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sending-the-message · 7 years ago

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What Happens when the Stars Go Out by TheJesseClark

The red lights are only making the pain worse. It is an immense, earth-shattering pain, in my midsection and in my head. I try to move, but I can't; I try to speak, but I can't do that either. It hurts too much, and my voice obeys me no more than do my joints or my muscles or my bones or my mind.

And yet still there is movement. I can feel myself being lifted up and placed on something - a bed, maybe, or - no.

A gurney.

“Alright!” one of the EMTs says, and several others then roll me into the back of an ambulance, and climb in behind me. But I'm already fading fast, and feeling an inexplicable heat, by the time those doors are shut.

One EMT, a blonde woman, looks at me with a furrowed brow, just as I'm slipping away, and says aloud, “Wait. Wait, I think I know...

”...we're made of that stuff, right?”

I turned around. There was a woman there, red-haired and about my age, give or take, and she was alarmingly beautiful. But how long she'd been staring at the exhibit alongside me I had no idea.

”I'm sorry?”

”I said ‘you know we're made of that stuff, right’?” She nodded at the museum wall, which depicted in detail the births and life cycle and deaths of stars. I pursed my lips.

”We’re… made of stars?”

”Yep. Isn't it awesome?” She stepped up beside me and moved her arm across the diagram as she spoke. “I just watched a documentary about it last night. Stars are just fusion factories held together by their own gravity. They start off fusing hydrogen to helium, and then they keep going on and on, fusing heavier and heavier elements until they're fusing the heaviest stuff. Then they exhaust their fuel and collapse under their own weight, and they blow off their outer layers and pretty much shower the galaxy with all these random elements, some of which are eventually used to create life.”

”Huh.”

”Yeah. I’m Robin, by the way.” She extended her hand, and I shook it.

”Uh, hey. Brian. Nice to meet you.” There was an awkward pause before I said, “Alright, I got one for you. If you replaced the sun with a black hole, what would happen?”

”Depends on its mass.”

”Nope! The answer is - drumroll please - nothing. I mean everything would get dark and cold, but we wouldn't fall in. Earth’s orbit would remain entirely unaffected.”

”IF the black hole had the same mass as the sun.”

”What?”

”What you said would only be true if the black hole in question happened to have the same mass as the sun. Which it wouldn't, because the sun isn't massive enough to collapse into a black hole.”

”Oh. Damn.”

”Yep. Me one, you zero. Sorry, pal.”

”Alright.” I said. “You're on. Whoever gets the most points by closing time buys drinks.”

She smiled at that and punched me in the shoulder, just light enough not to sting. ”Alright, loser. Come...”

“...on,” the EMT says. There is a flurry of activity around me, and there are voices, too, and blinding lights, and a cooling down of that monstrous heat.

One of the paramedics is looking me over. Then he looks to another colleague - the blonde woman - and he shakes his head, slowly.

“This one’s gone, Rachel.”

But she continues running tests, running diagnostics, placing a soft hand on my arm in case I'm awake enough to appreciate the comfort. I am. Barely. But I'm fading fast, and that heat is coming right on back as I do.

“Not yet he's not,” she says. There's pain in her voice that she does her fruitless best to conceal. “I already lost one earlier, Todd. I'm not losing…”

”... another one!” Robin said, and I laughed and agreed and we rushed to the back of the line.

”See? Told you you'd like Ferris Wheels. Can't believe you've never been on one before today.”

She shrugged. “Never thought they were as extreme as roller coasters, so I wasn’t interested.”

”Well they’re not supposed to be ‘extreme.’ Ferris Wheels are for all the parents waiting on their kids and sick people trying to relax their stomachs so they don’t puke funnel cake all over the pavement.”

”And adorable young couples, apparently.”

And just then we were waved into the next seat. We sat ourselves down, and moments later the great wheel began to groan and protest and, finally, to turn; it dragged our cart around its underside and then lifted it up, up, up to the top of its crest, where we could see the whole city at twilight, and the ships in the harbor that were backlit red with the setting sun, and the clouds that were lined at their tops with just a little bit of starlight. Robin snuggled up next to me and put her head on my shoulder, and I put my arm around her waist. For a moment then I could've sworn the empty seat in front of us move on its own, and furrowed my brow. But then Robin spoke.

”Thank you for being here with me,” she said. I didn't respond with words;I just kissed her on the head and held her tight, as the Wheel began taking us…

“...down on the eighteen hundred block of Gardersdale,” one of the EMTs says. “Yeah. Yeah. Another one, I know. Hell of a fucking night, isn't it?”

The conversation is muffled again in short order. I drift in and out, and there is a flurry of sound and lights and movement. But the jostling of the room and the sound of an engine tell me we're still in the ambulance.

The other paramedics, for their part, continue running tests and checking my vitals, and as they work I try to remember what's happened. But it hurts. Dammit, does it hurt, almost as much as that rushing heat, and the effort is further disrupted when the ambulance hits a bump in the road and I nearly spill out of the gurney. But Rachel puts her steadying hand on my chest and says, “Hang in there, Brian. We're almost…”

”...there!” Robin pointed at the interstate ramp, and I took the turn and put St. Thomas Vineyard away in the rearview.

”Still can't believe Mason got married,” I said. “He’s only known that girl for what, a year? Less?”

