The woke corruption of science

Calls to ‘trust the science’ need to be treated with severe scepticism. This was brought home by the recent debunking of a widely cited 2020 study in the prestigious journal, Proceedings of the National Academy of Sciences (PNAS). The article and the attention it attracted illustrate how the authority of science can be used to mislead the public.

The study at issue – entitled ‘Physician-patient racial concordance and disparities in birthing mortality for newborns’ – examined 1.8million childbirths in Florida between 1992 and 2015. It purported to show that black newborns died more frequently when cared for by white doctors than they do when cared for by black doctors. This led the researchers to conclude that ‘black physicians systemically outperform their colleagues when caring for black newborns’.

Most major media outlets interpreted this as a prime example of systemic racism in American healthcare. Some even wondered if perhaps white doctors were sabotaging the treatment of black infants. The findings were so shocking that Justice Ketanji Brown Jackson quoted the research in her dissent from the 2023 US Supreme Court ruling that ended affirmative action in higher education. Also in the affirmative-action case, several prestigious medical groups, including the American Medical Association and the American Academy of Pediatrics, filed an amicus brief containing the following conclusion: ‘For high-risk black newborns, having a black physician is tantamount to a miracle drug.’

The only problem is that the findings of the study were completely untrue.

The reason for the disparity in newborn deaths was not due to the race of the physicians or to systemic racism, but to a flawed study design. After four years, a second group of researchers finally revisited the study data and found the original researchers did not account for difference in birth weight, a key determinant of mortality in neonates. While uncommon, low birth weight occurs more frequently in black newborns and accounts for a disproportionate number of neonatal deaths.

Because these infants were usually treated at major medical centres, where most of the physicians are white, deaths in the original study attributed to white physicians were actually the result of their caring for sicker patients. After controlling for low birth weight, the difference in care between black and white physicians effectively disappeared.

This study was fundamentally flawed. When studying mortality in neonates, low birth weight is a key determinant. This is paediatrics 101. It is essential that low birth weight be factored in. Yet at every stage of the scientific publication process for this study, the role of low birth weight was ignored.

The problem began with the original authors. Before cause-and-effect conclusions can be drawn, any study of the relationship between mortality and care must account for severity of illness – in this case, low birth weight. For example, emergency-room patients with head trauma who receive CT scans have higher mortality than those patients who don’t have CT scans. This is because only those with more severe trauma are referred for scans. The higher mortality among CT-scanned patients has nothing to do with the CT scan itself.

In this case, the authors never even mentioned low birth weight in the article’s section on the limitations of the findings. One could give them the benefit of the doubt. After all, every researcher at one time or another has neglected an obvious variable. But such an obvious omission raises the suspicion that they wanted to obtain a desired result – that is, they wanted to demonstrate systemic racism in American healthcare. As Nobel laureate Richard Feynman once cautioned, ‘you must not fool yourself, and you are the easiest person to fool’.

At the pre-peer-review stage, the journal editors also failed to note the absence of low birth weight as a key factor in neonatal mortality. The PNAS editors who initially received the article are the pinnacle of scientific authority. They are all top scientists in their respective fields at major academic centres. This particular journal even includes a statistical review committee, which looks at methodology and statistics. It should have flagged the glaring omission of low birth weight immediately and sent the article back to the authors for revision before the next step of sending the article to outside peer reviewers.

And what about those outside peer reviewers? The whole job of these subject-specific experts is to read with a gimlet eye, looking for errors, contradictions, biases and flaws in study design. Not infrequently, they recommend rejecting publication of an article on the thinnest of pretexts. Overlooking severity of illness is not a minor mistake. It is a major study-invalidating error. It is almost unbelievable the peer reviewers did not reject the article on that basis. It raises the question of whether they wanted to see the publication of an example of systemic racism at the expense of a careful critique of the data.

After the outside peer reviewers, the article would have come back to the journal editors, in the post-peer-review phase. The original journal editors therefore had one more chance, with the help of the expert peer review comments, to consider whether the article should be published. Why in this case didn’t they ask what caused the excess mortality when white physicians cared for the infants? Did white doctors deny black newborns access to intensive care or ventilators or antibiotics? (These cases weren’t surgical, so surgical skill was not an issue.) In addition, if you believe in systemic racism of physicians then the differences in mortality were considerable (absent the consideration of low birth weight). They were almost too good (or bad) to be true. As the journal editors surely would have known, when data are too good to be true, they probably are not true.

After publication, the article would have been seen by scientific journalists. They are trained to evaluate and interpret science for the public. Journalists who read the initial article should have identified right away there was no control for severity of illness. Their failure to notice this suggests either incompetence or confirmation bias (that is, they believe so strongly that healthcare is systematically racist, this is precisely the result they expected to see.) If they did notice and did not report it, that is even worse. Did anyone in the community of scientific journalists really want to challenge the study?

After the scientific journalists come the lay journalists. When this study was reported in the lay press, especially in connection with the Supreme Court affirmative-action decision, it emphasised the disparity between the quality of black and white physicians and the huge effect on mortality in black newborns, which was going on for nearly a quarter of a century. Such an appalling situation would surely have been obvious to nurses, hospitals, patients and families well before the publication of this paper. Yet no journalists asked why no one had come forward in all that time to expose it.

If this debacle teaches us anything, it is to be far more sceptical when faced with studies of this kind. In one of his legendary lectures on science, Richard Feynman said that the layman has ‘as much right as anyone else, upon hearing about the experiments – but be patient and listen to all the evidence – to judge whether a sensible conclusion has been arrived at’. He added: ‘The experts who are leading you may be wrong.’

Remember this episode whenever someone tosses out the phrases ‘trust the science’ or its close cousin, ‘evidence-based’. This may be an attempt to pass off a political view as a scientific fact. Science is an ever-changing endeavour, difficult to interpret, subject to manipulation and susceptible to personal bias, as the 2020 PNAS study illustrates.

When it comes to science, it’s best to channel your inner Ronald Reagan, ‘Trust, but verify’.

Cory Franklin’s new book, The Covid Diaries 2020-2024: Anatomy of a Contagion As It Happened, is now available on Amazon in Kindle and book form.