Abstract
Background
Not much is known about the effects of glycemic variability
(GV) during the pre- and periconception period on pregnancy/perinatal
complications. GV could potentially contribute to ...identification of high-risk
pregnancies in women with type 1 diabetes.
Methods
An explorative retrospective cohort study was conducted between
January 2014 and May 2019. Glucose data were retrieved from electronic patient
charts. Pre-/periconceptional GV and GV during all three trimesters was
expressed as mean glucose, standard deviation (SD), Coefficient of Variation
(CV), High Blood Glucose Index (HBGI), Low Blood Glucose Index (LBGI) and
Average Daily Risk Range (ADRR). Maternal and neonatal complications were
summarized using a composite total complication score. Binary logistic
regression analyses were conducted to assess associations between the GV
measures and a total complication score>3, a maternal complication
score>1 and a neonatal complication score>1.
Results
Of 63 eligible women, 29 women (38 pregnancies) were included.
Women in the group with a total complication score>3 had a significantly
higher ADRR at conception (OR 1.1, CI 1.0–1.2, p=0.048). No
statistically significant correlations between complication score and any other
GV metric besides the ADRR were found. Although not significant, in the group
with a complication score>3, odds ratios>1 were found for SD in
trimester 1 (OR 1.6, CI 0.6–4.5, p=0.357) and trimester 2 (OR
1.8, CI 0.5–6.2, p=0.376).
Conclusions
Presence of a positive association between GV and pregnancy
and perinatal complications depends on which pregnancy period is assessed and
the GV metrics that are used.
Objectives To determine the prevalence of traditional cardiometabolic risk factors and to assess the effect of overweight/obesity on the occurrence of these risk factors in a cohort of children with ...type 1 diabetes mellitus (T1DM). Study design Two hundred eighty-three consecutive patients (3 to 18 years of age) attending an outpatient clinic for T1DM care were included. The prevalence of cardiometabolic risk factors, the metabolic syndrome, and high alanine aminotransferase, were assessed before and after stratification for weight status. Results Of all children (median age, 12.8 years; interquartile range, 9.9 to 16.0; median diabetes duration, 5.3 years; interquartile range, 2.9 to 8.6), 38.5% were overweight/obese ( Z -body mass index ≥1.1). Overall, median HbA1c levels were 8.2% (interquartile range, 7.4 to 9.8), and HbA1c ≥7.5% was present in 73.9%. Microalbuminuria was found in 17.7%, high triglycerides (>1.7 mmol/L) in 17.3%, high LDL-cholesterol (>2.6 mmol/L) in 28.6%, low HDL-cholesterol (<1.1 mmol/L) in 21.2%, and hypertension in 13.1% of patients. In the overweight/obese children with T1DM, versus normal-weight children, a higher prevalence of hypertension (23.9% vs 5.7%), the metabolic syndrome (25.7% vs 6.3%), and alanine aminotransferase >30 IU/L (15.6% vs 4.5%) was found (all P < .05). Conclusions Overweight/obesity and cardiometabolic risk factors were highly prevalent in a pediatric cohort with T1DM. Hypertension, the metabolic syndrome, and high alanine aminotransferase were significantly more prevalent in overweight/obese compared with normal-weight children with T1DM.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
To assess 1) the prevalence of children and adolescents with type 1 diabetes (T1D) changing from low-risk into borderline-high-risk lipid levels or from borderline-high-risk into high-risk lipid ...levels ('lose track of lipids') and 2) the power of a risk score including the determinants HbA1c, body mass index (BMI), gender, age, diabetes duration and ethnicity in predicting which patients lose track of lipids.
651 children and adolescents with T1D were included in this longitudinal retrospective cohort study. Lipid dynamics and the impact of the risk score on losing track of lipids were evaluated. Kaplan-Meier analysis was used to estimate screening intervals.
31-43% percent of the patients had lost track of one or more lipids at the next lipid measurement. This happened more frequently in patients with a low-risk lipid level at start. Depending on the lipid parameter, 5% of patients with low-risk lipid levels lost track of lipids after 13-23 months. The risk score based on concomitant information on the determinants was moderately able to predict which patients would lose track of lipids on the short term.
A considerable number of children and adolescents with T1D loses track of lipids and does so within a 2-year screening interval. The predictive power of a risk score including age, BMI, gender, HbA1c, diabetes duration and ethnicity is only moderate. Future research should focus on another approach to the determinants used in this study or other determinants predictive of losing track of lipids on the short term.
