Demographic, Clinical, Management, and Outcome Characteristics of 8,004 Young Children With Type 1 Diabetes
To compare demographic, clinical, and therapeutic characteristics of children with type 1 diabetes age
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| Veröffentlicht in: | Diabetes care 2024-04, Vol.47 (4), p.660-667 |
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| creator | Sandy, Jessica L Tittel, Sascha R Rompicherla, Saketh Karges, Beate James, Steven Rioles, Nicole Zimmerman, Anthony G Fröhlich-Reiterer, Elke Maahs, David M Lanzinger, Stefanie Craig, Maria E Ebekozien, Osagie |
| description | To compare demographic, clinical, and therapeutic characteristics of children with type 1 diabetes age |
| doi_str_mv | 10.2337/dc23-1317 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2929130454</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2929130454</sourcerecordid><originalsourceid>FETCH-LOGICAL-c273t-43a82dabd9fc92b6fd73212229bac1c5a544a3d484467ec3c6d1fa01979dff793</originalsourceid><addsrcrecordid>eNpdkTtPwzAQgC0EouUx8AeQJRaQGrB9ThOPqOUlFXUpQkzRxXZaQx7FTob-e1K1MDDdcJ8-ne4j5IKzWwGQ3BktIOLAkwMy5AriKI5lekiGjEsVxUqJATkJ4ZMxJmWaHpMBpMDiJBVD8jW1VbP0uF45PaKT0tVOYzmir1jj0la2bkcUa0PnXaubytLJCj3q1noXWqcDbQqajnov_Wi6etmvXWm8rem7a1d0sVlbyunUYW5bG87IUYFlsOf7eUreHh8Wk-doNn96mdzPIi0SaCMJmAqDuVGFViIfFyYBwYUQKkfNdYyxlAhGplKOE6tBjw0vkHGVKFMUiYJTcr3zrn3z3dnQZpUL2pYl1rbpQiaUUByYjGWPXv1DP5vO1_11GTAQY8GY2FI3O0r7JgRvi2ztXYV-k3GWbQtk2wLZtkDPXu6NXV5Z80f-vhx-AEG-foc</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3032620024</pqid></control><display><type>article</type><title>Demographic, Clinical, Management, and Outcome Characteristics of 8,004 Young Children With Type 1 Diabetes</title><source>MEDLINE</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><creator>Sandy, Jessica L ; Tittel, Sascha R ; Rompicherla, Saketh ; Karges, Beate ; James, Steven ; Rioles, Nicole ; Zimmerman, Anthony G ; Fröhlich-Reiterer, Elke ; Maahs, David M ; Lanzinger, Stefanie ; Craig, Maria E ; Ebekozien, Osagie</creator><creatorcontrib>Sandy, Jessica L ; Tittel, Sascha R ; Rompicherla, Saketh ; Karges, Beate ; James, Steven ; Rioles, Nicole ; Zimmerman, Anthony G ; Fröhlich-Reiterer, Elke ; Maahs, David M ; Lanzinger, Stefanie ; Craig, Maria E ; Ebekozien, Osagie ; Australasian Diabetes Data Network (ADDN) ; Prospective Diabetes Follow-Up Registry Initiative (DPV) ; T1D Exchanged Quality Improvement Collaborative (T1DX-QI)</creatorcontrib><description>To compare demographic, clinical, and therapeutic characteristics of children with type 1 diabetes age <6 years across three international registries: Diabetes Prospective Follow-Up Registry (DPV; Europe), T1D Exchange Quality Improvement Network (T1DX-QI; U.S.), and Australasian Diabetes Data Network (ADDN; Australasia).
An analysis was conducted comparing 2019-2021 prospective registry data from 8,004 children.
