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      Cluster Analysis: A New Approach for Identification of Underlying Risk Factors and Demographic Features of First Trimester Pregnancy Women

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          Abstract

          Thyroid pathology is reported internationally in 5–10% of all pregnancies. The overall aim of this research was to determine the prevalence of hypothyroidism and risk factors during the first trimester screening in a Mexican patients sample. We included the records of 306 patients who attended a prenatal control consultation between January 2016 and December 2017 at the Women’s Institute in Monterrey, Mexico. The studied sample had homogeneous demographic characteristics in terms of age, weight, height, BMI (body mass index) and number of pregnancies. The presence of at least one of the risk factors for thyroid disease was observed in 39.2% of the sample. Two and three clusters were identified, in which patients varied considerably among risk factors, symptoms and pregnancy complications. Compared to Cluster 0, one or more symptoms or signs of hypothyroidism occurred, while Cluster 1 was characterized by healthier patients. When three clusters were used, Cluster 2 had a higher TSH (thyroid stimulating hormone) value and pregnancy complications. There were no significant differences in perinatal variables. In addition, high TSH levels in first trimester pregnancy are characterized by pregnancy complications and decreased newborn weight. Our findings underline the high degree of disease heterogeneity with existing pregnant hypothyroid patients and the need to improve the phenotyping of the syndrome in the Mexican population.

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          Management of thyroid dysfunction during pregnancy and postpartum: an Endocrine Society clinical practice guideline.

          The aim was to update the guidelines for the management of thyroid dysfunction during pregnancy and postpartum published previously in 2007. A summary of changes between the 2007 and 2012 version is identified in the Supplemental Data (published on The Endocrine Society's Journals Online web site at http://jcem.endojournals.org). This evidence-based guideline was developed according to the U.S. Preventive Service Task Force, grading items level A, B, C, D, or I, on the basis of the strength of evidence and magnitude of net benefit (benefits minus harms) as well as the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system to describe both the strength of recommendations and the quality of evidence. The guideline was developed through a series of e-mails, conference calls, and one face-to-face meeting. An initial draft was prepared by the Task Force, with the help of a medical writer, and reviewed and commented on by members of The Endocrine Society, Asia and Oceania Thyroid Association, and the Latin American Thyroid Society. A second draft was reviewed and approved by The Endocrine Society Council. At each stage of review, the Task Force received written comments and incorporated substantive changes. Practice guidelines are presented for diagnosis and treatment of patients with thyroid-related medical issues just before and during pregnancy and in the postpartum interval. These include evidence-based approaches to assessing the cause of the condition, treating it, and managing hypothyroidism, hyperthyroidism, gestational hyperthyroidism, thyroid autoimmunity, thyroid tumors, iodine nutrition, postpartum thyroiditis, and screening for thyroid disease. Indications and side effects of therapeutic agents used in treatment are also presented.
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            Subclinical hypothyroidism and pregnancy outcomes.

            Clinical thyroid dysfunction has been associated with pregnancy complications such as hypertension, preterm birth, low birth weight, placental abruption, and fetal death. The relationship between subclinical hypothyroidism and pregnancy outcomes has not been well studied. We undertook this prospective thyroid screening study to evaluate pregnancy outcomes in women with elevated thyrotropin (thyroid-stimulating hormone, TSH) and normal free thyroxine levels. All women who presented to Parkland Hospital for prenatal care between November 1, 2000, and April 14, 2003, had thyroid screening using a chemiluminescent TSH assay. Women with TSH values at or above the 97.5th percentile for gestational age at screening and with free thyroxine more than 0.680 ng/dL were retrospectively identified with subclinical hypothyroidism. Pregnancy outcomes were compared with those in pregnant women with normal TSH values between the 5th and 95th percentiles. A total of 25,756 women underwent thyroid screening and were delivered of a singleton infant. There were 17,298 (67%) women enrolled for prenatal care at 20 weeks of gestation or less, and 404 (2.3%) of these were considered to have subclinical hypothyroidism. Pregnancies in women with subclinical hypothyroidism were 3 times more likely to be complicated by placental abruption (relative risk 3.0, 95% confidence interval 1.1-8.2). Preterm birth, defined as delivery at or before 34 weeks of gestation, was almost 2-fold higher in women with subclinical hypothyroidism (relative risk, 1.8, 95% confidence interval 1.1-2.9). We speculate that the previously reported reduction in intelligence quotient of offspring of women with subclinical hypothyroidism may be related to the effects of prematurity. II-2.
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              Disease progression and treatment response in data-driven subgroups of type 2 diabetes compared with models based on simple clinical features: an analysis using clinical trial data

