Thread to discuss our new RCT (ELAIA-1) appearing in @bmj_latest that showed some unexpected results in the world of electronic alerts for acute kidney injury.
bmj.com/content/372/bm…
We know that AKI goes unrecognized and, in theory, undertreated from large retrospective studies like this one from @dmoledina:
sciencedirect.com/science/articl…
Acknowledging that reality, many health systems (including the @NHSuk, have institute automated "alerts" for AKI).
But do they actually improve outcomes? We conducted a randomized trial to find out. Image
We built an automated alert into our electronic health record that was shared across 6 hospitals. It gave information about creatinine values, a link to an AKI order set, and a link to the study website. Image
The alert fired whenever the chart was opened while the patient had AKI until it was acknowledged by the provider. It could be seen by anyone who could enter orders (MDs, DOs, NPs, PAs - not med students, nurses, pharmacists).
Since this was an RCT - the alert only fired on 50% of patients. Building that logic into the EHR was not trivial, but that's a story for another day!
We enrolled 6,030 hospitalized adults with AKI. Image
The primary outcome was a composite of progression of AKI (to a higher stage), dialysis, or death within 14 days of randomization. But we looked at "process outcomes" along the way.
The alerts did move the needle a bit on some provider behaviors. They led to more IV fluids for example, and more documentation of AKI. ImageImage
Overall, though, the primary outcome was similar in the two groups.
21.3% of the alert group and 20.9% of the usual care group had progression of AKI, dialysis, or death (p=0.67).
But then things got weird. Image
We had prespecified (bmjopen.bmj.com/content/9/5/e0…) that we would look for heterogeneity of alert effect across our 6 study hospitals, and indeed we found it.
Specifically, the effect of alerting was markedly WORSE in the 2 non-teaching hospitals. Image
In the non-teaching hospitals, there were significantly more deaths in the alert compared to the usual care group - 15.6% vs 8.6%, p=0.003.
This was obviously very concerning to us, and after carefully checking our code, we conducted a series of post hoc mediation analyses to figure out what was going on.
I suspected it might be overly aggressive fluid resuscitation, but that didn't explain the effect.
Nor did use (or nonuse of contrast), kidney consults, or anything else we could throw at it. Image
We did a full, case-by-case review of each death in those hospitals looking for a pattern. Aside from the number being higher, we didn't find anything. Deaths happened for reasons deaths happen in the hospital (sepsis, cancer, heart failure, etc).
We reported the result to the IRB and the @NIH (who funded the study). It put much of our studies on hold while we finished an investigation.
I don't have a satisfying answer, though I wrote about our thinking here. blogs.bmj.com/bmj/2021/01/18…
Given this data, I would argue that AKI alerts that do not provide patient-specific recommendations may not be useful and may engender harms that we don't fully understand.
This is why RCTs of even "common sense" interventions are critical. You may be surprised.
What's next for us? We're already running our trial (ELAIA-2) that specifically makes recommendations about certain drug therapies in AKI. Image
If YOU want to explore the ELAIA-1 data you can - a deidentified dataset is posted free for all here:
datadryad.org/stash/dataset/…
No you don't need my permission to download. Have at it! #OpenData is awesome. Publicly funded data should be free.
We'll be discussing this on #nephjc Tuesday the 26th at 9pm EST. Join us then! (or ask questions here).
Also thanks to our external advisors Harv Feldman, Amit Garg and @PaulPalevsky.

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More from @fperrywilson

8 Dec 20
Looking through the @pfizer data submitted to #vrbpac now. Fascinating stuff here. Thread. 1/
Baseline characteristics. Not bad. ~10% Black. Would have liked to see more >=75 years old. 2/
Efficacy overall (that's the 95% you keep hearing about) and stratified by age group.
Looks similar whether > or < 55 years of age. 3/
Read 15 tweets
28 Oct 20
Thread:
Even a mediocre vaccine can end the pandemic. But there are some caveats. I wrote about this on vox.com last week,
vox.com/21528373/vacci…
but here are the highlights: (1/n)
Let's assume that, on average, every person with COVID-19 can infect 2 additional people (a bit lower than the R0 of 2.5 but makes math easier). (2/n)
To stop the pandemic, we need to prevent disease in 1 out of every 2 people.
So if the vaccine is 100% effective, we'd need to vaccinate 50% of the population.
(Technically vaccinate or infect 50% of the population but trying to stay simple.)
(3/n)
Read 13 tweets
16 Sep 20
I have no idea which #vaccine
@realDonaldTrump was talking about today. But if we are going to have a vaccine before 2021, it will be one of these seven.

Here are the details (THREAD)

methodsman.com/blog/current-c…
mRNA vaccines
Inactivated virus vaccines
Read 4 tweets
5 Aug 20
OK let's do this.
In one place - ALL the randomized trials of #Hydroxychloroquine for #COVID.

5 peer-reviewed RCTs. 1 large RCT still in pre-print, but deserves recognition.

All negative.

I don't know what else to say at this point.

medscape.com/index/list_124…
Read 10 tweets
19 May 20
There will be no "antibody passports" for a while. Even if an antibody test has a low (say 5%) false positive rate, if YOU get a positive test, it may only be 50/50 (or less) that you actually have antibodies. WTF? (1/n)
It comes down to the false positive rate versus the positive predictive value. The FPR is how often a test comes back positive in a group of people WITHOUT antibodies. For this example, let's say that's 5%. (2/n)
OK - but as an individual, that number doesn't mean a lot. After all, you don't know if you truly have antibodies or not. That's why you're getting the test. (3/n)
Read 13 tweets
12 Mar 20
We're testing the wrong people for #Covid_19, let me explain (a thread). (1/12)
OK - tests are limited. That's a given. If they were unlimited, we'd test everyone. That's not an option. We need to triage. (2/12)
But what health systems are doing is selecting those who get tested. And they are picking a very specific group to test:
They focus on those with "classic" symptoms - like fever.
(3/12)
Read 12 tweets

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