Objective
To examine the prevalence, time trends, and risk factors of diabetic retinopathy (DR) among youth with type 1 diabetes (T1D) from 11 countries (Australia, Austria, Denmark, England, ...Germany, Italy, Luxemburg, Netherlands, Slovenia, United States, and Wales).
Subjects and Methods
Data on individuals aged 10–21 years with T1D for >1 year during the period 2000–2020 were analyzed. We used a cross‐sectional design using the most recent year of visit to investigate the time trend. For datasets with longitudinal data, we aggregated the variables per participant and observational year, using data of the most recent year to take the longest observation period into account. DR screening was performed through quality assured national screening programs. Multiple logistic regression models adjusted for the year of the eye examination, age, gender, minority status, and duration of T1D were used to evaluate clinical characteristics and the risk of DR.
Results
Data from 156,090 individuals (47.1% female, median age 15.7 years, median duration of diabetes 5.2 years) were included. Overall, the unadjusted prevalence of any DR was 5.8%, varying from 0.0% (0/276) to 16.2% between countries. The probability of DR increased with longer disease duration (aORper‐1‐year‐increase = 1.04, 95% CI: 1.03–1.04, p < 0.0001), and decreased over time (aORper‐1‐year‐increase = 0.99, 95% CI: 0.98–1.00, p = 0.0093).
Evaluating possible modifiable risk factors in the exploratory analysis, the probability of DR increased with higher HbA1c (aORper‐1‐mmol/mol‐increase‐in‐HbA1c = 1.03, 95% CI: 1.03–1.03, p < 0.0001) and was higher among individuals with hypertension (aOR = 1.24, 95% CI: 1.11–1.38, p < 0.0001) and smokers (aOR = 1.30, 95% CI: 1.17–1.44, p < 0.0001).
Conclusions
The prevalence of DR in this large cohort of youth with T1D varied among countries, increased with diabetes duration, decreased over time, and was associated with higher HbA1c, hypertension, and smoking.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Samenvatting
De snelle technologische ontwikkelingen in de diabeteszorg zorgen voor betere uitkomsten, maar ook voor een toename van dataverkeer tussen patiënt en zorgverleners. De noodzaak voor die ...verbetering van uitkomsten wordt beschreven. De stappen die daartoe zijn gezet en die nog kunnen worden gezet, zijn aan de inzet van deze technologie verbonden. Daarbij moet en kan ook de diabeteszorg worden veranderd, waardoor er op nieuwe wijze continuïteit in contacten en coaching komt en traditionele zorg (3-4 x per jaar een consult) verandert naar nieuwe virtuele en automatische vormen. Daarvoor is een verandering nodig: in plaats van dat elk contact vanuit één patiënt of behandelaar wordt gestart, wordt op basis van de glucosedata populatiemanagement van diabetes verricht. Daarbij wordt op basis van zorggegevens een (continue) triage verricht en wordt direct persoonsgerichte zorg aangeboden aan mensen die problemen ervaren of risico hebben op problemen. De combinatie van diabetestechnologie en populatiemanagementmethoden wordt aan de hand van het ontwikkelde CloudCare-systeem toegelicht.
Aim
This study described the incidence and prevalence of type 1 diabetes in children in the Netherlands in 2010–2011 and to compare these results with earlier studies.
Methods
This was a ...retrospective nationwide cohort study of Dutch children aged 14 years or younger. Patients were identified using health insurance reimbursement registries for hospital care and invoices for insulin. In the Netherlands, all children with diabetes are treated by hospital‐based paediatricians and health care for all Dutch citizens is covered by law.
Results
The incidence of type 1 diabetes almost doubled between 1978–1980 and 2010–2011, from 11.1 to 21.4 per 100 000. In the youngest age group, who were under 5 years, the incidence rate doubled between 1996 and 1999 and remained stable after that. There were no relevant incidence differences between the sexes. The overall prevalence of type 1 diabetes in the Netherlands during 2009–2011 was 143.6 (95% confidence interval 141.1–146.2) per 100 000 children and was similar for boys and girls.
