MetS Risk Score: A Clear Scoring Model to Predict a 3-Year Risk for Metabolic Syndrome.
Horm Metab Res
; 50(9): 683-689, 2018 Sep.
Article
en En
| MEDLINE
| ID: mdl-30184562
ABSTRACT
Although several risk factors for metabolic syndrome (MetS) have been reported, there are few clinical scores that predict its incidence. Therefore, we created and validated a risk score for prediction of 3-year risk for MetS. Three-year follow-up data of 4395 initially MetS-free subjects, enrolled for an annual physical examination from Wenzhou Medical Center were analyzed. Subjects at enrollment were randomly divided into the training and the validation cohort. Univariate and multivariate logistic regression models were employed for model development. The selected variables were assigned an integer or half-integer risk score proportional to the estimated coefficient from the logistic model. Risk scores were tested in a validation cohort. The predictive performance of the model was tested by computing the area under the receiver operating characteristic curve (AUROC). Four independent predictors were chosen to construct the MetS risk score, including BMI (HR=1.906, 95% CI 1.040-1.155), FPG (HR=1.507, 95% CI 1.305-1.741), DBP (HR=1.061, 95% CI 1.002-1.031), HDL-C (HR=0.539, 95% CI 0.303-0.959). The model was created as -1.5 to 4 points, which demonstrated a considerable discrimination both in the training cohort (AUROC=0.674) and validation cohort (AUROC=0.690). Comparison of the observed with the estimated incidence of MetS revealed satisfactory precision. We developed and validated the MetS risk score with 4 risk factors to predict 3-year risk of MetS, useful for assessing the individual risk for MetS in medical practice.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Síndrome Metabólico
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Modelos Biológicos
Tipo de estudio:
Clinical_trials
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Etiology_studies
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Prognostic_studies
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Risk_factors_studies
Límite:
Adult
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
Horm Metab Res
Año:
2018
Tipo del documento:
Article
País de afiliación:
China