Clinical practice guideline recommendations for pediatric solid organ injury care: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Observed variations in the management of pediatric solid organ injuries (SOIs) may be due to difficulty in finding and integrating recommendations from multiple clinical practice guidelines (CPGs) with heterogeneous methodological approaches. We aimed to systematically review CPG recommendations for pediatric SOIs. METHODS: We conducted a systematic review of CPGs including at least one recommendation targeting pediatric SOI populations, using Medical Analysis and Retrieval System Online, Excerpta Medica dataBASE, Web of Science, and websites of clinical organizations. Pairs of reviewers independently assessed eligibility, extracted data, and evaluated the quality of CPGs using the Appraisal of Guidelines Research and Evaluation II tool. We synthesized recommendations from moderate to high-quality CPGs using a recommendations matrix based on Grades of Recommendation, Assessment, Development, and Evaluation criteria. RESULTS: We identified eight CPGs, including three rated moderate or high quality. Methodological weaknesses included lack of stakeholder involvement beyond surgeons, consideration of applicability (e.g., implementation tools), and clarity around the definition of pediatric populations. Five of the 15 recommendations from moderate to high-quality CPGs were based on moderate quality evidence or were rated as strong; these reflected nonoperative management and angioembolization for renal injuries and required length of stay for liver and spleen injuries. CONCLUSION: We identified 15 recommendations on pediatric SOI management from 3 moderate or high-quality CPGs, but only one third were based on at least moderate-quality evidence or were rated as strong. Our results prompt the following recommendations for future CPG development or updates: (1) include all types of clinicians involved in the care of pediatric SOIs and patient and family representatives in the process, (2) develop clear definitions of the target population, and (3) provide advice and tools to promote implementation. Results also underline the urgent need for more rigorous research to support strong evidence-based recommendations in this population. LEVEL OF EVIDENCE: Systematic Review/Meta-analysis; Level III.
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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 | 0.056 | 0.251 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.009 |
| Bibliometrics | 0.020 | 0.017 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".