The day that I found out when I’m going to die started normally.
asserted
I → find → ?
I filled out my DeathClock health profile (height, weight, allergies, family medical history, daily sugar and alcohol intake, and so on) and let the app know when my oldest grandparent died (in her 90s.)
asserted
grandparent → fill → 90s
I detailed how I rarely sleep more than seven hours per night (I have a toddler) but how I do cardio every day (again, I have a toddler.)
asserted
I → detail → toddler
In other words, I gave all of my information to a faceless AI app being run from Silicon Valley.
asserted
I → give → Valley
Then I signed up for the blood test.
asserted
I → sign → test
The date of death was decided before the bloodwork — 83 years old, with a “worst case scenario” of 50 and a stretch goal of 104.5 — and announced with an image of a little cartoon Grim Reaper reclining on a donut-shaped inner tube, grinning out the screen as he flashed a victory sign with his skeleton fingers.
asserted
he → decide → fingers
But this was simply an estimate based on a multiple choice test, and that wasn’t good for me.
asserted
that → base → me
When my World War Two-era grandparents kept going ‘til their mid-90s?
asserted
grandparents → keep → mid-90s
I wasn’t going to accept such slander.
asserted
I → go → slander
I selected one of the blood testing offices available through DeathClock in the evening and arrived at a nondescript building in midtown the next morning, took the rickety elevator up to the tenth floor, then followed some graying corridors around the building until I arrived at a claustrophobic little office under halogen lights.
asserted
I → select → lights
The waiting room was deserted; there were no sounds of nurses or doctors, though I supposed they were probably somewhere in the back.
asserted
they → desert → back
Behind the desk was a medical receptionist, who looked about as happy to be there as I was.
asserted
I → look → desk
“Hi,” I said, “I’m here for a blood test.”
asserted
I → say → test
The woman rolled her eyes and pointed at a piece of paper on a clipboard on the desk in front of her.
asserted
woman → roll → her
I dutifully filled out my name (first name only — a detail that struck me as unsettling, though I couldn’t fully articulate why), my appointment time, and what kind of bloodwork I was there for.
asserted
I → fill → bloodwork
On a Post-It note, I was told to add my home address.
asserted
I → tell → address
Then I was told to wait.
asserted
I → tell → ?
The tiny space was peppered with signs that had been handwritten in permanent marker on A4 paper and haphazardly pasted around the place: “DO NOT SLAM TOILET DOOR!”, “DO NOT TOUCH THIS WALL!”, “OPEN THIS ONE QUIETLY!” and so on.
asserted
that → pepper → ONE
As I sat, alone, with my hands in my lap, I watched the receptionist get up from her chair, disappear briefly into a small room beside the desk, and re-emerge, now dressed in scrubs.
asserted
receptionist → sit → scrubs
She then stood came round the desk, stood directly in front of me, and, making a show of looking down at the paper and scanning the completely empty room, shouted: “Holly?”
asserted
She → stand → Holly
When I got up, she introduced herself, as though we hadn’t met minutes before.
asserted
we → get → herself
At this point, I was obviously so-so about whether to allow the woman with two personalities to take my blood, but this iteration of her — the phlebotomist identity — was smiley and professional, and I allowed myself to be buoyed along by the idea that I was statistically unlikely to have my organs harvested and my best friend knew where I was.
asserted
I → allow → idea
As I exited the rickety elevator at the bottom of building and headed straight to a bakery — per the rules, I’d been fasting since the evening before — I felt a renewed vigor.
asserted
I → exit → vigor
One thing I will certainly say for DeathClock: they’re fast.
asserted
they → say → DeathClock
I got a text the very next morning that the tests had been completed, and when I logged in to the website, I felt a genuine jolt of victory.
asserted
I → get → victory
My date of death had changed!
asserted
date → change → death
Holly is going to die Wednesday, February 4, 2028, proclaimed the reclining Grim Reaper, happily, at age 92.
asserted
Reaper → go → age
Almost an entire decade added in the space of 24 hours, due to some really reassuring cholesterol markers and a good-quality metabolic panel.
asserted
decade → add → markers
Bit of a bummer to die right after my birthday, but I supposed it made sense that something would take me out in the winter at that age.
asserted
something → die → age
My lipids were doing well; my C-reactive proteins were all in range.
asserted
proteins → do → range
My “bad” cholesterol was low and my “good” cholesterol — the type that cleans up veins and lowers your risk of heart attack and stroke — was unusually high.
asserted
that → clean → attack
My “biological age” had been revised down from 36 to 29.
asserted
age → revise → 29
My Vitamin D levels were insufficient, but that’s solvable with a supplement.
asserted
that → ’ → supplement
Hell, if I got those in order, then even with my chronic stress and my child-inflicted insomnia, maybe I’d hit my new potential of 104.8.
asserted
I → get → 104.8
The reason DeathClock measures these things in particular, founder Brent Franson told me a couple days later, is because they’re cheap, they’re informative, and they’re the most reliable predictor of “phenotypic age” according to medical researchers.
uncertain
they → measure → researchers
The C-reactive proteins look at inflammation in your body that could be indicative of autoimmune issues or disease.
uncertain
that → look → issues
Lipids, glucose and other metabolic factors are good at predicting whether you’re at risk for conditions like diabetes.
asserted
you → predict → diabetes
The cholesterol, of course, speaks to your cardiac health.
asserted
cholesterol → speak → health
I tell him I felt a little disappointed when I saw my pre-bloodwork biological age and it was the same as my actual age, and he says that’s a problem in the industry: that there are a lot of health apps out there now that are “artificially deflating”.
asserted
that → tell → apps
Like vanity clothes sizes, they slap a number on you and make you feel better.
asserted
you → slap → you
…and 55 more, not listed.
The Aporia
