TABLE 6. Prediction model of gestational TG level on postpartum
hypertriglyceridemia |
TABLE 6. Prediction model of gestational
TG level on postpartum hypertriglyceridemia |
TABLE 6.
Prediction model of gestational TG level on postpartum
hypertriglyceridemia |
TABLE 6. Prediction model of gestational
TG level on postpartum hypertriglyceridemia |
TABLE 6.
Prediction model of gestational TG level on postpartum
hypertriglyceridemia |
TABLE 6. Prediction model of gestational
TG level on postpartum hypertriglyceridemia |
TABLE 6.
Prediction model of gestational TG level on postpartum
hypertriglyceridemia |
AUC and its 95% CIs were based on ROC curves of the predictive model of
gestational TG level on postpartum hypertriglyceridemia. Cutoff points
of serum TG level at each gestational week, sensitivity and specificity
were calculated by the point nearest to the top-left most corner of the
ROC curves, which was the point with the biggest Youden Index.
χ2 and P value were calculated by the
Hosmer-Lemeshow goodness-of-fit test, P value of >
0.05 was considered as the prediction model with good calibration. |
AUC
and its 95% CIs were based on ROC curves of the predictive model of
gestational TG level on postpartum hypertriglyceridemia. Cutoff points
of serum TG level at each gestational week, sensitivity and specificity
were calculated by the point nearest to the top-left most corner of the
ROC curves, which was the point with the biggest Youden Index.
χ2 and P value were calculated by the
Hosmer-Lemeshow goodness-of-fit test, P value of >
0.05 was considered as the prediction model with good calibration. |
AUC
and its 95% CIs were based on ROC curves of the predictive model of
gestational TG level on postpartum hypertriglyceridemia. Cutoff points
of serum TG level at each gestational week, sensitivity and specificity
were calculated by the point nearest to the top-left most corner of the
ROC curves, which was the point with the biggest Youden Index.
χ2 and P value were calculated by the
Hosmer-Lemeshow goodness-of-fit test, P value of >
0.05 was considered as the prediction model with good calibration. |
AUC
and its 95% CIs were based on ROC curves of the predictive model of
gestational TG level on postpartum hypertriglyceridemia. Cutoff points
of serum TG level at each gestational week, sensitivity and specificity
were calculated by the point nearest to the top-left most corner of the
ROC curves, which was the point with the biggest Youden Index.
χ2 and P value were calculated by the
Hosmer-Lemeshow goodness-of-fit test, P value of >
0.05 was considered as the prediction model with good calibration. |
AUC
and its 95% CIs were based on ROC curves of the predictive model of
gestational TG level on postpartum hypertriglyceridemia. Cutoff points
of serum TG level at each gestational week, sensitivity and specificity
were calculated by the point nearest to the top-left most corner of the
ROC curves, which was the point with the biggest Youden Index.
χ2 and P value were calculated by the
Hosmer-Lemeshow goodness-of-fit test, P value of >
0.05 was considered as the prediction model with good calibration. |
AUC
and its 95% CIs were based on ROC curves of the predictive model of
gestational TG level on postpartum hypertriglyceridemia. Cutoff points
of serum TG level at each gestational week, sensitivity and specificity
were calculated by the point nearest to the top-left most corner of the
ROC curves, which was the point with the biggest Youden Index.
χ2 and P value were calculated by the
Hosmer-Lemeshow goodness-of-fit test, P value of >
0.05 was considered as the prediction model with good calibration. |
AUC
and its 95% CIs were based on ROC curves of the predictive model of
gestational TG level on postpartum hypertriglyceridemia. Cutoff points
of serum TG level at each gestational week, sensitivity and specificity
were calculated by the point nearest to the top-left most corner of the
ROC curves, which was the point with the biggest Youden Index.
χ2 and P value were calculated by the
Hosmer-Lemeshow goodness-of-fit test, P value of >
0.05 was considered as the prediction model with good
calibration. |