Posted on by omarmetwally

The Match

A sequel, with one interruption

By Omar Nabil Metwally, MD

First published 11 October 2026

I. The Review

My last essay ended with a census of my readership: North Korea, Syria, a pirate ship off the coast of Yemen, and ten or twenty Chinese Googles.

I can now report a human. His name is Ali. I sent him the link at night, and the next afternoon he sent back a review. He loved it. He hadn’t realized the interviews are all done on Zoom now. What a loss, he said. Then he thought about it some more: although, he guessed, it was expensive.

The AAMC needed a survey to get there. Ali needed four sentences.

My wife’s position is unchanged.

II. The Gunner

Ali thought it was a loss, so I told him what we lost.

Every medical school class has a gunner. For the pirates: a gunner is the student who treats medical school as a contest and intends to win it. I say this with respect. A gunner knows your patient’s potassium before you know your patient’s name.

A classmate of mine at Michigan wanted dermatology. Dermatology is about the hardest residency to get, for reasons every doctor understands: the pay is good, the hours are sane, and skin rarely has an emergency at 3 a.m.

He took no chances. He applied to fifty programs and flew to every one that would have him.

III. The G-Wagen

This was the old way. Every invitation meant a plane, a hotel, and the suit.

He paid the application fees. He paid Southwest. He paid Spirit. He paid a series of hotels selected for price.

By my estimate he spent a G-Wagen’s worth. I have no evidence of the G-Wagen. I had no evidence of the yacht either, and I stand by the yacht.

For the same money he could have bought the G-Wagen and driven it to the interviews. He would have pulled up to every dermatology program in America looking like a man who had already finished one.

Spirit went out of business this May. The loans, I assume, are still in the air.

IV. The Match

Residency is decided by a computer. You rank the programs. The programs rank you. On a Friday in March the computer reads both lists and tells you where you live now.

The computer considered fifty programs, a G-Wagen’s worth of travel, and every city Southwest serves. It sent him to the University of Michigan.

He was a medical student at the University of Michigan. He was already there. He could have walked.

I know the route. I walked it once, in a black suit.

I would like to feel superior about this. But I flew all over the country for medical school interviews, got into the one school I could walk to, and declined the rest. I did the same thing. He did it in a nicer car.

V. The Closet

I have never written about my own Match Day.

I did not want to go to residency. I have said elsewhere what I wanted, which was to start a company out of a childhood friend’s closet in San Francisco. He’s the only person I’ve known that I can sincerely still call a friend even after starting a company together, spending a year coding shoulder to shoulder during most of our waking hours, while also sharing rent for studio apartments in SF and NYC. I decided to take another “gap year”, which turned out to be the start of a career in gap years, after seriously considering a career in surgery during a mind-changing medical school surgery rotation (that deserves its own story).

The computer does not match to closets.

I did not have the courage to submit zero applications. That would have been obvious. So I applied to four programs in a specialty I had no interest in. I chose radiology. Although I admire visual art and consider myself someone with decent aesthetic taste, my mind tends to reach first to text and numbers when solving a problem before taking a visual approach.

I put on the black suit and interviewed at all four, with no serious intention of attending any of them. My classmate wore the suit for jobs he wanted. I wore it for four I did not.

In the end I decided to hold off on residency for at least a year. It turned out to be a year.

We all carried pagers then, the size of bricks. I once dropped one in the toilet in University Hospital and was under the impression that I had to fish it out and return it to security in order to be issued a new pager. But that deserves its own story too. Anyway, I knew what would happen when the algorithm finished its work. Everyone who matched would get a page congratulating them. Everyone who did not would be summoned to the dean’s office, slapped on the ass, and hustled into an unfilled residency spot in a specialty that may or may not be related to the applicant’s original interest. Bottom line is, you have a chance to redeem yourself and eventually become a licensed physician in a residency program.

I am no idiot. I knew what was coming. An email arrived silently in my inbox, telling me that I had not matched. Surprise, surprise. It was the inevitable outcome of my own making.

