Palliative care consultation for end-of-life decision-making in hospitalised patients: protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Hospitalised patients nearing the end of life (EOL) often face complex treatment decisions, leading to potential conflicts among care teams, patients and families. Palliative care consultations may enhance decision-making processes, improve satisfaction and reduce unnecessary interventions. This systematic review will assess the impact of palliative care consultations on treatment decisions, family and patient satisfaction, and psychological outcomes in hospitalised adults. METHODS AND ANALYSIS: We will include randomised controlled trials comparing palliative care consultations to standard care in hospitalised adults. The primary outcomes will include decisions to withhold or withdraw treatments, patient and family satisfaction with EOL decision-making, and psychological outcomes such as anxiety, depression and post-traumatic stress disorder. Secondary outcomes will include intensive care unit (ICU) and hospital length of stay, utilisation of potentially non-beneficial treatments, and the use of institutional policies or legal actions. Databases including MEDLINE, Embase, CINAHL, Cochrane CENTRAL and PsycINFO will be systematically searched from inception to September 2025. Two independent reviewers will screen studies and extract data using Covidence. Meta-analyses will use random-effects models to generate pooled estimates for primary and secondary outcomes. Risk of bias will be assessed using the Cochrane Risk of Bias 2 tool, and evidence certainty will be evaluated using the Grading of Recommendations Assessment, Development and Evaluation approach. Subgroup analyses will explore variations by ICU versus non-ICU settings, cancer versus non-cancer diagnoses and default versus clinician-initiated consultations. ETHICS AND DISSEMINATION: Ethical approval is not required for this review. Findings will be disseminated through peer-reviewed publications and conference presentations. PROSPERO REGISTRATION NUMBER: CRD420250624190.
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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 | 0.061 | 0.083 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.023 | 0.033 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.063 | 0.006 |
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".