Robin shrugged. “They were in love.”

”They hardly knew each other! They don't know if whatever they're feeling is genuine, life-long love or just new relationship googley-eyes that hasn't worn off yet. I guarantee it - and I'll put money on this - they'll be done within a year. Just watch.”

”You don't know that,” she said. There was a brief pause, and then she added, “We’ve been dating for two years.”

”So?”

”So… how far off do you think we are?”

I shrugged. “I don't know. Haven’t really thought about it.”

”You haven't thought about it? At all?”

”I mean of course I've thought about it. I just… I don't know if we're ready, you know?” I looked over at her, but she just stared out there at the rain with her chin in her palm. So I continued. “Think about it like this: people prepare their whole lives for jobs, right? They start going to school as soon as they can talk, and they're not done till they're in their twenties, and it's all so they can get a piece of paper that says ‘hey, hire my ass, I’m smart enough to work.’ But marriage? Nobody trains for that shit. People just hook up and say, ‘hey we're twenty five, or twenty eight, you're cute, I'm cute. Let's spend fifteen thousand dollars on a giant ceremony and then live as glorified roommates for five years until we're both fat and hate each other and get divorced because neither one of us knew or cared how much work this thing would require.”

There was a longer pause then, before she said, with a degree of seriousness I wasn’t in the least bit prepared for, “Is that where you think we're headed? ‘Glorified roommates?’”

Quickly I calculated an avenue of retreat. But I calculated wrong. “No! Not you,” I said. “Not us. I mean most people, you know? Most people just dive in and either get divorced or stick it out till someone gets heart disease. The divorce rate is more than fifty percent now in the US. But the ‘I-don't-love-you-anymore’ rate? Shit, that's probably close to ninety by the time everyone hits middle age. I just want to make sure you're the right person, you know?”

If ever there were words I wish I could've taken back, it were those twelve. She said nothing, but I saw her reflection in the window, and the little tear that welled up in the corner of her eye said more than words ever could.

”Listen, I… that came out wrong. I just meant-”

”Can you drop me off at my car, please?”

”I thought you wanted to come over-?”

”I don't feel good. Please?”

And we drove in silence for a while, as the rain picked up its pace and fell in sheets and in torrents. After another twenty minutes I made the turn onto my street and parked, and once I did she got out without so much as a glance and walked across the road to her own car. I ran to follow.

”Robin, wait!” I grabbed her lightly by the arm. It was slick with rainwater. “Talk to me. Please?”

”What do you want?”

I blinked. ”I want you to talk to me. I just s-”

”No. I mean with us. Where do you want this to go?”

”Where do I want this to go? I want to be with you! Listen, I didn't mean to imply that - that I don't want that. I just want us to be smart about it. You know?”

”Well maybe love isn't something you can calculate on a fucking spreadsheet, Brian!” She was shouting over the cacophony of the storm. “Maybe it's just this thing you feel, you know? And maybe it doesn't make any damn logical sense. Maybe it's not supposed to. But that's part of what makes it special; it's an adventure; it's a ‘jump off a cliff with me’ type of thing. And yeah, sure. Not everyone survives the fall, I guess. But if you find the right person, then-”

”A ‘jump off the cliff with me’ type of adventure? Come on, Robin! We're not writing up a damn dating website profile here; this is real life! There are kids involved, and finances, and house buying, and mortgages and all that shit! Not every day is some cute little romance comedy. This is half your life we're talking about. Two-thirds, even. Okay? All I meant was that you have to be prepared for it. I just-”

”I thought we were prepared.”

”What do you mean?”

She dug through her purse for a moment, and then held up a ring that was brilliant even when covered in the rain. I felt my heart skip at least a full beat.

”Is that, um-”

”It was my mom’s,” she said. “She gave it to me before she died. She said, ‘find your partner in crime, Robin. Find someone who'll sweep you off your feet. And jump off a cliff with you.’” There was a pause before she added, “And at the time she said it I thought I knew exactly who that person was.”

I tried for a moment, but I knew, beyond the shadow of a doubt, that there was no combination of words in the English language that could be strung together to right this ship.

”Good-bye, Brian.” She kissed me on the cheek, and rubbed the back of her hand on down it. And then she turned and got in her Civic, and drove off until I couldn't see her tail-lights at all through the pouring of the...

“...rain’s comin’ down hard, boys,” another of the EMTs said. “Careful when you unload him.”

There were grunts of acknowledgement, and then the back of the ambulance flew open and the sound of the storm utterly exploded into it; I felt the rush of wind, and the rain pelting my skin in sheets, and together they helped a bit with the oncoming heat that still I couldn't place. And then I felt movement. The gurney dipped and hit pavement while the paramedics held me tight to its form. And then there were shouts, and lights, and running feet, and then the hospital door…

”Open?!” I shouted. The man behind the counter looked at me with a furrowed brow. I shouted it again, over the sound of rainfall and through the glass. “I said, are you open?!”

And then he pointed at the sign saying the opposite, and went back to reading. But I wasn't taking no for an answer; I dug out my wallet and pulled a twenty from the fold, and slapped it flat up against the glass. Within seconds the paper was soaked with rainwater. But it got his attention, and once he saw me there he took pity on my plight, and the door clicked and whirred and slid open.

