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Record W2768379031 · doi:10.1097/pcc.0000000000001372

End-Tidal Carbon Dioxide Use for Tracheal Intubation: Analysis From the National Emergency Airway Registry for Children (NEAR4KIDS) Registry

2017· article· en· W2768379031 on OpenAlexaff
Melissa L. Langhan, Beth Emerson, Sholeen Nett, Matthew Pinto, Ilana Harwayne‐Gidansky, Kyle J. Rehder, Conrad Krawiec, Keith Meyer, John S. Giuliano, Erin Owen, Keiko M. Tarquinio, Ron C. Sanders, Michael Shepherd, G. Kris Bysani, Asha Shenoi, Natalie Napolitano, Sandeep Gangadharan, Simon Parsons, Dennis Simon, Vinay Nadkarni, Akira Nishisaki

Bibliographic record

VenuePediatric Critical Care Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicAirway Management and Intubation Techniques
Canadian institutionsAlberta Children's Hospital
FundersAgency for Healthcare Research and Quality
KeywordsCapnographyMedicineIntubationTracheal intubationAnesthesiaInterquartile rangeAirwayIntensive careEmergency medicineIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Waveform capnography use has been incorporated into guidelines for the confirmation of tracheal intubation. We aim to describe the trend in waveform capnography use in emergency departments and PICUs and assess the association between waveform capnography use and adverse tracheal intubation-associated events. DESIGN: A multicenter retrospective cohort study. SETTING: Thirty-four hospitals (34 ICUs and nine emergency departments) in the National Emergency Airway Registry for Children quality improvement initiative. PATIENTS: Primary tracheal intubation in children younger than 18 years. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Patient, provider, and practice data for tracheal intubation procedure including a type of end-tidal carbon dioxide measurement, as well as the procedural safety outcomes, were prospectively collected. The use of waveform capnography versus colorimetry was evaluated in association with esophageal intubation with delayed recognition, cardiac arrest, and oxygen desaturation less than 80%. During January 2011 and December 2015, 9,639 tracheal intubations were reported. Waveform capnography use increased over time (39% in 2010 to 53% in 2015; p < 0.001), whereas colorimetry use decreased (< 0.001). There was significant variability in waveform capnography use across institutions (median 49%; interquartile range, 25-85%; p < 0.001). Capnography was used more often in emergency departments as compared with ICUs (66% vs. 49%; p < 0.001). The rate of esophageal intubation with delayed recognition was similar with waveform capnography versus colorimetry (0.39% vs. 0.46%; p = 0.62). The rate of cardiac arrest was also similar (p = 0.49). Oxygen desaturation occurred less frequently when capnography was used (17% vs. 19%; p = 0.03); however, this was not significant after adjusting for patient and provider characteristics. CONCLUSIONS: Significant variations existed in capnography use across institutions, with the use increasing over time in both emergency departments and ICUs. The use of capnography during intubation was not associated with esophageal intubation with delayed recognition or the occurrence of cardiac arrest.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.043
GPT teacher head0.361
Teacher spread0.318 · 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

Citations16
Published2017
Admission routes1
Has abstractyes

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