Do We Actually Help Choking Children? The Quality of Evidence on the Effectiveness and Safety of First Aid Rescue Manoeuvres: A Narrative Review
Bibliographic record
Abstract
The management of foreign body airway obstruction has evolved over time from back blows and chest thrusts to abdominal thrusts. However, current guidelines worldwide are based on outdated data, with unclear evidence regarding the effectiveness and safety of these rescue manoeuvres. Concerns persist about the potential of these techniques to cause injury, especially in children; therefore, a critical revision to ensure optimal child safety is necessary. The literature on first aid for paediatric choking was identified through the searching of various databases. Studies were evaluated for their relevance, quality, and currency. The analysis examined guideline consistency with current evidenced-based medicine and identified research gaps. The analysis of the available data was supplemented by adult-based evidence due to the scarcity of paediatric-specific research. First aid guidelines and recommendations for paediatric choking are divergent and generally grounded in low-quality evidence derived primarily from case studies. Studies since 2015 have shown highly diverse methodologies and often lack details on the execution of individual techniques, body positioning or the specific characteristics of study groups, which are crucial when comparing the effectiveness and safety of rescue manoeuvres. Updating evidence-based scientific knowledge for future recommendations is crucial.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".