Diabetes research and clinical practice · 2017
First trimester prediction of gestational diabetes mellitus: A clinical model based on maternal demographic parameters.
СтатьяНазвание и аннотация: Перевод в очереди
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.
Sweeting Arianne N, Appelblom Heidi, Ross Glynis P, Wong Jencia, Kouru Heikki, Williams Paul F, Sairanen Mikko, Hyett Jon A
Аннотация
AIM: Develop a first trimester risk prediction model for GDM based on maternal clinical characteristics in a large metropolitan multi-ethnic population and compare its performance to that of other recently published GDM prediction models and clinical risk scoring systems.
METHODS: A retrospective case control study of 248 women who developed GDM and 732 controls who did not. Maternal clinical parameters were prospectively obtained at 11-13+6 weeks' gestation. A predictive multivariate regression model for GDM was developed, evaluated using areas under the receiver-operating characteristic (AUC) curve. The performance of this model was then compared with other published GDM prediction models applied to our cohort and our existing clinical risk scoring system.
RESULTS: Previous GDM, family history of diabetes, age, south/east Asian ethnicity, parity and body mass index (BMI) were significant predictors for GDM. The AUC of our multivariate regression model was 0.88 (95% Confidence Interval 0.85-0.92). This performed better than other predictive models applied to our cohort (AUCs 0.77-0.82).
CONCLUSION: A multivariate model based on weighted maternal clinical risk factors accurately predicts GDM in early pregnancy and performs better than other proposed multivariate and clinical risk scoring models in a multiethnic cohort.
METHODS: A retrospective case control study of 248 women who developed GDM and 732 controls who did not. Maternal clinical parameters were prospectively obtained at 11-13+6 weeks' gestation. A predictive multivariate regression model for GDM was developed, evaluated using areas under the receiver-operating characteristic (AUC) curve. The performance of this model was then compared with other published GDM prediction models applied to our cohort and our existing clinical risk scoring system.
RESULTS: Previous GDM, family history of diabetes, age, south/east Asian ethnicity, parity and body mass index (BMI) were significant predictors for GDM. The AUC of our multivariate regression model was 0.88 (95% Confidence Interval 0.85-0.92). This performed better than other predictive models applied to our cohort (AUCs 0.77-0.82).
CONCLUSION: A multivariate model based on weighted maternal clinical risk factors accurately predicts GDM in early pregnancy and performs better than other proposed multivariate and clinical risk scoring models in a multiethnic cohort.