**3.3 T1D insulin doses assessment**

66 Type 1 Diabetes – Complications, Pathogenesis, and Alternative Treatments

The fraction of males among the 26,796 adults diagnosed before the age of 30 years corresponded to 52.95%, and varied from 49.2% in Luganska to 60.1% in Chernivetska regions. In the majority (23 out of 25) of the regions, this fraction was >50%. Comparison of

Gender Number of type1 adult

population males females total, n per 10 000 adults

diabetic patients Total adult

(95 % CI)

Region (oblast')

Ukrainian Regions (Khalangot et al., 2009d)

**3.2 T1D gender assessment** 

The data analysis of the 23,633 T1D patients (Table 2) from the register, who were classified according to insulin dose, age, and disease duration, indicated that women have a higher average age and disease duration, but lower daily insulin dose, when compared with men.


Note: Р (man/women) < 0.001

Table 2. Average Age, Disease Duration, and Daily Insulin Dose of Type 1 Diabetes Mellitus Patients in Ukraine According to the Diabetes Register data (Khalangot et al., 2009 d)

Prevalence of Type 1 Diabetes Correlates with Daily Insulin Dose, Adverse

**3.3.2 T1D insulin doses in territorial clusters** 

**Type 1 diabetes prevalence cluster** 

(figure 3, table 3).

Outcomes and with Autoimmune Process Against Glutamic Acid Decarboxylase in Adults 69

observation that T1D patients have long-standing insulin secretion at times (the study of cpeptide level), which was proven by Bonora (Bonora et al., 1984) and confirmed by the Diabetes Control and Complications Trial (DCCT). These research efforts uncovered the diverse influence of different insulin-therapy patterns on the process described (*The DCCT Research Group,* 1987; 1998). The confirmation of this data with the prospective observation was undertaken in Germany (Linn et al., 2003). Our results could be viewed as an indirect confirmation of the extended continuation of the β-cell secretion, obtained through the cross-sectional treatment data analysis of almost the entire population of T1D patients in Ukraine. The standardization of the daily insulin doses, depending on the disease duration, enables the necessary quantitative comparisons of the treatments for T1D adult patients.

It would be logical to consider that the rate of decrease in insulin secretion among the T1D patients that differs according to the prevalence of such autoimmune disease, as T1D will also vary. Table 3 presents the comparisons of the daily insulin doses (median) in all the

three clusters of the regions selected according to the prevalence of T1D in adults.

Note: Number of diabetes duration yearly groups (n) in all clusters is 16.

diabetes mellitus type 1 (Khalangot et al., 2009 d).

**Insulin doses standardized according to diabetes duration, median, U/day**

1. minimal 45.89 45.28 - 47.19 < 0.01 (1 vs 3) 2. intermediate 52 47.61 - 52.78 < 0.05 (1 vs 2) 3. maximal 56.59 53.33 -57.88 < 0.05 (2 vs 3)

Table 3. Comparison of daily insulin doses standardized for every year of disease duration in the range of 0-15 years in clusters of regions singled out according to prevalence of

Insulin doses standardized according to the disease duration within the range of 0–15 years in the minimal prevalence cluster of T1D prevalence were significantly lower, when compared with the intermediate and maximal prevalence clusters. The values in the intermediate prevalence cluster were lower than those in the maximal prevalence cluster

By evaluating the data presented in table 3, it should be noted that the probability coefficients (*P*), in this case, reflect a relatively small number of the "yearly" groups (*n*=16) in each cluster. If we were to assess the individual data on the insulin dose in each cluster without yearly grouping, then the number of cases (*n*) corresponding to the number of patients would greatly increase: 4,658; 14,712 and 2,879 in the minimal, intermediate, and maximal prevalence clusters, respectively. The unstandardized according to the diabetes duration average doses and their standard deviations (SD) in each of the three clusters, were observed to be 46.62 (19.38); 51.54 (17.57); and 55.94 (19.46) units/day, respectively, which was found to increase (*p* < 0.0001) in the clusters with higher T1D prevalence. However, the correlation of the insulin dose and the T1D prevalence found in this current region needs to be explained. One of the explanations for the difference in the daily insulin doses could be that in different Ukrainian regions, the doctors administer different levels of diabetes control: the lower dose is explained not only by the lower requirement of insulin by patients, but rather by the lower quality of treatment. An alternative explanation could be

**95%CI Р**

#### **3.3.1 T1D insulin doses and diabetes duration**

As the average duration of the disease was found to be 14.86 years, the average daily insulin doses were calculated for each year of the duration, from 0 (<1) to 15 years.

