Clearly, the zombie has transcended the constraints of its own genre. Whereas early zombie films closely adhered to horror tropes, more recent renditions have wed themselves to comedy and romance (Zack Snyder released the comedic Shaun of the Dead in 2004 to critical and popular acclaim), and broken away from melodrama.
Emphasis is mine, and I still can’t get over this mistake. Clearly the comedic masterpiece Shaun of the Dead is Part 1 of Edgar Wright’s Cornetto triologyPart 2, Hot Fuzz is even better! and has nothing to do with Zack Snyder.
Is this an intentional troll? Zack Snyder does attract a lot of 4Chan attention. But how am I supposed to take the any of the essay’s many meandering philosophical references
And I thought medical jargon was bad… seriously if they can’t get this one basic thing right? Submit myself to voluntary Gell-Man amnesia?
Physicians can use the free DocsGPT to prepare referrals, certificates of medical necessity and prior authorization requests or to write a letter about a medical condition. A growing menu of prompts offers many options, and users can type in a custom request.
Next up: medical insurance companies using their own AI to process the AI-generated BS they receive from healthcare workers into something more easily understandable.
A series of essays published in 1929 that shows just how much we have been spinning in circles since the spasm of WW2. A reactionary right that wants all of the privileges of a liberal democracy without any of its obligations. A revolutionary left which uses its disgust for the current state of things as an excuse not to get involved in the messy business of fixing them. A middle free for ideals, morals, or goals.
It makes for fine reading, if you ignore the European imperialism and unabashed racism of the author who would, I am sure, be horrified to learn that his worst fears about the faith of Europe have been realized.
This is when you do a retrospective study, select cohorts according to exposure, but measure outcomes — usually death, or hospitalization, or something else bad — in a way that guarantees one or more of the cohorts have a period of time when that outcome couldn’t have happened. That’s how you get “immortal”, or “guaranteed” time.
Three classic examples:
Courtesy of Bing.
A study that evaluated the hypothesis that menopause occurring before age 40 years is associated with the development of cardiovascular disease (CVD). The study counted women who had premature menopause as exposed to CVD risk from their date of birth, ignoring the fact that they could not have developed CVD before menopause.
A study that assessed the effect of statins on diabetes progression and insulin use. The study classified patients as statin users based on their first prescription after hospital discharge, but included the time between discharge and prescription as exposed time, even though they were not taking statins during that period.
A study that examined the association between beta-blocker use and mortality in patients with heart failure. The study defined beta-blocker exposure based on pharmacy claims after hospitalization, but did not account for the time lag between hospital discharge and drug initiation, which could have biased the results in favor of beta-blockers.
To these three classics we can now add two more, one highly publicized, the other less so, both surprising considering the journals and the supposed peer review they must have gone through:
A study that compared hospitalization rates of those who had a positive SARS-CoV-2 test and did not take the Covid-19 drug Paxlovid to those who took Paxlovid regardless of test status. The study counted the day of the positive test as “Day 0” for the untreated cohort; however, for patients who started taking Paxlovid and did not have records of a positive test “Day 0” was one day before treatment start.
See this Twitter thread for relevant excerpts and a more detailed explanation. As the study excluded patients who were already hospitalized when they started Paxlovid, but included untreated patients who had a positive test and were hospitalized on the same day, this guaranteed 1 day of “immortal time” for the Paxlovid cohort.
A study that used “real world data” to compare standard blood thinners to a procedure called left atrial appendage occlusion (LAAO) for prevention of death and stroke in patients with atrial fibrillation. However, patients who underwent LAAO had to live long enough with atrial fibrillation without getting a stroke to “graduate into” the procedure. Not only is immortal time here so glaring, the study is eerily similar to the original heart transplantation study in which this bias was first identified.
Cardiologist John Mandrola explains in depth why the LAAO paper, and the way it was spun, is particularly egregious.
Note that this is only a problem in retrospective — or, how they now like to be rebranded, “real-world” — studies. As the most recent cases show, these are not only worthless for informing anyone’s real-world decision, but also contribute to the noise, the chaos, and the general fear-uncertainty-doubt of medicine. A voluntary moratorium would not be out of line.
It is assigned reading for a course I’m helping prepare, so I thought I’d better read the book we’ll ask our students to use. Like many textbooks, it suffers from MANE — many authors no editors — and like many academic texts, it can get way too pedantic. Still, it is hard to argue with its overarching themes: that randomized controlled trials are the pinnacle of medical evidence generation, and that much of the trial paperwork done in the name of quality is unnecessary. I have more comments on that last point, but that is for another time.
February 18, 2023
Twitter greeted me this morning with a notification that, not being a subscriber, I will no longer be able to use two-factor authentication via text.
Sure, SMS a bad method of 2FA anyway, and sure, Elon needs to save on his phone bill. It still felt like an ass move.
Different independent sources I’ve followed for a while converging on the same couple of points means there just may be some fire to the large language model smoke.
Matt Birchler: “I’m seeing some people look at this ask just the next NFT fad that comes and goes by the summer, but I’m not so sure. There’s something real here, and I think things are going to get a lot weirder very soon.”
Dave Winer: “Maybe there will be negative consequences of ChatGPT, but I’m sure we’re not in a position to see what they are now, based on experience with similar changes. And maybe we’ll look back on this moment twenty years from now, and not be able to imagine what life was like before we had this fantastic tool.”
Twitter is still ablaze with screenshots, and of course yours truly had a few thoughts to share yesterday. The best explanation of ChatGPT and large language models in general is still Stephen Wolfram’s.
