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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 OpenAlex
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

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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