              Summary Background Research using data-driven cluster analysis has proposed five subgroups of diabetes with differences in diabetes progression and risk of complications. We aimed to compare the clinical utility of this subgroup-based approach for predicting patient outcomes with an alternative strategy of developing models for each outcome using simple patient characteristics. Methods We identified five clusters in the ADOPT trial (n=4351) using the same data-driven cluster analysis as reported by Ahlqvist and colleagues. Differences between clusters in glycaemic and renal progression were investigated and contrasted with stratification using simple continuous clinical features (age at diagnosis for glycaemic progression and baseline renal function for renal progression). We compared the effectiveness of a strategy of selecting glucose-lowering therapy using clusters with one combining simple clinical features (sex, BMI, age at diagnosis, baseline HbA1c) in an independent trial cohort (RECORD [n=4447]). Findings Clusters identified in trial data were similar to those described in the original study by Ahlqvist and colleagues. Clusters showed differences in glycaemic progression, but a model using age at diagnosis alone explained a similar amount of variation in progression. We found differences in incidence of chronic kidney disease between clusters; however, estimated glomerular filtration rate at baseline was a better predictor of time to chronic kidney disease. Clusters differed in glycaemic response, with a particular benefit for thiazolidinediones in patients in the severe insulin-resistant diabetes cluster and for sulfonylureas in patients in the mild age-related diabetes cluster. However, simple clinical features outperformed clusters to select therapy for individual patients. Interpretation The proposed data-driven clusters differ in diabetes progression and treatment response, but models that are based on simple continuous clinical features are more useful to stratify patients. This finding suggests that precision medicine in type 2 diabetes is likely to have most clinical utility if it is based on an approach of using specific phenotypic measures to predict specific outcomes, rather than assigning patients to subgroups. Funding UK Medical Research Council.
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                Author and article information

                Journal
                J Clin Med
                J Clin Med
                jcm
                Journal of Clinical Medicine
                MDPI
                2077-0383
                15 July 2020
                July 2020
                : 9
                : 7
                : 2247
                Affiliations
                [1 ]NIT Lab, Univ. Bourgogne Franche-Comte, UTBM, F-90010 Belfort, France; amir.hajjam@ 123456utbm.fr
                [2 ]Monterrey Institute of Technology and Higher Education, Monterrey 64700, Mexico; edelmiro13@ 123456gmail.com (E.G.-P.); agustin.carvajal@ 123456itesm.mx (A.C.R.); dracelinasalas@ 123456gmail.com (C.S.-C.)
                [3 ]Service de Médecine Interne, Diabète et Maladies Métaboliques de la Clinique Médicale B, CHRU de Strasbourg, 67091 Strasbourg, France; emmanuel.andres@ 123456chru-strasbourg.fr
                Author notes
                Author information
                https://orcid.org/0000-0002-7914-7616
                https://orcid.org/0000-0002-8470-806X
                Article
                jcm-09-02247
                10.3390/jcm9072247
                7408845
                32679845
                35291df9-f07a-4701-9239-43ca95753e98
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 12 June 2020
                : 13 July 2020
                Categories
                Article

                thyroid pathology,k-means,first trimester pregnancy,pregnancy complications,pregnancy risk factors

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