A systematic review of the integration of palliative care in dementia management
Bibliographic record
Abstract
OBJECTIVE: Dementia is a progressive illness with a complex biopsychosocial constellation of symptoms faced by millions of individuals and families worldwide. Palliative care teams have specialized in symptom management and end-of-life care for decades; however, the role of palliative care in dementia management is not yet well elucidated. The aim of this systematic review was to understand the impact of palliative care in dementia management. METHOD: This systematic review was conducted using a prospective study protocol. Medline and PubMed were searched from January 1, 1998 to October 2017. Eligible studies included single-blind cluster, two-arm parallel cluster, or unblinded randomized controlled trials (RCTs), observational studies, retrospective cohort studies, cross-sectional studies, concurrent mixed methods study, qualitative study, and Delphi studies. RESULTS: Four key themes were identified in this review: goals of care and end-of-life conversations, symptom management, emergency room visits, and prescribing behavior. In each domain, palliative care consultation either showed benefit or was postulated to have benefit if implemented. SIGNIFICANCE OF RESULTS: Although the literature to support or refute thematic conclusions is not large, there was a trend toward patient care benefit across several domains. Large RCTs with longer follow-up across different settings should be undertaken to solidify the themes and trends outlined in this review. Understanding the views of healthcare providers including referral sources (i.e., general practitioners and specialists) through qualitative research could optimize palliative care referrals, implement palliative care recommendations, and improve a targeted palliative care education curriculum.
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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 | 0.014 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".