”Make it quick, man.”

”I know, I know. I will. Thank you so much.” I ran down the aisles and then, true to my word, made it back to the counter in less than a minute. The man put down his book, and processed the sale.

”Date night?” He said, bagging the card after the flowers. I smiled a bit.

”Something like that.” And then I thanked him and ran back out to my car, and got inside, and took out the card and scribbled on its inner sleeve the words, ‘Jump off a cliff…

“...with me, with me!” A doctor running alongside the cart motioned to some nurses in the hall, and they ran to follow. He turns to the EMTs. “Is he stable?”

“He’s slipping. Heart rate’s falling, breathing slowing. Not good. Mumbled something about being too hot earlier, but if anything his temperature’s too low.” Someone shows the doctor a chart. He reads it as he runs, and his face is grim.

“Shit. Alright,” he says. “Let's…”

”...move!” I shout at the car I'm passing. “Just a little rain, assholes.” But it wasn't. It was a lot of rain. Sheets and buckets and torrents of it, in fact; it’d long since turned the dirt to mud, and it swept up against my windshield like ocean surf, and the road was slick with little rivers of it than ran on down past the pebbles. I was going far, far too fast for such conditions. But I didn't…*

“...care about that,” the doctor said. “I just want to get his fluids up. Rachel!”

The woman from the ambulance runs up and discusses my condition in harsh whispers with the doctor. As I fade, and as the damn heat floods on back in, it becomes impossible to hear what they're saying. But it's abundantly clear from the body language that she hasn't yet give up…

’...hope for a reunion with these guys?’

’Well, Bolan and Snake say they’re against it, entirely. So that doesn't bode well for fans. But look what happened with-’

I switched the radio off, and then wrapped both hands around the wheel with such force the knuckles turned white on the grip. The car hit seventy miles per hour. Seventy five. Seventy nine. The windshield wipers were flying, but they weren't going fast en-

”FUCK!” I slammed my foot on the brakes as the lights of activity in the road came in out of nowhere from the rain. The car jolted and shuddered and fought for traction with the pavement, and I felt the tires squeal and the metal of the car grind in…

“...protest.”

“I don't care if he wants to protest!” the doctor snaps back. “You tell him to wait in the damn lobby like everyone else!”

The nurse accepts her orders and heads back out into the hallway. “I'm sorry, sir,” she says. “You can't see him until-”

“Until what?! That's my son in there! That's my son! That's-” and then there's a scuffle of feet, and more shouts as a security guard drags my father from the wing. Rachel pauses as she hears the shouts, and then her eyes well up a bit with tears, and she looks at my face and appears to realize something. But she doesn't say what. The shouts continue, but they fade. And so do I. And in comes the heat as I do.

“That's my son!” Dad says. “That's my boy! Let me see my boy! Stop! Please...!”

”...stop!” The police officer had both hands up as my car barreled towards him. “Stop! Stop the car!”

Finally there was a jolt and a shudder as the tires gained control at last, and the car slammed to a halt. Both the officer and I sighed in relief, and then he approached my window and tapped the glass with his knuckle. I lowered it.

I shouted over the rain, “I'm sorry, sir! Roads are crazy out here. You okay?”

He ignored the question. “I'm gonna need you to sit here for a bit, okay?” He said. “Just until the accident’s cleared up.”

”Accident?”

”Its bad.” He nodded in the direction of the wreckage, and then he said again, “Just sit tight! We’ll waive you over when there's an open lane.” And then he ran off into the storm.

I scanned the scene. There was a man on the side of the road, I saw, sitting on the pavement with a poncho for the rainfall and his head in his hands. His SUV was totaled; the front end was bent and twisted and hideously mangled.

But the other car was in far, far worse shape than that. I squinted hard, and could only make out panels of white amidst charred black chunks of metal and the force of the rain. But it was enough.

It was a Civic.

Oh, God. Oh, God, no. No, no, no.

I got out of the car and left the door hanging open in the rain, and then I ran forward, at least until the officer caught sight of me and ran back over and grabbed me by the shoulders.

”Hey!” He said. “I told you to wait in the car! What're you-”

”ROBIN!!” I shouted over him. “ROBIN!”

And then I saw it; a fleeting glimpse of movement, a white sheet flipped on a gurney. A strand of red hair fell from the right side and hung there as the EMTs carted away the body.

”ROBIN!” I screamed. “That's my girl! That's my girl!” The officer was confused and stunned and did the only thing he could think to do - drag me back to my car.

”No! Stop!” I was inconsolable but in no shape at all to resist. “Stop, please! That's my girl! Let me see my girl! Please, stop!”

One of the EMTs, covered in blood from the waist up, turned to look at the spectacle. But then someone shouted her name.

“Rachel!” The doctor says. “You with us, or what? Let's go!”

She blinks as she stares at me, and then says, “Uh, yeah. Sorry. I just realized, this guy was-”

“Just get the charcoal, please? We don't have time.”

And she does; she runs off to fetch exactly that. And then I feel a hideously invasive sensation - a tube is being placed in my nose, and then I feel it falling down, into my throat. I'm too weak to gag, but I somehow manage to clench my fist. A nurse sees the movement, and he holds me down to steady me.

