Understanding Early Decisions to Withdraw Life-Sustaining Therapy in Cardiac Arrest Survivors. A Qualitative Investigation
Bibliographic record
Abstract
RATIONALE: Early withdrawal of life-sustaining therapy contributes to the majority of deaths following out-of-hospital cardiac arrest (OHCA), despite current recommendations for delayed neurological prognostication (≥72 h) after treatment with targeted temperature management. Little is known about clinicians' experiences of early withdrawal of life support decisions in patients with OHCA. OBJECTIVES: To explore clinicians' experiences and perceptions of early withdrawal of life support decisions and barriers to guideline-concordant neurological prognostication in comatose survivors of OHCA treated with targeted temperature management. METHODS: We conducted qualitative interviews with intensive care unit (ICU) physicians and nurses following withdrawal of life support in comatose patients with OHCA treated with targeted temperature management. The study was carried out across 18 academic and community hospitals participating in a multicenter, stepped-wedge, cluster-randomized controlled trial designed to improve quality-of-care processes for patients after OHCA in Ontario, Canada. We used a focused thematic analysis to capture barriers to guideline-concordant neurological prognostication and used these barriers to identify potentially modifiable issues. MEASUREMENTS AND MAIN RESULTS: The core thematic finding was a high emotional burden of ICU family-team communication in which strong feelings inhibited information transfer and delayed decision making following OHCA. Four subthemes describing sources of communication strain were identified: (1) requests from family members to provide early outcome predictions, (2) incomplete family comprehension of critical care, (3) family requests for early withdrawal of life support based on their understanding of patients' preferences and values, and (4) family-team communication gaps related to prognostic uncertainty. Participants worried that gaps in timely and clear prognostic information contributed to surrogates' perceptions of a poor outcome and to inappropriately early decisions to withdraw life support. CONCLUSIONS: Family-team communication difficulties may be an underestimated factor leading to early withdrawal of life support in ICUs for individuals who initially survive OHCA.
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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 | 0.016 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".