ABSTRACT
UNLABELLED: Polycystic ovary syndrome (PCOS) is characterized by hyperandrogenism (H), oligo-anovulation (O) and / or polycystic ovaries (P). There is currently little information on perinatal complications. OBJECTIVE: to investigate obstetric and neonatal characteristics of women with PCOS in our population. MATERIAL AND METHODS: we studied 87 pregnant women with PCOS (categorized in four phenotypes according Rotterdam Consensus: A (H + O + P) n = 53; B (H + O) n = 9; C (H + P) n = 16 and D (O + P) n = 9) and 96 without PCOS (control). We analyzed clinical and biochemical features (age, anthropometry hirsutism, acanthosis nigricans, OGTT, insulin, lipid profile, androgen and gonadotropins) during preconception, (weight gain, blood pressure, OGTT) through gestation and occurrence of perinatal complications. RESULTS: we found no differences in age (29.4 ± 4 and 28.7 ± 5 years) and body mass index (28.2 ± 6 and 27.8 ± 6 kg / m2) in both groups; while patients with PCOS had higher waist circumference, blood pressure and acanthosis nigricans versus control. Despite similar weight gain, patients with PCOS had higher percentage of perinatal complications. In the A phenotype RR for perinatal adverse outcomes was 2.37 (95%CI: 1.67-3.36, p <0.001). The HOMA-IR index preconception and fasting glucose during pregnancy were the predictors for these complications (p=0.01). CONCLUSION: patients with PCOS have a higher risk for complications during pregnancy and newborns more frequently have low weight or macrosomy. A careful history can recognize patients with higher perinatal risk to develop complications.
Subject(s)
Fetus , Polycystic Ovary Syndrome/complications , Pregnancy Complications/etiology , Adolescent , Adult , Anthropometry , Case-Control Studies , Female , Fetal Diseases/etiology , Gestational Age , Humans , Infant, Newborn , Infant, Newborn, Diseases/etiology , Phenotype , Polycystic Ovary Syndrome/physiopathology , Pregnancy , Pregnancy Complications/physiopathology , Pregnancy Outcome , Risk Factors , Young AdultABSTRACT
Introducción: Se denominan interacciones farmacológicas (IF) a las relaciones que se establecen entre los fármacos dentro del organismo, que pueden resultar en cambios en la eficacia y seguridad de los mismos, a veces con efectos desfavorables. La polifarmacia genera una inmensa cantidad de combinaciones de drogas que aumenta el riesgo de IF. Este crecimiento es exponencial. Existen softwares que permiten conocer los pares de drogas capaces de generar IF. Estudiamos uno de ellos: Interdrugs® "http://www.medicamentos-rothlin.com.ar/ para conocer su desempeño y utilizarlo para estudiar el riesgo de IF en pacientes ancianos hospitalizados. Materiales y Métodos: Estudio transversal. Se ingresaron pacientes hospitalizados mayores de 65 años. Se consignaron datos demográficos, motivos de ingreso, patologías crónicas y medicación utilizada durante las primeras 24 hs de hospitalización. Las prescripciones se analizaron con el software "Interdrugs® para pesquizar IF. Fueron clasificadas en leves, moderadas y severas. Se estimaron las frecuencias de: motivos de ingreso, drogas prescriptas y severidad de las IF. Se correlacionaron y compararon las frecuencias de IF moderadas a severas con los pacientes sin riesgo de IF o con IF leves. Se utilizaron los programas estadísticos SPSS 17 y EpiDat 3.
ABSTRACT: Introduction: Drug interactions (DI) are the relationships established between drugs inside the body, which can result in changes in the efficacy and safety of themselves, sometimes with adverse effects. Polypharmacy generates an immense amount of drug combinations that makes DI more frequent. There are software that allow to know the pairs of drugs capable of generating DI. We studied: Interdrugs® http://www.medicamentosrothlin.com.ar/" for their performance and use it to study the risk of DI in a group of hospitalized older patients. Materials and Methods: A cross-sectional study. We included patients 65 years old or older admitted to common room in three hospitals at Cordoba.We recorded demographic data, reason for admission, diagnoses of chronic diseases and medication used during the first 24 hours of hospitalization. The prescriptions were analyzed with the software "Interdrugs®" to search for DI. These were classified as mild, moderate, or severe. Frequencies were estimated for admission reasons, drugs prescription and severity of DI. Were correlated and compared moderate to severe DI frequencies with patients who had no risk of DI or mild DI. We used SPSS 17 and EpiDat 3 for statistical analysis.
