Numbers.

Millions of them.

Columns upon columns, rows following more rows. Square and squiggly, brutal and austere, stoic or with a multitude of decimal points. Waiting for someone to make them tell a story, sing a song. Waiting for someone to figure out if there was a song in them at all.

The column headings seemed to blur into a melting pot of meaning. Age, gender, body mass index, blood pressure, cholesterol, resting glucose, ELISA quantifications of lactate plus a multitude of metabolites, enzymes and hormones monitored in blood, urine, saliva. Sometimes even DNA sequencing and qPCR results, both for humans and their respective microbiotas. Measurements the significance of which no one can be asked to remember by heart. Numbers that the program was begging to compare, if someone were so kind as to tell it exactly what to do. Someone who could make the numbers meaningful, help avoid the fate usually reserved (not out loud of course) for any form of statistical analysis on impossibly large datasets.

Because there are Lies; there are Damn Lies. And then there are Statistics.

The student knew the expression (not that it is attributed to Mark Twain, supposedly quoting Benjamin Disraeli, though); it was hammered in by the epidemiologist she was working with (for) on her internship project.

Not that it helped. This was supposed to be fun, she thought, plodding through the unending Excel file, copy-pasting selected columns into that mysterious SPSS program everyone in the lab talked about in reverenced whispers, the user manual handed to her like an apocryphal sacred text. (Did they know it had been developed for Social Sciences, which was what two of the S’s represented, she wondered?). Fun as in Summer, fun as in travel to exotic places, fun as in meeting exciting new people, fun as in figuring out how the rest of the world viewed medical training. Except that to embark on these wondrous adventures you had to figure out medical training where you were first.

It was not exactly how this supposedly triumphant journey she had been promised was turning out to be. Sure, it was exciting. Sure, she had met good friends to last a lifetime (and obnoxious assholes to last two or three). Sure, some subjects were great and she had really enjoyed all the activities that brought students closer to actual research or clinical practice. But that had been offset by unexpected failures, which had seeped through what had once been an unshakable confidence.

As proof, she recognized saliva measurements for alpha-amylase and cortisol flashing across the screen for the stress markers they were. One for the sympathetic nervous system, one for the hypothalamus-pituitary axis. Why did she know this? To control one’s current weaknesses one must learn its signs, and she had recently become all too familiar with those two. Too bad the same wasn’t true of the names and locations of all the bones, muscles, nerves and sutures in the human head, which she supposedly had to parrot back from memory during a stupid oral exam, under the relentless pressure of an insufferable professor. No use wondering what all those names would one day be good for. It was a test, another obstacle course; a part of the process most of her friends, enemies, and long lists of other anonymous students had completed.

But not her, not even after three tries. In the end nervousness always derailed her brain, the professor pounced on any weakness he sensed, and that was that; better luck next time. Medicine is performance under pressure, the professor said – today it was random bones, tomorrow someone’s life might depend of whether she could get her stuff sorted out. It was all well and good, except for that professional smirk on his lips, suggesting he knew for a fact that she didn’t belong.

She’d prove him wrong, this she knew. Even if it was the last think she ever did, even if she quit Medical School right afterwards to join her parents’ travel agency business, which had been their original plan anyway. But right now, she was forced to languish in her own school hospital for the summer internship project, rather than bask in the foreign glory of Italy, Germany, Brazil, Canada, Indonesia, Australia, Cape Verde. Those glamorous destinations were for the top students in the course. At the very least, the above-average ones.

There are two things you learn gradually while working your way through training, whether in primary school, university or on the job. One is that, however hard you try, you will never escape morons or bullies. They may change shape, style or wardrobe, but they never disappear. If you can’t identify them, the only likely answer is that you are them. The second thing is that, however good you are, there is an increased likelihood that there will be someone better, as primary school turns to high school turns to college; it’s purely a matter of concentrating the sample. Not necessarily at all levels or all the time, but regardless. Depending on your internal mechanisms and outlook on life these can be either trivial or daunting discoveries.

That is the curse of, among many other places, Medical School. It brings together previous college and high school alphas, men and (now mostly) women who are used to having grades and evaluations sing their praises. But in this novel reality the game begins anew, and statistics predicts that a group of high school geniuses moving on to the next level will, inevitably, include half that reside below the dreaded midline.

Interestingly she knew that at its core the word “mediocre” did not mean “bad”. It basically meant “average”, by definition not bad (not good either). Except one word sounds like a dooming curse, while the other seems to pull you through at the very last moment, avoiding the “below average” crowd. Like “abortion” or “pregnancy interruption” (or “cloning” and “somatic cell nuclear transfer”) these are expressions that pretend to be very different, while standing on the exact same spot. Of course, this is easy to discuss in the abstract: when gathering the best prospects and joining them in one sole group, logic dictates that inevitably not all of them will remain the “best”; its statistically impossible.

But it can be hard when statistics happen to you. And statistics had happened to her.