“Whoa, whoa…”

”...Whoa, whoa, you okay, man? My roommate stumbled back as I threw open the door. I charged past him. “You're comin’ in hot!” He said again. “You good, bro?”*

But I ignored him. I went to the bathroom, and I leaned up against the sink for a long moment, and I grabbed my temples and set my jaw and sobbed without a sound; aching, wracking, heaving sobs. I heard a knock.

”Hey, man,” he said. “You good, dude? Anything I can like, get for you? Or-?”

”I'm fine,” I managed. It wasn't convincing in the slightest, but I didn't care. I opened up my phone. There was a text from Robin there, from this morning.

*It read, ‘I love you,’ and they were all at once the most beautiful and the most painful words I'd ever read. ‘I love you.’

I love you, too. I'm coming. Hang on, baby. I'm coming.

Then I backed out, and found my dad in the contacts list, and typed, ‘I love you, Dad.’

Moments later I got a response: ‘I love you too, son! You okay?’

But I ignored it, and then I threw open the cupboard, and I grabbed an old…

“...bottle of pills,” a nurse said. “Swallowed the whole damn thing. Lucky his roommate called it in when he did.”

But the doctor is incredulous. “Well. That remains to be seen, now, doesn't it?” Then he turns to the door. “Rach-”

And she pushes it open with her elbow before he finishes. “I got it, I got it. I'm here.”

“Alright!” He says. “Fingers crossed, people. Let's see if we can't save a psycho!”

There are isolated chuckles. Rachel, though, almost snaps at her superior for the insult, but then someone says, “Here we go!”

And then there is thick, wretched black stuff funneling down that tube and down into my throat. I'm almost desperate enough, but not quite strong enough, to resist it. I can feel it sliding, and hitting bottom, and pumping, and pulsing. My heart rate is erratic; my breathing is erratic; my ability to comprehend the situation is every bit as erratic. I struggle as much as I can against the restraints, but all my effort and all my strength of arms musters up not more than the faintest whimper.

But Rachel hears it. She moves to my side, and she holds my head, and says, in soft enough a whisper that only I can hear the words, “Don't follow her, Brian. Don't follow her. Please, Jesus. I need him here. I need this win.”

But I begin to fade all the same. One by one, as the spikes on the EKG slow to sporadic pulses, I see the nurses turn to each other and shake their heads. One by one by one, that is, until there is only a trembling Rachel there, and she's holding on for me tight enough for everyone in the room.

“Call it,” the doctor says, just as the darkness swirls in and I feel like I’m starting to fall away.

The conversation carries on as I pass.

“Two thirty two AM,” one nurse says.

But I can hear Rachel screaming in protest - “No! He's not gone! There's still time, there's still time to save him, there's still…”

But she's wrong. I'm already gone. Her voice, and her face - those things are behind me as I pass. They're fading away into the darkness that's consuming me, and swallowing me whole, and throwing me to the winds.

And just when the magnitude of the situation dawns on me - then comes the heat. There are monstrous amounts of it. It rips and tears and scorches and scalds, and had I the ability to scream out or even to breathe I would've done so until my throat was hoarse. But then there is a new pain. A different pain.

A hand reaches out of the blackness, and it grabs my left-side forearm with such mighty force that the resulting pain eclipses that of the heat, and the nails of that hand rip right through the flesh. And then I’m being pulled, and there is a rushing wind. It is cool and refreshing and beautiful, and suddenly I'm somewhere else entirely.

I blinked. The darkness was gone, and the heat with it, and that sensation of being devoured. Instead, those things had been replaced with starlit clouds as far off in every direction as the eye could see. But my arm stung like hell all the same. I looked at it. There were nail-marks, I saw. Four deep cuts beneath the inner wrist and a fifth on the side, in the shape of a hand. They bled a bit. And then I heard an all too familiar voice.

“You okay?”

I stood up, slowly, and I turned, holding my damned stinging arm while I did it, and said, “Robin. Robin, w-what was that? That darkness? And the heat, and th-”

“Its where you would’ve spent your eternity, Brian, had I not pulled you out.”

I had no words other than the weakest, “Thanks.”

“You know,” she said, holding her own arm. “Suicide’s not exactly what I meant by ‘jumping off a cliff.”

I blinked again, and took a long, deep breath. “Yeah. I guess I didn’t think things through.”

“Not sure you fully realize how much of an understatement that is.”

“Well, maybe I don’t. But you know what? I'd do it again, Robin. I’m serious.”

She nearly rolled her eyes, but I doubled down on the sentiment.

“What I said? Out there on my street? I'm sorry. I mean it, I’m sorry. You were right. Love isn't about taxes or headaches or just tolerating each other until we’re seventy. It's like your mom said. It's about sweeping your girl off her feet. It's about jumping over cliffs with someone, and not knowing where you'll land, and not caring, as long as you get there together. And if this is where we land, wherever this is, I'm okay with that.” And I leaned in for a kiss.

But she stopped me with her hand before it landed, and I opened my eyes.

“I can tell you've been working on that speech for a while,” she said.

“Over and over again In my head, in the car, until… until I got to the scene of the wreck.” I looked at the ground, and then back up at her. “And I realized, right then, that if you fucking left the earth itself than I would, too. So here I a-”

“I was wrong, too.” She cut me off.

