Diabetes research and clinical practice · 2018
Novel nomogram for screening the risk of developing diabetes in a Korean population.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Chung Seung Min, Park Jae Cheol, Moon Jun Sung, Lee Jea Young
Аннотация
AIMS: We propose a novel nomogram, which graphically expresses the numerical relationship between type 2 diabetes (T2D) and disease-related risk factors.
METHODS: Data of 8999 patients from the 2013-2014 Korean National Health and Nutrition Examination Survey were analyzed. Multiple logistic regression analysis was performed to assess risk factors for T2D and a nomogram was constructed based on screened risk factors. A receiver operating curve (ROC) and calibration plot were created to evaluate the accuracy of the nomogram.
RESULTS: The risk factor with the greatest impact on the prevalence of T2D was age over 60 years (95% CI 5.97-15.00, OR = 9.46), followed by presence of dyslipidemia and cardiovascular disease (95% CI 5.90-13.68, OR = 8.98), family history of T2D (95% CI 2.33-3.64, OR = 2.92), abdominal obesity (OR = 1.76), hypertension (OR = 1.75), male gender (OR = 1.55), current-smoking status (OR = 1.52), lower education level (OR = 1.42), and lower income (OR = 1.30). The area under the ROC curve (AUC) showed statistically significant determination (AUC = 0.83). The equation of the calibration plot was drawn along the ideal line; coefficient of determination was 0.864.
CONCLUSION: Our proposed nomogram could accurately predict the risk of T2D from nationwide data. The novel nomogram can be a useful tool for screening patients with T2D risk in a Korean population.
METHODS: Data of 8999 patients from the 2013-2014 Korean National Health and Nutrition Examination Survey were analyzed. Multiple logistic regression analysis was performed to assess risk factors for T2D and a nomogram was constructed based on screened risk factors. A receiver operating curve (ROC) and calibration plot were created to evaluate the accuracy of the nomogram.
RESULTS: The risk factor with the greatest impact on the prevalence of T2D was age over 60 years (95% CI 5.97-15.00, OR = 9.46), followed by presence of dyslipidemia and cardiovascular disease (95% CI 5.90-13.68, OR = 8.98), family history of T2D (95% CI 2.33-3.64, OR = 2.92), abdominal obesity (OR = 1.76), hypertension (OR = 1.75), male gender (OR = 1.55), current-smoking status (OR = 1.52), lower education level (OR = 1.42), and lower income (OR = 1.30). The area under the ROC curve (AUC) showed statistically significant determination (AUC = 0.83). The equation of the calibration plot was drawn along the ideal line; coefficient of determination was 0.864.
CONCLUSION: Our proposed nomogram could accurately predict the risk of T2D from nationwide data. The novel nomogram can be a useful tool for screening patients with T2D risk in a Korean population.