I turned off my pager and my phone. Then I did the only thing I could. I celebrated wildly with my friends, hugging and kissing, as though I had just landed a dermatology residency at an academic medical center with floors of perfectly reflective marble, and where the waiting lists are so long that patients perish outside on the front steps waiting for their first appointment. YES WE DID IT!!! I screamed in feigned ecstasy.

After about five minutes of celebrating, the receptionist huffed up the stairs to the small windowless room where my cohort of medical students was huddled.

“Omar, honey? You didn’t match. You need to come to the dean’s office, honey.” I quickly avoided eye contact with all of my classmates and darted to a remote bathroom that I reserved for emergencies like these.

My digestion is, overall, OK. On that particular day I made my way quickly to a bathroom deep in the bowels of the Medical Science II building and engaged in a continuous, fifteen-minute episode of watery diarrhea. It was catharsis in a gastroenterologic sense. The whole time I was trying to silence my pager. I had turned it off. It kept notifying me that I had not matched, even as I ripped out the AA batteries. I prayed that the woman who had huffed her way through a mile of indoor med sci labrynths wouldn’t track me down by my scent and walk into the bathroom. Omar, honey? I could imagine her  voice echo in the bathroom.

To make a long story short, I ended up learning to write iOS apps the old-fashioned way, which is a human actually writing the code. I had help from a friend, the only other physician coder I know. He is also a University of Michigan Medical School alumnus, an electrical engineer, and one of the most gifted programmers I know. He donated his time to meet me in cafés around Parnassus and in the UCSF medical library, where he helped me debug my GET and POST API calls. I owe him, at  least, a great deal of gratitude for all that time and help.

I did that for as long as I could, which was one year after medical school. Then I needed a paycheck, and I enlisted as a human battering ram for a local internal medicine residency program, where I met some of the most uniquely unforgettable and gifted people I’ve known: at St. Mary’s Hospital in San Francisco (now UCSF Health) and later at Highland Hospital in Oakland.

I am an internal medicine physician.

VI. Portland

An interruption.

This just popped into my brain.

Later I did it again, applying for a clinical informatics fellowship at Oregon Health & Science University. It is a  forward-looking university in one of my favorite cities. In reality, I ended up choosing UCSF. I was lucky enough to have many great options. In a parallel universe I went to Portland. The memory of a bright morning ride on the Seilbahn (Portland aerial tram) is a happy and lasting one.

I finished my shift at the county hospital in Oakland at 11 p.m. I got in my car with my white coat still on, drove to Oakland International, and flew to Portland. I checked into a hotel room that cost between $250 and $300 a night and slept in it for about two hours. That is roughly $140 per hour of sleep.

The morning after the interview I woke at 3:30 for the flight home. I woke with the hardest direction I have ever had. I am dictating this part, and the software has chosen the word direction. I am leaving it. It was the ordinary morning kind. Only the hour was unusual.

At security the scanner beeped. The TSA agent pointed to his screen. It showed the outline of a person, and on the outline, over my direction, a large red dot.

“I’m going to have to pat it down,” he said.

I was patted down without objection or resistance. Then I was on my way to the gate, to sip Portland-roasted coffee and wait for my flight back to Oakland.

Since then, when I go through airport security, I put my hands at my waist where they are clearly visible and ask the agent: do you need to pat me down?

Years later I told this to my family. Half of them are physicians. The other half are lawyers. My father snorted an insolent snort and said the TSA guy probably liked it.

I thought: he better have.

What was I saying?

VII. The Loss

So what did we lose?

Today’s gunner applies to fifty programs from his apartment. He does fifty interviews in one chair. On the screen there is no stool, and everyone is the same height. The camera shows him from the chest up. I was seen on a screen once during an interview trip, and the framing was different.

He spends nothing. In March the computer tells him he is staying where he is, and he has gone nowhere to find that out.

This is better. For decades we sent applicants around the country in black suits, on borrowed money, so that a computer could tell some of them to stay put. Ninety percent of applicants wanted the option of skipping it. I would have wanted it too.

