantly higher with AVA/H than with AVA/BSA (P < 0.05). Similar results were observed across the three countries. An AVA/H cut-off value of 0.6 cm2/m [HR = 8.2(5.6–12.1)] provided the best predictive value for the occurrence of AS-related events [absolute AVA of 1 cm2: HR = 7.3(5.0–10.7); AVA/BSA of 0.6 cm2/m2 HR = 6.7(4.4–10.0)]. Conclusion In a large multinational/multiracial cohort, AVA/H was better correlated with AVA than AVA/BSA and a cut-off value of 0.6 cm2/m provided a better diagnostic and prognostic value than 0.6 cm2/m2. Our results suggest that severe AS should be defined as an AVA < 1 cm2 or an AVA/H < 0.6 cm2/m rather than a BSA-indexed value of 0.6 cm2/m2.

scholarly journals Prognostic value of D-dimer for adverse outcomes in patients with infective endocarditis: an observational study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ying-Wen Lin ◽  
Mei Jiang ◽  
Xue-biao Wei ◽  
Jie-leng Huang ◽  
Zedazhong Su ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Infective Endocarditis ◽  
Adverse Events ◽  
Prognostic Value ◽  
Multivariable Analysis ◽  
Adverse Outcomes ◽  
Hospital Death ◽  
Large Sample Size ◽  
Cox Regression Analysis ◽  
D Dimer

Abstract Background Increased D-dimer levels have been shown to correlate with adverse outcomes in various clinical conditions. However, few studies with a large sample size have been performed thus far to evaluate the prognostic value of D-dimer in patients with infective endocarditis (IE). Methods 613 patients with IE were included in the study and categorized into two groups according to the cut-off of D-dimer determined by receiver operating characteristic (ROC) curve analysis for in-hospital death: > 3.5 mg/L (n = 89) and ≤ 3.5 mg/L (n = 524). Multivariable regression analysis was used to determine the association of D-dimer with in-hospital adverse events and six-month death. Results In-hospital death (22.5% vs. 7.3%), embolism (33.7% vs 18.2%), and stroke (29.2% vs 15.8%) were significantly higher in patients with D-dimer > 3.5 mg/L than in those with D-dimer ≤ 3.5 mg/L. Multivariable analysis showed that D-dimer was an independent risk factor for in-hospital adverse events (odds ratio = 1.11, 95% CI 1.03–1.19, P = 0.005). In addition, the Kaplan–Meier curve showed that the cumulative 6-month mortality was significantly higher in patients with D-dimer > 3.5 mg/L than in those with D-dimer ≤ 3.5 mg/L (log-rank test = 39.19, P < 0.0001). Multivariable Cox regression analysis showed that D-dimer remained a significant predictor for six-month death (HR 1.11, 95% CI 1.05–1.18, P < 0.001). Conclusions D-dimer is a reliable prognostic biomarker that independently associated with in-hospital adverse events and six-month mortality in patients with IE.

scholarly journals Developing a scoring tool to estimate the risk of deterioration for normotensive patients with acute pulmonary embolism on admission

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yizhuo Gao ◽  
Chao Ji ◽  
Hongyu Zhao ◽  
Jun Han ◽  
Haitao Shen ◽  
...  
Keyword(s):  
Pulmonary Embolism ◽  
Acute Pulmonary Embolism ◽  
Clinical Laboratory ◽  
Systolic Pressure ◽  
Adverse Outcomes ◽  
Web Based ◽  
Derivation Cohort ◽  
Risk Scoring ◽  
Scoring Tool ◽  
Acute Pe

Abstract Background It is important to identify deterioration in normotensive patients with acute pulmonary embolism (PE). This study aimed to develop a tool for predicting deterioration among normotensive patients with acute PE on admission. Methods Clinical, laboratory, and computed tomography parameters were retrospectively collected for normotensive patients with acute PE who were treated at a Chinese center from January 2011 to May 2020 on admission into the hospital. The endpoint of the deterioration was any adverse outcome within 30 days. Eligible patients were randomized 2:1 to derivation and validation cohorts, and a nomogram was developed and validated by the aforementioned cohorts, respectively. The areas under the curves (AUCs) with 95% confidence intervals (CIs) were calculated. A risk-scoring tool for predicting deterioration was applied as a web-based calculator. Results The 845 eligible patients (420 men, 425 women) had an average age of 60.05 ± 15.43 years. Adverse outcomes were identified for 81 patients (9.6%). The nomogram for adverse outcomes included heart rate, systolic pressure, N-terminal-pro brain natriuretic peptide, and ventricle/atrial diameter ratios at 4-chamber view, which provided AUC values of 0.925 in the derivation cohort (95% CI 0.900–0.946, p < 0.001) and 0.900 in the validation cohort (95% CI 0.883–0.948, p < 0.001). A risk-scoring tool was published as a web-based calculator (https://gaoyzcmu.shinyapps.io/APE9AD/). Conclusions We developed a web-based scoring tool that may help predict deterioration in normotensive patients with acute PE.

