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)
💵K awards fund you (mostly) to have time to do research, learn, and apply for grants.
⭐️commit to 75% research/25% clinical
➡️”funds” 75% research time (capped at 75-125k depending on institution)-ie institution on hook for salary cap gap
⬇️ 💵 for project (~25-40k/year) (4/)
Is a K award right for you?
⭐️answer is individual , some people may be ready to go straight to an R01 or similar award
⭐️needs to fill gap in knowledge/skills to advance in research
⭐️goal to become independently funded researcher (5/)
How do you get a K award?
Lots of different paths, some of our common themes were
⭐️mentorship
⭐️institution
⭐️prelim pubs/data
⭐️protected time
⭐️children/family
⭐️rejection
⭐️reluctance
⭐️fellowships/training
⭐️”atypical” paths
⭐️finding your niche (6/)
Mentorship is key
✅ For K awards,a “mentor” must be someone with individual NIH funding
✅They don’t get salary support for their mentoring so need to believe in mentorship and growing academic researchers
✅should have a shared specialization in trainee area of research
(7/)
Institutional support
⭐️b/c a Ks cost dept (salary cap gap) they must be on board and “write” a powerful letter of support
⭐️find a place that values growing EM research. peers can make you better (eg @emschoenfeld prompted me to apply for K12 & hooked me up w/great mentor (8/)
Protected (“academic”) time is important. It’s how you get and maintain grants and get research done. It’s helpful if you have some BEFORE you get a K to get the K (a research fellowship or some sweet deal) (/9)
Preliminary data and collaboration is important. Shows your project is feasible and that your team will give you adequate support. Building networks and collaborations can never start too early (/10)
⭐️Rejection. Embrace it. It will happen and it can make you better. Use the feedback
⭐️look at lots of funded Ks. The more you read, the more you will see the patters of success (hint: it’s a game) (/11)
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/)
In fact, teaching in MEDICAL SCHOOLS / TRAINING conflates being trans/gender expansive with being mentally ill - not good for patients, also harmful for T/GE clinicians. Leads to burnout and ⬇️representation in medicine (3/)
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/)
An important question in studies is-who got into the study? ⭐What did the population look like?
Here duration of symptoms to infusion is important- these people got the infusion quickly (~ 4 days after symptom onset).Often ED patients are further into the disease course (3/)
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 )
...but, the hard part of knowledge translation? DOING. for example, let's look at handwashing....we've only known it's helpful for a couple of centuries...but we are still TERRIBLE at it*+ ...
*pre-SARS-CoV-2 data
+I'm sure it still ain't ideal