The regression analysis (figure 2) indicated that in this range, the insulin dose rises with the increase in the disease duration:

Insulin (units/day) = 0.7326 × duration (years) + 43.74 (coefficient of linear correlation, *R* = 0.899, *p* < 0.001).

Fig. 2. Average (Mean ± SE) daily insulin doses of type 1 diabetes mellitus patients depending on the disease duration in the range of 0-15 years (Khalangot et al., 2009 d)

A further increase in the disease duration in the range of 16–31 years was not accompanied by regular changes in the insulin dose. The regular rise of insulin dose, observed with the increase in the duration of T1D in adults diagnosed before the age of 30 years, is still an unknown phenomenon. However, this phenomenon was observed to correspond to the observation that T1D patients have long-standing insulin secretion at times (the study of cpeptide level), which was proven by Bonora (Bonora et al., 1984) and confirmed by the Diabetes Control and Complications Trial (DCCT). These research efforts uncovered the diverse influence of different insulin-therapy patterns on the process described (*The DCCT Research Group,* 1987; 1998). The confirmation of this data with the prospective observation was undertaken in Germany (Linn et al., 2003). Our results could be viewed as an indirect confirmation of the extended continuation of the β-cell secretion, obtained through the cross-sectional treatment data analysis of almost the entire population of T1D patients in Ukraine. The standardization of the daily insulin doses, depending on the disease duration, enables the necessary quantitative comparisons of the treatments for T1D adult patients.

#### **3.3.2 T1D insulin doses in territorial clusters**

68 Type 1 Diabetes – Complications, Pathogenesis, and Alternative Treatments

As the average duration of the disease was found to be 14.86 years, the average daily insulin

The regression analysis (figure 2) indicated that in this range, the insulin dose rises with the

Insulin (units/day) = 0.7326 × duration (years) + 43.74 (coefficient of linear correlation, *R* =

Fig. 2. Average (Mean ± SE) daily insulin doses of type 1 diabetes mellitus patients depending on the disease duration in the range of 0-15 years (Khalangot et al., 2009 d)

A further increase in the disease duration in the range of 16–31 years was not accompanied by regular changes in the insulin dose. The regular rise of insulin dose, observed with the increase in the duration of T1D in adults diagnosed before the age of 30 years, is still an unknown phenomenon. However, this phenomenon was observed to correspond to the

doses were calculated for each year of the duration, from 0 (<1) to 15 years.

**3.3.1 T1D insulin doses and diabetes duration** 

increase in the disease duration:

0.899, *p* < 0.001).

It would be logical to consider that the rate of decrease in insulin secretion among the T1D patients that differs according to the prevalence of such autoimmune disease, as T1D will also vary. Table 3 presents the comparisons of the daily insulin doses (median) in all the three clusters of the regions selected according to the prevalence of T1D in adults.


Note: Number of diabetes duration yearly groups (n) in all clusters is 16.

Table 3. Comparison of daily insulin doses standardized for every year of disease duration in the range of 0-15 years in clusters of regions singled out according to prevalence of diabetes mellitus type 1 (Khalangot et al., 2009 d).

Insulin doses standardized according to the disease duration within the range of 0–15 years in the minimal prevalence cluster of T1D prevalence were significantly lower, when compared with the intermediate and maximal prevalence clusters. The values in the intermediate prevalence cluster were lower than those in the maximal prevalence cluster (figure 3, table 3).

By evaluating the data presented in table 3, it should be noted that the probability coefficients (*P*), in this case, reflect a relatively small number of the "yearly" groups (*n*=16) in each cluster. If we were to assess the individual data on the insulin dose in each cluster without yearly grouping, then the number of cases (*n*) corresponding to the number of patients would greatly increase: 4,658; 14,712 and 2,879 in the minimal, intermediate, and maximal prevalence clusters, respectively. The unstandardized according to the diabetes duration average doses and their standard deviations (SD) in each of the three clusters, were observed to be 46.62 (19.38); 51.54 (17.57); and 55.94 (19.46) units/day, respectively, which was found to increase (*p* < 0.0001) in the clusters with higher T1D prevalence. However, the correlation of the insulin dose and the T1D prevalence found in this current region needs to be explained. One of the explanations for the difference in the daily insulin doses could be that in different Ukrainian regions, the doctors administer different levels of diabetes control: the lower dose is explained not only by the lower requirement of insulin by patients, but rather by the lower quality of treatment. An alternative explanation could be

Prevalence of Type 1 Diabetes Correlates with Daily Insulin Dose, Adverse

However, the reason for the heterogenic prevalence of T1D is still unknown.

