Statistical analysis
REGRESSION
Data analysis was performed using SPSS software (version 23.0; IBM Corp., Armonk, New York, USA). Continuous variables were presented as mean ± standard deviation or median (interquartile range). Categorical variables were expressed as number (percentage).The patients were randomized into exploratory and validation groups by SPSS software. HbA1c prediction models were developed in the exploratory group and validated in the validation group. The correlation coefficient between MEANrespectively. Bland–Altman plots and concordance correlation coefficient (CCC) were used to evaluate the agreement between actual HbA1c and predicted HbA1c in the validation group. The CCC >0.80 suggested a strong agreement between actual and predicted values. Receiver operating characteristic (ROC) curves were used to assess the sensitivity and specificity of the new HbA1c prediction model and simple linear regression models to detect patients with HbA1c <7% using MedCalc version 20.0. The areas under the ROC curves (AUC) of HbA1c prediction models were calculated and compared using the DeLong test. All 