scholarly journals Concordance probability as a meaningful contrast across disparate survival times

2020 ◽  
pp. 096228022097369
Author(s):  
Sean M Devlin ◽  
Glenn Heller
Keyword(s):  
Prognostic Score ◽  
Area Under The Curve ◽  
Risk Scores ◽  
Survival Times ◽  
Time To Event ◽  
Cell Renal Cell Carcinoma ◽  
Concordance Probability ◽  
Direct Input ◽  
The Times ◽  
Definition Of

The performance of time-to-event models is frequently assessed in part by estimating the concordance probability, which evaluates the probabilistic pairwise ordering of the model-based risk scores and survival times. The standard definition of this probability conditions on any survival time pair ordering, irrespective of whether the times are meaningfully separated. Inclusion of survival times that would be deemed clinically similar attenuates the concordance and moves the estimate away from the contrast-of-interest: comparing the risk scores between individuals with disparate survival times. In this manuscript, we propose a concordance definition and corresponding method to estimate the probability conditional on survival times being separated by at least a minimum difference. The proposed estimate requires direct input from the analyst to identify a separable survival region and, in doing so, is analogous to the clinically defined subgroups used for binary outcome area under the curve estimates. The method is illustrated in two cancer examples: a prognostic score in clear cell renal cell carcinoma and two biomarkers in metastatic prostate cancer.

scholarly journals External assessment of the EUROMACS right-sided heart failure risk score

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hirak Shah ◽  
Thomas Murray ◽  
Jessica Schultz ◽  
Ranjit John ◽  
Cindy M. Martin ◽  
...  
Keyword(s):  
Heart Failure ◽  
Right Ventricular ◽  
Risk Score ◽  
Pressure Ratio ◽  
Area Under The Curve ◽  
Left Ventricular ◽  
Right Atrial ◽  
Risk Scores ◽  
External Assessment ◽  
Failure Risk

AbstractThe EUROMACS Right-Sided Heart Failure Risk Score was developed to predict right ventricular failure (RVF) after left ventricular assist device (LVAD) placement. The predictive ability of the EUROMACS score has not been tested in other cohorts. We performed a single center analysis of a continuous-flow (CF) LVAD cohort (n = 254) where we calculated EUROMACS risk scores and assessed for right ventricular heart failure after LVAD implantation. Thirty-nine percent of patients (100/254) had post-operative RVF, of which 9% (23/254) required prolonged inotropic support and 5% (12/254) required RVAD placement. For patients who developed RVF after LVAD implantation, there was a 45% increase in the hazards of death on LVAD support (HR 1.45, 95% CI 0.98–2.2, p = 0.066). Two variables in the EUROMACS score (Hemoglobin and Right Atrial Pressure to Pulmonary Capillary Wedge Pressure ratio) were not predictive of RVF in our cohort. Overall, the EUROMACS score had poor external discrimination in our cohort with area under the curve of 58% (95% CI 52–66%). Further work is necessary to enhance our ability to predict RVF after LVAD implantation.

scholarly journals Multi-scale characterizations of colon polyps via computed tomographic colonography

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Weiguo Cao ◽  
Marc J. Pomeroy ◽  
Yongfeng Gao ◽  
Matthew A. Barish ◽  
Almas F. Abbasi ◽  
...  
Keyword(s):  
Area Under The Curve ◽  
Texture Features ◽  
Learning Model ◽  
Colon Polyps ◽  
Texture Descriptor ◽  
Operating Characteristics ◽  
Computed Tomographic ◽  
Multi Scale ◽  
Definition Of ◽  
Occurrence Matrix