**3.5 T1D outcomes assessment in territorial prevalence clusters** 

diagnosed before 19 years of age exceeded 25 years (Nishimura et al., 2001).

**3.5.1 Main characteristics of T1D patients from the cohort studied** 

**clusters** 

maximal prevalence cluster.

Outcomes and with Autoimmune Process Against Glutamic Acid Decarboxylase in Adults 71

The level of HbA1c in the maximal prevalence cluster was significantly greater than that in the minimal prevalence cluster, which does not support the assumption of lower treatment quality in the regions with lower T1D prevalence. Therefore, the alternative explanation using the discovered phenomenon remains rather the most likely one. Its confirmation may include c-peptide determination as well as the determination of antibodies associated with diabetes in patients residing in the Ukrainian territories with different T1D prevalence.

**3.4 GADA, IA and c-peptide levels in plasma of T1D patients from different prevalence** 

The GADA and IA levels in children recently diagnosed with T1D are observed to be higher in countries with a greater incidence of this disease, such as Sweden, when compared with those where the T1D incidence is lower, such as Lithuania (Holmberg et al., 2006). In our study, the GADA levels and persistence in patients from the maximal T1D prevalence cluster (*n*=38), were higher than that in patients from the minimal prevalence cluster (*n*=48): 14.1±4.6 and 3.2±1.2 U/ml, respectively, mean ± SE = 0.028; OR = 9.66 (3.31–28.17), p< 0.001. Adjusting for age, gender, and duration of diabetes affected the results only slightly: OR = 7.91 (2.44–25.57), p< 0.001. However, the IA and c-peptide levels and their persistence were not observed to be associated with T1D prevalence. It should be noted that persistence of IA is common only for children with T1D (reviewed by Dib & Gomes, 2009), when our study analyzed adults. These data was obtained in 2007 and published earlier elsewhere (Khalangot et al., 2009 d). In another series of our studies (unpublished data) conducted in 2010 on T1D patients (11 from Minimal cluster and 18 from Maximal one) selected in the same way, the GADA levels also differed significantly: 0.92 (0.61-3.04) and 24.43 (3.28-61.42) U/l, Me , 95% CI, p = 0.003; adjusted for diabetes duration OR = 8.6 (1.1-65.7), p=0.036. That is, the chance to have high GADA levels is almost 9 times higher for patients from the Maximal cluster as compared to the Minimal cluster, and this ratio was stable during repeated trials in these populations of T1D. Thus, the phenomenon of stable GADA persistence was discovered among adult T1D patients, residing in Ukraine within the

The obtained results allow us to assume that there may be differences in the incidence of adverse outcomes of the disease among populations with varying prevalence of T1D. The gathered large cohort (29 708 T1D patients) may be viewed as almost complete data on this category of patients in Ukraine (Khalangot et al., 2009 c, 2010). It should be noted, that the average duration of T1D is low (17.32 years). According to the data from a cross sectional study of Swedish National Diabetic Register (NDR), in 1997 the duration of T1D was 23.1 years and in 2004 it increased to 26.1 years. The criteria for T1D in the NDR study were treatment by insulin only and diagnosis before the age of 30 (Eeg-Olofsson et al., 2007), which corresponds to criteria used by us. According to the data from one of the regional diabetic registers in the US, the average T1D duration in a cohort of patients who were

The number of men in this cohort is greater than the number of women. Men have shorter disease duration (P <0,001) and higher levels of blood pressure (BP) (p <0,001), whereas

the higher intensity of the autoimmune process in patients residing in a territory with higher T1D prevalence.

