Unravelling complex choices: multi-stakeholder perceptions on dialysis withdrawal and end-of-life care in kidney disease
Bibliographic record
Abstract
BACKGROUND: For patients on dialysis with poor quality of life and prognosis, dialysis withdrawal and subsequent transition to palliative care is recommended. This study aims to understand multi-stakeholder perspectives regarding dialysis withdrawal and identify their information needs and support for decision-making regarding withdrawing from dialysis and end-of-life care. METHODS: Participants were recruited through purposive sampling from eight dialysis centers and two public hospitals in Singapore. Semi-structured in-depth interviews were conducted with 10 patients on dialysis, 8 family caregivers, and 16 renal healthcare providers. They were held in-person at dialysis clinics with patients and caregivers, and virtually via video-conferencing with healthcare providers. Interviews were audio-recorded, transcribed, and thematically analyzed. The Ottawa Decision Support Framework's decisional-needs manual was used as a guide for data collection and analysis, with two independent team members coding the data. RESULTS: Four themes reflecting perceptions and support for decision-making were identified: a) poor knowledge and fatalistic perceptions; b) inadequate resources and support for decision-making; c) complexity of decision-making, unclear timing, and unpreparedness; and d) internal emotions of decisional conflict and regret. Participants displayed limited awareness of dialysis withdrawal and palliative care, often perceiving dialysis withdrawal as medical abandonment. Patient preferences regarding decision-making ranged from autonomous control to physician or family-delegated choices. Cultural factors contributed to hesitancy and reluctance to discuss end-of-life matters, resulting in a lack of conversations between patients and providers, as well as between patients and their caregivers. CONCLUSIONS: Decision-making for dialysis withdrawal is complicated, exacerbated by a lack of awareness and conversations on end-of-life care among patients, caregivers, and providers. These findings emphasize the need for a culturally-sensitive tool that informs and prepares patients and their caregivers to navigate decisions about dialysis withdrawal and the transition to palliative care. Such a tool could bridge information gaps and stimulate meaningful conversations, fostering informed and culturally aligned decisions during this critical juncture of care.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".