Bibliographic record
Abstract
When Intensive Care Becomes Good End-of-Life Care Years ago, I began a research project with colleagues to demonstrate that physicians receive different, and arguably better, endof-life care because of our greater knowledge about dying.We hypothesized, as had others, that physicians would be more likely to die at home, would be less likely to die in an ICU, and would generally receive less "aggressive" care.It took years to complete the study.The findings were not what we had expected: Physicians did receive more palliative care, but they also were more likely to die in an ICU and, among those with cancer, more likely to receive chemotherapy in the last 6 months of life; it was more of everything (1).The work by Rolnick and colleagues (2) in this issue of the Journal (pp.832-839), demonstrating that family satisfaction with end-of-life care for patients dying in the hospital is higher for patients who have received intensive care, is aligned with our findings, and it challenges the general belief regarding what constitutes a "good" death.The study forces us to reevaluate what we strive for as caregivers when we have conversations with patients and families, helping them to navigate the complex decision-making regarding where to go in the hospital for care.This finding regarding greater satisfaction was true among medical and surgical subgroups, as well as when focused on those with severe, life-limiting illnesses.Whether these responses were a reaction to intensive monitoring and invasive support or, as I suspect is often the case, to the reassurance of skilled caregivers is not answered by these data.Although overall satisfaction with care was high, a notable (and very concerning) finding was that only 50% of individuals believed that pain was well controlled.As a physician who is responsible for determining which patients should or should not be admitted to an ICU, I have had my share of frustration admitting patients I believe I cannot help, that my efforts have been wasted because the patient will not leave the hospital or even the ICU.I have felt resentment toward patients and families who have insisted on coming to the ICU because I viewed intensive care primarily through the lens of what I and the rest of the team could do in terms of providing lifesaving therapies.However, that has changed.The man I married just 6 years ago died in June 2019.He was diagnosed with metastatic cancer less than 2 years after our wedding and died 4 years after that.He received palliative care but also chemotherapy in his last week of life and died in the ICU; we were both intensive care physicians, and the story was exactly as told writ large in my own study.There was clearly a comfort in the ICU-the knowledge that excellent nurses and doctors were always available.A symptom such as dyspnea is scary, either to experience oneself or to watch
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".