“Everything has been tried and his heart can’t recover…”: A Descriptive Review of “Do Everything!” in the Archive of Ontario Consent and Capacity Board
Bibliographic record
Abstract
BACKGROUND: In end-of-life situations, the phrase "do everything" is sometimes invoked by physicians, patients, or substitute decision-makers (SDM), though its meaning is ambiguous. We examined instances of the phrase "do everything" in the archive of the Ontario Consent and Capacity Board (CCB) in Canada, a tribunal with judicial authority to adjudicate physician-patient conflicts in order to explore its potential meanings. METHODS: We systematically searched the CCB's online public archive from its inception to 2018 for any references to "do everything" in the context of critical care medicine and end-of-life care. Two independent assessors reviewed decisions, collected characteristics, and identified key themes. RESULTS: Of 598 cases in the archive, 41 referred to "do everything" in end-of-life situations. The phrase was overwhelmingly invoked by SDMs (38/41, 93%), typically to advocate for life-prolonging measures that contradicted physician advice. Physicians generally related "doing everything" to describe the interventions they had already performed (3/41, 7%), using it to recommend focusing on patients' quality of life. SDMs were generally reluctant to accept death, whereas physicians found prolonging life at all costs to be morally distressing. The CCB did not interpret appeals to "do everything" legally but followed existing laws by deferring to patients' prior wishes whenever known, or to concepts of "best interests" when not. The CCB generally recommended against life-prolonging measures in these cases (26/41, 63%), focusing on patients' "well-being" and "best interests." CONCLUSIONS: In this unique sample of cases involving conflict surrounding resuscitation and end-of-life care, references to "do everything" highlighted conflicts over quantity versus quality of life. These appeals were associated with signs of cognitive distress on the behalf of SDMs who were facing the prospect of a patient's death, whereas physicians identified moral distress related to the prolongation of patients' suffering through their use of life-sustaining interventions. This divergence in perspectives on death versus suffering was consistently the locus of conflict. These findings support the importance of tools such as the Serious Illness Conversation Guide that can be used by physicians to direct conversations on the patients' goals, wishes, trade-offs, and to recommend a treatment plan that may include palliative care. TRIAL REGISTRATION: Not applicable.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".