The only thing lost is the story. Nobody pats today’s applicant down. My classmate has a story with fifty cities in it, and he paid a G-Wagen for it. I have Portland, and I paid for that too. That is experience.

His story cost me nothing. I just know the guy. That is reference.

VIII. Intellectual Property

I ended my message to Ali with a warning. If he writes a story about this before I get around to telling it, I’ll sue. I’ll sue him, and I’ll sue my classmate. For plagiarism.

I see the weakness in the case against my classmate. It’s his life. He lived it first, at great expense, and he has the receipts.

My position is that he only lived it. I’m the one who told somebody.

IX. Coda

The stopwatch is still running.

Experience is airport security with a 3:30AM direction. A machine can describe one. It has never been patted down for one.

Reference is a man who flew to fifty cities to end up where he started. I didn’t have to make him up.

Thank you for the opportunity.

Posted on by omarmetwally

Internal Medicine: Distilled

By Omar Nabil Metwally, MD
Internal Medicine Physician
First published 30 August 2026 · Revised and expanded with references

One of the most important classes that I attended as a Clinical Informatics Fellow at UCSF was a course on clinical research. This reflection surprises me in hindsight because I long associated “Clinical Informatics”, which was then a new medical specialty (I was in UCSF’s second class and their third Clinical Informatics Fellow), with the intersection of technology and patient care — a niche for technologically-affine physicians capable of transforming healthcare, if only (so the reasoning) they connected with the right decision makers, got on the right Teams calls, and joined the most elite mailing lists. I was not expecting to sit down almost 10 years later to write a blog post about what I then considered the driest of subjects: biostatistics.

In retrospect, I had a lot to learn, and I could have learned those valuable lessons with a more open and receptive mindset. I consider Professor Pletcher’s course significant in two regards. First, it gave me an opportunity to think deeply about the tests that doctors (especially non-surgeon physicians) routinely order on behalf of their patients and are expected to interpret and act upon correctly. Second, it planted the seed for the realization, many years after my time at Parnassus, that the specialty of Internal Medicine boils down to one concept: a priori likelihood.

There are two types of doctors that take care of people: physicians and surgeons. Physicians — doctors like internists and pediatricians — do a bulk of their work in the cognitive realm, which often takes the form of making a short-list of diagnoses and honing in possibilities (in medical jargon, this is called making a differential diagnosis). This is in contrast to surgeons, whose work tends to be more operative in a hands-on, physical sense than a physician. A physician who does not understand the tests they are ordering, the diagnostic consequences of their choice of test, and how to interpret the results, is like a surgeon without the physical skills necessary to perform a particular operation. I’m deliberately over-simplifying to make the point that despite the fact that test ordering and interpretation has traditionally been a core competency of physicians in general, I encounter an alarming number of physicians, new and experienced alike, who lack the skills to understand what they’re ordering (or not ordering) and how to correctly interpret positive and negative results. Equally alarming, and I suspect related, is organizational policies that narrowly prescribe diagnostic protocols in order to move a patient from point A to point B on the healthcare labyrinth — in the process, stripping physicians of what little autonomy they still have to exercise their clinical judgement.

The objective of this writing is to capture that lesson for any doctor who will ever order (or decide not to order) a test and be expected to interpret the result — if they are lucky to even have the choice.

The order that sounds correct

A middle-aged man presents with months of progressive hip and buttock pain. The pain is worst in the first hours after waking and after prolonged sitting. It wakes him at night. He has a years-long history of intermittent low back pain, a personal history of eosinophilic esophagitis, and a family history of autoimmune disease. Plain films show mild bilateral hip osteoarthritis — premature for his age. He asks for a rheumatology referral.

A reasonable-sounding plan: order an ANA and rheumatoid factor first. If negative, hold the referral. If positive, refer.

That plan has the shape of good medicine — screen, then escalate. It is also, for this presentation, close to backwards. Two errors are stacked inside it, and the second one is the more instructive.