Mean ± SD ages at diabetes diagnosis were 3.2 ± 1.4 (DPV and ADDN) and 3.7 ± 1.8 years (T1DX-QI). Mean ± SD diabetes durations were 1.4 ± 1.3 (DPV), 1.4 ± 1.6 (T1DX-QI), and 1.5 ± 1.3 years (ADDN). BMI z scores were in the overweight range in 36.2% (DPV), 41.8% (T1DX-QI), and 50.0% (ADDN) of participants. Mean ± SD HbA1c varied among registries: DPV 7.3 ± 0.9% (56 ± 10 mmol/mol), T1DX-QI 8.0 ± 1.4% (64 ± 16 mmol/mol), and ADDN 7.7 ± 1.2% (61 ± 13 mmol/mol). Overall, 37.5% of children achieved the target HbA1c of <7.0% (53 mmol/mol): 43.6% in DPV, 25.5% in T1DX-QI, and 27.5% in ADDN. Use of diabetes technologies such as insulin pump (DPV 86.6%, T1DX 46.6%, and ADDN 39.2%) and continuous glucose monitoring (CGM; DPV 85.1%, T1DX-QI 57.6%, and ADDN 70.5%) varied among registries. Use of hybrid closed-loop (HCL) systems was uncommon (from 0.5% [ADDN] to 6.9% [DPV]).
Across three major registries, more than half of children age <6 years did not achieve the target HbA1c of <7.0% (53 mmol/mol). CGM was used by most participants, whereas insulin pump use varied across registries, and HCL system use was rare. The differences seen in glycemia and use of diabetes technologies among registries require further investigation to determine potential contributing factors and areas to target to improve the care of this vulnerable group.</description><identifier>ISSN: 0149-5992</identifier><identifier>EISSN: 1935-5548</identifier><identifier>DOI: 10.2337/dc23-1317</identifier><identifier>PMID: 38305782</identifier><language>eng</language><publisher>United States: American Diabetes Association</publisher><subject>Blood Glucose ; Blood Glucose Self-Monitoring ; Child ; Child, Preschool ; Children ; Closed loops ; Demographics ; Demography ; Diabetes ; Diabetes mellitus (insulin dependent) ; Diabetes Mellitus, Type 1 - drug therapy ; Diabetes Mellitus, Type 1 - epidemiology ; Glucose monitoring ; Glycated Hemoglobin ; Humans ; Hybrid systems ; Hypoglycemic Agents - therapeutic use ; Infusion pumps ; Insulin ; Insulin - therapeutic use ; Insulin Infusion Systems ; Insulins - therapeutic use ; Quality control ; Registries ; Research design</subject><ispartof>Diabetes care, 2024-04, Vol.47 (4), p.660-667</ispartof><rights>2024 by the American Diabetes Association.</rights><rights>Copyright American Diabetes Association Apr 2024</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c273t-43a82dabd9fc92b6fd73212229bac1c5a544a3d484467ec3c6d1fa01979dff793</cites><orcidid>0000-0001-6004-576X ; 0000-0002-2406-8419</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38305782$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Sandy, Jessica L</creatorcontrib><creatorcontrib>Tittel, Sascha R</creatorcontrib><creatorcontrib>Rompicherla, Saketh</creatorcontrib><creatorcontrib>Karges, Beate</creatorcontrib><creatorcontrib>James, Steven</creatorcontrib><creatorcontrib>Rioles, Nicole</creatorcontrib><creatorcontrib>Zimmerman, Anthony G</creatorcontrib><creatorcontrib>Fröhlich-Reiterer, Elke</creatorcontrib><creatorcontrib>Maahs, David M</creatorcontrib><creatorcontrib>Lanzinger, Stefanie</creatorcontrib><creatorcontrib>Craig, Maria E</creatorcontrib><creatorcontrib>Ebekozien, Osagie</creatorcontrib><creatorcontrib>Australasian Diabetes Data Network (ADDN)</creatorcontrib><creatorcontrib>Prospective Diabetes Follow-Up Registry Initiative (DPV)</creatorcontrib><creatorcontrib>T1D Exchanged Quality Improvement Collaborative (T1DX-QI)</creatorcontrib><title>Demographic, Clinical, Management, and Outcome Characteristics of 8,004 Young Children With Type 1 Diabetes</title><title>Diabetes care</title><addtitle>Diabetes Care</addtitle><description>To compare demographic, clinical, and therapeutic characteristics of children with type 1 diabetes age <6 years across three international registries: Diabetes Prospective Follow-Up Registry (DPV; Europe), T1D Exchange Quality Improvement Network (T1DX-QI; U.S.), and Australasian Diabetes Data Network (ADDN; Australasia).
