In a medical landscape increasingly dominated by algorithmic decision-making, Dr. Michael Cohen delivers a startling reminder that the most effective treatment plan often begins not with a protocol, but with a question. John Campbell's latest deep dive into the concept of "N-of-1" medicine challenges the prevailing orthodoxy of standardized care, arguing that for complex issues like infertility, the "normal" lab result is often a dangerous lie. This is not merely a discussion about vitamins; it is a critique of a system that prioritizes population averages over individual physiology, potentially steering patients toward invasive, high-risk interventions when a simple metabolic correction might suffice.
The Trap of the Average
The core of the argument rests on a fundamental flaw in how modern medicine interprets data. Campbell notes that Dr. Cohen, a general practitioner with nearly three decades of experience, observes a shift toward "stereotyping, a collectivization, a we must follow the guidelines sort of approach." While the intention behind evidence-based guidelines is to raise the minimum standard of care, Campbell suggests this compartmentalization often fails the individual. "The problem with evidence-based guidelines is also that they can miss things," Campbell writes, highlighting that human biology is too variable to fit neatly into a single algorithm. "Our bodies are different. Everyone's genetic is different. Our environments are different. Our microbiomes are different."
This framing is compelling because it exposes the limitations of the "one-size-fits-all" model without dismissing the value of data. It recalls the historical evolution of the N-of-1 trial, a methodology that gained traction in the 1990s to test interventions on single patients when large-scale studies were impossible. Campbell effectively uses this context to argue that we have regressed, allowing broad guidelines to obscure the specific metabolic realities of the patient in front of the doctor. As Campbell puts it, "If we were just following guidelines, we could get rid of doctors and just have an AI algorithm to an extent, couldn't we?" The implication is stark: the human element of medical intuition is being eroded by a reliance on statistical norms that may not apply to the specific individual.
If we were just following guidelines, we could get rid of doctors and just have an AI algorithm to an extent, couldn't we?
The Invisible Deficit
The piece pivots to a concrete, high-stakes example: infertility. Here, Campbell details how Dr. Cohen identifies a critical gap in routine diagnostics. The standard blood count, often the first line of inquiry, can appear perfectly normal even when a patient is functionally iron-deficient. "Unless you're specifically looking for them, no," Campbell paraphrases Cohen's view on why routine tests miss the mark. The issue lies in the interpretation of ferritin levels. Campbell explains that laboratory reference ranges are often based on the average population, which for women of childbearing age includes many with depleted reserves. "The reality is that unless you've got a ferritin of at least 30 and I would say probably around 50, you are likely deficient in iron," Campbell writes, quoting Cohen's clinical threshold.
This distinction is vital. A patient might have a "normal" hemoglobin level but lack the iron reserves necessary for optimal cellular function. Campbell elaborates on the physiological consequences, noting that iron is crucial for the electron transport chain and ATP production within the mitochondria. Without adequate iron, the body is essentially "running on empty." This metabolic deficit compromises egg quality, endometrial thickness, and embryo viability. "The enzymes in the mitochondria don't work so well," Campbell reports, summarizing Cohen's explanation of why subclinical deficiency can lead to failed conception even when the patient appears healthy on paper.
Critics might note that relying on a single nutrient correction as a panacea for infertility risks oversimplifying a multifactorial condition. Infertility often involves complex hormonal, genetic, or structural issues that no amount of iron can fix. However, Campbell balances this by emphasizing that Cohen's approach is about establishing a "physiological background" rather than guaranteeing a cure. The argument is not that iron is the only answer, but that it is a necessary foundation that is frequently overlooked.
Beyond the Protocol
The most powerful evidence Campbell presents is the anecdotal success of bypassing the standard fertility pathway. He recounts a case where a couple, poised to begin aggressive hormonal treatments, was instead advised to correct their micronutrient deficiencies. "I said, 'Look, just slow down for a second. Let's just do some basic tests over here,'" Campbell quotes Cohen describing his intervention. The result was not just a pregnancy, but twins, achieved without the risks of ovarian hyperstimulation syndrome or the emotional toll of invasive procedures. "We never saw the specialist in the end and we never had the treatment," Campbell relays the patient's account. "But we took the iron and the vitamins and everything and we had twins."
This narrative arc reinforces the broader theme of the series: the value of asking "why" before acting. Campbell connects this to the concept of pharmacogenomics, where treatment is tailored to an individual's genetic makeup, suggesting that we are moving toward an era where "bespoke" care is not a luxury but a necessity. "You want their cellular function to be working at its best," Campbell writes, capturing the essence of Cohen's philosophy. "Their cells need to function at their most optimal way."
We never saw the specialist in the end and we never had the treatment. But we took the iron and the vitamins and everything and we had twins.
Bottom Line
Campbell's commentary on Dr. Cohen's "N-of-1" approach offers a necessary corrective to the over-reliance on standardized medical algorithms, proving that the most advanced tool in a doctor's arsenal is often the willingness to look deeper than the reference range. While the argument risks oversimplifying complex reproductive challenges, its strongest point is the demonstration that subclinical deficiencies can derail fertility long before a patient ever meets a specialist. The reader is left with a clear imperative: in an age of automated care, the most radical act is still to treat the individual, not the statistic.