The previous year had been worse though, so at least there had been progress… At that time, besides the head exam, she had also missed out on the extremities one with yet another insufferable professor (what was it with her and memorizing the exact names and locations of bones, ligaments, nerves, muscles?), and had been exiled to medical community work in a troubled neighborhood, where only the truly committed or those completely devoid of options chose to tread. There she had met both impressive people who wanted to better themselves and those around them, and good-for-nothing cheats with iPhones bought off government subsidies who gave credence to the caricature of poor neighborhoods she had watched her parents buy into during recent election campaigns.

At least this year, having squeaked by on the limb exam, she was indoors. The AC disguised the impossible August heat. And this was part of an important project the hospital was involved in, monitoring the effects of several ongoing clinical trials that had been green-lit all at once, by way of the multitudes of additional exams carried out not really because they were strictly necessary for each one of the trials, but because they could. The patients had signed mostly generic informed consents and were coming in regardless; the material was available, and the projects had been (due to an uncharacteristic oversight) overfunded. It was the summer when all the technicians had needed to haggle for vacation time, to ensure all labs would be running at full speed throughout. Usually that had never been a concern in August; people are never as sick during the Summer … And it was also why they could use all the students they could find.

Naturally the lines and columns flowing in the several Excel files she had to check and put into the statistics program were not related to the main outcomes of the clinical trials. Summer interns (and “mediocre” ones, at that) could not be trusted with data that were supposed to figure out the efficiency of a novel antiepileptic drug, or how different regimens of immune suppressors being tested in liver transplants compared with the standard methodology. Or whatever was going on in a brain imaging study she was forgetting. But, if one also included all the controls for each trial, there were analyses galore on the largest cohort the hospital had ever seen, a cohort that could provide a cross-section of the community. Different ages, genders, lifestyle habits, genetic backgrounds, health issues. If they were ever going to get into the “Big Data” craze that was going around, the epidemiologist said (and the way she said it, it did not sound like a choice), what better way of starting? Not that the student was sure what “Big Data” meant, but she could certainly vouch for a daily deluge of numbers.

The epidemiologist had her whole team on it; in fact she seemed somewhat overexcited to even have a team, often reminiscing on the early days when she alone did all the statistics for the entire hospital. Right now, the epidemiologist was taking care of the more sensitive clinical trial data herself, while trying to come up with side projects for junior colleagues and graduate students, or whoever was around. Did epileptic women suffer from different kinds of stresses than men? Could they find genetic background links related to metabolic disease, which could perhaps even predict the need for a liver transplant down the road? What kinds of things changed with age, all other parameters being equal? What kind of lifestyle-related issues could they find, and how did they compare when gender, education, age, place of residence, zodiac or Chinese year sign were considered (the last two were a joke, the team thought…)?

Furthermore, did they have enough data to even thoroughly test a given hypothesis, so that the effort would be publishable? Enough numbers in comparable columns? What did the Power Analysis say? All of this was made harder by the fact that most of the results were blinded; the statistics team wasn’t supposed to know exactly where they had come from unless the epidemiologist could prove that some sort of major finding (or any presentable data, to be honest) might be pursued.

And this was the student’s summer internship project: helping to figure out what sort of science could come of it all. On one hand, it reminded her of why she had never considered going into the research part of Medicine, it just took too goddamned long to get anywhere. On the other, she felt grateful that she no longer had to check if the medications prescribed for grandma were taken by grandma, not cut up and peddled by some entrepreneur family member in burned-out street corners she had been sorry to learn were real.

Plus, the epidemiologist did not let anyone falter with her unending cheer, always optimistic they would find things that would prove the worth of statistics as a real research tool, not merely a validation scam many researchers and clinicians viewed them as, where you merely ran the program and chose the tests that “worked”.

More importantly, she had given (some) power of choice to all internship students. While doing their mindless chores, each could propose one research question to be addressed with the datasets. They could, as she put it, write their own song and see if the numbers would oblige, and sing it. During the hard first week the student had slowly discovered that this small thing made all the difference: it gave her a sense of purpose, brought the experience to a level well above “average”.

And by the way, the epidemiologist said to the student on her way out, she had also flunked all the Anatomy courses, three times in a row. In case the student hadn’t heard right, she repeated: the chief hospital epidemiologist had also been part of the statistics that made the course scary to newcomers. But she had dug herself out of that hole, one memorization mnemonic after another, and vowed never to work with anything vaguely related to bones and muscles ever again, unless they could be turned into numbers. Or did the poor marooned summer student think that this misery was being piled on her alone? That a totally novel experience was being offered as an exclusive deal?

The epidemiologist winked as she closed the door, leaving the student feeling both grateful and mortified. Grateful for obvious reasons, mortified as she realized that the bitching about her academic failures must have been considerable, for it to leak all the way to the top. But this was unimportant now. Oodles of numbers were in front of her. All that was left was to try to find some sort of purpose in them, make them sing. If not, at least hum, whistle. And go from there.

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© 2018 by the author; story dedicated to Diana Callebaut