Identification of predictive factors of diabetic ketoacidosis in type 1 diabetes using a subgroup discovery algorithm
Abstract: Aim
To identify predictive factors for diabetic ketoacidosis (DKA) by retrospective analysis of registry data and the use of a subgroup discovery algorithm.
Materials and Methods
Data from adults and children with type 1 diabetes and more than two diabetes-related visits were analysed from the Diabetes Prospective Follow-up Registry. Q-Finder, a supervised non-parametric proprietary subgroup discovery algorithm, was used to identify subgroups with clinical characteristics associated with increased DKA risk. DKA was defined as pH less than 7.3 during a hospitalization event.
Results
Data for 108 223 adults and children, of whom 5609 (5.2%) had DKA, were studied. Q-Finder analysis identified 11 profiles associated with an increased risk of DKA: low body mass index standard deviation score; DKA at diagnosis; age 6-10 years; age 11-15 years; an HbA1c of 8.87% or higher (≥ 73 mmol/mol); no fast-acting insulin intake; age younger than 15 years and not using a continuous glucose monitoring system; physician diagnosis of nephrotic kidney disease; severe hypoglycaemia; hypoglycaemic coma; and autoimmune thyroiditis. Risk of DKA increased with the number of risk profiles matching patients’ characteristics.
Conclusions
Q-Finder confirmed common risk profiles identified by conventional statistical methods and allowed the generation of new profiles that may help predict patients with type 1 diabetes who are at a greater risk of experiencing DKA
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
Diabetes, obesity and metabolism. - 25, 7 (2023) , 1823-1829, ISSN: 1463-1326
- Klassifikation
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Medizin, Gesundheit
- Ereignis
-
Veröffentlichung
- (wo)
-
Freiburg
- (wer)
-
Universität
- (wann)
-
2023
- Urheber
-
Ibald‐Mulli, Angela
Seufert, Jochen
Grimsmann, Julia M.
Laimer, Markus
Bramlage, Peter
Civet, Alexandre
Blanchon, Margot
Gosset, Simon
Templier, Alexandre
Paar, W. Dieter
Zhou, Fang Liz
Lanzinger, Stefanie
- DOI
-
10.1111/dom.15039
- URN
-
urn:nbn:de:bsz:25-freidok-2343946
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
25.03.2025, 13:42 MEZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Ibald‐Mulli, Angela
- Seufert, Jochen
- Grimsmann, Julia M.
- Laimer, Markus
- Bramlage, Peter
- Civet, Alexandre
- Blanchon, Margot
- Gosset, Simon
- Templier, Alexandre
- Paar, W. Dieter
- Zhou, Fang Liz
- Lanzinger, Stefanie
- Universität
Entstanden
- 2023
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