Lauren Westafer, DO MPH MS Profile picture
EM doc @BaystateEM |@EMresearchUMMSB fellowship director |@FOAMpodcast co-founder #FOAMed |#impsci researcher|🏳️‍🌈she/her #LGBTQinMedicine
May 18, 2023 11 tweets 4 min read
Are you considering going down the investigator route 🤓 in EM? Then you probably want to know about K awards. Some highlights from our panel at #SAEM23 🧵 What are early career K awards?
⭐️ career development awards
⭐️focus on developing research skills to turn you into an independent investigator
✌️broad types: institutional (k12/kl2) and individual awards (eg k08,k23)

researchtraining.nih.gov/programs/caree… (2/x) Image
May 18, 2023 12 tweets 7 min read
Navigating the binary gender paradigm - experiences of trans 🏳️‍⚧️ and gender expansive physicians at #SAEM23
⭐️Is there a problem?
⭐️What do we do?
From our work ➡️ jamanetwork.com/journals/jaman… @JarmanAF
🧵 We *know* trans/gender expansive patients don’t have same access or experience in healthcare. We *know* there’s stigma in healthcare delivery pubmed.ncbi.nlm.nih.gov/24184160/
It turns out that physicians also experience stigma and transphobia in the workplace jamanetwork.com/journals/jaman… (2/)
Feb 2, 2021 17 tweets 9 min read
At @BaystateEM we devoted a "Stats are fun" lecture to bamlanivimab in #COVID19 last week. We reviewed 2 RCTs in outpatients (BLAZE-1) on the topic - the consensus was, we should rename the series to "Stats are sneaky".. A 🧵 with some fun methodology pearls First up - Chen et al nejm.org/doi/full/10.10… - This study came out first. It was a 4-arm RCT : 3 doses of bamlanivimab or placebo. Primary outcome: change in viral load on day 11.
⭐Not a patient-centered outcome. In fact, viral load (Ct) is of questionable significance (2/)
Mar 10, 2020 15 tweets 12 min read
I was supposed to deliver the @SAEMonline #NERDS20 Keynote. Bummed it's canceled due to #COVID19, b/c it's one of my favorite topics...knowledge translation (and the impact of the digital era on KT). KT seems simple-knowing what the evidence-based approach is...and doing it Knowledge translation is hard because knowing what the right thing to do is really really really hard. #1 There is an insurmountable amount of literature
#2 Much of it is irrelevant (or garbage)
#3 Researchers are sneaky
#4 things change (#medicalreversal )