AbstractTexture features have played an essential role in the field of medical imaging for computer-aided diagnosis. The gray-level co-occurrence matrix (GLCM)-based texture descriptor has emerged to become one of the most successful feature sets for these applications. This study aims to increase the potential of these features by introducing multi-scale analysis into the construction of GLCM texture descriptor. In this study, we first introduce a new parameter - stride, to explore the definition of GLCM. Then we propose three multi-scaling GLCM models according to its three parameters, (1) learning model by multiple displacements, (2) learning model by multiple strides (LMS), and (3) learning model by multiple angles. These models increase the texture information by introducing more texture patterns and mitigate direction sparsity and dense sampling problems presented in the traditional Haralick model. To further analyze the three parameters, we test the three models by performing classification on a dataset of 63 large polyp masses obtained from computed tomography colonoscopy consisting of 32 adenocarcinomas and 31 benign adenomas. Finally, the proposed methods are compared to several typical GLCM-texture descriptors and one deep learning model. LMS obtains the highest performance and enhances the prediction power to 0.9450 with standard deviation 0.0285 by area under the curve of receiver operating characteristics score which is a significant improvement.

scholarly journals Clinical risk scores for the early prediction of severe outcomes in patients hospitalized for COVID-19

2021 ◽  
Author(s):  
Walter Ageno ◽  
◽  
Chiara Cogliati ◽  
Martina Perego ◽  
Domenico Girelli ◽  
...  
Keyword(s):  
Hospital Admission ◽  
Predictive Value ◽  
Clinical Laboratory ◽  
Area Under The Curve ◽  
Orotracheal Intubation ◽  
Risk Scores ◽  
Algorithm Selection ◽  
Derivation Cohort ◽  
Neutrophil Lymphocyte Ratio ◽  
Predictive Risk

AbstractCoronavirus disease of 2019 (COVID-19) is associated with severe acute respiratory failure. Early identification of high-risk COVID-19 patients is crucial. We aimed to derive and validate a simple score for the prediction of severe outcomes. A retrospective cohort study of patients hospitalized for COVID-19 was carried out by the Italian Society of Internal Medicine. Epidemiological, clinical, laboratory, and treatment variables were collected at hospital admission at five hospitals. Three algorithm selection models were used to construct a predictive risk score: backward Selection, Least Absolute Shrinkage and Selection Operator (LASSO), and Random Forest. Severe outcome was defined as the composite of need for non-invasive ventilation, need for orotracheal intubation, or death. A total of 610 patients were included in the analysis, 313 had a severe outcome. The subset for the derivation analysis included 335 patients, the subset for the validation analysis 275 patients. The LASSO selection identified 6 variables (age, history of coronary heart disease, CRP, AST, D-dimer, and neutrophil/lymphocyte ratio) and resulted in the best performing score with an area under the curve of 0.79 in the derivation cohort and 0.80 in the validation cohort. Using a cut-off of 7 out of 13 points, sensitivity was 0.93, specificity 0.34, positive predictive value 0.59, and negative predictive value 0.82. The proposed score can identify patients at low risk for severe outcome who can be safely managed in a low-intensity setting after hospital admission for COVID-19.

scholarly journals Different chest CT scoring systems in patients with COVID-19: could baseline CT be a helpful tool in predicting survival in patients with matched ages and co-morbid conditions?

2021 ◽  
pp. 028418512110063
Author(s):  
Okan Dilek ◽  
Emin Demirel ◽  
Hüseyin Akkaya ◽  
Mehmet Cenk Belibagli ◽  
Gokhan Soker ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Severity Score ◽  
Area Under The Curve ◽  
Scoring Systems ◽  
Survival Prediction ◽  
Success Rates ◽  
Survival Times ◽  
The Mean ◽  
Early Decision ◽  
Age Range

Background Computed tomography (CT) gives an idea about the prognosis in patients with COVID-19 lung infiltration. Purpose To evaluate the success rates of various scoring methods utilized in order to predict survival periods, on the basis of the imaging findings of COVID-19. Another purpose, on the other hand, was to evaluate the agreements among the evaluating radiologists. Material and Methods A total of 100 cases of known COVID-19 pneumonia, of which 50 were deceased and 50 were living, were included in the study. Pre-existing scoring systems, which were the Total Severity Score (TSS), Chest Computed Tomography Severity Score (CT-SS), and Total CT Score, were utilized, together with the Early Decision Severity Score (ED-SS), which was developed by our team, to evaluate the initial lung CT scans of the patients obtained at their initial admission to the hospital. The scans were evaluated retrospectively by two radiologists. Area under the curve (AUC) values were acquired for each scoring system, according to their performances in predicting survival times. Results The mean age of the patients was 61 ± 14.85 years (age range = 18–87 years). There was no difference in co-morbidities between the living and deceased patients. The survival predicted AUC values of ED-SS, CT-SS, TSS, and Total CT Score systems were 0.876, 0.823, 0.753, and 0.744, respectively. Conclusion Algorithms based on lung infiltration patterns of COVID-19 may be utilized for both survival prediction and therapy planning.