“W-what do you mean?”

“About love. I was wrong. My mother was wrong. It's not just about crap you see in rom-coms and greeting-cards, Brian.”

Again I blinked. “I know that! I know, it's - it's something you feel in your heart; that defies logic and reason. Not something you can put on a spreadsheet. Like you said earlier.”

She sighed a bit, and then said, “Can I show you something?”

“Uh, yeah! Yeah, okay. Sure.”

And then she took my hand, and Infinity rolled in and faded back out, and all of a sudden we were somewhere else entirely.

“Are we -?”

“On the Ferris Wheel? Yep. Turn around.”

I did, and there we were, past Robin and past me, on the seat above and behind us. I remembered it like yesterday; we were staring out at the whole city at twilight, and the ships in the harbor that were backlit red with the setting sun, and the clouds that were lined at their tops with just a little bit of starlight.

I rustled in my seat a bit and it moved, and past Me furrowed his brow when he saw it. But then past Robin said “Thank you for being here with me,” and got a kiss on the head.

“What do you see?” Robin said.

“Us. A year ago and change. I remember that day like it was yesterday. Your mom had just died, so I took you here. To get your mind off things.”

“You did. That was the first day in months I'd felt truly safe and truly at peace. That was love.”

“I know it was. And I still love you, just the s-.”

“It's a kind of love,” she said, cutting me off again. “And it's absolutely beautiful when it lasts. But can I show you something else?”

“Uh… okay. Yeah.”

She took my hand again, and again Infinity itself rolled in and out like the tide, and then we were somewhere else. The hospital, it looked like. St. Joseph’s.

“What do you see here?”

I looked around. Nurses running up and down the hallway. Doctors reviewing notes and talking to their patients.

“I don't know. A hospital.”

She nodded in the direction of a particular room. “Look in there.”

So I did. There was a woman on the cot. She was emaciated and hairless and deathly frail, and the Doctors inside were shutting off the last of the machines.

“A dying woman,” I said. “Looks like cancer.”

“Yep. And what about there?”

I looked down. There was a nurse crouched down in front of the same door and talking to a girl - eight or nine years old, if I had to guess - in silly voices. The girl had been crying, but the nurse managed to make her smile a bit, even as her mother died on the other side of the door.

“Looks like a nurse comforting a little girl.”

“That's right,” Robin said. “And that little girl will remember that nurse for the rest of her life - even if they never meet again or so much as exchange names - as the lady who came to her in her darkest hour and made her smile.” She turned to me. “That's love, too. Just as beautiful and just as previous as what we had.”

“What's your point?”

She didn't answer; she just stuck out her hand with a sad smile, and I took it. Infinity faded in and back out a third time. And then we were in the waiting room.

“See that?” Robin said. She pointed to the corner of the room, and I squinted.

“Oh hey!” I said. “That's Dylan! What's he doing here?”

“He called the ambulance when you didn't come out of the bathroom,” she said. “He knew something was wrong, and when they drove you off he followed them here. Been standing there ever since, asking for information on you every time a nurse walks by. He's starting to annoy them.”

I watched my roommate for a bit, and sure enough he grabbed a nurse, and asked her a question that I couldn't hear. She said something pleasantly dismissive, and he nodded, and then leaned his head back up against the wall and closed his eyes.

“Wow. I uh, I had no idea he cared that much.”

“That's love, too, Brian. Would you do the same for him?” But she held out her hand again before I could answer, and I took it. For a fourth time Infinity blinked.

And then I was in the emergency room, looking down on myself. I was covered in vomit from the charcoal and the pills, but I was still, too. Deathly still. Most of the nurses and the doctor were still walking out the door.

But Rachel wasn't. She was crying openly now, and making no effort to hide it. She reached for something. A needle, it looked like, or a syringe.

“What's she doing?”

“You'll see soon enough,” Robin said. “But that there? That's also love.” She held out her hand once again and said, “One more.” And I took it.

And then we were in the parking lot of the same place. The rain was coming down harder than ever.

“Turn around,” Robin said. And I did. And then I stopped; There were no words.

It was my father in his car. He was holding a Bible up to his chest with both hands, and he was crying in a way no child should ever have to see their father cry.

“And that there?” Robin said. “That's the kind of love that can move mountains.”

I put my hand up against his window. He didn't seem to notice.

“He can't see you, Brian. Not from there.”

I wiped my eyes with the back of my hand. “Okay,” I said. “I get it. I fucked up.”

And then she released my hand, and all of a sudden we were back in the clouds again, under the stars. I wiped another tear before it fell.

“So now what? It's too late for me to go back down there. I'm already gone.”

Robin took another step forward, and without another word she put her hand on my temple, and my eyes rolled back.

And then I saw it.

*Rachel and I are on a beach. Our child is playing out in the surf, and the sun hits her hair just right, and for a moment it is made of gold.

And then the image fades, and another one takes its place.

A birthday party. I have silver hair at my temples. Rachel does too. But it doesn't matter. Our little girl is turning ten.

And then that image fades, too, and is replaced by another, and another, and another; each one yielding another moment where someone loved someone else enough for it to break through the clouds and be seen forever, even if the moment itself lasted only for a heartbeat.