Features of the course of coronavirus infection in patients with diabetes mellitus

2022 ◽  
pp. 18-21
Author(s):  
Vladimir Anatolievich Klimov ◽  
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Human Population ◽  
Fatal Outcome ◽  
Significant Risk ◽  
Adverse Outcomes ◽  
Concomitant Disease ◽  
Patients With Diabetes ◽  
Coronavirus Infection ◽  
Population Mortality

Diabetesmellitus, overweight and the age of a patient over 65 years old are identified by clinicians as themain factors that can complicate the course of the coronavirus infection and increase the likelihood of fatal outcome. Although in the general human population mortality from coronavirus fluctuateswithin 3–5 %, sometimes very significantly differing in individual countries, this level can reach 15–25 % among patientswith diabetes, especially for those receiving insulin therapy. Diabetes mellitus as a concomitant disease in COVID-19 is considered one of the most significant risk factors for the development of adverse outcomes due to a more severe course of infection in conditions of hyperglycemia and other aggravating factors.

scholarly journals Rhabdomyolysis is Associated with Hospital Mortality in Patients with COVID-19

2020 ◽  
Author(s):  
Yan Geng ◽  
Yong-sheng Du ◽  
Na Peng ◽  
Ting Yang ◽  
Shi-yu Zhang ◽  
...  
Keyword(s):  
Kidney Injury ◽  
Adverse Outcomes ◽  
Hospital Death ◽  
Proportional Hazard ◽  
Coagulation Activation ◽  
Virus Clearance ◽  
Cox Proportional Hazard ◽  
Independent Risk Factors ◽  
Cox Proportional Hazard Regression ◽  
Serum Myoglobin

Abstract Purpose: To evaluate the clinical features and outcomes of rhabdomyolysis (RM) in patients with COVID-19. Method: A single center retrospective cohort study of 1,014 consecutive hospitalized patients with confirmed COVID-19 at the Huoshenshan hospital in Wuhan, China, between February 17 and April 12, 2020. Results: The overall incidence of RM was 2.2%. Comparing with patients without RM, patients with RM tended to have a higher risk of deterioration, representing by higher ratio to be admitted to the intensive care unit (ICU) (90.9 % vs 5.3%, P<0.001), and to undergo mechanical ventilation (86.4 % vs 2.7% P<0.001). Compared with patients without RM, patients with RM had laboratory test abnormalities, including indicators of inflammation, coagulation activation and kidney injury. Patients with RM had a higher risk of hospital death (P < 0.001). Cox proportional hazard regression model confirmed that RM indicators, including peak creatine kinase (CK) >1000 IU/L (HR=6.46, 95% CI: 3.02-13.86), peak serum myoglobin (MYO) >1000 ng/mL (HR=9.85, 95% CI: 5.04-19.28) were independent risk factors for in-hospital death. Additionally, patients with COVID-19 that developed RM tended to have a delayed virus clearance.Conclusion: RM might be an important factor contributing to adverse outcomes of patients with COVID-19. Early detection and effective intervention of RM may help reduce deaths of patients with COVID-19.

A Nomogram to Predict the Probability of Relapse during Hospitalization after Minor Ischemic Stroke in Chinese Patients.

2020 ◽  
Author(s):  
Yu xianfeng ◽  
Yin wenwen ◽  
Huang chaojuan ◽  
Yuan xin ◽  
Xia yu ◽  
...  
Keyword(s):  
Heart Disease ◽  
Ischemic Stroke ◽  
Total Bilirubin ◽  
Individual Characteristics ◽  
Adverse Outcomes ◽  
Unfavorable Outcome ◽  
Chinese Patients ◽  
Serum Total Bilirubin ◽  
Risk Of Recurrence ◽  
Minor Ischemic Stroke

