Background
Compliance to dietary recommendations by patients is the most difficult part of diabetes management. The nature of any educational method is to increase patients’ awareness. But the question is, what is the effect of each method and for this purpose a comparative method should be considered. Therefore, this study was conducted to compare the effects of in-person education versus video tele-education on dietary regimen compliance in patients with T2DM.
Methods
In this trial, 378 patients with type 2 diabetes mellitus (T2DM) were random allocated into video tele-education, in-person education and control groups. The patients’ weight and biochemical parameters were measured before educational programs and three-month later.
Results
The mean changes of patients’ weight, glycemic parameters, and Lipid profiles decreased more in the two educational groups than the control group in a three-month period. There were no significant differences in the all study variables between the in-person and video education groups in post interventions except Total Cholesterol (TC). The pre- and post-intervention changes in the weight, TC, hemoglobin A1c, Triglyceride, and Very Low-density Lipoprotein Cholesterol were significant in both in-person group and video group. None of the educational programs had a significant impact on the Fasting blood sugar, Low-Density Lipoprotein Cholesterol, and High-Density Lipoprotein Cholesterol.
Discussion
Video tele-education was just as effective as in-person educational method on dietary regimen compliance among patients with T2DM in a three-month period. Therefore, it is recommended to use video tele-education in combination with or as an alternative to the in-person education method. This study provides support for diabetes educator.
Trial registration
This investigation was registered in the Iranian Registry of Clinical Trials Center (IRCT20150302021307N4).
Although the discrimination between β-thalassemia trait (βTT) and Iron deficiency anemia (IDA) is important clinically, but it is challenging and normally difficult; so if a patient with IDA is diagnosed as βTT, then it is deprived of iron therapy. This study purpose was to evaluate the 26 different discriminating indices diagnostic function in patients with microcytic anemia by using accuracy measures, and also recommending two distinct new discriminating indices as well. In this study, 907 patients were enrolled with the ages over 18-year-old with either βTT or IDA. Twenty-six discrimination indices diagnostic performance presented in earlier studies, and two new indices were introduced in this study (CRUISE index and index26) in order to evaluate the differential between βTT and IDA by using accuracy measures. 537 (59%) patients with βTT (299 (56%) women, and 238 (44%) men), and also 370 (41%) patients with IDA (293 (79%) women, and 77 (21%) men) were participated in this study for evaluating the 28 discrimination indices diagnostic performance. Two new introduced indices (CRUISE index and index26) have better performance than some discrimination indices. Indices with the amount of AUC higher than 0.8 had very appropriate diagnostic accuracy in discrimination between βTT and IDA, and also CRUISE index has good diagnostic accuracy, too. The present study was also the first cluster analysis application in order to identify the homogeneous subgroups of different indices with similar diagnostic function. In addition, new indices that offered in this study have presented a relatively closed diagnostic performance by using cluster analysis for the different indices described in earlier studies. Thus, we suggest the using of cluster analysis in order to determine differential indices with similar diagnostic performances.
Several discrimination indices have been proposed to distinct between β‐thalassemia trait (βTT) and iron deficiency anemia (IDA). This study is the first application of tree‐based methods for differential diagnosis of βTT from IDA. One hundred forty‐four patients with hypochromic microcytic anemia aged 18–40 years old from Ayat Hospital of Tehran were recruited. Classification and Regression tree, CHi‐squared Automatic Interaction Detector (CHAID), Exhaustive CHi‐squared Automatic Interaction Detector (E‐CHAID), Quick, Unbiased, Efficient Statistical Tree (QUEST), Classification Rule with Unbiased Interaction Selection and Estimation (CRUISE), and Generalized, Unbiased, Interaction Detection and Estimation (GUIDE) have been used to discriminate the diagnosis. Mean corpuscular volume (MCV) was found as the main predictor in discrimination. All the mentioned tree‐based methods showed acceptable sensitivity, specificity, accuracy, Youden's index, false positive and negative rate, positive and negative predictive values and AUC in differential diagnosis of βTT from IDA. However, Classification Rule with Unbiased Interaction Selection and Estimation revealed more precise classification with an area under the curve value of 0.99. Decision‐tree‐based methods can be used to develop sensitive and accurate diagnostic methods for differentiating βTT from IDA.
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