Fig. 3. Average daily insulin doses of diabetes mellitus type 1 patients depending on the disease duration (in the range of 0-15 years) as well as on the territorial cluster, selected according to disease prevalence (Khalangot et al., 2009 d)

#### **3.3.3 Quality of glucose lowering treatment and mean insulin doses in T1D prevalence clusters**

Glycated hemoglobin (HbA1c) is considered as the most evident criteria in determining the quality of glucose-lowering treatment. We have analyzed and compared the levels of HbA1c of 1,288 T1D patients, included in the register. Table 4 shows the average HbA1c levels and the daily insulin doses according to the T1D prevalence clusters.


Table 4. Average levels of HbA1c (%) and insulin doses (units/day) considering territorial clusters with various diabetes type 1 prevalence (Khalangot et al., 2009 d)

the higher intensity of the autoimmune process in patients residing in a territory with higher

Fig. 3. Average daily insulin doses of diabetes mellitus type 1 patients depending on the disease duration (in the range of 0-15 years) as well as on the territorial cluster, selected

**3.3.3 Quality of glucose lowering treatment and mean insulin doses in T1D prevalence** 

Glycated hemoglobin (HbA1c) is considered as the most evident criteria in determining the quality of glucose-lowering treatment. We have analyzed and compared the levels of HbA1c of 1,288 T1D patients, included in the register. Table 4 shows the average HbA1c levels and

**N Mean HbA1c level, %** 

1. Minimal 111 8.57 (3.29) 40.91(16.24) 2. Intermediate 778 8.24 (2,3) 51.5 (14.8) 3. Maximal 240 9.52 (2.24) 54.79 (18.05) Р (1 vs 3) < 0.01 < 0.001 Table 4. Average levels of HbA1c (%) and insulin doses (units/day) considering territorial

**(SD)** 

**Mean insulin dose, U/day (SD)** 

according to disease prevalence (Khalangot et al., 2009 d)

the daily insulin doses according to the T1D prevalence clusters.

clusters with various diabetes type 1 prevalence (Khalangot et al., 2009 d)

T1D prevalence.

**clusters** 

**Type1 diabetes prevalence cluster**  The level of HbA1c in the maximal prevalence cluster was significantly greater than that in the minimal prevalence cluster, which does not support the assumption of lower treatment quality in the regions with lower T1D prevalence. Therefore, the alternative explanation using the discovered phenomenon remains rather the most likely one. Its confirmation may include c-peptide determination as well as the determination of antibodies associated with diabetes in patients residing in the Ukrainian territories with different T1D prevalence. However, the reason for the heterogenic prevalence of T1D is still unknown.

#### **3.4 GADA, IA and c-peptide levels in plasma of T1D patients from different prevalence clusters**

The GADA and IA levels in children recently diagnosed with T1D are observed to be higher in countries with a greater incidence of this disease, such as Sweden, when compared with those where the T1D incidence is lower, such as Lithuania (Holmberg et al., 2006). In our study, the GADA levels and persistence in patients from the maximal T1D prevalence cluster (*n*=38), were higher than that in patients from the minimal prevalence cluster (*n*=48): 14.1±4.6 and 3.2±1.2 U/ml, respectively, mean ± SE = 0.028; OR = 9.66 (3.31–28.17), p< 0.001. Adjusting for age, gender, and duration of diabetes affected the results only slightly: OR = 7.91 (2.44–25.57), p< 0.001. However, the IA and c-peptide levels and their persistence were not observed to be associated with T1D prevalence. It should be noted that persistence of IA is common only for children with T1D (reviewed by Dib & Gomes, 2009), when our study analyzed adults. These data was obtained in 2007 and published earlier elsewhere (Khalangot et al., 2009 d). In another series of our studies (unpublished data) conducted in 2010 on T1D patients (11 from Minimal cluster and 18 from Maximal one) selected in the same way, the GADA levels also differed significantly: 0.92 (0.61-3.04) and 24.43 (3.28-61.42) U/l, Me , 95% CI, p = 0.003; adjusted for diabetes duration OR = 8.6 (1.1-65.7), p=0.036.

That is, the chance to have high GADA levels is almost 9 times higher for patients from the Maximal cluster as compared to the Minimal cluster, and this ratio was stable during repeated trials in these populations of T1D. Thus, the phenomenon of stable GADA persistence was discovered among adult T1D patients, residing in Ukraine within the maximal prevalence cluster.

