Comparison of SWAN and WISE Menopausal Status Classification Algorithms.
BACKGROUND: Classification of menopausal status is important for epidemiological and clinical studies as well as for clinicians treating midlife women. Most epidemiological studies, including the Study of Women's Health Across the Nation (SWAN), classify women based on self-reported bleeding history...
| Publicado en: | Journal of Women's Health (15409996) Vol. 15; no. 10; pp. 1184 - 1195 |
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| Autores principales: | , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Mary Ann Liebert, Inc.
Dec2006
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105879287&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105879287 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15409996 Q13 jtl: Journal of Women's Health (15409996) issn: 15409996 maglogo: N pubinfo: dt: Dec2006 vid: 15 iid: 10 pid: 1365 pub: Mary Ann Liebert, Inc. place: New Rochelle, New York artinfo: ui: 105879287 23555607 23555607 10.1089/jwh.2006.15.1184 NLM17199459 105879287 ppf: 1184 ppct: 11 formats: tig: atl: Comparison of SWAN and WISE Menopausal Status Classification Algorithms. aug: au: Johnston JM Colvin A Johnson BD Santoro N Harlow SD Merz CNB Sutton-Tyrrell K sug: subj: Classification Algorithms Health Status Menopause Women's Health Adult Female Middle Age Multicenter Studies Prospective Studies United States Human Adult: 19-44 years Middle Aged: 45-64 years Female ab: BACKGROUND: Classification of menopausal status is important for epidemiological and clinical studies as well as for clinicians treating midlife women. Most epidemiological studies, including the Study of Women's Health Across the Nation (SWAN), classify women based on self-reported bleeding history. METHODS: The Women's Ischemia Syndrome Evaluation (WISE) study developed an algorithm using menstrual and reproductive history and serum hormone levels to reproduce the menopausal status classifications assigned by the WISE hormone committee. We applied that algorithm to women participating in SWAN and examined characteristics of women with concordant and discordant SWAN and WISE classifications. RESULTS: Of the 3215 SWAN women with complete information at baseline (1995-1997), 2466 (76.7%) received concordant classifications (kappa = 0.52); at the fifth annual follow-up visit, of the 1623 women with complete information, 1154 (72.7%) received concordant classifications (kappa = 0.57). At each time point, we identified subgroups of women with discordant SWAN and WISE classifications. These subgroups, ordered by chronological age, showed increasing trends for menopausal symptoms and follicle-stimulating hormone (FSH) and a decreasing trend for estrogen (p < 0.001). CONCLUSIONS: The WISE algorithm is a useful tool for studies that have access to blood samples for hormone data unrelated to menstrual cycle phase, with or without an intact uterus, and no resources for adjudication. Future studies may want to combine aspects of the SWAN and WISE algorithms by adding hormonal measures to the series of bleeding questions in order to determine more precisely where women are in the perimenopausal continuum. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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