Bibliographic record
Abstract
Editorials20 November 2018To β or Not to β? Very Likely OK to βJoel G. Ray, MD, MScJoel G. Ray, MD, MScSt. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada (J.G.R.)Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/M18-2500 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail There is little reason to believe that daily use of an oral β-antagonist in the first trimester of pregnancy heightens risk for congenital malformations. There is reason, however, why the fetus of a woman prescribed this class of medication might be at higher risk for a structural birth defect: Women with chronic hypertension are more likely than women without hypertension to have higher body mass index, older age, and prepregnancy diabetes mellitus (1), factors which are themselves risk factors for birth defects (2). In fact, chronic hypertension itself, whether treated or not, is associated with slightly higher odds of fetal ...References1. Bateman BT, Bansil P, Hernandez-Diaz S, Mhyre JM, Callaghan WM, Kuklina EV. Prevalence, trends, and outcomes of chronic hypertension: a nationwide sample of delivery admissions. Am J Obstet Gynecol. 2012;206:134.e1-8. [PMID: 22177190] doi:10.1016/j.ajog.2011.10.878 CrossrefMedlineGoogle Scholar2. Stothard KJ, Tennant PW, Bell R, Rankin J. Maternal overweight and obesity and the risk of congenital anomalies: a systematic review and meta-analysis. JAMA. 2009;301:636-50. [PMID: 19211471] doi:10.1001/jama.2009.113 CrossrefMedlineGoogle Scholar3. Bateman BT, Huybrechts KF, Fischer MA, Seely EW, Ecker JL, Oberg AS, et al. Chronic hypertension in pregnancy and the risk of congenital malformations: a cohort study. Am J Obstet Gynecol. 2015;212:337. [PMID: 25265405] doi:10.1016/j.ajog.2014.09.031 CrossrefMedlineGoogle Scholar4. Bateman BT, Heide-Jørgensen U, Einarsdóttir K, Engeland A, Furu K, Gissler M, et al. β-blocker use in pregnancy and the risk for congenital malformations. An international cohort study. Ann Intern Med. 2018;169:665-73. doi:10.7326/M18-0338 LinkGoogle Scholar5. Ray JG. The efficacy and safety of beta-blockers for the treatment of hypertension during pregnancy: what the trials can and cannot tell us. J Obstet Gynaecol Can. 1999;21:670-83. Google Scholar6. MacCarthy EP, Bloomfield SS. Labetalol: a review of its pharmacology, pharmacokinetics, clinical uses and adverse effects. Pharmacotherapy. 1983;3:193-219. [PMID: 6310529] CrossrefMedlineGoogle Scholar7. Tanaka K, Tanaka H, Kamiya C, Katsuragi S, Sawada M, Tsuritani M, et al. Beta-blockers and fetal growth restriction in pregnant women with cardiovascular disease. Circ J. 2016;80:2221-6. [PMID: 27593227] doi:10.1253/circj.CJ-15-0617 CrossrefMedlineGoogle Scholar8. Bartsch E, Medcalf KE, Park AL, Ray JG; High Risk of Pre-eclampsia Identification Group. Clinical risk factors for pre-eclampsia determined in early pregnancy: systematic review and meta-analysis of large cohort studies. BMJ. 2016;353:i1753. [PMID: 27094586] doi:10.1136/bmj.i1753 CrossrefMedlineGoogle Scholar9. LeFevre ML; U.S. Preventive Services Task Force. Low-dose aspirin use for the prevention of morbidity and mortality from preeclampsia: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med. 2014;161:819-26. [PMID: 25200125]. doi:10.7326/M14-1884 LinkGoogle Scholar10. Mason E, Rosene-Montella K, Powrie R. Medical problems during pregnancy. Med Clin North Am. 1998;82:249-69. [PMID: 9531925] CrossrefMedlineGoogle Scholar Author, Article, and Disclosure InformationAffiliations: St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada (J.G.R.)Disclosures: The author has disclosed no conflicts of interest. The form can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M18-2500.Corresponding Author: Joel G. Ray, MD, MSc, Departments of Medicine and Obstetrics and Gynaecology, St. Michael's Hospital, University of Toronto, 30 Bond Street, Toronto, Ontario M5B 1W8, Canada; e-mail, [email protected]ca.This article was published at Annals.org on 16 October 2018. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee Alsoβ-Blocker Use in Pregnancy and the Risk for Congenital Malformations Brian T. Bateman , Uffe Heide-Jørgensen , Kristjana Einarsdóttir , Anders Engeland , Kari Furu , Mika Gissler , Sonia Hernandez-Diaz , Helle Kieler , Anna-Maria Lahesmaa-Korpinen , Helen Mogun , Mette Nørgaard , Johan Reutfors , Randi Selmer , Krista F. Huybrechts , and Helga Zoega Metrics Cited byWhat's new in obstetric anesthesia in 2018? 20 November 2018Volume 169, Issue 10Page: 718KeywordsCongenital disordersDiabetes mellitusDrugsFetusesHeart rateHospital medicineHypertensionMaternal healthPregnancyUltrasound imaging ePublished: 16 October 2018 Issue Published: 20 November 2018 Copyright & PermissionsCopyright © 2018 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.168 | 0.094 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".