scholarly journals Carotid Lumen Diameter Is Associated With All‐Cause Mortality in the General Population

2020 ◽  
Vol 9 (16) ◽  
Author(s):  
Felix Fritze ◽  
Stefan Groß ◽  
Till Ittermann ◽  
Henry Völzke ◽  
Stephan B. Felix ◽  
...  

Background Common carotid intima–media thickness (cIMT) is a biomarker for subclinical atherosclerosis and is associated with all‐cause as well as cardiovascular mortality. Higher cIMT is accompanied by a compensatory increase in lumen diameter (LD) of the common carotid arteries. Whether cIMT or LD carry more information with regard to mortality is unclear. Methods and Results A total of 2751 subjects (median age 53 years; 52% female) were included. During a median follow‐up of 14.9 years (range: 12.8–16.5) a total of 506 subjects died. At baseline, cIMT and LD were assessed by carotid ultrasound scans. Multivariable Cox regression models were used to relate cIMT, LD, LD adjusted for cIMT (LD+cIMT), and LD/cIMT ratio with all‐cause, cardiovascular, and noncardiovascular mortality. All models were ranked using Akaike's information criterion. Harrel's c statistic was used to compare the models' predictive power for mortality. A 1‐mm increase in LD was related to a higher risk for all‐cause mortality (hazard ratio [HR], 1.29; 95% CI, 1.14–1.45, P <0.01). This association remained significant when cIMT was added to the model (HR, 1.26; 95% CI, 1.11–1.42; P <0.01). A 1‐mm higher cIMT was also related with greater mortality risk (HR, 1.73; 95% CI, 1.09–2.75). The LD/cIMT ratio was not associated with all‐cause mortality. LD had the lowest Akaike's information criterion regarding all‐cause mortality and improved all‐cause mortality prediction compared with the null model ( P =0.01). CIMT weakened all‐cause mortality prediction compared with the LD model. Conclusions LD provided more information for all‐cause mortality compared with cIMT in a large population‐based sample.

1990 ◽  
Vol 29 (03) ◽  
pp. 200-204 ◽  
Author(s):  
J. A. Koziol

AbstractA basic problem of cluster analysis is the determination or selection of the number of clusters evinced in any set of data. We address this issue with multinomial data using Akaike’s information criterion and demonstrate its utility in identifying an appropriate number of clusters of tumor types with similar profiles of cell surface antigens.


2003 ◽  
Vol 40 (2) ◽  
pp. 235-243 ◽  
Author(s):  
Rick L. Andrews ◽  
Imran S. Currim

Despite the widespread application of finite mixture models in marketing research, the decision of how many segments to retain in the models is an important unresolved issue. Almost all applications of the models in marketing rely on segment retention criteria such as Akaike's information criterion, Bayesian information criterion, consistent Akaike's information criterion, and information complexity to determine the number of latent segments to retain. Because these applications employ real-world data in which the true number of segments is unknown, it is not clear whether these criteria are effective. Retaining the true number of segments is crucial because many product design and marketing decisions depend on it. The purpose of this extensive simulation study is to determine how well commonly used segment retention criteria perform in the context of simulated multinomial choice data, as obtained from supermarket scanner panels, in which the true number of segments is known. The authors find that an Akaike's information criterion with a penalty factor of three rather than the traditional value of two has the highest segment retention success rate across nearly all experimental conditions. Currently, this criterion is rarely, if ever, applied in the marketing literature. Experimental factors of particular interest in marketing contexts, such as the number of choices per household, the number of choice alternatives, the error variance of the choices, and the minimum segment size, have not been considered in the statistics literature. The authors show that they, among other factors, affect the performance of segment retention criteria.


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