RESUMO
INTRODUCTION: Preeclampsia and gestational diabetes mellitus share risk factors such as obesity and increased maternal age, which have become more prevalent in recent decades. We examined changes in the prevalence of preeclampsia and gestational diabetes between 2005 and 2018 in Denmark and Alberta, Canada, and investigated whether the observed trends can be explained by changes in maternal age, parity, multiple pregnancy, comorbidity, and body mass index (BMI) over time. MATERIAL AND METHODS: This study was a register-based cohort study conducted using data from the Danish National Health Registers and the provincial health registers of Alberta, Canada. We included in the study cohort all pregnancies in 2005-2018 resulting in live-born infants and used binomial regression to estimate mean annual increases in the prevalence of preeclampsia and gestational diabetes in the two populations across the study period, adjusted for maternal characteristics. RESULTS: The study cohorts included 846 127 (Denmark) and 706 728 (Alberta) pregnancies. The prevalence of preeclampsia increased over the study period in Denmark (2.5% to 2.9%) and Alberta (1.7% to 2.5%), with mean annual increases of 0.03 (95% confidence interval [CI] 0.02-0.04) and 0.06 (95% CI 0.05-0.07) percentage points, respectively. The prevalence of gestational diabetes also increased in Denmark (1.9% to 4.6%) and Alberta (3.9% to 9.2%), with average annual increases of 0.20 (95% CI 0.19-0.21) and 0.44 (95% CI 0.42-0.45) percentage points. Changes in the distributions of maternal age and BMI contributed to increases in the prevalence of both conditions but could not explain them entirely. CONCLUSIONS: The prevalence of both preeclampsia and gestational diabetes increased significantly from 2005 to 2018, which portends future increases in chronic disease rates among affected women. Increasing demand for long-term follow up and care will amplify the existing pressure on healthcare systems.
Assuntos
Diabetes Gestacional , Pré-Eclâmpsia , Gravidez , Feminino , Humanos , Pré-Eclâmpsia/epidemiologia , Diabetes Gestacional/epidemiologia , Estudos de Coortes , Alberta/epidemiologia , Fatores de Risco , Dinamarca/epidemiologiaRESUMO
OBJECTIVE: The effect of expanded obstetrical ultrasound cardiac views on the diagnosis of fetal congenital heart disease (CHD) has not been fully examined at a population level. We hypothesized there has been a significant increase in the prenatal detection of CHD in Alberta, particularly for CHD associated with cardiac outflow tract and 3-vessel view abnormalities. METHODS: Using provincial databases, we retrospectively identified all fetuses and infants diagnosed between 2008 and 2018 in Alberta with major CHD requiring surgical intervention within the first postnatal year. We evaluated individual lesions and categorized CHDs into the following groups based on the obstetrical ultrasound cardiac views required for detection: (1) 4-chamber view (e.g., hypoplastic left heart syndrome, Ebstein's anomaly, single ventricle); (2) outflow tract view (e.g., tetralogy of Fallot, d-transposition, truncus arteriosus); (3) 3-vessel or other non-standard cardiac views (e.g., coarctation, anomalous pulmonary veins); and (4) isolated ventricular septal defects using any view. RESULTS: Of 1405 cases of major CHD, 814 (58%) were prenatally diagnosed. Over the study period, prenatal detection increased in all groups, with the greatest increase observed for groups 1 and 2 (75%-88%; P = 0.008 and 56%-79%; P = 0.0002, respectively). Although rates of prenatal detection also increased for groups 3 and 4 (27%-43%; P = 0.007 and 13%-30%; P = 0.04, respectively), fewer than half of the cases in each group were detected prenatally, even in more recent years. CONCLUSIONS: While rates of prenatal detection of CHD have significantly improved during the past decade, many defects with abnormal 3-vessel and non-standard views, as well as isolated ventricular septal defects, still go undetected.