Finally there is an image of Rachel and myself on a porch as old as we are, and she holds my hand and says, “I'm glad you didn't follow her.”

And I say back, “Me too,” and I kiss her on the head.

And then Robin pulls back her hand, and again standing out there in the clouds together.

“How did you do that?” I asked.

She shrugged. “Time has nearly no meaning in this place. I've been here for a while, Brian, and yet the doctors haven't even left your operating room. Don't think too much about it. Just think about what you want.”

“That,” I said. “Was… was that my future?”

She shrugged again. “Could be. I don't know what you saw, and I don't need to know. Was it enough?”

I nodded, and she stepped forward again, and said “Then go and get it.”

“I'll miss you too damn much.”

“Well there's nothing wrong with missing someone,” she said. “That just means love lasted a little longer than what ignited it. So go ahead and miss me. You owe me that much. Feel the loss; stand up to the storm like a man, and memorize the pain, and learn it inside and out, and let it roll over you in waves and run its course. And then one day you'll wake up and realize you have scar-tissue where the skin used to be, and you'll be stronger than the grief ever was.”

“I can tell you've been working on that speech for a while.”

“Like I said. I've been here for a while.” She said. “You're made up of the stars, kid. Now go light up the world.”

And she kissed me, one last time. And then she was…

“...gone, Rachel. Okay? He's gone. Give it up for Christ's sakes and-”

But I shot upright before the doctor could finish the thought, and I gasped for air when I did and grabbed at my chest with more strength than I'd had in hours. There was a needle in it; a bolt of life to the heart, and Rachel broke down in tears when she saw me.

“Well I'll be damned,” the doctor said. “Welcome back to the land of the living, son. And Rachel?”

She turned around.

“Good work, kid. Made me proud.”

And he left, and she turned back to me and tried to hide a smile while she did it. “Hey there. How’re you feeling?”

“Better than dead.” There was a pause before I added, “Hey. I'm glad you got your win.”

She took my hand and squeezed it. For a moment she paused when she saw a scar below the wrist that looked like the result of fingernails dragging through flesh. But then she dismissed it and said, “I am too. And you'll get yours. Okay? I promise you will.”

I said, “I know.” And with that she got up and left the room to go save someone else’s life, while I took out my phone, and opened up the most recent text, and hit reply.

‘Am now.’

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craigbrownphd-blog-blog · 7 years ago

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A Common Data Analysis Pattern with a Simple Solution in R

It seems that much of the data analysis work I've done over the last few months has followed a "script". First, identify data, often government-sponsored and freely-available, that's of keen interest. Next, find the websites that house the data and download the relevant files to my notebook. The downloads might ultimately be one-off or included in the data analysis programs. Finally, load the data into either R or python and have at it with queries, visualizations, and statistical/learning models. Several examples of recent work come to mind. The first involves data from the Bureau of Labor Statistics on jobs and educational attainment from 1992-2017. On this site, 24 spreadsheets are available detailing monthly statistics on six measures of employment by 4 levels of educational attainment. For a previous blog, I downloaded 12 of these files, including measurements laborforce, employed, and unemployed by educational levels no HS, HS grad, some college, and college grad. I renamed the spreadsheets on my SSD to include indicators of dimension -- eg "clf_laborforce_collegegrad.xls". The second example, the topic of this blog, has to do with Medicare charges summarized by hospital and diagnostic related group (DRG). At this point there are five files (either csv or spreadsheet) available for download, representing the years 2011-2015. Year is embedded in the website file names. A third illustration, and the topic of a coming blog, revolves on census data from the American Community Survey. The pattern behind the three cases includes: * readily downloadable files, generally either csv or xls. These files can either be copied by hand or moved programmatically. * multiple of these files, often dimensioned by time or other variable(s). * a common, consistent format to the files, so that "reads" will work similarly on each. * a structured file naming convention, either given or assigned, that provides dimensional info for data loads. Date/Time is the most common diemnsion. In this article, I looked at the Medicare charges data that consists of five yearly csv files. I expect the next year in the sequence, 2016, to be posted in the near future. I first downloaded the five files to my laptop, programmatically in this case. I then used Jupyter Notebook and R 3.4 to analyze the data with code that takes advantage of the commonalities. The data.table package along with the tidyverse ecosystem and fast file compression, read/write library fst, plus a functional approach, are central to the work. This is not your older sibling's R. None of the highly-performant packages used here are included in core R. Rather, they are the bounty of an exhuberant and capable R ecosystem of developers. Incidentally, if this notebook were written in python, I'd be giving similar accolades to its community. The remainder of the notebook details the R code to implement the loading of this data into R and some simple subsequent analysis. The structure of the code in this instance is very similar to that of the other examples cited. To read entire content, click here https://goo.gl/71mCCX #DataScience #Cloud

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doctorcindia · 8 years ago

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Predicting medical chronic conditions with Machine Learning

Note - Some parts of this post requires some familiarity with basics of Machine Learning. These terms should be understood in a technical form - Binary Classification, Accuracy, AUC, Biased Dataset

TLDR -

It is possible to build a system to predict medical chronic conditions with ML.

The path to actually building an ML system from scratch is long and winding and will probably differ for each company. It’s very messy and undefined in the start - and that's ok.