Performance of Automated Telemetry in Diagnosing QT Prolongation in Critically Ill Patients

2021 ◽  
Vol 30 (6) ◽  
pp. 466-470
Author(s):  
Enrique Calvo-Ayala ◽  
Vince Procopio ◽  
Hayk Papukhyan ◽  
Girish B. Nair
Keyword(s):  
Critically Ill ◽  
Critically Ill Patients ◽  
Demographic Data ◽  
Area Under The Curve ◽  
Qt Prolongation ◽  
Altman Analysis ◽  
Poor Agreement ◽  
Bland Altman Analysis ◽  
Prolonged Qt ◽  
Definition Of

Background QT prolongation increases the risk of ventricular arrhythmia and is common among critically ill patients. The gold standard for QT measurement is electrocardiography. Automated measurement of corrected QT (QTc) by cardiac telemetry has been developed, but this method has not been compared with electrocardiography in critically ill patients. Objective To compare the diagnostic performance of QTc values obtained with cardiac telemetry versus electrocardiography. Methods This prospective observational study included patients admitted to intensive care who had an electrocardiogram ordered simultaneously with cardiac telemetry. Demographic data and QTc determined by electrocardiography and telemetry were recorded. Bland-Altman analysis was done, and correlation coefficient and receiver operating characteristic (ROC) coefficient were calculated. Results Fifty-one data points were obtained from 43 patients (65% men). Bland-Altman analysis revealed poor agreement between telemetry and electrocardiography and evidence of fixed and proportional bias. Area under the ROC curve for QTc determined by telemetry was 0.9 (P < .001) for a definition of prolonged QT as QTc ≥ 450 milliseconds in electrocardiography (sensitivity, 88.89%; specificity, 83.33%; cutoff of 464 milliseconds used). Correlation between the 2 methods was only moderate (r = 0.6, P < .001). Conclusions QTc determination by telemetry has poor agreement and moderate correlation with electrocardiography. However, telemetry has an acceptable area under the curve in ROC analysis with tolerable sensitivity and specificity depending on the cutoff used to define prolonged QT. Cardiac telemetry should be used with caution in critically ill patients.

scholarly journals A Novel m6A Gene Signature Associated With Regulatory Immune Function for Prognosis Prediction in Clear-Cell Renal Cell Carcinoma

2021 ◽  
Vol 8 ◽  
Author(s):  
Siteng Chen ◽  
Ning Zhang ◽  
Encheng Zhang ◽  
Tao Wang ◽  
Liren Jiang ◽  
...  
Keyword(s):  
Risk Score ◽  
Clear Cell ◽  
Area Under The Curve ◽  
The Cancer Genome Atlas ◽  
Survival Prediction ◽  
Cell Renal Cell Carcinoma ◽  
Training Cohort ◽  
Rna Methylation ◽  
Cancer Genome Atlas ◽  
Genome Atlas

The important role of N6-methyladenosine (m6A) RNA methylation regulator in carcinogenesis and progression of clear-cell renal cell carcinoma (ccRCC) is poorly understood by now. In this study, we performed comprehensive analyses of m6A RNA methylation regulators in 975 ccRCC samples and 332 adjacent normal tissues and identified ccRCC-related m6A regulators. Moreover, the m6A diagnostic score based on ccRCC-related m6A regulators could accurately distinguish ccRCC from normal tissue in the Meta-cohort, which was further validated in the independent GSE-cohort and The Cancer Genome Atlas-cohort, with an area under the curve of 0.924, 0.867, and 0.795, respectively. Effective survival prediction of ccRCC by m6A risk score was also identified in the Cancer Genome Atlas training cohort and verified in the testing cohort and the independent GSE22541 cohort, with hazard ratio values of 3.474, 1.679, and 2.101 in the survival prognosis, respectively. The m6A risk score was identified as a risk factor of overall survival in ccRCC patients by the univariate Cox regression analysis, which was further verified in both the training cohort and the independent validation cohort. The integrated nomogram combining m6A risk score and predictable clinicopathologic factors could accurately predict the survival status of the ccRCC patients, with an area under the curve values of 85.2, 82.4, and 78.3% for the overall survival prediction in 1-, 3- and 5-year, respectively. Weighted gene co-expression network analysis with functional enrichment analysis indicated that m6A RNA methylation might affect clinical prognosis through regulating immune functions in patients with ccRCC.

