Validation of Danish registry-cases of type 1 diabetes in women giving live birth using a clinical cohort as gold standard
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Validation of Danish registry-cases of type 1 diabetes in women giving live birth using a clinical cohort as gold standard. / Gundersen, Tina Wullum; Ebbehoj, Andreas; Knorr, Sine; Jensen, Dorte Møller; Damm, Peter; Løkkegaard, Ellen Christine Leth; Mathiesen, Elisabeth R; Thomsen, Reimar W.; Clausen, Tine Dalsgaard.
I: Endocrinology, Diabetes and Metabolism, Bind 6, Nr. 1, e374, 2023.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Validation of Danish registry-cases of type 1 diabetes in women giving live birth using a clinical cohort as gold standard
AU - Gundersen, Tina Wullum
AU - Ebbehoj, Andreas
AU - Knorr, Sine
AU - Jensen, Dorte Møller
AU - Damm, Peter
AU - Løkkegaard, Ellen Christine Leth
AU - Mathiesen, Elisabeth R
AU - Thomsen, Reimar W.
AU - Clausen, Tine Dalsgaard
N1 - Publisher Copyright: © 2022 The Authors. Endocrinology, Diabetes & Metabolism published by John Wiley & Sons Ltd.
PY - 2023
Y1 - 2023
N2 - Introduction: The aim of this study was to validate type 1 diabetes in women giving live birth in the Danish national registries against a clinical cohort of confirmed cases (the Danish Diabetes Birth Registry [DDBR] cohort). Methods: National registries including diagnosis codes, redeemed prescriptions and background data were combined. Three main algorithms were constructed to define type 1 diabetes in women giving live birth: (1) Any diabetes diagnosis registered before delivery and before age of 30, (2) a specific type 1 diabetes diagnosis registered before delivery regardless of maternal age and (3) a ‘preexisting type 1 diabetes in pregnancy’ diagnosis registered before delivery. In additional sub-algorithms, we added information on anti-diabetic medicine and gestational diabetes diagnosis. We calculated positive predictive value (PPV) and completeness using the DDBR cohort as gold standard. Since DDBR included between 75 and 93% of women with confirmed type 1 diabetes giving live birth, we used quantitative bias analysis to assess the potential impact of missing data on PPV and completeness. Results: Main algorithm 2 had the highest PPV (77.4%) and shared the highest completeness (92.4%) with main algorithm 1. Information on anti-diabetic medicine and gestational diabetes increased PPV, on expense of completeness. All algorithms varied with PPV between 65.7 and 87.6% and completeness between 73.6 and 92.4%. The quantitative bias analysis indicated that PPV was underestimated, and completeness overestimated for all algorithms. For algorithm 2, corrected PPV was between 82.1 and 94.6% and corrected completeness between 84.7 and 91.2%. Conclusions: The Danish national registries can identify type 1 diabetes in women giving live birth with a reasonably high accuracy. The registries are a valuable source for future comparative outcome studies and may also be suitable for monitoring prevalence and incidence of type 1 diabetes in women giving live birth.
AB - Introduction: The aim of this study was to validate type 1 diabetes in women giving live birth in the Danish national registries against a clinical cohort of confirmed cases (the Danish Diabetes Birth Registry [DDBR] cohort). Methods: National registries including diagnosis codes, redeemed prescriptions and background data were combined. Three main algorithms were constructed to define type 1 diabetes in women giving live birth: (1) Any diabetes diagnosis registered before delivery and before age of 30, (2) a specific type 1 diabetes diagnosis registered before delivery regardless of maternal age and (3) a ‘preexisting type 1 diabetes in pregnancy’ diagnosis registered before delivery. In additional sub-algorithms, we added information on anti-diabetic medicine and gestational diabetes diagnosis. We calculated positive predictive value (PPV) and completeness using the DDBR cohort as gold standard. Since DDBR included between 75 and 93% of women with confirmed type 1 diabetes giving live birth, we used quantitative bias analysis to assess the potential impact of missing data on PPV and completeness. Results: Main algorithm 2 had the highest PPV (77.4%) and shared the highest completeness (92.4%) with main algorithm 1. Information on anti-diabetic medicine and gestational diabetes increased PPV, on expense of completeness. All algorithms varied with PPV between 65.7 and 87.6% and completeness between 73.6 and 92.4%. The quantitative bias analysis indicated that PPV was underestimated, and completeness overestimated for all algorithms. For algorithm 2, corrected PPV was between 82.1 and 94.6% and corrected completeness between 84.7 and 91.2%. Conclusions: The Danish national registries can identify type 1 diabetes in women giving live birth with a reasonably high accuracy. The registries are a valuable source for future comparative outcome studies and may also be suitable for monitoring prevalence and incidence of type 1 diabetes in women giving live birth.
KW - case-identification
KW - diabetes mellitus
KW - pregnancy
U2 - 10.1002/edm2.374
DO - 10.1002/edm2.374
M3 - Journal article
C2 - 36412090
AN - SCOPUS:85143223218
VL - 6
JO - Endocrinology, Diabetes and Metabolism
JF - Endocrinology, Diabetes and Metabolism
SN - 2398-9238
IS - 1
M1 - e374
ER -
ID: 334265837