Impact of accredited advanced life support course participation on in-hospital cardiac arrest patient outcomes: A systematic review
Why this work is in the frame
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Bibliographic record
Abstract
Aim: Advanced life support courses have a clear educational impact; however, it is important to determine whether participation of one or more members of the resuscitation team in an accredited advanced life support course improves in-hospital cardiac arrest patient survival outcomes. Methods: We searched EMBASE.com, Medline, Cochrane and CINAHL from inception to 1 November 2022. Included studies were randomised or non-randomised interventional studies assessing the impact of attendance at accredited life support courses on patient outcomes. Accredited life support courses were classified into 3 contexts: Advanced Life Support (ALS), Neonatal Resuscitation Training (NRT), and Helping Babies Breathe (HBB). Existing systematic reviews were identified for each of the contexts and an adolopment process was pursued. Appropriate risk of bias assessment tools were used across all outcomes. When meta-analysis was appropriate a random-effects model was used to produce a summary of effect sizes for each outcome. Results: Of 2714 citations screened, 19 studies (1 ALS; 7 NRT; 11 HBB) were eligible for inclusion. Three systematic reviews which satisfied AMSTAR-2 criteria for methodological quality, included 16 of the studies we identified in our search. Among adult patients all outcomes including return of spontaneous circulation, survival to discharge and survival to 30 days were consistently better with accredited ALS training. Among neonatal patients there were reductions in stillbirths and early neonatal mortality. Conclusion: These results support the recommendation that accredited advanced life support courses, specifically Advanced Life Support, Neonatal Resuscitation Training, and Helping Babies Breathe improve patient outcomes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it