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Development of a clinical calculator to aid the identification of MODY in pediatric patients at the time of diabetes diagnosis.
Shields, Beverley M; Carlsson, Annelie; Patel, Kashyap; Knupp, Julieanne; Kaur, Akaal; Johnston, Des; Colclough, Kevin; Larsson, Helena Elding; Forsander, Gun; Samuelsson, Ulf; Hattersley, Andrew; Ludvigsson, Johnny.
Afiliación
  • Shields BM; The Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK. B.Shields@exeter.ac.uk.
  • Carlsson A; Skånes University Hospital, Lund, Sweden.
  • Patel K; The Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.
  • Knupp J; The Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.
  • Kaur A; Faculty of Medicine, Imperial College London, London, UK.
  • Johnston D; Faculty of Medicine, Imperial College London, London, UK.
  • Colclough K; Exeter Genomics Laboratory, The Royal Devon University Healthcare NHS Foundation Trust, Exeter, UK.
  • Larsson HE; Department of Clinical Sciences Malmö, Lund University, Lund, Sweden.
  • Forsander G; Department of Pediatrics, Skånes University Hospital, Malmö, Sweden.
  • Samuelsson U; Department of Paediatrics, Institute for Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
  • Hattersley A; Region Västra Götaland, Department of Paediatrics, Sahlgrenska University Hospital, Queen Silvia Children's Hospital, Gothenburg, Sweden.
  • Ludvigsson J; Crown Princess Victoria Children's Hospital and Division of Pediatrics, Linköping University, Linköping, Sweden.
Sci Rep ; 14(1): 10589, 2024 05 08.
Article en En | MEDLINE | ID: mdl-38719926
ABSTRACT
Maturity Onset Diabetes of the Young (MODY) is a young-onset, monogenic form of diabetes without needing insulin treatment. Diagnostic testing is expensive. To aid decisions on who to test, we aimed to develop a MODY probability calculator for paediatric cases at the time of diabetes diagnosis, when the existing "MODY calculator" cannot be used. Firth logistic regression models were developed on data from 3541 paediatric patients from the Swedish 'Better Diabetes Diagnosis' (BDD) population study (n = 46 (1.3%) MODY (HNF1A, HNF4A, GCK)). Model performance was compared to using islet autoantibody testing. HbA1c, parent with diabetes, and absence of polyuria were significant independent predictors of MODY. The model showed excellent discrimination (c-statistic = 0.963) and calibrated well (Brier score = 0.01). MODY probability > 1.3% (ie. above background prevalence) had similar performance to being negative for all 3 antibodies (positive predictive value (PPV) = 10% v 11% respectively i.e. ~ 1 in 10 positive test rate). Probability > 1.3% and negative for 3 islet autoantibodies narrowed down to 4% of the cohort, and detected 96% of MODY cases (PPV = 31%). This MODY calculator for paediatric patients at time of diabetes diagnosis will help target genetic testing to those most likely to benefit, to get the right diagnosis.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Diabetes Mellitus Tipo 2 Límite: Adolescent / Child / Child, preschool / Female / Humans / Male País/Región como asunto: Europa Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Diabetes Mellitus Tipo 2 Límite: Adolescent / Child / Child, preschool / Female / Humans / Male País/Región como asunto: Europa Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article País de afiliación: Reino Unido
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