scholarly journals Increasing Incidence of Type 1 Diabetes in Youth: Twenty years of the Philadelphia Pediatric Diabetes Registry

Diabetes Care ◽  
2013 ◽  
Vol 36 (6) ◽  
pp. 1597-1603 ◽  
Author(s):  
T. H. Lipman ◽  
L. E. Levitt Katz ◽  
S. J. Ratcliffe ◽  
K. M. Murphy ◽  
A. Aguilar ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Diabetes Registry ◽  
Pediatric Diabetes ◽  
Diabetes In Youth

scholarly journals A description of clinician reported diagnosis of type 2 diabetes and other non-type 1 diabetes included in a large international multicentered pediatric diabetes registry (SWEET)

2016 ◽  
Vol 17 ◽  
pp. 24-31 ◽  
Author(s):  
Danièle Pacaud ◽  
Anke Schwandt ◽  
Carine de Beaufort ◽  
Kristina Casteels ◽  
Jacques Beltrand ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Type 1 Diabetes ◽  
Diabetes Registry ◽  
Pediatric Diabetes

scholarly journals Comparison of Cystic Fibrosis-Related Diabetes With Type 1 Diabetes Based on a German/Austrian Pediatric Diabetes Registry

Diabetes Care ◽  
2012 ◽  
Vol 36 (4) ◽  
pp. 879-886 ◽  
Author(s):  
K. Konrad ◽  
A. Thon ◽  
M. Fritsch ◽  
E. Frohlich-Reiterer ◽  
E. Lilienthal ◽  
...  
Keyword(s):  
Cystic Fibrosis ◽  
Type 1 Diabetes ◽  
Diabetes Registry ◽  
Pediatric Diabetes

The proportion of familial cases of type 1 diabetes is increasing simultaneously with the disease incidence: Eighteen years of the Israeli Pediatric Diabetes Registry

2017 ◽  
Vol 19 (4) ◽  
pp. 693-698 ◽  
Author(s):  
Amnon Zung ◽  
Wasef Na'amnih ◽  
Yulia Bluednikov ◽  
Nisim Mery ◽  
Orit Blumenfeld ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Disease Incidence ◽  
Diabetes Registry ◽  
Familial Cases ◽  
Pediatric Diabetes

scholarly journals New-onset type 1 diabetes in Finnish children during the COVID-19 pandemic

2021 ◽  
pp. archdischild-2020-321220
Author(s):  
Heli Salmi ◽  
Santtu Heinonen ◽  
Johanna Hästbacka ◽  
Mitja Lääperi ◽  
Paula Rautiainen ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Viral Infections ◽  
Incidence Rate Ratio ◽  
University Hospital ◽  
Diabetes Registry ◽  
Number Of Children ◽  
Pediatric Diabetes ◽  
Delays In Diagnosis ◽  
New Onset

BackgroundViral infections may trigger type 1 diabetes (T1D), and recent reports suggest an increased incidence of paediatric T1D and/or diabetic ketoacidosis (DKA) during the COVID-19 pandemic.ObjectiveTo study whether the number of children admitted to the paediatric intensive care unit (PICU) for DKA due to new-onset T1D increased during the COVID-19 pandemic, and whether SARS-CoV-2 infection plays a role.MethodsThis retrospective cohort study comprises two datasets: (1) children admitted to PICU due to new-onset T1D and (2) children diagnosed with new-onset T1D and registered to the Finnish Pediatric Diabetes Registry in the Helsinki University Hospital from 1 April to 31 October in 2016–2020. We compared the incidence, number and characteristics of children with newly diagnosed T1D between the prepandemic and pandemic periods.ResultsThe number of children admitted to PICU due to new-onset T1D increased from an average of 6.25 admissions in 2016–2019 to 20 admissions in 2020 (incidence rate ratio [IRR] 3.24 [95% CI 1.80 to 5.83]; p=0.0001). On average, 57.75 children were registered to the FPDR in 2016–2019, as compared with 84 in 2020 (IRR 1.45; 95% CI 1.13 to 1.86; p=0.004). 33 of the children diagnosed in 2020 were analysed for SARS-CoV-2 antibodies, and all were negative.ConclusionsMore children with T1D had severe DKA at diagnosis during the pandemic. This was not a consequence of SARS-CoV-2 infection. Instead, it probably stems from delays in diagnosis following changes in parental behaviour and healthcare accessibility.

scholarly journals Coeliac disease is associated with depression in children and young adults with type 1 diabetes: results from a multicentre diabetes registry

2021 ◽  
Author(s):  
Sascha René Tittel ◽  
◽  
Désirée Dunstheimer ◽  
Dörte Hilgard ◽  
Burkhild Knauth ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Young Adults ◽  
Coeliac Disease ◽  
Diabetes Patient ◽  
Routine Care ◽  
Diabetes Registry ◽  
Increased Risk ◽  
Treatment Data ◽  
Children And Young Adults

