The Journal of cardiovascular nursing · 2018
Comparison Between Non-High-Density Lipoprotein Cholesterol and Low-Density Lipoprotein Cholesterol to Estimate Cardiovascular Risk Using a Multivariate Model.
Сравнительное исследованиеСтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Palazón-Bru Antonio, Carbayo-Herencia Julio Antonio, Simarro-Rueda Marta, Artigao-Ródenas Luis Miguel, Divisón-Garrote Juan Antonio, Molina-Escribano Francisca, Ponce-García Isabel, Gil-Guillén Vicente Francisco, GEVA (Group of Vascular Diseases From Albacete)
Аннотация
BACKGROUND: Although studies exist comparing low-density lipoprotein cholesterol (LDL-C) and non-high-density lipoprotein cholesterol (HDL-C) in the development of cardiovascular disease (CVD), most have limitations in the mathematical models used to evaluate their prognostic power adjusted for the other risk factors (cardiovascular risk).
OBJECTIVE: The aim of this study was to compare LDL-C and non-HDL-C in patients with CVD to determine whether both parameters predict CVD similarly.
METHODS: A cohort of 1322 subjects drawn from the general population of a Spanish region was followed between 1992 and 2006. The outcome was time to CVD. Secondary variables were gender, age, hypertension, diabetes, personal history of CVD, current smoker, body mass index, LDL-C, and non-HDL-C. Two CVD prediction models were constructed with the secondary variables, with only the lipid parameter varying (non-HDL-C or LDL-C). In the construction of the models, the following were considered: multiple imputation, events per variable of 10 or more, and continuous predictors as powers. The validation was conducted by bootstrapping obtaining the distribution of the C statistic (discrimination) and the probabilities observed by smooth curves. These results were compared in both models using graphical and analytical testing.
RESULTS: There were a total of 137 CVD events. The models showed no differences in the distributions of the C statistic (discrimination, P = .536) or in the calibration plot.
CONCLUSIONS: In our population, LDL-C and non-HDL-C were equivalent at predicting CVD. More studies using this methodology are needed to confirm these results.
OBJECTIVE: The aim of this study was to compare LDL-C and non-HDL-C in patients with CVD to determine whether both parameters predict CVD similarly.
METHODS: A cohort of 1322 subjects drawn from the general population of a Spanish region was followed between 1992 and 2006. The outcome was time to CVD. Secondary variables were gender, age, hypertension, diabetes, personal history of CVD, current smoker, body mass index, LDL-C, and non-HDL-C. Two CVD prediction models were constructed with the secondary variables, with only the lipid parameter varying (non-HDL-C or LDL-C). In the construction of the models, the following were considered: multiple imputation, events per variable of 10 or more, and continuous predictors as powers. The validation was conducted by bootstrapping obtaining the distribution of the C statistic (discrimination) and the probabilities observed by smooth curves. These results were compared in both models using graphical and analytical testing.
RESULTS: There were a total of 137 CVD events. The models showed no differences in the distributions of the C statistic (discrimination, P = .536) or in the calibration plot.
CONCLUSIONS: In our population, LDL-C and non-HDL-C were equivalent at predicting CVD. More studies using this methodology are needed to confirm these results.