#### **3.5 T1D outcomes assessment in territorial prevalence clusters**

The obtained results allow us to assume that there may be differences in the incidence of adverse outcomes of the disease among populations with varying prevalence of T1D. The gathered large cohort (29 708 T1D patients) may be viewed as almost complete data on this category of patients in Ukraine (Khalangot et al., 2009 c, 2010). It should be noted, that the average duration of T1D is low (17.32 years). According to the data from a cross sectional study of Swedish National Diabetic Register (NDR), in 1997 the duration of T1D was 23.1 years and in 2004 it increased to 26.1 years. The criteria for T1D in the NDR study were treatment by insulin only and diagnosis before the age of 30 (Eeg-Olofsson et al., 2007), which corresponds to criteria used by us. According to the data from one of the regional diabetic registers in the US, the average T1D duration in a cohort of patients who were diagnosed before 19 years of age exceeded 25 years (Nishimura et al., 2001).

#### **3.5.1 Main characteristics of T1D patients from the cohort studied**

The number of men in this cohort is greater than the number of women. Men have shorter disease duration (P <0,001) and higher levels of blood pressure (BP) (p <0,001), whereas

Prevalence of Type 1 Diabetes Correlates with Daily Insulin Dose, Adverse

Outcomes and with Autoimmune Process Against Glutamic Acid Decarboxylase in Adults 73

of death. Renal failure is the leading cause of death (28.4%) in T1D patient cohort, whereas according to a British study of DM patient register containing primary care data, the leading cause of death among T1D patients was CVD (Laing et al., 1999). Similar results were obtained by a European study EURODIAB (Soedamah-Muthu et al., 2008). Comparison of main causes of death according to EURODIAB data and Ukrainian Diabetes Register (UDR) data is shown in figure 4. Apparently death from renal failure among T1D patients in Ukraine prevails several times over other causes, while in other parts of Europe the main cause of death is CVD. It was previously noted by epidemiologists that the main cause of death for T1D patients is renal failure (Dorman et al., 1984), however these data were relevant in 1960s-1970s. Today's experts believe that the shift in mortality structure towards CVD happened due to intensification of hypotensive therapy and insulin treatment (Maahs et al., 2006), therefore the mortality structure of T1D patients that we have revealed when

analyzing UDR can be assumed to conform to earlier time period of clinical practice.

Note: given Means (%) ± SE (the dot within the box and height of boxes respectively), 95% CI (lines that emerge above and below the boxes). Data from Ukrainian Diabetes Register given according to

To build the regression model we used 1925 deaths recorded among 27 896 patients. We have found that the patients living on the territory belonging to the maximal T1D prevalence cluster associated with increased risk of total mortality compared with the minimal prevalence cluster. In the minimal territorial cluster mortality was 15.68, and in the maximal -- 22.64 cases per 1000 person-years of follow up, p < 0.001. The risk (hazard ratio - HR) of death from all-cause mortality in patients from maximal in relation to the the minimal cluster was 1.5 (95% CI 1.31-1.79). Adjusting for gender had almost no effect on this risk: HRs standardized according to age, gender, and T1D duration for all cause mortality in

Fig. 4. Interval estimation of structure (%) of the main death causes among T1D patients, diagnosed before 30 years of age according to EURODIAB data (white boxes) and Ukrainian Diabetes Register (black boxes). Death causes: CVD (A); renal failure (B); DKA or coma (C);

Khalangot et al., 2010; EURODIAB given according to Soedamah-Muthu et al., 2008.

**3.5.2 Mortality assesment in territorial T1D prevalence clusters** 

cancer (D).

women have slightly higher levels of fasting glycemia (P <0,05). Blindness, cataracts and proliferative retinopathy more common for women (P <0,001). During 122,656.9 personyears (median observation period 4.7 years) 1958 deaths were recorded. The main cause of death was kidney failure. Cancer was very insignificant among other causes of death (table 5) . Possible reason for this phenomenon may be a short life expectancy of patients with diabetes.