Subject(s)
Humans , Male , Adult , Female , Aged , Aged, 80 and over , Aged , Electronic Data Processing , Databases, Pharmaceutical/trends , Drug Interactions , Information Management/trends , Hospitalization , Inpatients , ArgentinaABSTRACT
Introducción: Se denominan interacciones farmacológicas (IF) a las relaciones que se establecen entre los fármacos dentro del organismo, que pueden resultar en cambios en la eficacia y seguridad de los mismos, a veces con efectos desfavorables. La polifarmacia genera una inmensa cantidad de combinaciones de drogas que aumenta el riesgo de IF. Este crecimiento es exponencial. Existen softwares que permiten conocer los pares de drogas capaces de generar IF. Estudiamos uno de ellos: Interdrugs« "http://www.medicamentos-rothlin.com.ar/ö para conocer su desempeño y utilizarlo para estudiar el riesgo de IF en pacientes ancianos hospitalizados. Materiales y Métodos: Estudio transversal. Se ingresaron pacientes hospitalizados mayores de 65 años. Se consignaron datos demográficos, motivos de ingreso, patologías crónicas y medicación utilizada durante las primeras 24 hs de hospitalización. Las prescripciones se analizaron con el software "Interdrugs«ö para pesquizar IF. Fueron clasificadas en leves, moderadas y severas. Se estimaron las frecuencias de: motivos de ingreso, drogas prescriptas y severidad de las IF. Se correlacionaron y compararon las frecuencias de IF moderadas a severas con los pacientes sin riesgo de IF o con IF leves. Se utilizaron los programas estadísticos SPSS 17 y EpiDat 3.(AU)
ABSTRACT: Introduction: Drug interactions (DI) are the relationships established between drugs inside the body, which can result in changes in the efficacy and safety of themselves, sometimes with adverse effects. Polypharmacy generates an immense amount of drug combinations that makes DI more frequent. There are software that allow to know the pairs of drugs capable of generating DI. We studied: Interdrugs« http://www.medicamentosrothlin.com.ar/" for their performance and use it to study the risk of DI in a group of hospitalized older patients. Materials and Methods: A cross-sectional study. We included patients 65 years old or older admitted to common room in three hospitals at Cordoba.We recorded demographic data, reason for admission, diagnoses of chronic diseases and medication used during the first 24 hours of hospitalization. The prescriptions were analyzed with the software "Interdrugs«" to search for DI. These were classified as mild, moderate, or severe. Frequencies were estimated for admission reasons, drugs prescription and severity of DI. Were correlated and compared moderate to severe DI frequencies with patients who had no risk of DI or mild DI. We used SPSS 17 and EpiDat 3 for statistical analysis.(AU)
Subject(s)
Humans , Male , Adult , Female , Aged , Aged, 80 and over , Drug Interactions , Databases, Pharmaceutical/trends , Information Management/trends , Aged , Hospitalization , Electronic Data Processing , Inpatients , ArgentinaABSTRACT
OBJECTIVE: To provide a framework for the clinical presentation, evolution, treatment, and outcome of the unusual association between primary adrenal insufficiency (AI) during pregnancy and life-threatening complications for the mother and fetus. DESIGN: Case reports. SETTING: Pregnant women with AI treated in the Endocrine and Diabetes Department, Hospital Universitario de Maternidad y Neonatología, Córdoba, Argentina. PATIENT(S): Three pregnant women with AI. INTERVENTION(S): Review of hospital records. MAIN OUTCOME MEASURE(S): Clinical, laboratory features, treatment, and outcome. RESULT(S): Two women with AI were diagnosed before conception, and one was diagnosed during gestation. Two of the cases were associated with other autoimmune diseases. Two newborns were born with signs of fetal distress, and one passed away hours later. Poor outcome was related to low compliance with treatment. CONCLUSION(S): AI is often overlooked during pregnancy because of its rarity and pregnancy-like symptoms. Nevertheless, other autoimmune diseases, hyponatremia, metabolic acidosis, nausea and vomiting, and orthostatic hypotension that does not improve with usual treatment or persists after first trimester should evoke a diagnosis of AI. If diagnosis and treatment are properly managed, pregnancy, labor, and delivery may occur without complications. If not, AI is associated with high maternal and fetal morbidity and mortality.
