ABSTRACT
Background: The prevalence of gestational diabetes (GDM) is increasing along with obesity and gestational age. This prevalence varies in populations and with different guidelines used for the diagnoses. Aim: To estimate the change in prevalence of GDM and obesity in a period 11 years. Material and Methods: Analysis of pregnancies attended at an obstetrics ward of a general hospital between 2001 and 2018. Those women who were diabetic prior to their pregnancy were excluded from the analysis. Annual crude and adjusted prevalence using direct standardization by age were estimated. Results: We analyzed 33,985 pregnancies. GDM screening was performed in 20,139 (59%), and 1,466 (7%) had GDM. In 2007 the crude and adjusted prevalence of GDM were 4.9 and 5.2%, respectively. The figures in 2018 were 8.8 and 8.5%, respectively, with an annual percentage of change (APC) of 6.9% (p < 0.001). The frequency of obesity also increased with an APC of 4.1% (p < 0.001). In women with GDM the APC of obesity was 4.6% (p < 0.001). There was also an increase in the frequency of screening, with a joinpoint in 2011. The APC of screening in the periods 2007-2011 and 2011-2018 were 16.6 and 2.9%, respectively (p < 0.001). Conclusions: The prevalence of GDM increased in this period of eleven years along with the prevalence of obesity.
Subject(s)
Female , Humans , Pregnancy , Diabetes, Gestational , Obesity , Prevalence , Risk Factors , Gestational Age , Diabetes, Gestational/epidemiology , Obesity/epidemiologyABSTRACT
Introducción: El objetivo fue estimar la incidencia de diabetes y explorar la mortalidad de pacientes hospitalizados durante el seguimiento posterior al alta, clasificados durante la misma según el comportamiento glucémico como hiperglucemia de estrés (HE) o normoglucemia (NG). Material y métodos: Cohorte retrospectiva de adultos no diabéticos con HE (>140mg/dl y HbA1c<6,5%) o NG (todos los valores de glucemia <=140mg/dl). Resultados: Se identificaron 3981 pacientes con NG y 884 con HE. Durante el período de observación (mediana de seguimiento de 1,83 años), hubo un total de 255 casos de diabetes y 831 muertes. La incidencia acumulada de diabetes al año fue de 1,59% (IC95%:1,23-2,06) en NG y 7,39% (IC95% 5,70-9,56) en HE. HE se asoció significativamente con la incidencia de diabetes (HR crudo 1,33; IC95% 1,13-1,73; p 0,025), incluso después del ajuste por edad y sexo (HR ajustado 1,38; IC95% 1,06-1,78; p 0,014). La incidencia de mortalidad al año fue 10,07% (IC95%:9,18-11,05) en NG y 13,24% (IC95%:11,17-15,65) en HE. El sub hazard ratio de desarrollar diabetes considerando la muerte como evento competitivo fue 1,41 (IC95% 1,29-1,53; p<0,001). Conclusiones: La HE es un factor de riesgo para desarrollar diabetes. No hubo diferencias de mortalidad en el seguimiento, pero la muerte parece comportarse como un evento competitivo al desarrollo de diabetes en esta población
Introduction: The study objective was to estimate during post-discharge follow-up the incidence of diabetes and to ascertain mortality in hospitalized patients, classified during follow-up as having stress hyperglycemia (SH) or normoglycemia (NG) based on blood glucose levels. Material and methods: A retrospective cohort of non-diabetic adults with SH (> 140mg/dl and HbA1c <6.5%) or NG (all blood glucose values ≤ 140mg/dl) was used. Results: There were 3981 patients with NG and 884 with SH. During the observation period (median follow-up of 1.83 years), there were 255 cases of diabetes and 831 deaths. The cumulative incidence of diabetes per year was 1.59% (95% CI: 1.23-2.06) in patients with NG and 7.39% (95% CI: 5.70-9.56) in those with SH. SH was significantly associated to diabetes (crude HR 1.33, 95% CI: 1.13-1.73, p .025), even after adjusting for age and sex (adjusted HR 1.38, 95% CI 1.06-1.78, p .014). The mortality rate at one year was 10.07% (95% CI: 9.18-11.05) in NG patients and 13.24% (95% CI: 11.17-15.65) in SH patients. The sub-hazard ratio of developing diabetes considering death as a competitive event was 1.41 (95% CI 1.29-1.53, p <.001). Conclusions: SH is a risk factor for diabetes. There were no differences in mortality during follow-up, but death appears to be a competitive event in development of diabetes in this population
Subject(s)
Humans , Female , Aged , Aged, 80 and over , Male , Hyperglycemia/epidemiology , Hospitalization , Diabetes Mellitus/etiology , Stress, Psychological/pathology , Argentina , Hyperglycemia/physiopathology , Hyperglycemia/mortality , Incidence , Mortality , Cohort Studies , Retrospective Studies , Risk FactorsABSTRACT
Resumen Objetivo Evaluar la asociación entre las diferencias de mediciones de 2 ECG separados en el tiempo, con el desarrollo de fibrilación auricular (FA). Método Cohorte retrospectiva de 9,975 pacientes adultos, afiliados a la prepaga del Hospital Italiano de Buenos Aires, Argentina, con realización de al menos 2 ECG sinusales digitales entre 2006-2011. Se siguieron clínicamente para la detección de FA. Todas las mediciones electrocardiográficas y los deltas (diferencias entre los 2 ECG) fueron estandarizadas. Se estimaron los hazard ratio para desarrollo de FA, para cada delta de los distintos componentes electrocardiográficos utilizando un modelo de regresión de Cox. Resultados Durante una mediana de seguimiento de 3,5 años se detectaron 189 episodios de FA. El delta FC, delta intervalo ST y delta amplitud onda P se asociaron significativamente a FA. Ajustado por características clínicas y mediciones de ECG basal, el hazard ratio ajustado para FA fue 0.86 (IC95%: 0.75-0.98, p = 0.024) para delta FC; 1.12 (IC95%0.98-1.27, p = 0.082) para delta intervalo ST; y 1.21 (IC95%: 1.05-1.38, p = 0.006) para delta amplitud onda P. Conclusiones Las diferencias FC y amplitud onda P, entre mediciones de ECG, predicen FA en forma independiente de características clínicas y mediciones de ECG basal.
Abstract Objetive To evaluate the association between delta variations in the parameters of 2 sinusal ECG with atrial fibrillation (AF) onset. Method Retrospective cohort of 9,975 adult patients and members of the prepaid system at Hospital Italiano de Buenos Aires from Argentina, who had at least 2 sinusal ECG between 2006 and 2011. Population was followed up for detection of AF. All measurements and electrocardiographic deltas (differences between the 2 ECG) were standardized. Hazard ratio (HR) was estimated for the development of AF for each delta of the different ECG parameters using a Cox regression model. Results During a median follow up of 3.5 years, 189 patients (1.89%) developed AF. Heart rate delta, ST interval delta and P wave amplitude were predictors of AF. Hazard ratio Adjusted for clinical characteristics and ECGbasal values was 0,86 (CI95%: 0.75-0.98, p = 0.024) for heart rate delta, 1.12 (CI95%: 0.98-1.27, p = 0.082) for ST interval delta and 1.21 (CI95%: 1.05-1.38, p = 0.006) for P wave amplitude delta. Conclusion Differences of heart rate and P wave amplitude between ECG's measurements may predict AF, independently of clinical features and ECGbasal values.