Notes. BP – blood pressure, DKA – diabetic ketoacydosis;

\* - data concerned to 14723 man and 13092 women

Table 5. Same characteristics of T1D patients' cohort (Khalangot et al., 2010)

Life expectancy of T1D patients in Ukraine in 2007, assessed according to age at the time of death did not exceed 40.2 yrs (Khalangot, 2008). In UK, according to similar cohort study this value is 55 yrs (Soedamah-Muthu et al., 2006), however the British cohort also included children, which could influence the assessment of average T1D duration and age at the time

women have slightly higher levels of fasting glycemia (P <0,05). Blindness, cataracts and proliferative retinopathy more common for women (P <0,001). During 122,656.9 personyears (median observation period 4.7 years) 1958 deaths were recorded. The main cause of death was kidney failure. Cancer was very insignificant among other causes of death (table 5) . Possible reason for this phenomenon may be a short life expectancy of patients with

Characteristics Men Women All

Number of patients, n 15738 13970 29 708 Mean age, years (SD) 34.35(12.55) 34.61(13.30) 34.47(12.91)

Body mass index, kg/m2 (SD) 23.01(3.84)

BP diastolic, mm Hg. (SD) 78.57(10.53)

Fasting blood glucose, mmol/l (SD) 9.23(2.82)

HbA1c, % (SD) 8.68(2.53)

Notes. BP – blood pressure, DKA – diabetic ketoacydosis; \* - data concerned to 14723 man and 13092 women

Table 5. Same characteristics of T1D patients' cohort (Khalangot et al., 2010)

Life expectancy of T1D patients in Ukraine in 2007, assessed according to age at the time of death did not exceed 40.2 yrs (Khalangot, 2008). In UK, according to similar cohort study this value is 55 yrs (Soedamah-Muthu et al., 2006), however the British cohort also included children, which could influence the assessment of average T1D duration and age at the time

n=14331

n=14298

n=13747

n=1784

Smoking, n (%)\* 3223 (20.48) 414(2.96) 3637(12.24) Mean T1D duration, years 16.73 17.98 17.32 Nephropathy treatment, n (%)\* 4627(31.42) 4921(37.59) 9548(34.32) Cataract, n (%) \* 1573(10.68) 2041(15.59) 3614(12.99) Proliferative retinopathy, n (%) \* 1187(8.06) 1297(9.91) 2484(8.93) Blindness, n (%) \* 459(3.1) 506(3.9) 965(3.47) Follow up period, median, years 4.7 4.73 4.71 Total mortality cases, n (%) 1149 (100) 809(100) 1958(100) CVD mortality, n (%) 266(23.15) 182(22.5) 448(22.88) Cancer mortality, n (%) 16(1.39) 7(0.87) 23(1.17) Renal failure, n (%) 295(25.67) 262(32.39) 557(28.45) DKA and Coma 25(2.18) 36(4.45) 61(3.12) Other reasons (%) 344(29.94) 174(21.51) 518(26.46) Unknown 203(17.68) 148(18.29) 351(17.93)

BP systolic, mm Hg (SD) 126.29(18.75) 125.48(20.81) 125.91(19.75)

23.34(4.37)

77.66(11.38)

9.30(2.87)

8.83(2.61)

n=12729 23.16(4.10)

n=12654 78.15(10.94)

n=12174 9.26(2.85)

n=1789 8.75(2.57)

diabetes.

of death. Renal failure is the leading cause of death (28.4%) in T1D patient cohort, whereas according to a British study of DM patient register containing primary care data, the leading cause of death among T1D patients was CVD (Laing et al., 1999). Similar results were obtained by a European study EURODIAB (Soedamah-Muthu et al., 2008). Comparison of main causes of death according to EURODIAB data and Ukrainian Diabetes Register (UDR) data is shown in figure 4. Apparently death from renal failure among T1D patients in Ukraine prevails several times over other causes, while in other parts of Europe the main cause of death is CVD. It was previously noted by epidemiologists that the main cause of death for T1D patients is renal failure (Dorman et al., 1984), however these data were relevant in 1960s-1970s. Today's experts believe that the shift in mortality structure towards CVD happened due to intensification of hypotensive therapy and insulin treatment (Maahs et al., 2006), therefore the mortality structure of T1D patients that we have revealed when analyzing UDR can be assumed to conform to earlier time period of clinical practice.

Note: given Means (%) ± SE (the dot within the box and height of boxes respectively), 95% CI (lines that emerge above and below the boxes). Data from Ukrainian Diabetes Register given according to Khalangot et al., 2010; EURODIAB given according to Soedamah-Muthu et al., 2008.

Fig. 4. Interval estimation of structure (%) of the main death causes among T1D patients, diagnosed before 30 years of age according to EURODIAB data (white boxes) and Ukrainian Diabetes Register (black boxes). Death causes: CVD (A); renal failure (B); DKA or coma (C); cancer (D).
