Trigger Criteria for Advance Care Planning in Adults With Congenital Heart Disease: A Systematic Review
Bibliographic record
Abstract
Background: Adults with congenital heart disease (CHD) face increased risks of premature morbidity and mortality. Advance care planning (ACP) facilitates longitudinal, patient-centered care but remains underused in this population, partly due to the lack of validated trigger criteria to initiate ACP. This study aimed to systematically review the literature to identify proposed triggers to initiate ACP conversations in adults with CHD. Methods: We conducted a systematic search of MEDLINE, Embase, PsycInfo, CINAHL, Web of Science, Scopus, and the Cochrane Library from database inception to July 26, 2024. The search focused on 2 core concepts: CHD and adults, and ACP or palliative care. Two reviewers independently screened articles for inclusion and extracted potential trigger criteria for ACP initiation. Results: Of 4257 articles screened, 21 were included for data extraction. Nearly half (48%) were published between 2020 and 2024, with most (81%) appearing in cardiology journals. ACP was most often recommended during routine follow-up (15 articles, 71%), independent of defect complexity or functional status. Specific interventions (10 articles, 48%) and signs of disease progression (10 articles, 48%) were the second most frequently cited trigger criteria, followed by defect-specific triggers (7 articles, 33%). Symptom- and patient-based triggers were less frequently reported. Conclusions: This review highlights a wide range of proposed triggers and a lack of consensus on when to initiate ACP in adults with CHD. The identified triggers can inform clinical practice and serve as a foundation for developing standardized criteria. However, findings are limited by the heterogeneity among the included studies. Registration: PROSPERO CRD42024597771.
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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 | 0.013 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".