scholarly journals Plasma Choline as a Diagnostic Biomarker in Slow Coronary Flow

2020 ◽  
Vol 2020 ◽  
pp. 1-8 ◽  
Author(s):  
Yuan-Ting Zhu ◽  
Ling-Ping Zhu ◽  
Zhen-Yu Wang ◽  
Xue-Ting Qiu ◽  
Wan-Zhou Wu ◽  
...  
Keyword(s):  
Coronary Artery ◽  
Receiver Operating Characteristic ◽  
Coronary Flow ◽  
Operating Characteristic ◽  
Confounding Factor ◽  
Accurate Method ◽  
Diagnostic Biomarker ◽  
Roc Curve Analysis ◽  
Slow Coronary Flow ◽  
Receiver Operating

Aim. The slow coronary flow (SCF) phenomenon was characterized by delayed perfusion of epicardial arteries, and no obvious coronary artery lesion in coronary angiography. The prognosis of patients with slow coronary flow was poor. However, there is lack of rapid, simple, and accurate method for SCF diagnosis. This study aimed to explore the utility of plasma choline as a diagnostic biomarker for SCF. Methods. Patients with coronary artery stenosis <40% evaluated by the coronary angiogram method were recruited in this study and were grouped into normal coronary flow (NCF) and SCF by thrombolysis in myocardial infarction frame count (TFC). Plasma choline concentrations of patients with NCF and SCF were quantified by Ultra Performance Liquid Chromatography Tandem Mass Spectrometry. Correlation analysis was performed between plasma choline concentration and TFC. Receiver operating characteristic (ROC) curve analysis with or without confounding factor adjustment was applied to predict the diagnostic power of plasma choline in SCF. Results. Forty-four patients with SCF and 21 patients with NCF were included in this study. TFC in LAD, LCX, and RCA and mean TFC were significantly higher in patients with SCF in comparison with patients with NCF (32.67 ± 8.37 vs. 20.66 ± 3.41, P < 0.01). Plasma choline level was obviously higher in patients with SCF when compared with patients with NCF (754.65 ± 238.18 vs. 635.79 ± 108.25, P=0.007). Plasma choline level had significantly positive correlation with Mean TFC (r = 0.364, P=0.002). Receiver operating characteristic (ROC) analysis showed that choline with or without confounding factor adjustment had an AUC score of 0.65 and 0.77, respectively. Conclusions. TFC were closely related with plasma choline level, and plasma choline can be a suitable and stable diagnostic biomarker for SCF.

scholarly journals Identification of an optimal prolactin threshold to determine prolactinoma size using receiver operating characteristic analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bianca M. Leca ◽  
Maria Mytilinaiou ◽  
Marina Tsoli ◽  
Andreea Epure ◽  
Simon J. B. Aylwin ◽  
...  
Keyword(s):  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Tumour Size ◽  
Area Under The Curve ◽  
Serum Prolactin ◽  
Pituitary Neoplasms ◽  
Characteristic Analysis ◽  
Roc Curve Analysis ◽  
Baseline Serum ◽  
Receiver Operating

AbstractProlactinomas represent the most common type of secretory pituitary neoplasms, with a therapeutic management that varies considerably based on tumour size and degree of hyperprolactinemia. The aim of the current study was to evaluate the relationship between serum prolactin (PRL) concentrations and prolactinoma size, and to determine a cut-off PRL value that could differentiate micro- from macro-prolactinomas. A retrospective cohort study of 114 patients diagnosed with prolactinomas between 2007 and 2017 was conducted. All patients underwent gadolinium enhanced pituitary MRI and receiver operating characteristic (ROC) analyses were performed. 51.8% of patients in this study were men, with a mean age at the time of diagnosis of 42.32 ± 15.04 years. 48.2% of the total cohort were found to have microadenomas. Baseline serum PRL concentrations were strongly correlated to tumour dimension (r = 0.750, p = 0.001). When performing the ROC curve analysis, the area under the curve was 0.976, indicating an excellent accuracy of the diagnostic method. For a value of 204 μg/L (4338 mU/L), sensitivity and specificity were calculated at 0.932 and 0.891, respectively. When a cut off value of 204 μg/L (4338 mU/L) was used, specificity was 93.2%, and sensitivity 89.1%, acceptable to reliably differentiate between micro- and macro- adenomas.

