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Impact of clinical characteristics on human chorionic gonadotropin regression after molar pregnancy

OBJECTIVES: This study aimed to determine the effects of age, race/ethnicity, body mass index, and contraception on human chorionic gonadotropin (hCG) regression following the evacuation of a molar pregnancy. METHODS: This was a retrospective cohort study of 277 patients with molar pregnancies betwe...

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Detalles Bibliográficos
Autores principales: Gockley, Allison A., Lin, Lawrence H., Davis, Michelle, Melamed, Alexander, Rizzo, Anthony, Sun, Sue Yazaki, Elias, Kevin, Goldstein, Donald P., Berkowitz, Ross S., Horowitz, Neil S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Faculdade de Medicina / USP 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8366901/
https://www.ncbi.nlm.nih.gov/pubmed/34468539
http://dx.doi.org/10.6061/clinics/2021/e2830
Descripción
Sumario:OBJECTIVES: This study aimed to determine the effects of age, race/ethnicity, body mass index, and contraception on human chorionic gonadotropin (hCG) regression following the evacuation of a molar pregnancy. METHODS: This was a retrospective cohort study of 277 patients with molar pregnancies between January 1, 1994 and December 31, 2015. The rate of hCG regression was estimated using mixed-effects linear regression models on daily log-transformed serum hCG levels after evacuation. RESULTS: There were no differences in hCG half-lives among age (p=0.13) or race/ethnicity (p=0.16) groups. Women with obesity and hormonal contraceptive use demonstrated faster hCG regression than their counterparts (3.2 versus. 3.7 days, p=0.02 and 3.4 versus. 4.0 days, p=0.002, respectively). CONCLUSION: Age and race/ethnicity were not associated with hCG regression rates. Hormonal contraceptive use and obesity were associated with shorter hCG half-lives, but with unlikely clinical significance. It is important to understand whether the clinical characteristics of patients may influence the hCG regression curve, as it has been proposed as a way to predict the risk of gestational trophoblastic neoplasia.