Ethical guidance for extracorporeal and paracorporeal device use in children: a systematic review
Bibliographic record
Abstract
Abstract Background To provide substantive, practical guidance on the ethical use of pediatric extra/paracorporeal devices, we first need a comprehensive understanding of existing guidance. The objective was to characterize how ethical guidance for device use in children is provided in published literature and to summarize quantity, quality, and themes. Data sources PubMed, Web of Science, and EMBASE databases were systematically searched 2.1.2023. Study selection Methodology followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses rapid review. Citations discussing ethical guidance for, initiation/continuation/discontinuation decision-making, or allocation of, devices in children were identified. Devices included tracheostomy/mechanical ventilation (MV), renal replacement therapy (RRT), mechanical circulatory support (MCS), and extracorporeal membrane oxygenation (ECMO). We included policy statements/guidelines, reviews, conceptual articles, and surveys. Data extraction A standardized extraction tool was used. Quality was assessed using a multimodal tool. Data synthesis Of 97 citations, ethical analysis was the primary objective in 31%. 55% were pediatric-specific. Nineteen percent were high-quality. The USA and Europe were overrepresented with 12% from low- to middle-income countries. Devices included MV (40%), RRT (21%), MCS/ECMO (35%). Only one guideline was identified with a primary goal of ethical analysis of pediatric device use. Three empiric analyses examined patient-level data according to guideline implementation and 24 explored clinician/public perspectives on resource allocation or device utilization. Two non-empiric citations provided pediatric decision-making recommendations. Conclusions This comprehensive review of ethical guidance for device use in children identified numerous gaps and limited scope. Future research is warranted globally to promote the beneficial use of devices, minimize harm, and ensure equitable access.
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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 | 0.067 | 0.268 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".