scholarly journals Procollagen I and III as Prognostic Markers in Patients Treated with Extracorporeal Membrane Oxygenation: A Prospective Observational Study

2021 ◽  
Vol 10 (16) ◽  
pp. 3686
Author(s):  
Christoph Boesing ◽  
Peter T. Graf ◽  
Manfred Thiel ◽  
Thomas Luecke ◽  
Joerg Krebs
Keyword(s):  
Extracorporeal Membrane Oxygenation ◽  
Receiver Operating Characteristic ◽  
Roc Curve ◽  
Operating Characteristic ◽  
Roc Curve Analysis ◽  
Membrane Oxygenation ◽  
Icu Discharge ◽  
Procollagen Iii Peptide ◽  
Poor Outcomes ◽  
Receiver Operating

Background: Procollagen peptides have been associated with lung fibroproliferation and poor outcomes in patients with acute respiratory distress syndrome (ARDS). Therefore, serum procollagen concentrations might have prognostic value in ARDS patients treated with extracorporeal membrane oxygenation (ECMO). Methods: In a prospective cohort study, serum N-terminal procollagen I-peptide (PINP) and N-terminal procollagen III-peptide (PIIINP) concentrations in twenty-three consecutive patients with severe ARDS treated with ECMO were measured at the time of ECMO initiation and during the course of treatment. The predictive value of PINP and PIIINP at the time of ECMO initiation was tested with a univariable logistic regression and a receiver operating characteristic (ROC) curve analysis. Results: Thirteen patients survived to intensive care unit (ICU) discharge. Non-survivors had higher serum PINP and PIIINP concentrations at all points in time during the course of treatment. Serum PIIINP at the day of ECMO initiation showed an odds ratio of 1.37 (95% CI 1.10–1.89, p = 0.017) with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.87 (95% CI 0.69–1.00, p = 0.0029) for death during the course of treatment. Conclusions: PINP and PIIINP concentrations differ between survivors and non-survivors in ARDS treated with ECMO. This exploratory hypothesis generating study suggests an association between PIIINP serum concentrations at ECMO initiation and an unfavorable clinical outcome.

scholarly journals Assessment of Semi-automated Computed Tomographic Measures of Segmental Perfusion Defects in a Swine Model (Sus scrofa) of Intermediate Coronary Lesions

2020 ◽  
Vol 70 (3) ◽  
pp. 258-265
Author(s):  
Bryan C Ramsey ◽  
Amy E Field ◽  
Dustin M Thomas ◽  
Christopher A Pickett ◽  
Alisa J Leon ◽  
...  
Keyword(s):  
Coronary Artery ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Fractional Flow ◽  
Characteristic Analysis ◽  
Predictive Values ◽  
Computed Tomographic ◽  
Flow Reserve ◽  
Perfusion Defects ◽  
Receiver Operating

Computed tomographic myocardial perfusion (CTP) imaging is a tool that shows promise in emergent settings for defining the hemodynamic significance of coronary artery disease. In this study, we examined the accuracy with which the transmural perfusion ratio (TPR) derived through semiautomated CTP analysis reflected segmental perfusion defects associated with intermediate coronary artery lesions in swine. Lesions (diameter stenosis, 65% ± 11%) of the left anterior descending coronary artery (LAD) were created in 10 anesthetized female swine (weight, 47.5 ± 1.9 kg) by using a pneumatic occlusion device implanted on the LAD. Occluder inflation pressures were adjusted to maintain fractional flow reserve (FFR, 74.3 ± 1.7) during adenosine infusion (140ug/kg/min). Static CTP imaging using a stress-rest protocol and segmental TPR derived from semiautomated CT perfusion software was compared with microsphere-derived TPR (mTPR) by using a 16-segment model and polar mapping. Intermediate LAD stenosis was verified through multiplanar coronary CT angiography. Receiver operating characteristic analysis identified an optimal threshold for segmental perfusion defects for intermediate lesions (TPR threshold, ≤0.80); however, the area under the receiver operating characteristic curve was 0.58, and the overall accuracy was 63%. At this threshold, the sensitivity and specificity were 65% and 61%, and the positive and negative predictive values were 61% and 65%, respectively. Although CTP–TPR illustrated segmental perfusion defects with intermediate lesions, the disparity between CTP–TPR and mTPR measures of segmental perfusion suggests that further advances in analysis software may be necessary to improve the localization of segmental defects for intermediated lesions.