Conclusion
The incidence of type 1 diabetes in children in the Netherlands almost doubled between 1978–1980 and 2010–2011, but the incidence in children under 5 years appeared to stabilise between 1996 and 1999. There were no statistical differences between the sexes.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
IntroductionCardiovascular disease (CVD) is the leading cause of mortality in individuals with type 1 diabetes mellitus (T1DM). Cardiovascular risk management is therefore essential in the management ...of individuals with T1DM. This study describes the performance of lipid and blood pressure management in individuals with T1DM using three guidelines.Research design and methodsIndividuals ≥18 years with T1DM, treated with insulin for ≥1 year, visiting Diabeter or the University Medical Center Groningen between January 1, 2018 and December 31, 2018, were included. Lipid and blood pressure management were examined using the Dutch, American Diabetes Association (ADA) and National Institute for Health and Care Excellence (NICE) guidelines. Concordance of recommended and prescribed lipid-lowering (LLM) or antihypertensive medication (AHM) was assessed per guideline and 10-year age groups. Achievement of treatment targets was assessed for those prescribed medication.ResultsA total of 1855 individuals with T1DM were included. LLM and AHM was prescribed in 19% and 17%, respectively. In individuals recommended LLM, this was prescribed in 22%–46% according to Dutch, ADA or NICE guideline recommendations. For individuals recommended AHM, this was prescribed in 52%–75%. Recommended and actual prescription of LLM and AHM increased over age for all three guidelines. However, discordance between treatment recommendation and medication prescribed was higher in younger, compared with older, age groups. Low-density lipoprotein-cholesterol targets were achieved by 50% (without CVD) and 31% (with CVD) of those prescribed LLM. The blood pressure target was achieved by 46% of those prescribed AHM.ConclusionThis study suggests that there is undertreatment of lipid and blood pressure according to guideline recommendations, particularly in younger age groups. Treatment targets are not met by most individuals prescribed medication, while guidelines recommendations differ considerably. We recommend to investigate the factors influencing undertreatment of lipid and blood pressure management in individuals with T1DM.
Objective
To establish whether diabetic ketoacidosis (DKA) or HbA1c at onset is associated with year‐three HbA1c in children with type 1 diabetes (T1D).
Methods
Children with T1D from the SWEET ...registry, diagnosed <18 years, with documented clinical presentation, HbA1c at onset and follow‐up were included. Participants were categorized according to T1D onset: (a) DKA (DKA with coma, DKA without coma, no DKA); (b) HbA1c at onset (low <10%, medium 10 to <12%, high ≥12%). To adjust for demographics, linear regression was applied with interaction terms for DKA and HbA1c at onset groups (adjusted means with 95% CI). Association between year‐three HbA1c and both HbA1c and presentation at onset was analyzed (Vuong test).
Results
Among 1420 children (54% males; median age at onset 9.1 years Q1;Q3: 5.8;12.2), 6% of children experienced DKA with coma, 37% DKA without coma, and 57% no DKA. Year‐three HbA1c was lower in the low compared to high HbA1c at onset group, both in the DKA without coma (7.1% 6.8;7.4 vs 7.6% 7.5;7.8, P = .03) and in the no DKA group (7.4% 7.2;7.5 vs 7.8% 7.6;7.9, P = .01), without differences between low and medium HbA1c at onset groups. Year‐three HbA1c did not differ among HbA1c at onset groups in the DKA with coma group. HbA1c at onset as an explanatory variable was more closely associated with year‐three HbA1c compared to presentation at onset groups (P = .02).
Conclusions
Year‐three HbA1c is more closely related to HbA1c than to DKA at onset; earlier hyperglycemia detection might be crucial to improving year‐three HbA1c.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Early identification of children and adolescents with type 1 diabetes at high risk for development of complications is important, as early intervention may prevent further deterioration. Here we ...investigate the applicability of assessing skin advanced glycation end products (sAGEs) by skin autofluorescence (SAF) as a potential surrogate risk marker.
This study included a cross-sectional analysis of SAF in 77 patients with type 1 diabetes mellitus and 118 healthy controls across age categories (11-12, 13-14, 15-16, and 17-19 years old). In patients, the impact of current and historical glycated hemoglobin (HbA1c) values, age, and duration of diabetes on SAF was studied in a retrospective cohort study and analyzed with multivariable analyses.
SAF was significantly and similarly higher in patients when compared with controls across all age categories (P ≤0.009). For patients, age, duration of diabetes, and current and historical HbA1c were associated with SAF in univariate analysis. Multivariate analysis showed no association between HbA1c and SAF. A subgroup of patients with a HbA1c-within-target (≤7.5 %/59 mmol/mol) were observed to have high SAF.
Children and adolescents with type 1 diabetes show higher SAF than controls. The presumed correlation of high HbA1c with high SAF does not exist in all patients. Thus, use of this non-invasive measure may provide a surrogate marker for diabetic complications, additional to HbA1c.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
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