You do NOT need a huge amount of data to start. Use proxies and try to get some real world data points.

There are plenty of ways to use the initial results in a commercial application - especially for targeting/identifying customer types.

Read the newly released Machine Learning Yearning if you don’t know where to start.

DoctorC has been doing diagnostics for 3 years now. We have gone from running operations on spreadsheet to end to end automated systems which handle everything, from placing an order, to delivery of reports. We also store all reports and some report values for our customers so that they can easily access their medical history from anywhere.

A few months ago, we started an initiative to see if we can apply ML on our data and get some useful applications out of it. We are an extremely small company with very limited amount of resources. So it was basically just me running some experiments and dedicating only a few hours a week.

The first question we asked ourselves before starting was - “How is it going to be useful to us as a business?”. The answer was surprisingly easy.

We have two kinds of customers -

People who undergo some illness/accident etc where they need some medical help - but only one time.

People who have chronic conditions like hypertension, diabetes, cholesterol issues etc.

#1 are transactional and #2 are our repeat customers. #2 use/need our service the most and they are consequently very valuable to us. In Urban India, chronic conditions (non communicable diseases) are on the rise rapidly and the prevalence of diseases vary from 15% all the way to 35% (WHO link - http://www.who.int/choice/publications/Chronic_diseaseIndia.pdf).

These are the customers we are looking for. So the question boiled down to - “How do we identify people with chronic conditions?”. Once we identify them - we can enroll them in a program specifically tailored for people who need medications and diagnostic tests frequently.

The hardest point - Starting

We needed to start with a training set of people who are identified as chronic. We had 0 points of data for this.

So we looked for proxies. “What behaviour indicates if a person has a chronic condition?”. Answer - People who used our services frequently are more likely to be chronic.

We keep track of every test that was bought and their results for every customer. Therefore, we had a (comparatively speaking) rich medical history at our fingertips. On top of that - our in-house proprietary system can “read” a diagnostic report and infer structured medical data for a whole array of tests.

Based on this, we started with an initial training set of a couple of hundred people who were deemed “chronic”. We used another set of infrequent buyers as negative examples for our model.

I explored a whole bunch of options on what platform to use for training ML - Scikit Learn, Tensorflow, AWS Machine Learning and Microsoft Azure. Azure’s ease of use puts it in another league altogether - especially for people who want to just apply existing ML algorithms. Drag and drop, kicking off experiments parallely, easy to construct flows etc. allow you to move really really fast as compared to writing code.

This might become a bottleneck later as we scale or it might become more expensive to run - but the tools they provide save tons of time, especially for prototyping and experimentation. I highly recommend trying out Azure - their free tier gives a good taste of what’s possible on their platform.

Before you start, or while you are playing with your dataset - you need to decide what your “One True Metric™” is. This is the thing you are going to optimize for while evaluating different machine learning models. By definition, it is very specific to your problem and cannot be purely decided based on a formula.

For us, it was identifying people with chronic conditions with a highly imbalanced data set (we have a lot less people with chronic conditions compared to normal population). It’s a binary classification problem. I chose AUC as a measure and started experiments to optimize that. Why did I not choose Accuracy? That is a post for another day.

We did an initial split of 50/50 of positive and negative samples to ensure we didn’t bias the system with a small initial set. Then i started my experiments. This is the messy part - you have to start from the simplest models and run different models simultaneously on the same data.

The first set of results yielded AUC curve similar to this -

Tight Iterations

We did our first real world test with a model of an AUC of 0.58 (which is not a very good score). We took the top 100 predictions by the model and started verifying if the identified people were chronic. We recorded this data and then used it to create a newer model. This gave us another 100 predictions. Then we repeated the cycle again.

The model started improving with each iteration. Reconstructing new model with new data took only a couple of days and the model training process itself was only a few minutes. Gathering the data was the only bottleneck.

Our model’s curve improved as shown below. And our total dataset from a raw data standpoint was around 1.2 million discrete values. Our accuracy was approaching ~80% (first couple of hundred predictions for every iteration). The AUC of the best model would vary from 0.74 to 0.80. The accuracy had a steep fall afterwards, but it was still significantly better than the 15% to 20% accuracy you would get with a random sample.

Predictive Factors

More interesting were the predictive factors for chronic conditions. While I cannot delve into too many details, one of the most interesting find was that Vitamin D (both the number of purchases done and the values of it) were one of the most predictive factors for someone being chronic or not. It neatly fits into the current research which suggests that Vit D is extremely important to maintain since it affects almost every system in our body. You should get Vit D levels checked every 6 months or a year - especially if a large part of your day is spent indoors.

Conclusion

Yes, you can predict, with a high degree of accuracy as well as high AUC, if someone is suffering from a chronic condition based on a combination of their purchase behavior (surprising) and their test values (not very surprising, still exciting). The next question was whether we could actually hone down to a specific condition like Diabetes, Thyroid disorders etc. That is a post for another day.

There is also the long term possibility of actually providing diagnosis while working side by side with doctors. This system is a small step in fulfilling that vision. We have miles to go before we sleep.

We are very excited about the possibilities that this kind of data enables. If you would like access to this data (especially for medical research purposes) or would like to know additional details please contact me on karan at the rate doctorc dot in.

