Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Editorial
. 2022 Nov 1;226(9):1678.
doi: 10.1093/infdis/jiac193.

The Potential Confounders Hiding in a United States Cohort About Severe Acute Respiratory Syndrome Coronavirus 2 Infection During Pregnancy

Affiliations
Editorial

The Potential Confounders Hiding in a United States Cohort About Severe Acute Respiratory Syndrome Coronavirus 2 Infection During Pregnancy

Pei-Yun Shih et al. J Infect Dis. .
No abstract available

PubMed Disclaimer

Conflict of interest statement

Potential conflicts of interest . All authors: No potential conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.

Comment in

Comment on

References

    1. Regan AK, Arah OA, Fell DB, Sullivan SG. SARS-CoV-2 infection during pregnancy and associated perinatal health outcomes: a national US cohort study. J Infect Dis 2022; 225:759–67. - PMC - PubMed
    1. OptumLabs . OptumLabs and OptumLabs Data Warehouse descriptions and citation. Eden Prairie, MN: OptumLabs, 2020.
    1. Diejomaoh MFE, Al-Jassar W, Bello Z, Karunakaran K, Mohammed A. The relevance of the second cesarean delivery in the reduction of institutional cesarean delivery rates. Med Princ Pract 2018; 27:555–61. - PMC - PubMed
    1. Marchi J, Berg M, Dencker A, Olander EK, Begley C. Risks associated with obesity in pregnancy, for the mother and baby: a systematic review of reviews. Obes Rev 2015; 16:621–38. - PubMed
    1. Zhang Z, Li X, Wu X, Qiu H, Shi H; AME Big-Data Clinical Trial Collaborative Group. Propensity score analysis for time-dependent exposure. Ann Transl Med 2020; 8:246. - PMC - PubMed