scholarly journals Asthma Exacerbation Prediction and Risk Factor Analysis Based on a Time-Sensitive, Attentive Neural Network: Retrospective Cohort Study

10.2196/16981 ◽  
2020 ◽  
Vol 22 (7) ◽  
pp. e16981
Author(s):  
Yang Xiang ◽  
Hangyu Ji ◽  
Yujia Zhou ◽  
Fang Li ◽  
Jingcheng Du ◽  
...  
Keyword(s):  
Neural Network ◽  
Risk Factors ◽  
Asthma Exacerbation ◽  
Area Under The Curve ◽  
Risk Scores ◽  
Model Parameters ◽  
Supporting Evidence ◽  
Contributing Factors ◽  
Clinical Variables ◽  
Personalized Risk

Background Asthma exacerbation is an acute or subacute episode of progressive worsening of asthma symptoms and can have a significant impact on patients’ quality of life. However, efficient methods that can help identify personalized risk factors and make early predictions are lacking. Objective This study aims to use advanced deep learning models to better predict the risk of asthma exacerbations and to explore potential risk factors involved in progressive asthma. Methods We proposed a novel time-sensitive, attentive neural network to predict asthma exacerbation using clinical variables from large electronic health records. The clinical variables were collected from the Cerner Health Facts database between 1992 and 2015, including 31,433 adult patients with asthma. Interpretations on both patient and cohort levels were investigated based on the model parameters. Results The proposed model obtained an area under the curve value of 0.7003 through a five-fold cross-validation, which outperformed the baseline methods. The results also demonstrated that the addition of elapsed time embeddings considerably improved the prediction performance. Further analysis observed diverse distributions of contributing factors across patients as well as some possible cohort-level risk factors, which could be found supporting evidence from peer-reviewed literature such as respiratory diseases and esophageal reflux. Conclusions The proposed neural network model performed better than previous methods for the prediction of asthma exacerbation. We believe that personalized risk scores and analyses of contributing factors can help clinicians better assess the individual’s level of disease progression and afford the opportunity to adjust treatment, prevent exacerbation, and improve outcomes.

scholarly journals Validation of Predictive Ability of Bobi Score in Burn Patients

2021 ◽  
Vol 6 (4) ◽  
Keyword(s):  
Burn Injury ◽  
Prognostic Score ◽  
Area Under The Curve ◽  
Predictive Ability ◽  
Scoring Systems ◽  
Good Prediction ◽  
Burn Patients ◽  
Severe Burns ◽  
Inhalation Burn ◽  
Outstanding Result

Introduction: Scoring systems have been used successfully in burn centers to predict the prognosis and take measures for careful monitoring of the burned patient. Belgium Outcome Burn Injury score is one of them which takes into consideration age, burn surface area, and presence of inhalation burn. Objectives: This presentation aims to validate the use of the BOBI prognostic score in our patients. Patients and Methods: The study is a retrospective analytical study that utilized the investigation of the medical charts of 1515 patients hospitalized with severe burns within the ICU of the Service of Burns in Tirana, Albania during 2010-2019. Results: The overall mortality of our patients was 7.06% (107 deaths in 1515 patients). Up to BOBI score 6, we have noticed better mortality than prediction while there is a very good prediction up to score 10. Area Under the Curve was 0.978 (p<0.0001) which is an outstanding result in being a classifier between deaths and survivors. Conclusions: BOBI score is a very good prediction score for mortality in burn patients.