#machine learning #healthcare #artificial intelligence #ai #ml

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gordonwilliamsweb · 4 years ago

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‘I love hearing my Rice Krispies’

Retiree Greg Green has faced more than his share of challenges.

Born with congenital glaucoma, his sight deteriorated over time until he lost his vision completely in 2012. To top it off, Meniere’s disease affected his hearing.

Now blind and nearly deaf, the 68-year-old counts his blessings.

“Life is not about how many times I fall down,” Green said. “It’s about how many times I get up and keep going.”

A story of perseverance

After graduating Belding High School in 1971, Green started working as a janitor at a (then) small company named Amway Corporation in Ada, Michigan. Although blind in his right eye and with limited vision in his left, he enjoyed toying with his first computer, a little Tandy 64. He taught himself BASIC language programming, and parlayed his creativity and willingness to learn into a long career in information technology.

“It was a job I loved, not a doldrum,” Green said. “I loved creating things and solving problems.”

When his second daughter, Heidi, was also born with congenital glaucoma, much of the family’s time and resources were spent getting both Greg and Heidi needed medical attention. The family got by with a run-down AMC Gremlin and shopping at yard sales.

“God was faithful, and I thank him for his care,” Green said. “It sure taught me how to trust God and work hard.”

In his mid-30s, Green experienced major bouts of vertigo that slammed him to the floor without any warning. A neurologist diagnosed Meniere’s disease, a disorder of the inner ear that leads to vertigo and eventual hearing loss. In Green’s case, the disease robbed him of hearing in his left ear about 15 years ago, and the right ear became worse over time.

Hearing aids alleviated the problem for many years. But eventually they weren’t enough. While others with hearing loss may rely on reading lips, that wasn’t an option for Green, who can’t distinguish between dark and light.

His communication became nearly cut off.

Then, in 2017, Green saw Gregory Artz, MD, a specialist in otology and neurotology with Grand Rapids Ear, Nose and Throat, who is credentialed to operate at Spectrum Health hospitals. Dr. Artz recommended a cochlear implant, a device that picks up sound with a microphone and delivers it to the auditory nerve.

Next he met Darcy Jaarsma, AuD, an audiologist in the neuro diagnostics department of Spectrum Health Butterworth Hospital, who tested Green’s hearing and confirmed he was a good candidate for a cochlear implant.

After receiving an implant in his left ear, Green quickly realized that it wasn’t an instant solution. When his device was turned on a few weeks after surgery, the sounds he heard? Unrecognizable.

“All I heard was a really squeaky sound, and I had zero understanding,” said Green, noting that voices reminded him of early Mickey Mouse movies.

The issue didn’t surprise Dr. Jaarsma.

“The way a cochlear implant provides sound is completely different from the sounds you and I hear,” she said. “There definitely is a time period it takes to acclimate.”

Green, a self-described “tech head,” took on the challenge with determination.

He created an alphabetized spreadsheet of 21,000 different words, then used screen-reading software to listen to the words for hours on end every day.

For the first few months, he couldn’t understand a word.

“Luckily I have a good strong level of perseverance,” Green said. “I was taught as a kid that you work on it until you get it done. I was determined to get the job done if it killed me.”

He recalled the words of inventor Thomas Edison, who also had hearing difficulties: “Genius is 1% inspiration and 99% perspiration.”

“For me, the inspiration was the spreadsheet, but the perspiration was working through it so slowly for months,” Green said.

Within a year, he trained himself to the point of understanding 93% of words using the implants in his left ear.

Unfortunately, as the left ear improved, the right one worsened.

Late in 2019, he received a cochlear implant for his right ear.

It was time to go back to work on this self-created audio therapy.

“I’ve been hammering away at the spreadsheet about four to five hours a day,” he said. “It really helps with communication skills.”

Dr. Jaarsma said Green is an ideal patient.

“It’s definitely patients who have a positive outlook on life, and are grateful for what the technology can do, who receive the most benefit and do the best with their implant,” she said. “And patients who ‘practice’ listening, like Greg did with his computer program, maximize their outcomes.”

In the world of cochlear implant patients, Green is a bit of a rock star. In fact, he was invited to share his story to a group of otolaryngologists in West Michigan in March.

“It was a thrill to tell my story,” Green said. “They were very receptive.”

‘Keep on keeping on’

Green’s motto is “keep on keeping on,” and that’s exactly what he does.

After retirement, Green and his wife, Louise, moved to the Allegan area to be near family.

He’s attuned to the little sounds that make up his world: cars going past the house, water running from a faucet, shoelaces being tied.

Even food noises, like burgers frying and wrappers coming off a slice of cheese. And the snap, crackle, pop of a bowl of cereal.

“I love hearing my Rice Krispies,” Green said.

Green stays in shape mentally and physically. A World War II buff, he enjoys listening to books and walks 3 miles on the treadmill daily. He also spends time encouraging others in his church through phone calls and inspiring emails.

Throughout it all, Green appreciated the patience of Louise, his wife of 47 years, his two adult daughters and their families.

“They have been so supportive and patient with the old man. I understand trying to deal with a hearing impaired person who is also blind isn’t easy,” he said.

‘I love hearing my Rice Krispies’ published first on https://nootropicspowdersupplier.tumblr.com/

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michellelinkous · 4 years ago