An analysis was conducted comparing 2019-2021 prospective registry data from 8,004 children.
Mean ± SD ages at diabetes diagnosis were 3.2 ± 1.4 (DPV and ADDN) and 3.7 ± 1.8 years (T1DX-QI). Mean ± SD diabetes durations were 1.4 ± 1.3 (DPV), 1.4 ± 1.6 (T1DX-QI), and 1.5 ± 1.3 years (ADDN). BMI z scores were in the overweight range in 36.2% (DPV), 41.8% (T1DX-QI), and 50.0% (ADDN) of participants. Mean ± SD HbA1c varied among registries: DPV 7.3 ± 0.9% (56 ± 10 mmol/mol), T1DX-QI 8.0 ± 1.4% (64 ± 16 mmol/mol), and ADDN 7.7 ± 1.2% (61 ± 13 mmol/mol). Overall, 37.5% of children achieved the target HbA1c of <7.0% (53 mmol/mol): 43.6% in DPV, 25.5% in T1DX-QI, and 27.5% in ADDN. Use of diabetes technologies such as insulin pump (DPV 86.6%, T1DX 46.6%, and ADDN 39.2%) and continuous glucose monitoring (CGM; DPV 85.1%, T1DX-QI 57.6%, and ADDN 70.5%) varied among registries. Use of hybrid closed-loop (HCL) systems was uncommon (from 0.5% [ADDN] to 6.9% [DPV]).
Across three major registries, more than half of children age <6 years did not achieve the target HbA1c of <7.0% (53 mmol/mol). CGM was used by most participants, whereas insulin pump use varied across registries, and HCL system use was rare. The differences seen in glycemia and use of diabetes technologies among registries require further investigation to determine potential contributing factors and areas to target to improve the care of this vulnerable group.</description><subject>Blood Glucose</subject><subject>Blood Glucose Self-Monitoring</subject><subject>Child</subject><subject>Child, Preschool</subject><subject>Children</subject><subject>Closed loops</subject><subject>Demographics</subject><subject>Demography</subject><subject>Diabetes</subject><subject>Diabetes mellitus (insulin dependent)</subject><subject>Diabetes Mellitus, Type 1 - drug therapy</subject><subject>Diabetes Mellitus, Type 1 - epidemiology</subject><subject>Glucose monitoring</subject><subject>Glycated Hemoglobin</subject><subject>Humans</subject><subject>Hybrid systems</subject><subject>Hypoglycemic Agents - therapeutic use</subject><subject>Infusion pumps</subject><subject>Insulin</subject><subject>Insulin - therapeutic use</subject><subject>Insulin Infusion Systems</subject><subject>Insulins - therapeutic use</subject><subject>Quality control</subject><subject>Registries</subject><subject>Research design</subject><issn>0149-5992</issn><issn>1935-5548</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpdkTtPwzAQgC0EouUx8AeQJRaQGrB9ThOPqOUlFXUpQkzRxXZaQx7FTob-e1K1MDDdcJ8-ne4j5IKzWwGQ3BktIOLAkwMy5AriKI5lekiGjEsVxUqJATkJ4ZMxJmWaHpMBpMDiJBVD8jW1VbP0uF45PaKT0tVOYzmir1jj0la2bkcUa0PnXaubytLJCj3q1noXWqcDbQqajnov_Wi6etmvXWm8rem7a1d0sVlbyunUYW5bG87IUYFlsOf7eUreHh8Wk-doNn96mdzPIi0SaCMJmAqDuVGFViIfFyYBwYUQKkfNdYyxlAhGplKOE6tBjw0vkHGVKFMUiYJTcr3zrn3z3dnQZpUL2pYl1rbpQiaUUByYjGWPXv1DP5vO1_11GTAQY8GY2FI3O0r7JgRvi2ztXYV-k3GWbQtk2wLZtkDPXu6NXV5Z80f-vhx-AEG-foc</recordid><startdate>20240401</startdate><enddate>20240401</enddate><creator>Sandy, Jessica L</creator><creator>Tittel, Sascha R</creator><creator>Rompicherla, Saketh</creator><creator>Karges, Beate</creator><creator>James, Steven</creator><creator>Rioles, Nicole</creator><creator>Zimmerman, Anthony G</creator><creator>Fröhlich-Reiterer, Elke</creator><creator>Maahs, David M</creator><creator>Lanzinger, Stefanie</creator><creator>Craig, Maria E</creator><creator>Ebekozien, Osagie</creator><general>American Diabetes Association</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-6004-576X</orcidid><orcidid>https://orcid.org/0000-0002-2406-8419</orcidid></search><sort><creationdate>20240401</creationdate><title>Demographic, Clinical, Management, and Outcome Characteristics of 8,004 Young Children With Type 1 Diabetes</title><author>Sandy, Jessica L ; 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Europe), T1D Exchange Quality Improvement Network (T1DX-QI; U.S.), and Australasian Diabetes Data Network (ADDN; Australasia).
