Transitions to End-of-Life Care for Patients With Chronic Critical Illness: A Meta-Synthesis
Bibliographic record
Abstract
BACKGROUND: Adults with chronic critical illness (CCI) frequently experience a terminal trajectory but receive varying degrees of palliation and end-of-life care (EOLC) in intensive care units (ICUs). Why palliation (over curative treatment) is not augmented earlier for patients with CCI in ICU is not well understood. PURPOSE: To identify the social structures that contribute to timely, context-dependent decisions for transition from acute care to EOLC for patients with CCI and their families. METHODS: We conducted a meta-synthesis of qualitative and/or mixed-method studies that recruited adults with CCI, their families or close friends, and/or health-care providers (HCPs) in an ICU environment. RESULTS: Five studies reported data from 83 patients, 109 family members, and 57 HCPs across 5 institutions in Canada and the United States. Overall, we found that morally ambiguous social expectations of treatment tended to lock in HCPs to focus on prescriptive work of preserving life, despite pathways that could "open" access to augmenting palliation and EOLC. This process limited space for families' reflexivity and reappraisal of CCI as a phase liminal to active dying. Notably, EOLC mechanisms were informal and less visible. CONCLUSION: The management of dying is one of the central tenets of ICU care. Our findings suggest that patients and families need help in negotiating meanings of this situation and in using mechanisms that allow reappraisal and permit understanding of CCI as a phase liminal to dying. Moreover, these mechanisms may paradoxically reduce the ambiguity of patients' future, allowing them to live more fully in the present.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.032 | 0.094 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.020 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".