Abstract Background: Predicting the risk of recurrence during hospitalization in patients with minor ischemic stroke (MIS) is of great significance for clinical and treatment. Compared with early models and prognostic scores, nomogram is a better visualization tool for predicting clinical outcomes. It combines different factors to develop a graphical continuous scoring system, and accurately calculates the risk probability of adverse outcomes based on individual characteristics. Our goal is to develop and validate a nomogram for individualized prediction of hospitalization recurrence in patients with mild ischemic stroke in the Chinese population.Methods: Based on retrospective collection, a single center study was conducted in the first affiliated Hospital of Anhui Medical University from January 2014 to December 2019. The subjects were stroke patients with NIHSS≤5.In order to generate the nomogram, age, systolic blood pressure,previous heart disease, serum total bilirubin, ferritin and smoking were integrated into the model. The predictive accuracy of the nomogram model to predict the probability of unfavorable outcome was assessed by calculation of the area under the receiver operating characteristic curve (AUC–ROC). Calibration of the risk prediction model was assessed by the plot comparing the observed probability of unfavorable outcome against the predicted, and by using the Hosmer–Lemeshow test.Results: Age at admission (OR,0.946; 95% CI,-0.002 to 0.048), SBP (OR,0.012,95%CI,0.000 to 0.024), previous heart disease (OR,0.867,95%CI, 0.084 to 1.651), UA (OR,-0.003,95%CI,-0.006 to 0.001), serum total bilirubin (OR,-0.022,95%CI,-0.036 to -0.008), ferritin (OR,0.004,95%CI, 0.002 to 0.005), smoking (OR,0.494,95%CI,-0.115 to 1.103) are significant predictors of in-hospital recurrence in Chinese patients with minor ischemic stroke.The model shows good discrimination, the AUC-ROC value is 0.737 (95%CI:0.676-0.798), and has perfect calibration performance. Calibration was good (p=0.1457 for the Hosmer-Lemesshow test), which could predict the risk of recurrence of MIS patients during hospitalization.Conclusion: The nomogram developed and validated in this study can provide individualized, intuitive and accurate prediction of recurrence in Chinese patients with minor ischemic stroke during hospitalization.

scholarly journals Inequalities of visceral leishmaniasis case-fatality in Brazil: A multilevel modeling considering space, time, individual and contextual factors

2021 ◽  
Vol 15 (7) ◽  
pp. e0009567
Author(s):  
Gláucia Cota ◽  
Astrid Christine Erber ◽  
Eva Schernhammer ◽  
Taynãna Cesar Simões
Keyword(s):  
Visceral Leishmaniasis ◽  
Multilevel Modeling ◽  
Univariate Analysis ◽  
Fatal Outcome ◽  
Case Fatality ◽  
Female Gender ◽  
Individual Characteristics ◽  
Individual Risk ◽  
Aggregated Data ◽  
Disease Information

Background In Brazil, case-fatality from visceral leishmaniasis (VL) is high and characterized by wide differences between the various political-economic units, the federated units (FUs). This study was designed to investigate the association between factors at the both FU and individual levels with the risk of dying from VL, after analysing the temporal trend and the spatial dependency for VL case-fatality. Methodology The analysis was based on individual and aggregated data of the Reportable Disease Information System-SINAN (Brazilian Ministry of Health). The temporal and spatial distributions of the VL case-fatality between 2007 and 2017 (27 FUs as unit of analysis) were considered together with the individual characteristics and many other variables at the FU level (socioeconomic, demographic, access to health and epidemiological indicators) in a mixed effects models or multilevel modeling, assuming a binomial outcome distribution (death from VL). Findings A linear increasing temporal tendency (4%/year) for VL case-fatality was observed between 2007 and 2017. There was no similarity between the case-fatality rates of neighboring FUs (non-significant spatial term), although these rates were heterogeneous in this spatial scale of analysis. In addition to the known individual risk factors age, female gender, disease’s severity, bacterial co-infection and disease duration, low level schooling and unavailability of emergency beds and health professionals (the last two only in univariate analysis) were identified as possibly related to VL death risk. Lower VL incidence was also associated to VL case-fatality, suggesting that unfamiliarity with the disease may delay appropriate medical management: VL patients with fatal outcome were notified and had VL treatment started 6 and 3 days later, respectively, in relation to VL cured patients. Access to garbage collection, marker of social and economic development, seems to be protective against the risk of dying from VL. Part of the observed VL case-fatality variability in Brazil could not be explained by the studied variables, suggesting that factors linked to the intra FU environment may be involved. Conclusions This study aimed to identify epidemiological conditions and others related to access to the health system possibly linked to VL case-fatality, pointing out new prognostic determinants subject to intervention.

scholarly journals Epidemiology and Mortality Predictors for Severe Childhood Pneumonia in ICUs: A Real-World Study in China

