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Record W2791187322 · doi:10.1097/pcc.0000000000001520

Characterization of Pediatric In-Hospital Cardiopulmonary Resuscitation Quality Metrics Across an International Resuscitation Collaborative*

2018· article· en· W2791187322 on OpenAlexaffabout
Dana Niles, Jordan Duval‐Arnould, Sophie Skellett, Lynda Knight, Felice Su, Tia T. Raymond, Todd Sweberg, Anita Sen, Dianne L. Atkins, Stuart H. Friess, Allan R. de Caen, Hiroshi Kurosawa, Robert M. Sutton, Heather Wolfe, Annemarie Silver, Elizabeth A. Hunt, Vinay Nadkarni

Bibliographic record

VenuePediatric Critical Care Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsStollery Children's Hospital
FundersU.S. Food and Drug Administration
KeywordsCardiopulmonary resuscitationMedicineInterquartile rangeResuscitationData compression ratioCompression (physics)Chest painEmergency medicineCardiologyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: Pediatric in-hospital cardiac arrest cardiopulmonary resuscitation quality metrics have been reported in few children less than 8 years. Our objective was to characterize chest compression fraction, rate, depth, and compliance with 2015 American Heart Association guidelines across multiple pediatric hospitals. DESIGN: Retrospective observational study of data from a multicenter resuscitation quality collaborative from October 2015 to April 2017. SETTING: Twelve pediatric hospitals across United States, Canada, and Europe. PATIENTS: In-hospital cardiac arrest patients (age < 18 yr) with quantitative cardiopulmonary resuscitation data recordings. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: There were 112 events yielding 2,046 evaluable 60-second epochs of cardiopulmonary resuscitation (196,669 chest compression). Event cardiopulmonary resuscitation metric summaries (median [interquartile range]) by age: less than 1 year (38/112): chest compression fraction 0.88 (0.61-0.98), chest compression rate 119/min (110-129), and chest compression depth 2.3 cm (1.9-3.0 cm); for 1 to less than 8 years (42/112): chest compression fraction 0.94 (0.79-1.00), chest compression rate 117/min (110-124), and chest compression depth 3.8 cm (2.9-4.6 cm); for 8 to less than 18 years (32/112): chest compression fraction 0.94 (0.85-1.00), chest compression rate 117/min (110-123), chest compression depth 5.5 cm (4.0-6.5 cm). "Compliance" with guideline targets for 60-second chest compression "epochs" was predefined: chest compression fraction greater than 0.80, chest compression rate 100-120/min, and chest compression depth: greater than or equal to 3.4 cm in less than 1 year, greater than or equal to 4.4 cm in 1 to less than 8 years, and 4.5 to less than 6.6 cm in 8 to less than 18 years. Proportion of less than 1 year, 1 to less than 8 years, and 8 to less than 18 years events with greater than or equal to 60% of 60-second epochs meeting compliance (respectively): chest compression fraction was 53%, 81%, and 78%; chest compression rate was 32%, 50%, and 63%; chest compression depth was 13%, 19%, and 44%. For all events combined, total compliance (meeting all three guideline targets) was 10% (11/112). CONCLUSIONS: Across an international pediatric resuscitation collaborative, we characterized the landscape of pediatric in-hospital cardiac arrest chest compression quality metrics and found that they often do not meet 2015 American Heart Association guidelines. Guideline compliance for rate and depth in children less than 18 years is poor, with the greatest difficulty in achieving chest compression depth targets in younger children.

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 imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.023
GPT teacher head0.379
Teacher spread0.355 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations113
Published2018
Admission routes2
Has abstractyes

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