No abstract

Existing standards of the management of the diabetic patients are not efficient enough, and further improvement is needed. The major objective of this paper is to present and discuss the therapeutic effectiveness of an intensive care telematic system designed and applied for intensive treatment of pregnant type 1 diabetic women. The developed system operates automatically, every night transferring all the data recorded during the day in the patient's glucometer memory to a central clinical unit. In order to assess the efficiency of the designed and developed system, a 3-year randomized prospective clinical trial was conducted, using the study group and the control group, each consisting of 15 pregnant type 1 diabetic women. All patients were treated by the same diabetologist. In the presented analysis, two indices calculated weekly were used for the assessment of glycemic control: MBG represents mean blood glucose level, and the universal J-index is sensitive to the glycemic level and glycemic variations. The most important results from the study concern: (a) better glycemic control in the study group in comparison with the control group during the course of treatment, as assessed by the average differences of the MBG and J indices calculated weekly (n = 24) (deltaMBG = -3.2 +/- 4.3 mg/dL, p = 0.0016, deltaJ = -1.4 +/- 2.3, p = 0.0065); (b) much more similar results in glycemic control among members of the study group compared to each other, than among members of the control group compared to each other, as indicated by significantly lower variations of the applied glycemic control indices (SDMBG: 11.9 vs. 18.7 mg/dL, p = 0.0498; SDJ: 6.5 vs. 10.9, p = 0.0318); (c) the observed tendency of a better glycemic control for patients with a lower level of intelligence (IQ < 100) supported by the telematic system in comparison with all other assessed groups of patients. The last result was not statistically significant (p > 0.05). This telematic intensive care system improved the effectiveness of diabetes treatment during pregnancy. It also allows the diabetologist's strategy to be much more precise than if it were conducted without telematic support. This telematic system is inexpensive and simple in use.

Glycated hemoglobin A1c (HbA1c) concentration in blood is an index of the glycemic control widely used in diabetology. The aim of the work was to validate two mathematical models of HbA1c formation (assuming irreversible or reversible glycation, respectively) and select a model, which was able to predict changes of HbA1c concentration in response to varying glycemia courses with higher accuracy. The experimental procedure applied consisted of an original combination of: in vivo continuous glucose concentration monitoring, long-term in vitro culturing of the human erythrocytes and mathematical modeling of HbA1c formation in vivo and in vitro with HbA1c values scaled according to the most specific analytical methods. Sixteen experiments were conducted in vitro using blood samples collected from healthy volunteer and stable type 1 diabetic patients whose glycemia was estimated beforehand based on long-term monitoring. The mean absolute difference of the measured and predicted HbA1c concentrations for the in vitro experiments were equal to 0.64 +/- 0.29% and 1.42 +/- 0.16% (p = 0.0007) for irreversible and for reversible model, respectively, meaning that the irreversible model was able to predict the glycation kinetics with a higher accuracy. This model was also more sensitive to a deviation of the erythrocytes life span.

We examined the influence of the increased frequency of data reporting on metabolic control in patients with diabetes. Data reporting was via a home telecare system that stored blood glucose values and was integrated with a simple electronic logbook. The data collected by the patient were automatically transmitted via the telephone network every night. The study population consisted of 30 patients with type I diabetes, who were randomly allocated to the home telecare group or the control group. The control group was treated based on clinical examinations performed every three weeks. In the home telecare group, the patient-collected data were transmitted to hospital daily, enabling more frequent interventions by the doctor. The average study period was 180 days (SD 22) in the home telecare group and 176 days (SD 16) in the control group. The mean level of metabolic control and the insulin dose adjustment patterns were very similar in both groups regardless of the much higher (15 times) reporting frequency in the home telecare group. The patient-collected data were not fully utilized, mainly because of too high within-day variability in glycaemic control and the high workload connected with daily data analysis.

The objectives were as follows: (1) estimating mean value of the overall hemoglobin glycation rate constant (k); (2) analyzing inter-individual variability of k; (3) verifying ability of the hemoglobin A1c (HbA1c) formation model to predict changes of HbA1c during red blood cells cultivation in vitro and to reproduce the clinical data. The mean k estimated in a group of 10 non-diabetic subjects was equal to 1.257 ± 0.114 × 10(-9) L mmol(-1) s(-1). The mean k was not affected by a way of estimation of glycemia. The mean k differed less than 20% from values reported earlier and it was almost identical to the mean values calculated on basis of the selected published data. Analysis of variability of k suggests that inter-individual heterogeneity of HbA1c formation is limited or rare. The HbA1c mathematical model was able to predict changes of HbA1c in vitro resulting from different glucose levels and to reproduce a linear relationship of HbA1c and average glucose obtained in the A1C-Derived Average Glucose Study. This study demonstrates that the glycation model with the same k value might be used in majority of individuals as a tool supporting interpretation of HbA1c in different clinical situations.

The Elliptical method gives overestimation up to 33%; thus, it should not be used in applications where the actual wound area is an important parameter (like the prediction of wound healing). The TeleDiaFoS system and the SilhouetteMobile device showed the best accuracy of all used methods; however, the precision of the TeleDiaFoS system was revealed to be higher than the precision of the SilhouetteMobile device. The accuracy and the precision of the Visitrak device are significantly reduced for wounds smaller than 2 cm².

Proper wound healing can be assessed by monitoring the wound surface area. Its reduction by 10 or 50% should be achieved after 1 or 4 weeks, respectively, from the start of the applied therapy. There are various methods of wound area measurement, which differ in terms of the cost of the devices and their accuracy. This article presents an originally developed method for wound area measurement. It is based on the automatic recognition of the wound contour with a software application running on a smartphone. The wound boundaries have to be traced manually on transparent foil placed over the wound. After taking a picture of the wound outline over a grid of 1 × 1 cm, the AreaMe software calculates the wound area, sends the data to a clinical database using an Internet connection, and creates a graph of the wound area change over time. The accuracy and precision of the new method was assessed and compared with the accuracy and precision of commercial devices: Visitrak and SilhouetteMobile. The comparison was performed using 108 wound shapes that were measured five times with each device, using an optical scanner as a reference device. The accuracy of the new method was evaluated by calculating relative errors and comparing them with relative errors for the Visitrak and the SilhouetteMobile devices. The precision of the new method was determined by calculating the coefficients of variation and comparing them with the coefficients of variation for the Visitrak and the SilhouetteMobile devices. A statistical analysis revealed that the new method was more accurate and more precise than the Visitrak device but less accurate and less precise than the SilhouetteMobile device. Thus, the AreaMe application is a superior alternative to the Visitrak device because it provides not only a more accurate measurement of the wound area but also stores the data for future use by the physician.

The study revealed that the PM can be used as a home telemonitoring device, and the analysis of the data sent from patient's home enables the assessment of wound healing progress, giving the physician the possibility for earlier change of the treatment if the wound area reduction is not satisfactory.