An analysis was conducted comparing 2019-2021 prospective registry data from 8,004 children.
Mean ± SD ages at diabetes diagnosis were 3.2 ± 1.4 (DPV and ADDN) and 3.7 ± 1.8 years (T1DX-QI). Mean ± SD diabetes durations were 1.4 ± 1.3 (DPV), 1.4 ± 1.6 (T1DX-QI), and 1.5 ± 1.3 years (ADDN). BMI z scores were in the overweight range in 36.2% (DPV), 41.8% (T1DX-QI), and 50.0% (ADDN) of participants. Mean ± SD HbA1c varied among registries: DPV 7.3 ± 0.9% (56 ± 10 mmol/mol), T1DX-QI 8.0 ± 1.4% (64 ± 16 mmol/mol), and ADDN 7.7 ± 1.2% (61 ± 13 mmol/mol). Overall, 37.5% of children achieved the target HbA1c of <7.0% (53 mmol/mol): 43.6% in DPV, 25.5% in T1DX-QI, and 27.5% in ADDN. Use of diabetes technologies such as insulin pump (DPV 86.6%, T1DX 46.6%, and ADDN 39.2%) and continuous glucose monitoring (CGM; DPV 85.1%, T1DX-QI 57.6%, and ADDN 70.5%) varied among registries. Use of hybrid closed-loop (HCL) systems was uncommon (from 0.5% [ADDN] to 6.9% [DPV]).
Across three major registries, more than half of children age <6 years did not achieve the target HbA1c of <7.0% (53 mmol/mol). CGM was used by most participants, whereas insulin pump use varied across registries, and HCL system use was rare. The differences seen in glycemia and use of diabetes technologies among registries require further investigation to determine potential contributing factors and areas to target to improve the care of this vulnerable group.</abstract><cop>United States</cop><pub>American Diabetes Association</pub><pmid>38305782</pmid><doi>10.2337/dc23-1317</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0001-6004-576X</orcidid><orcidid>https://orcid.org/0000-0002-2406-8419</orcidid></addata></record> |
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| ispartof | Diabetes care, 2024-04, Vol.47 (4), p.660-667 |
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| language | eng |
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| source | MEDLINE; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
| subjects | Blood Glucose Blood Glucose Self-Monitoring Child Child, Preschool Children Closed loops Demographics Demography Diabetes Diabetes mellitus (insulin dependent) Diabetes Mellitus, Type 1 - drug therapy Diabetes Mellitus, Type 1 - epidemiology Glucose monitoring Glycated Hemoglobin Humans Hybrid systems Hypoglycemic Agents - therapeutic use Infusion pumps Insulin Insulin - therapeutic use Insulin Infusion Systems Insulins - therapeutic use Quality control Registries Research design |
| title | Demographic, Clinical, Management, and Outcome Characteristics of 8,004 Young Children With Type 1 Diabetes |
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