Nine Pints: A Journey Through the Money, Medicine, and Mysteries of Blood
Bibliographic record
Abstract
Despite a busy clinical life, I find time to read creative medical nonfiction, and I refuse to see this as an indulgence. Instead, it is an investment in empathy and a reminder of why the social context of medicine is important. If you can relate, then I suggest making haste to your local bookseller, library, or computer to pick up or download Rose George’s latest book, Nine Pints. Released in October 2018, the title reminds us of the approximate blood volume sloshing around in our bodies. The intriguing subheading, A Journey Through the Money, Medicine, andMysteries of Blood, presages a book about the traditions and symbolism of blood, plus cutting-edge science, political expose, engaging history, and the patient experience—including her own patient experience. In my (occasionally) humble opinion, and to paraphrase the book jacket, it is a “bloody good read.” Rose George’s paean to blood—the literal elixir of life—is no traditional medical text. This is clear from page 1. Its opening dedication is not to an august individual, but instead, it celebrates the UK National Health Service. Similarly, the opening quote is not the considered words of a bioscientist, but the poignant thanks of a pediatric patient: “Blood makes me feel better and once I’ve had blood I want to play with my toys again.” She does stalwart work by summarizing complex important topics such as the resurgence of whole blood donation, the allure of blood doping, the attraction of synthetic and cultured blood, and the diagnostic possibility of “liquid biopsy.” The science matters, but so does the politics of blood. As just one example, despite decades as a doctor, I finally understand the central fantastic paradox of donation, namely that a voluntary system is more reliable and safer than exchanging bucks for blood. Rose George is a popular science writer and journalist with a bachelor of arts from Oxford; not a health care professional. This is her fourth book and the most clinically relevant one. Like my doctoring job, her books are about comforting the afflicted and afflicting the comfortable and addressing the worthy but unheralded causes. George’s first book, A Life Removed: Hunting for Refuge in the Modern World (Penguin 2004), highlights those displaced by civil war. Her second book, The Big Necessity: The Unmentionable World of Human Waste (Metropolitan/Portobello 2008), argues that sanitation is the world’s most neglected public health issue. George’s peripatetic reporting reminds us that much of what matters happens away from the first-world gaze. This book proffers reports from Delhi and Nepal, South Africa, and indigenous Canada. This global perspective emphasizes that the seemingly ordinary act of donation is astonishing, and that discussions about blood are replete with contradictions. For example, leeches once built fortunes, then represented quackery, and have now returned to the bleeding edge. Blood can be life-saving, but it is a vector for death and a byword for tribalism. Blood is immensely valuable, but for centuries, it was drained by the bowlful. Her story of bloodletting also reminds us that dogma costs lives, and doctors can hurt while attempting to heal. George’s journalistic style means never shying away from her opinions and judgment. Readers of this Journal might prefer her to stick to objective facts and figures and to dedicate less space to menstruation and so-called “blood rejuvenation.” However, I believe that consternation and social justice concerns are justified, especially regarding the infected blood scandals of the 1980s, and because women are still shamed and banished during menses. Regardless, George gives equal time to blood villains, blood loonies, and blood heroes. Nine Pints is 351 pages of engaging popular science. It covers not only the pioneering scientists and volunteers who created the modern blood service, but also the social entrepreneurs who help stigmatized low-income women. George is also hagiographic about trauma teams and how they mix high tech and hard graft. She assists us doctors by informing the public that bleeding may be the “biggest disease people have never heard of.” She concludes by stating: “Blood is not done teaching us what it can do. More wonders will come.” For that, clinicians, researchers, and patients can all be grateful. Peter G. Brindley, MD, FRCPC, FRCP (Edin), FRCP (Lond)Department of Critical Care MedicineDepartment of Anesthesiology and Pain MedicineDossetor Ethics CentreUniversity of AlbertaEdmonton, Canada[email protected]
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.012 |
| Scholarly communication | 0.015 | 0.016 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.017 |
| Insufficient payload (model declined to judge) | 0.016 | 0.006 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".