Comment on: How U.S. Doctors Die: A Cohort Study of Healthcare Use at the End of Life
Bibliographic record
Abstract
To the Editor: In a stimulating study published in this Journal, Matlock and colleagues found that U.S. physicians are given more-intensive care than the general population at the end of their life.1 Although “it was expected that their knowledge of medicine and its limitations would be evident in their avoidance of high-intensity and end-of-life care,” Dr. Matlock findings suggest “a more mixed and nuanced picture” and also that the reply to the question of how one wants to die still merits more reflection. Leaving aside questionable efforts to freeze human bodies waiting to be resuscitated in the future, probably most people would prefer to die like the old man that Leonardo da Vinci described 5 centuries ago: “a few years before death, he said he had lived for one hundred years and that he felt a little tired and while he was sitting on a bed at the hospital of S.M. Nuova in Florence without any peculiar movement left quietly this life.” It is difficult to imagine a “romantic” view of death today, as artistically realized in a 2003 Canadian film, “Les Invasions Barbares,” and proposed in a blog by Richard Smith, former director of the British Medical Journal.2 The protagonist of the film removed his father (who was terminally ill) from a dreary hospital and dedicated all his personal time and economic resources to assist him in dying at home, surrounded by family and friends, with the aid of pharmacological therapy to fight pain. Richard Smith wrote that death from cancer is preferable to other types of sudden death, from dementia or organ failure, because it gives the person enough time to prepare how to die. Smith also suggested that the best therapies are love and morphine. Although his blog received much criticism, including personal insults to the author, the core message that time and love are essential to the dying person cannot be eluded. “Time is money”: Benjamin Franklin's advice to young tradesmen in 17483 was not in Dr. Elisabeth Kubler-Ross’ mind while she listened endlessly to individuals who were near death. She reported her experience in her book On Death and Dying, published nearly half a century ago.4 Its central message is the importance of listening to what people who are dying have to tell us about their needs. She also observed several “stages” in these individuals, such as denial of the initial diagnosis, isolation, anger, bargaining, depression, and acceptance of death. Many of these overlap, occur together, or are skipped altogether. Those who are around the dying person, such as doctors, nurses, and family members, may also experience these “stages.” If they are not recognized, dialog with the person who is dying may become difficult or impossible. It is thus necessary for healthcare professionals to have enough time to evaluate the personal, family, and social problems of their patients so as to reduce anxiety while waiting for nonurgent diagnostic and therapeutic procedures, to evaluate new methods and technologies carefully, and finally, to offer adequate emotional support to people who are dying and their families.5-7 “Love which moves the world and the other stars” is the last verse of Paradise by Dante Alighieri, Italy's greatest poet. Love is a powerful feeling that may remain merely a word if it is not transformed into “actions of love,” which require time. Family members and friends who surround the person who is dying should have enough love and time to face the last, most-difficult “stage,” depression, as Kubler-Ross describes. The sorrow we experience about the absence of a loved one during the terminal period in an environment in which there are healthcare professionals who are outsiders and there is a rupture of an interpersonal relationship may be even greater than what we feel about our own death and prevents us from attending to loved ones who remain alive. Dying in a hospital undoubtedly favors this factor. Our fear of death, our attempts to postpone it with overwhelming technology, the absence of adequate time to assist individuals who are dying with love are the major obstacles to our acceptance of death as a natural event and a part of life. Matlock's work indirectly suggests that physicians should be among the first to remove these obstacles. I wish to thank Mary Forrest for correcting the English. Conflict of Interest: None. Author Contributions: Dolara is sole author. Sponsor's Role: None.
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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 | 0.010 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.016 | 0.019 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".