Error one: the tests cannot see the disease

The clinical question here is axial spondyloarthritis. AxSpA is a seronegative spondyloarthropathy — and “seronegative” is not decoration. RF is expected to be negative. ANA has no association with the disease and appears nowhere in the ASAS classification criteria [1]. No result either test returns can move the probability of axSpA in either direction.

So the proposed gate was built from tests that cannot detect the condition being gated. A negative result would have been recorded as reassurance while carrying zero information about the actual question.

Error two: predictive value belongs to the patient, not the test

Here is the concept the wards tend to erode: sensitivity and specificity are properties of the assay. Positive and negative predictive value are properties of the encounter. The same ANA, on the same analyzer, means something entirely different depending on who is in the chair.

Do the arithmetic once and it inoculates you.

Worked example: the ANA in this patient

ANA is positive in roughly 20–30% of healthy adults at a 1:40 titer, and 10–15% at 1:80 [2]. Our patient has monoarticular hip pain with a mechanical mechanism, an axial pain pattern, and no features of connective tissue disease. Be generous and set the pretest probability of an ANA-associated disease at 0.5% — 1 in 200.

Per 1,000 similar patients Test positive Test negative
Disease present (5) 5 0
Disease absent (995) ~120 ~875
Total ~125 ~875
Assuming ~95% sensitivity and ~88% specificity at a 1:80 cutoff [3].

PPV = 5 / 125 = 4%. Twenty-four out of every twenty-five positives are false. A positive ANA in this patient is not a signal — it is noise wearing the costume of data.

And the costume is expensive. A positive ANA in the chart is never inert: it cascades to an ENA panel, a dsDNA, a “possible early connective tissue disease” note, a referral placed for the wrong reason, a patient reading about lupus at 2 a.m., and a label copied forward through every future chart review. The harm of a low-value test is rarely the test. It is the machinery the result switches on.

Worked example: the test that actually earns its place

Now run HLA-B27 through the same patient. Sensitivity is roughly 85% for axSpA — best established for radiographic disease, somewhat lower for non-radiographic axSpA and in non-European ancestries — with specificity around 90%, capped by a background allele frequency of roughly 6–8% in US populations of European descent (and higher still in Scandinavia) [4]. That yields LR+ ≈ 9 and LR− ≈ 0.15.

Given the inflammatory pain pattern, morning predominance, hip involvement, male sex, and family history, a pretest probability of 35% is defensible (pretest odds ≈ 0.54).

  • Positive: 0.54 × 9 = posterior odds 4.9 → ~83% post-test probability. Decision-changing.
  • Negative: 0.54 × 0.15 = posterior odds 0.08 → ~7% post-test probability. Also decision-changing, in the opposite direction.

That is the signature of a test worth ordering: both results move you substantially, from an intermediate starting point. Note the dependency, though — run that same B27 on unselected back pain with a 2% pretest probability and the PPV falls under 20%. The likelihood ratio is a property of the assay; the usefulness is a property of your clinical reasoning.

And the tests that are neither: CRP and ESR

Worth naming because their prominence in “inflammatory workups” oversells them. CRP is elevated in only 40–50% of axSpA — a normal value carries a likelihood ratio near 1 and excludes essentially nothing. Their value here is prognostic (elevated CRP is one of the strongest predictors of radiographic progression, alongside baseline syndesmophytes and smoking [5]), as a baseline for treatment monitoring and ASDAS scoring, and for flagging infection. Diagnostically, they are close to inert. Order them knowing which job they are doing.

A worked example everyone lived through: the COVID home test

During the pandemic the federal government mailed free rapid antigen tests to any household that asked — well over a billion tests moved through federal programs before distribution wound down and was finally suspended in March 2025 [6]. Today the same tests sit on pharmacy shelves at $10–20 a box, and most people with a cough don’t bother. That shift is the thesis of this essay playing out at national scale — though the arithmetic contains a surprise worth sitting with.

