Metabolic Syndrome and Its Components Reduce Coronary Collateralization in Chronic Total Occlusion: an Observational Study

Abstract Background: Metabolic syndrome (METs) is an independent risks for the incidence of cardiovascular diseases. We investigated whether or to what extent the METs and its components was associated with coronary collateralization (CC) in chronic total occlusion (CTO).Methods: This study involved 1709 inpatients with CTO. Data on demographic and clinical characteristics were collected by cardiovascular doctors. The CC condition was defined by Rentrop score system. Subgroup analysis, mixed models regression analysis, score systems and receiver-operating characteristic curves (ROC) analysis were done. Results: Overall, 1709 inpatients were assigned to the Poor CC group (n = 370), good CC group (n = 1339) with or without METs. Compared to good CC, the incidence of METs was higher in poor CC for overall patients. Poor collateralization was present in 9.1%, 14.4%, 19.9%, 18.1%, 35.1% and 54.2% of the six groups, who met the diagnostic criteria of MetS 0, 1, 2, 3, 4 and 5 times. For multivariable logistic regression, quartiles of BMI remained the risk factors of CC growth in all subgroups (adjusted OR = 1.728, 95% CI 1.518-1.967, P < 0.001 all patient group , adjusted OR = 1.827, 95% CI 1.484-2.249, P < 0.001 No-METs group and adjusted OR = 1.771, 95% CI 1.484-2.115,P < 0.001 METs group). After adjustment for potential confounding factors, METs was an independent risk factors of CC growth in several models. Assigning a score of one for each components, this score system had significant predictive value for the CC conditions by Receiver-operating characteristic(AUC: 0.622, 95%CI: 0.588-0.655) .Conclusions: METs, especially for body mass index, confers greater risk for CC formation in CTO. Score systems may help to predict CC condition.

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Metabolic syndrome and its components reduce coronary collateralization in chronic total occlusion: An observational study

Cardiovascular Diabetology ◽

10.1186/s12933-021-01297-4 ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Tong Liu ◽

Zheng Wu ◽

Jinghua Liu ◽

Yun Lv ◽

Wenzheng Li

Keyword(s):

Metabolic Syndrome ◽

Risk Factor ◽

Receiver Operating Characteristic ◽

Chronic Total Occlusion ◽

Independent Risk Factor ◽

Operating Characteristic ◽

Scoring Systems ◽

Total Occlusion ◽

The Poor ◽

Receiver Operating

Abstract Background Metabolic syndrome (MetS) is an independent risk factor for the incidence of cardiovascular diseases. We investigated whether or to what extent MetS and its components was associated with coronary collateralization (CC) in chronic total occlusion (CTO). Methods This study involved 1653 inpatients with CTO. Data on demographic and clinical characteristics were collected by cardiovascular doctors. The CC condition was defined by the Rentrop scoring system. Subgroup analysis, mixed model regression analysis, scoring systems and receiver operating characteristic (ROC) curve analysis were performed. Results Overall, 1653 inpatients were assigned to the poor CC group (n = 355) and good CC group (n = 1298) with or without MetS. Compared to the good CCs, the incidence of MetS was higher among the poor CCs for all patients. Poor collateralization was present in 7.6%, 14.2%, 19.3%, 18.2%, 35.6% and 51.1% of the six groups who met the diagnostic criteria of MetS 0, 1, 2, 3, 4 and 5 times, respectively. For multivariable logistic regression, quartiles of BMI remained the risk factors for CC growth in all subgroups (adjusted OR = 1.755, 95% CI 1.510–2.038, P < 0.001 all patients; adjusted OR = 1.897, 95% CI 1.458–2.467, P < 0.001 non-MetS; and adjusted OR = 1.814, 95% CI 1.482–2.220, P < 0.001 MetS). After adjustment for potential confounding factors, MetS was an independent risk factor for CC growth in several models. Assigning a score of one for each component, the AUCs were 0.629 (95% CI 0.595–0.662) in all patients, 0.656 (95% CI 0.614–0.699) in MetS patients and 0.569 (95% CI 0.517–0.621) in non-MetS patients by receiver operating characteristic analysis. Conclusions MetS, especially body mass index, confers a greater risk of CC formation in CTO. The value of scoring systems should be explored further for CTO.

