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Record W2588128806 · doi:10.1097/pcc.0000000000001074

Relationship Between Adverse Tracheal Intubation Associated Events and PICU Outcomes*

2017· article· en· W2588128806 on OpenAlexaff
Margaret M. Parker, Gabrielle Nuthall, Calvin A. Brown, Katherine Biagas, Natalie Napolitano, Lee Polikoff, Dennis Simon, Michael Miksa, Eleanor Gradidge, Jan Hau Lee, Ashwin Krishna, David Téllez, Geoffrey L. Bird, Kyle J. Rehder, David Turner, Michelle Adu‐Darko, Sholeen Nett, Ashley T. Derbyshire, Keith Meyer, John S. Giuliano, Erin Owen, Keiko M. Tarquinio, Pradip Kamat, Ronald C. Sanders, Matthew Pinto, G. Kris Bysani, Guillaume Émériaud, Yuki Nagai, Melissa A. McCarthy, Karen Walson, Paula A. Vanderford, Anthony Lee, Jesse Bain, Peter Skippen, Ryan Breuer, Sarah Tallent, Vinay Nadkarni, Akira Nishisaki

Bibliographic record

VenuePediatric Critical Care Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicAirway Management and Intubation Techniques
Canadian institutionsBC Children's HospitalUniversity of British ColumbiaCentre Hospitalier Universitaire Sainte-Justine
FundersAgency for Healthcare Research and Quality
KeywordsMedicineTracheal intubationIntubationInterquartile rangeMechanical ventilationAnesthesiaAdverse effectUnivariate analysisAirwaySurgeryInternal medicineMultivariate analysis

Abstract

fetched live from OpenAlex

OBJECTIVE: Tracheal intubation in PICUs is a common procedure often associated with adverse events. The aim of this study is to evaluate the association between immediate events such as tracheal intubation associated events or desaturation and ICU outcomes: length of stay, duration of mechanical ventilation, and mortality. STUDY DESIGN: Prospective cohort study with 35 PICUs using a multicenter tracheal intubation quality improvement database (National Emergency Airway Registry for Children: NEAR4KIDS) from January 2013 to June 2015. Desaturation defined as Spo2 less than 80%. SETTING: PICUs participating in NEAR4KIDS. PATIENTS: All patients less than18 years of age undergoing primary tracheal intubations with ICU outcome data were analyzed. MEASUREMENTS AND MAIN RESULTS: Five thousand five hundred four tracheal intubation encounters with median 108 (interquartile range, 58-229) tracheal intubations per site. At least one tracheal intubation associated event was reported in 892 (16%), with 364 (6.6%) severe tracheal intubation associated events. Infants had a higher frequency of tracheal intubation associated event or desaturation than older patients (48% infants vs 34% for 1-7 yr and 18% for 8-17 yr). In univariate analysis, the occurrence of tracheal intubation associated event or desaturation was associated with a longer mechanical ventilation (5 vs 3 d; p < 0.001) and longer PICU stay (14 vs 11 d; p < 0.001) but not with PICU mortality. The occurrence of severe tracheal intubation associated events was associated with longer mechanical ventilation (5 vs 4 d; p < 0.003), longer PICU stay (15 vs 12 d; p < 0.035), and PICU mortality (19.9% vs 9.6%; p < 0.0001). In multivariable analyses, the occurrence of tracheal intubation associated event or desaturation was significantly associated with longer mechanical ventilation (+12%; 95% CI, 4-21%; p = 0.004), and severe tracheal intubation associated events were independently associated with increased PICU mortality (OR = 1.80; 95% CI, 1.24-2.60; p = 0.002), after adjusted for patient confounders. CONCLUSIONS: Adverse tracheal intubation associated events and desaturations are common and associated with longer mechanical ventilation in critically ill children. Severe tracheal intubation associated events are associated with higher ICU mortality. Potential interventions to decrease tracheal intubation associated events and oxygen desaturation, such as tracheal intubation checklist, use of apneic oxygenation, and video laryngoscopy, may need to be considered to improve ICU outcomes.

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)0.001
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.069
GPT teacher head0.397
Teacher spread0.329 · 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

Citations87
Published2017
Admission routes1
Has abstractyes

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