At the Omicron peak, roughly half of symptomatic adults with acute respiratory symptoms actually had COVID: in CDC’s outpatient surveillance network, 56% of symptomatic adults tested positive during Omicron predominance [7]. Rapid antigen tests in symptomatic people carry a pooled sensitivity of about 73% and a specificity of about 99.6% [8]. Per 1,000 symptomatic people at 50% prevalence: 365 true positives against 2 false ones — a positive predictive value near 99.5%. The test was superb, and it was superb because of who was taking it.

Today, the same symptoms in the same person carry perhaps a 10% probability of COVID in a typical week — the rest is rhinovirus, RSV, influenza, and everything else — and closer to 3% in a deep trough between waves. Same assay, same operating characteristics. At 10% prevalence: 73 true positives against about 4 false ones — PPV around 95%. At 3%: PPV around 85%.

Here is where the intuition usually goes wrong, and it is the most instructive moment in this essay. The PPV fell — but nowhere near as far as it did for the ANA in our patient, whose PPV was 4% at low pretest probability. Why the difference? Specificity. The antigen test generates false positives at a rate of about 0.4%; the ANA at a 1:80 cutoff generates them at about 12%. When prevalence drops, a test with a fraction-of-a-percent false-positive rate degrades gracefully, and a test with a double-digit false-positive rate falls off a cliff. Pretest probability sets your ceiling; specificity determines how fast you fall from it. A positive home COVID test today is still probably real. A positive ANA in a patient without connective-tissue-disease features almost never is.

One more property worth internalizing: the sensitivity of a strategy is not the sensitivity of a test. A single antigen test on the first day of symptoms detects only about 60% of infections, but two tests taken 48 hours apart detect over 93% [9] — which is exactly why the FDA recommends repeat testing after a negative result [10]. Operating characteristics belong not just to the assay but to how you deploy it.

So why did universal home testing wind down? Partly for structural reasons that have nothing to do with epidemiology: the public health emergency ended in May 2023 and took the insurer free-test mandate with it, federal distribution stopped, and the tests now cost real money. But the clinical logic tracks the third question of this essay: will the result change what I do next? Under CDC’s unified respiratory-virus guidance, isolation is now symptom-based — stay home until improving and fever-free for 24 hours — regardless of which virus you have [11]. For a healthy, low-risk adult with mild symptoms, a positive test changes little about their own care.

And notice that the answer flips right back for the people in whom question three is still answered yes: anyone eligible for antiviral therapy, where a positive result starts a five-day treatment clock [12]; anyone about to sit down with an immunocompromised relative; healthcare workers and congregate settings, which the relaxed guidance explicitly does not cover. The newer over-the-counter combination flu/COVID tests sharpen the point further — in a high-risk patient, distinguishing influenza from COVID selects between two different antivirals. Same test, same prevalence, opposite recommendation — because the question being asked is different.

We ran a natural experiment on 300 million people, and the lesson was the one Professor Pletcher was teaching in a classroom on Parnassus: the test never changed. Who we gave it to, and what we planned to do with the answer, changed everything.

The three questions that replace the panel

The fix isn’t memorizing which panel goes with which complaint — panels are how we got here. It’s a habit, asked in order, before anything is ordered:

  1. What disease am I testing for? Named and specific, out loud. Not “inflammatory something.” If you can’t name the disease, you can’t choose the test — tests are only interpretable against a named hypothesis.
  2. What is my pretest probability — even crudely? “Under 5%, coin flip, or over 50%” is enough resolution to change behavior. The discipline is committing to a number before the result exists. A probability estimated afterward isn’t an estimate; it’s a rationalization.
  3. Will either result change what I do next? If positive changes nothing and negative changes nothing, the test’s only outputs are cost, noise, and cascade risk.

Run the case through them. Disease: axSpA. Pretest probability: intermediate. Will ANA/RF change the next step? No — the MRI and the referral were indicated regardless of serology. Question three deletes the ANA in about four seconds. It also reveals something sharper: the problem wasn’t only which tests formed the gate. There should have been no gate.