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A conditional approach for the receiver operating characteristic curve construction to evaluate diagnostic test performance in a family-matched case–control design

Statistical Methods in Medical Research ◽

10.1177/0962280221995956 ◽

2021 ◽

pp. 096228022199595

Author(s):

Yalda Zarnegarnia ◽

Shari Messinger

Keyword(s):

Receiver Operating Characteristic Curve ◽

Receiver Operating Characteristic ◽

Operating Characteristic ◽

Characteristic Curve ◽

Case Control ◽

Paired Data ◽

Characteristic Curves ◽

Receiver Operating Characteristic Curves ◽

Operating Characteristic Curve ◽

Receiver Operating

Receiver operating characteristic curves are widely used in medical research to illustrate biomarker performance in binary classification, particularly with respect to disease or health status. Study designs that include related subjects, such as siblings, usually have common environmental or genetic factors giving rise to correlated biomarker data. The design could be used to improve detection of biomarkers informative of increased risk, allowing initiation of treatment to stop or slow disease progression. Available methods for receiver operating characteristic construction do not take advantage of correlation inherent in this design to improve biomarker performance. This paper will briefly review some developed methods for receiver operating characteristic curve estimation in settings with correlated data from case–control designs and will discuss the limitations of current methods for analyzing correlated familial paired data. An alternative approach using conditional receiver operating characteristic curves will be demonstrated. The proposed approach will use information about correlation among biomarker values, producing conditional receiver operating characteristic curves that evaluate the ability of a biomarker to discriminate between affected and unaffected subjects in a familial paired design.

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The length of the receiver operating characteristic curve and the two cutoff Youden index within a robust framework for discovery, evaluation, and cutoff estimation in biomarker studies involving improper receiver operating characteristic curves

Statistics in Medicine ◽

10.1002/sim.8869 ◽

2021 ◽

Author(s):

Leonidas E. Bantis ◽

John V. Tsimikas ◽

Gregory R. Chambers ◽

Michela Capello ◽

Samir Hanash ◽

...

Keyword(s):

Receiver Operating Characteristic Curve ◽

Receiver Operating Characteristic ◽

Operating Characteristic ◽

Characteristic Curve ◽

Youden Index ◽

Characteristic Curves ◽

Receiver Operating Characteristic Curves ◽

Operating Characteristic Curve ◽

Robust Framework ◽

Receiver Operating

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Three Approaches to Regression Analysis of Receiver Operating Characteristic Curves for Continuous Test Results

Biometrics ◽

10.2307/2534001 ◽

1998 ◽

Vol 54 (1) ◽

pp. 124 ◽

Cited By ~ 101

Author(s):

Margaret Sullivan Pepe

Keyword(s):

Regression Analysis ◽

Receiver Operating Characteristic ◽

Operating Characteristic ◽

Test Results ◽

Characteristic Curves ◽

Receiver Operating Characteristic Curves ◽

Continuous Test ◽

Receiver Operating

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Development and Validation of a Nomogram for Renal Involvement in Primary Sjögren Syndrome Patients: A Retrospective Analysis

Modern Rheumatology ◽

10.1093/mr/roab123 ◽

2021 ◽

Author(s):

Xinshi Huang ◽

Xiaobing Wang ◽

Dinglai Yu

Keyword(s):

Risk Factors ◽

Prediction Model ◽

Receiver Operating Characteristic ◽

Operating Characteristic ◽

Renal Involvement ◽

Calibration Plot ◽

Receiver Operating Characteristic Curves ◽

Logistic Analysis ◽

Validation Set ◽

Multivariate Logistic Analysis

Abstract Objective To establish and validate a nomogram for individualized prediction of renal involvement in pSS patients. Methods A total of 1293 patients with pSS from the First Affiliated Hospital of Wenzhou Medical University between January 2008 to January 2020 were recruited and further analyzed retrospectively. The patients were randomly divided into a development set (70%, n = 910) and a validation set (30%, n = 383). The univariable and multivariate logistic regression were performed to analyze the risk factors of renal involvement in pSS. Based on the regression β coefficients derived from multivariate logistic analysis, an individualized nomogram prediction model was developed. The prediction model of discrimination and calibration was evaluated with the area under the receiver operating characteristic curves and Calibration plot. Results Multivariate logistic analysis showed that hypertension, anemia, albumin, uric acid, anti-Ro52, hematuria and Chisholm-Mason grade were independent risk factors of renal involvement in pSS. The area under the receiver operating characteristic curves were 0.797 and 0.750 respectively in development set and validation set, indicating the nomogram had a good discrimination capacity. The Calibration plot showed nomogram had a strong concordance performance between the prediction probability and the actual probability. Conclusion The individualized nomogram for pSS patients those who had renal involvement could be used by clinicians to predict the risk of pSS patients developing into renal involvement and improve early screening and intervention.

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