Acute adrenal insufficiency (AI) is a life-threatening condition. While Addison's disease (AD) is rare, in developing countries, tuberculosis (TB) still remains as the primary cause in 7 to 20% of cases. Urinary TB is also the third most common form of extrapulmonary disease. We report a case of 37-year-old male who presented with weakness, anorexia, weight loss, dysuria, flank pain and low grade fever. Examination revealed hypotension, hyperpigmentation, hyponatremia, hypoglycemia and low serum cortisol. He was diagnosed to have adrenal crisis due to Addison's disease and extrapulmonary TB manifesting as urinary tract infection (UTI). He was treated with corticosteroids and anti-TB medications. Urologic reconstructive surgery was subsequently planned..
Abstract. Bayesian statistics proposes an approach that is very flexible in the number of samples and distribution of data. Bayesian Mixture Model (BMM) is a Bayesian approach for multimodal models. Diabetes Mellitus (DM) is more commonly known in the Indonesian community as sweet pee. This disease is one type of chronic non-communicable diseases but it is very dangerous to humans because of the effects of other diseases complications caused. WHO reports in 2013 showed DM disease was ranked 6th in the world as the leading causes of human death. In Indonesia, DM disease continues to increase over time. These research would be studied patterns and would be built the BMM models of the DM data through simulation studies where the simulation data built on cases of blood sugar levels of DM patients in RSUD Saiful Anwar Malang. The results have been successfully demonstrated pattern of distribution of the DM data which has a normal mixture distribution. The BMM models have succeed to accommodate the real condition of the DM data based on the data driven concept. IntroductionWhen a set of real data observed have a very small amount and a multimodal distribution then it is necessary need specially handling. The Bayesian statistics proposes an approach that is very flexible in the number of samples and distribution of data. These approach is based directly on the posterior distribution of the data. Therefore Bayesian approach can accommodate the real condition of the data based on the data driven concept and [5]). Bayesian Mixture Model (BMM) is one model that uses a Bayesian approach for multimodal models and its parameter models is seen as random variables in the model parameter space [6].Various studies have previously been carried out by BMM modeling. The modeling of BMM for the DM data in Surabaya is the research that has been done by [7] and the research of [8] has been conducted for the DM data in Malang by BMMA modeling. Some of the BMM research in the other field, among others [9] and [10]. Modeling of cases is very important in order to know the exact model and can be used for decision making in accordance with the cases observed [11].
Prevalensi wanita dengan diagnosis Diabetes Mellitus (DM) meningkat sepanjang tahunnya termasuk dalam kehamilan. Kami laporkan kasus seorang wanita 36 tahun dengan persalinan anak pertama yang dikonsultasikan dengan peningkatan gula darah sesudah persalinan. Dari hasil anamnesa dan pemeriksaan fisik tidak didapatkan riwayat DM pada pasien dan keluarga yang dapat menjadi penyebab keterlambatan diagnosis DM pada kehamilan. Anamnesis, observasi dan hasil pemeriksaan laboratorium mengindikasikan potensi DM yang dimulai sebelum kehamilan namun tidak dikonfirmasi melalui skrining pemeriksaan gula darah pada kehamilan. Bayi yang dilahirkan mempunyai berat badan normal namun sempat mengalami hipoglikemia. Pasien diberikan terapi injeksi insulin basal dimulai pada dosis 6 iu dan dinaikkan bertahap menjadi 8 iu dan 10 iu, sesuai dengan hasil evaluasi hingga tujuan terapi tercapai. Kasus ini menunjukkan pentingnya penggalian riwayat dengan teliti dan skrining DM dalam kehamilan pada mereka yang berisiko untuk mencegah komplikasi pada janin maupun ibu. Kata Kunci: Diabetes mellitus, kehamilan, komplikasiÂ
A hazard to global health is being posed by diabetes mellitus (DM). Macrovascular and microvascular abnormalities in blood vessels are one type of DM complication that might happen. In most cases, blood arteries, the brain, and the heart are affected by macrovascular problems. Obesity is well-known to have a substantial significant risk factor for coronary heart disease on its own (CHD). As a result, many persons with DM have a 2 to 4 times higher risk of dying from CHD than those without DM. In fact, different goal parameters (such glucose management, blood pressure, cholesterol status, or body composition) can improve with exercise training to varying degrees in each patient; here is where cardiovascular rehabilitation can help. To attain the best results, the type and intensity of exercise training must be tailored to the unique characteristics of each patient. The clinician's challenge is to teach the patient the skills necessary to maintain lifestyle modifications and to explain the relationship between exercise and blood sugar, BG goal ranges, and the types and amounts of activity that can be done safely.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.