Why good physicians make this error

This is not stupidity. It is a systems failure with a cognitive assist, and you should recognize the ingredients, because they will be your working conditions:

  • Order sets are frozen decisions. Someone decided once that ANA + RF = “rheum labs,” and the EHR has been re-making that decision on autopilot ever since. Every checkbox panel is a colleague from the past overriding your present reasoning — sometimes correctly, and you won’t know which times unless you look.
  • Covering is medicine at low resolution. An unfamiliar chart, an intermediary, a message queue. Pattern-matching to “joint pain → rheum panel” is what cognition produces under those constraints. The antidote isn’t heroic effort; it’s cheap heuristics that survive low resolution — which is what the three questions are.
  • “Baseline” is a thought-terminating word. Nobody argues with a baseline. But a baseline is just a test whose pretest probability nobody bothered to state.

And the sequel matters. When this reasoning was raised — politely, in writing — the physician reviewed the chart and ordered the appropriate labs within two hours. That responsiveness is the trait to emulate. The initial error was ordinary; the rapid update was excellent medicine. If you take a villain from this story, you’ve misread it. The villain is the reflex, and every one of us has it.

The distillation

A test result is not information about the patient. It is information about the patient conditional on why you ordered it.

The test doesn’t know who you ordered it on. You do. The entire interpretive weight of every result you will ever receive rests on the probability you assigned — explicitly, or by default — before you clicked the order.

Assign it explicitly. Every time. Ten seconds, and it is the highest-yield ten seconds in diagnostic medicine.

References

  1. Rudwaleit M, van der Heijde D, Landewé R, et al. The development of Assessment of SpondyloArthritis international Society classification criteria for axial spondyloarthritis (part II): validation and final selection. Ann Rheum Dis. 2009;68(6):777–783.
  2. Tan EM, Feltkamp TE, Smolen JS, et al. Range of antinuclear antibodies in “healthy” individuals. Arthritis Rheum. 1997;40(9):1601–1611.
  3. Leuchten N, Hoyer A, Brinks R, et al. Performance of antinuclear antibodies for classifying systemic lupus erythematosus: a systematic literature review and meta-regression of diagnostic data. Arthritis Care Res (Hoboken). 2018;70(3):428–438.
  4. Reveille JD, Hirsch R, Dillon CF, Carroll MD, Weisman MH. The prevalence of HLA-B27 in the United States: data from the US National Health and Nutrition Examination Survey, 2009. Arthritis Rheum. 2012;64(5):1407–1411.
  5. Poddubnyy D, Rudwaleit M, Haibel H, et al. Rates and predictors of radiographic sacroiliitis progression over 2 years in patients with axial spondyloarthritis. Ann Rheum Dis. 2011;70(8):1369–1374.
  6. US Department of Health and Human Services. Federal at-home COVID-19 test distribution program (COVIDTests.gov), January 2022; distribution suspended March 2025.
  7. Kim SS, Chung JR, Talbot HK, et al. Effectiveness of two and three mRNA COVID-19 vaccine doses against Omicron- and Delta-related outpatient illness among adults, October 2021–February 2022. Influenza Other Respir Viruses. 2022;16(6):975–985.
  8. Dinnes J, Sharma P, Berhane S, et al. Rapid, point-of-care antigen tests for diagnosis of SARS-CoV-2 infection. Cochrane Database Syst Rev. 2025;CD013705.
  9. Soni A, Herbert C, Lin H, et al. Performance of rapid antigen tests to detect symptomatic and asymptomatic SARS-CoV-2 infection: a prospective cohort study. Ann Intern Med. 2023;176(7):975–982.
  10. US Food and Drug Administration. At-home COVID-19 antigen tests: take steps to reduce your risk of false negative results. FDA Safety Communication, August 2022.
  11. Centers for Disease Control and Prevention. Respiratory virus guidance. March 2024.
  12. US Food and Drug Administration. Nirmatrelvir-ritonavir (Paxlovid) prescribing information: treatment of mild-to-moderate COVID-19 in patients at high risk for progression, initiated within 5 days of symptom onset.

Clinical details are composite and deidentified. Test characteristics are approximate, vary by assay, cutoff, population, and timing, and are cited to their principal sources above — the arithmetic is illustrative, and the habit is the point.