2020 ◽  
Author(s):  
lu cao ◽  
zhaohua ji ◽  
yan zuo ◽  
jingwen wang
Keyword(s):  
Real World ◽  
Age Groups ◽  
Severe Pneumonia ◽  
Hospital Death ◽  
Observation Study ◽  
Childhood Pneumonia ◽  
Prophylactic Measures ◽  
Sedative Hypnotics ◽  
Independent Risk Factors ◽  
Mortality Predictors

Abstract Background To identify the epidemiology and mortality predictors for severe childhood pneumonia and evaluate the influence of medications on clinical outcome in the real world.Methods We performed a retrospective observation study among children with severe pneumonia aged ≤ 5 years of age, separately comparing the detailed information between the in-hospital death cases and the survival cases in two different age groups. Multivariate regression model was used to figure out mortality predictors.Results 945 children were recruited, including 604 infants and 341 young children. Overall 88 deaths occurred (9.3%). There was low adherence to guidelines in antimicrobials and carbapenems were widely served as initial empiric regimens, but the efficacy was not superior to the guidelines recommended. In multivariate analyses, very severe pneumonia (OR: 3.55; 95% CI: 1.39–9.09), lower birth weight (OR: 3.92; 95% CI: 1.50-10.23), severe underweight (OR: 4.72; 95% CI: 1.92–11.62), mechanical ventilation (OR: 5.06; 95% CI: 1.97–12.95;OR: 14.43; 95% CI 3.31–62.96),comorbidity including anemia (OR: 5.61; 95% CI: 2.36–13.35), neonatal asphyxia (OR: 6.03; 95% CI: 1.57–23.12), gastrointestinal hemorrhage (OR: 3.73; 95% CI: 1.21–11.48) and sedative-hypnotics ( OR: 4.32; 95% CI: 1.76–10.61; OR: 4.13; 95% CI༚1.50-11.38) were independent risk factors for death, whereas a lower mortality was present in infants with probiotics (OR: 0.24; 95% CI: 0.10–0.54).Conclusions Severe pneumonia remains a primary cause of death in children under 5 years of age. Clinical characteristics, comorbidity and medications are evidently associated with death. Importantly, we should pay particular attention to the identification of the mortality predictors and establish prophylactic measures to reduce the mortality.

scholarly journals Derivation and Validation of a Nomogram for Predicting 90-Day Survival in Patients With HBV-Related Acute-on-Chronic Liver Failure

2021 ◽  
Vol 8 ◽  
Author(s):  
Jun-feng Chen ◽  
Wei-zhen Weng ◽  
Miao Huang ◽  
Xiao-hua Peng ◽  
Jian-rong He ◽  
...  
Keyword(s):  
Liver Failure ◽  
Calibration Curve ◽  
Retrospective Cohort ◽  
Predictive Accuracy ◽  
Multivariable Analysis ◽  
Scoring Systems ◽  
Chronic Liver ◽  
Prognostic Models ◽  
Chronic Liver Failure ◽  
Derivation Cohort

Background: Conventional prognostic models do not fully reflect the severity of hepatitis B virus (HBV)-related acute-on-chronic liver failure (ACLF). This study aimed to establish an effective and convenient nomogram for patients with HBV-related ACLF.Methods: A nomogram was developed based on a retrospective cohort of 1,353 patients treated at the Third Affiliated Hospital of Sun Yat-sen University from January 2010 to June 2016. The predictive accuracy and discriminatory ability of the nomogram were determined by a concordance index (C-index) and calibration curve, and were compared with current scoring systems. The results were validated using an independent retrospective cohort of 669 patients consecutively treated at the same institution from July 2016 to March 2018. This study is registered at ClinicalTrials.gov (NCT03992898).Results: Multivariable analysis of the derivation cohort found that independent predictors of 90-day survival were age, white blood cell (WBC) count, hemoglobin (Hb), aspartate aminotransferase (AST), total bilirubin (TBil), international normalized ratio, serum creatinine (Cr), alpha fetoprotein (AFP), serum sodium (Na), hepatic encephalopathy (HE), pre-existing chronic liver disease(PreLD), and HBV DNA load. All factors were included in the nomogram. The nomogram calibration curve for the probability of 90-day survival indicated that nomogram-based predictions were in good agreement with actual observations. The C-index of the nomogram was 0.790, which was statistically significantly greater than those for the current scoring systems in the derivation cohort (P &lt; 0.001). The results were confirmed in the validation cohort.Conclusions: The proposed nomogram is more accurate in predicting the 90-day survival of patients with HBV-related ACLF than current commonly used methods.

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