Abstract Aims To analyse the association between coeliac disease (CD) and depression in children, adolescents, and young adults with type 1 diabetes (T1D). Methods We included 79,067 T1D patients aged 6–20 years, with at least six months of diabetes duration, and treatment data between 1995 and 2019 were documented in the diabetes patient follow-up registry. We categorized patients into four groups: T1D only (n = 73,699), T1 + CD (n = 3379), T1D + depression (n = 1877), or T1D + CD + depression (n = 112). Results CD and depression were significantly associated (adjusted OR: 1.25 [1.03–1.53]). Females were more frequent in both the depression and the CD group compared with the T1D only group. Insulin pumps were used more frequently in T1D + CD and T1D + depression compared with T1D only (both p < .001). HbA1c was higher in T1D + depression (9.0% [8.9–9.0]), T1D + CD + depression (8.9% [8.6–9.2]), both compared with T1D only (8.2% [8.2–8.2], all p < .001). We found comorbid autism, attention deficit hyperactivity disorder, anxiety, schizophrenia, and eating disorders more frequently in the T1D + CD + depression group compared with T1D only (all p < .001). Conclusions CD and depression are associated in young T1D patients. The double load of T1D and CD may lead to an increased risk for depression. Depression was associated with additional psychological and neurological comorbidities. Aside from imperative CD screening after T1D diagnosis and regular intervals, depression screening might be helpful in routine care, especially in patients with diagnosed CD.

scholarly journals Insulin Regimens and Clinical Outcomes in a Type 1 Diabetes Cohort: The SEARCH for Diabetes in Youth study

Diabetes Care ◽  
2012 ◽  
Vol 36 (1) ◽  
pp. 27-33 ◽  
Author(s):  
C. Pihoker ◽  
A. Badaru ◽  
A. Anderson ◽  
T. Morgan ◽  
L. Dolan ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Clinical Outcomes ◽  
Youth Study ◽  
Diabetes In Youth

scholarly journals Retinal vascular fractals predict long-term microvascular complications in type 1 diabetes mellitus: the Danish Cohort of Pediatric Diabetes 1987 (DCPD1987)

Diabetologia ◽  
2014 ◽  
Vol 57 (10) ◽  
pp. 2215-2221 ◽  
Author(s):  
Rebecca Broe ◽  
Malin L. Rasmussen ◽  
Ulrik Frydkjaer-Olsen ◽  
Birthe S. Olsen ◽  
Henrik B. Mortensen ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Type 1 Diabetes Mellitus ◽  
Microvascular Complications ◽  
Pediatric Diabetes ◽  
Danish Cohort

scholarly journals Diabetic ketoacidosis at diagnosis of type 1 diabetes and glycemic control over time: The SEARCH for diabetes in youth study

2018 ◽  
Vol 20 (2) ◽  
pp. 172-179 ◽  
Author(s):  
Lindsey M. Duca ◽  
Beth A. Reboussin ◽  
Catherine Pihoker ◽  
Giuseppina Imperatore ◽  
Sharon Saydah ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Diabetic Ketoacidosis ◽  
Youth Study ◽  
Diabetes In Youth ◽  
Over Time

scholarly journals Detection of Diabetes Status and Type in Youth using Electronic Health Records (EHRs): The SEARCH for Diabetes in Youth Study

2020 ◽  
Author(s):  
Brian J. Wells ◽  
Kristin M. Lenoir ◽  
Lynne E. Wagenknecht ◽  
Elizabeth J. Mayer-Davis ◽  
Jean M. Lawrence ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Type 1 Diabetes ◽  
Multinomial Regression ◽  
Rule Based ◽  
Diabetes Status ◽  
Icd 10 ◽  
Youth Study ◽  
Diabetes In Youth

<u>Objective:</u> Diabetes surveillance often requires manual medical chart reviews to confirm status and type. This project aimed to create an electronic health record (EHR)-based procedure for improving surveillance efficiency through automation of case identification. <p><u> </u></p> <p><u>Research Design and Methods:</u> Youth (< 20 years) with potential evidence of diabetes (N=8,682) were identified from EHRs at three children’s hospitals participating in the SEARCH for Diabetes in Youth Study. True diabetes status/type was determined by manual chart reviews. Multinomial regression was compared with an ICD-10 rule-based algorithm in the ability to correctly identify diabetes status and type. Subsequently, the investigators evaluated a scenario of combining the rule based algorithm with targeted chart reviews where the algorithm performed poorly.</p> <p> </p> <p><u>Results:</u> The sample included 5308 true cases (89.2% type 1 diabetes). The rule-based algorithm outperformed regression for overall accuracy (0.955 vs 0.936). Type 1 diabetes was classified well by both methods: sensitivity (<i>Se</i>) (>0.95), specificity (<i>Sp</i>) (>0.96), and positive predictive value (PPV) (>0.97). In contrast, the PPVs for type 2 diabetes were 0.642 and 0.778 for the rule-based algorithm and the multinomial regression, respectively. Combining the rule-based method with chart reviews (n=695, 7.9%) of persons predicted to have non type 1 diabetes resulted in perfect PPV for the cases reviewed, while increasing overall accuracy (0.983). The sensitivity, specificity, and PPV for type 2 diabetes using the combined method were >=0.91. </p> <p> </p> <p><u>Conclusions</u>: An ICD-10 algorithm combined with targeted chart reviews accurately identified diabetes status/type and could be an attractive option for diabetes surveillance in youth. </p> <br>

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