Assuntos
Doenças Fetais , Cardiopatias Congênitas , Comunicação Interventricular , Alberta/epidemiologia , Feminino , Doenças Fetais/epidemiologia , Coração Fetal/anormalidades , Coração Fetal/diagnóstico por imagem , Cardiopatias Congênitas/diagnóstico por imagem , Cardiopatias Congênitas/epidemiologia , Humanos , Lactente , Gravidez , Estudos Retrospectivos , Ultrassonografia Pré-NatalRESUMO
OBJECTIVE: Our aim in this study was to implement a newly validated algorithm to identify pregnant women with type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM), and gestational diabetes mellitus (GDM), and to identify temporal trends in rates over the last decade. We also compared obstetric and neonatal outcomes of pregnancies with and without diabetes mellitus (DM). METHODS: Among women with live births between 2005 and 2018 in Alberta, we calculated yearly rates of T1DM, T2DM, and GDM, overall, and stratified by ethnicity, urban or rural residence, material deprivation score, and maternal age. RESULTS: Between 2005 and 2018, GDM rates increased from 42.3 to 101.8 per 1,000 deliveries (p<0.0001), T2DM rates increased from 2.6 to 6.4 per 1,000 deliveries (p<0.0001), whereas T1DM remained constant at 3.0 per 1,000 deliveries each year (p=0.4301). Higher GDM and T2DM rates were observed among Chinese and South Asian women, respectively, and among women who were materially deprived and living in urban areas. Women with T2DM were older and had the highest rates of pre-existing hypertension (16%). In contrast, women with T1DM were younger and had the highest rates of gestational hypertension (12%), pre-eclampsia (12%), and cesarean section deliveries (62%). Children of women with T1DM had the highest rates of large for gestational age (46%), neonatal hypoglycemia (41.1%), respiratory distress syndrome (7.7%), and jaundice (29.3%). CONCLUSIONS: Diabetes-in-pregnancy rates have more than doubled over the last decade, driven primarily by increases in GDM and T2DM. These trends may have significant implications for the future health of mothers and children in Alberta.
Assuntos
Diabetes Mellitus Tipo 1 , Diabetes Mellitus Tipo 2 , Diabetes Gestacional , Hipertensão Induzida pela Gravidez , Recém-Nascido , Criança , Gravidez , Feminino , Humanos , Diabetes Gestacional/epidemiologia , Diabetes Mellitus Tipo 1/epidemiologia , Diabetes Mellitus Tipo 2/epidemiologia , Cesárea , Etnicidade , População Rural , Resultado da Gravidez/epidemiologia , Estudos RetrospectivosRESUMO
OBJECTIVE: Our aim in this study was to evaluate the accuracy of alternative algorithms for identifying pre-existing type 1 or 2 diabetes (T1DM or T2DM) and gestational diabetes mellitus (GDM) in pregnant women. METHODS: Data from a clinical registry of pregnant women presenting to an Edmonton diabetes clinic between 2002 and 2009 were linked and administrative health records. Three algorithms for identifying women with T1DM, T2DM, and GDM based on International Classification of Diseases---tenth revision (ICD-10) codes were assessed: delivery hospitalization records (Algorithm #1), outpatient clinics during pregnancy (Algorithm #2), and delivery hospitalization plus outpatient clinics during pregnancy (Algorithm #3). In a subset of women with clinic visits between 2005 and 2009, we examined the performance of an additional Algorithm #4 based on Algorithm #3 plus outpatient clinics in the 2 years before pregnancy. Using the diabetes clinical registry as the "gold standard," we calculated true positive rates and agreement levels for the algorithms. RESULTS: The clinical registry included data on 928 pregnancies, of which 90 were T1DM, 89 were T2DM, and 749 were GDM. Algorithm #3 had the highest true positive rate for the detection of T1DM, T2DM, and GDM of 94%, 72%, and 99.9%, respectively, resulting in an overall agreement of 97% in diagnosis between the administrative databases and the clinical registry. Algorithm #4 did not provide much improvement over Algorithm #3 in overall agreement. CONCLUSIONS: An algorithm based on ICD-10 codes in the delivery hospitalization and outpatient clinic records during pregnancy can be used to accurately identify women with T1DM, T2DM, and GDM.