scholarly journals Working Class in Soviet and Russian Sociological Discourse

2018 ◽  
Vol 14 (4) ◽  
pp. 86-92
Author(s):  
V. Gavriliuk ◽  
T. Gavriliuk
Keyword(s):  
Social Change ◽  
Working Class ◽  
Social Structure ◽  
Organizational Structures ◽  
Russian Society ◽  
Capitalist System ◽  
Planning And Control ◽  
The Times ◽  
Definition Of ◽  
And Control

The Object of the Study. The correlation of class and stratification approaches in Soviet and post-Soviet sociology.The Subject of the Study. New working class in Russian sociological discourse.The Purpose of the Study. The objectives are to substantiate the necessity of actualizing of the class approach in the study of modern Russian society social structure; identifying the signs of a new working class.The Main Provisions of the Article. In accordance with Marxist ideology, in Soviet sociology a working class was regarded as a protagonist of social change and a center of attraction for the forces of social change. The contemporary integration of workers into the capitalist system, the transition to the economy of the sixth order, the defeat of socialism, the global transition to a postindustrial society require to comprehend the «working question» from a new prospective. The authors actualize the problem of revealing the content and structure of the «new working class», traditional and actual methods of its theoretical conceptualization. The features of class and stratification approaches to the allocation of the working class in the structure of society have been studied. It has been shown that the excessive specification of criteria, non-critical declarative positioning of the middle class into the basis of the Russian society structure, led to a high degree of uncertainty in the model of the social structure of the Russian society of the early XXI century. The author's definition of the concept of a new working class has been given. Defining “the new working class of modern Russia”, we mean a group of employees in all spheres of material production and services whose content and nature of work are routinized and segmented; not participating in management and not having the property rights to the enterprise in which they work. Most of the times, these are workers without higher education. Power and control in the organization do not belong to them, their degree of freedom and authority in organizational structures are limited, they do not influence on the planning and control of labor

ON THE FORMATION OF GERMAN REALISM

2021 ◽  
Vol 23 (77) ◽  
pp. 81-90
Author(s):  
A.S. Bakalov ◽  
Keyword(s):  
Literary Criticism ◽  
Literary Realism ◽  
Regional Literature ◽  
Empirical Level ◽  
New Business ◽  
Main Thing ◽  
The Times ◽  
Life Phenomena ◽  
Definition Of ◽  
The 19Th Century

The relevance of research. In German literary criticism, there is no unambiguous definition of the phenomenon of literary realism, however, at the empirical level, it is understood as a literary system based on a mimetic-oriented depiction of reality, often critically comprehended and subjectively colored due to the norms and ideas that are taking shape in society. Research methodology. Complex and systematic methods of literature analysis are applied. In this article, the author comes to the conclusion that the realism of the turn of the XIX - early XX centuries. retains its main principles of artistic comprehension of the world, and at the same time the signs that do not allow talking about its dissolution in the eclectic picture of the emerging modernity. The main thing remains the disclosure of "the essence of life phenomena through their individualized generalization (typification)", analysis and specific historical logic of presentation Realism at the turn of the 19th - early 20th centuries. closely associated with such phenomena as regional literature, "new business-like", historical novel. On its basis, workers' and proletarian-revolutionary literature developed in many ways. In German literature of the twentieth century. realistic tendencies intensified in the times following the historical and political catastrophes, primarily after the two world wars lost by Germany. Realism played a significant role in the literature of the Weimar Republic (the works of E.M. Remarque, L. Feuchtwanger, L. Frank and others), while in contact with modernist and avant-garde trends (for example, with "new business-like"). Realism turned out to be no less significant after 1945, having equally influenced the formation of the literatures of West and East Germany (writers of the "group of 47", Erwin Strittmatter, "socialist realism", etc.). German realism, which emerged in the middle of the 19th century, was able to demonstrate its flexibility and ability to enter into alliances with other natural artistic directions, without losing its main specificity - the desire for materiality, the authenticity of personal and collective experience, as well as symbolizing the "obvious" with the goal of approaching the "true".

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