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Some Pregnant Women Film Themselves Taking Tylenol After Trump Administration Warns of Risks in Pregnancy
A social media trend led a pregnant woman to overdose on Tylenol trying to refute autism risk claims linked to acetaminophen during pregnancy.
- This past week, an unnamed pregnant woman around 25 weeks ingested large amounts of Tylenol to try to disprove President Donald Trump and was rushed to hospital, where accounts say she is on a ventilator suffering liver failure, details shared by Nicole Sirotek.
- Earlier this week, President Donald Trump and Health and Human Services advised pregnant women to avoid Tylenol, citing a White House fact sheet released Monday that referenced Harvard and Johns Hopkins studies.
- TikTok and X users have posted videos of pregnant users taking Tylenol, while podcast host Joe Rogan and Nicole Sirotek, founder of American Frontline Nurses, amplified the trend.
- Her husband now faces a decision to try to save an unborn baby at about 23-25 weeks gestation, while the wife may not survive through the week.
- The FDA warns acetaminophen overdose can cause liver failure and has required label changes, while the WHO says evidence is inconclusive on prenatal autism links despite company records suggesting concerns.
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'This Science Came From Harvard': Joe Rogan Blasts 'Pregnant Women Taking Tylenol' To Own Trump Admin
Joe Rogan called out pregnant women who have been filming themselves consuming Tylenol in objection to Donald Trump's administration's recommendation.
·Washington, United States
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Claim: Pregnant Woman Overdoses On Tylenol Trying To “Prove Trump Wrong”
by Steve Watson, Modernity News: The Tylenol taking TikTok trend just took a deadly turn if an account related by Nicole Sirotek, founder of American Frontline Nurses, is accurate. Sirotek has claimed that a woman who is around 25 weeks pregnant has overdosed on Tylenol in an effort to defy the warning issued by President Trump […]
Coverage Details
Total News Sources14
Leaning Left1Leaning Right9Center1Last UpdatedBias Distribution82% Right
Bias Distribution
- 82% of the sources lean Right
82% Right
R 82%
Factuality
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