scholarly journals On the Binormal Predictive Receiver Operating Characteristic Curve for the Joint Assessment of Positive and Negative Predictive Values

Entropy ◽  
2020 ◽  
Vol 22 (6) ◽  
pp. 593 ◽  
Author(s):  
Gareth Hughes
Keyword(s):  
Receiver Operating Characteristic ◽  
Roc Curve ◽  
Operating Characteristic ◽  
Statistical Evaluation ◽  
Characteristic Curve ◽  
Disease Status ◽  
Curve Analysis ◽  
Roc Curve Analysis ◽  
Predictive Values ◽  
Receiver Operating

The predictive receiver operating characteristic (PROC) curve is a diagrammatic format with application in the statistical evaluation of probabilistic disease forecasts. The PROC curve differs from the more well-known receiver operating characteristic (ROC) curve in that it provides a basis for evaluation using metrics defined conditionally on the outcome of the forecast rather than metrics defined conditionally on the actual disease status. Starting from the binormal ROC curve formulation, an overview of some previously published binormal PROC curves is presented in order to place the PROC curve in the context of other methods used in statistical evaluation of probabilistic disease forecasts based on the analysis of predictive values; in particular, the index of separation (PSEP) and the leaf plot. An information theoretic perspective on evaluation is also outlined. Five straightforward recommendations are made with a view to aiding understanding and interpretation of the sometimes-complex patterns generated by PROC curve analysis. The PROC curve and related analyses augment the perspective provided by traditional ROC curve analysis. Here, the binormal ROC model provides the exemplar for investigation of the PROC curve, but potential application extends to analysis based on other distributional models as well as to empirical analysis.

scholarly journals Plasma miR-181a as a Candidate Diagnostic Biomarker for Kawasaki Disease Patients with Coronary Artery lesions

2020 ◽  
Author(s):  
Yu Peng ◽  
Xiaohui Liu ◽  
Junkai Duan ◽  
Zhao Duan ◽  
Zheng Zou ◽  
...  
Keyword(s):  
Coronary Artery ◽  
Kawasaki Disease ◽  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Systemic Vasculitis ◽  
Characteristic Curve ◽  
Coronary Artery Lesions ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Abstract Background: Kawasaki disease (KD) is an acute and systemic vasculitis, and the critical complication in KD patients is coronary artery lesions (CAL). Plasma miR-181a was found dysregulated in a variety of cardiovascular disease. The aim of this study was to define the relationship between the plasma miR-181a levels and CAL in KD. Methods: Plasma miR-181a levels were analyzed by quantitative reverse transcriptase-polymerase chain reaction in 121 patients with KD. Results:We found that plasma miR-181a levels at the acute phase were significantly elevated in KD patients with CAL than those without CAL. Correlation analysis showed that plasma miR-181a levels were positively correlated with the concentrations of CRP (r=0.363, P < 0.05) and NT-proBNP (r=0.389, P < 0.05). Receiver operating characteristic curve analyses showed that plasma miR-181a was of significant prediction value for CAL in KD, the area under receiver operating characteristic curve value for plasma miR-181a in prediction of CAL was 0.747, and the estimated sensitivity and specificity were 75.0% and 68.8%, respectively. Conclusions: Plasma miR-181a is prone to be a candidate biomarker for predicting CAL in KD. Therefore, further investigations are warranted to fully elucidate its role in KD.

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