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Record W2760891333 · doi:10.1093/pch/20.5.e58b

69: Identifying Risk Factors for Unplanned Extubations in the NICU: Laying the Groundwork for a Quality Improvement Initiative

2015· article· en· W2760891333 on OpenAlexaff
Michael P. Hewitt, Erin Sproul, Julie Emberley

Bibliographic record

VenuePaediatrics & Child Health · 2015
Typearticle
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMedicineGestational ageNeonatal intensive care unitEmergency medicinePopulationMechanical ventilationAdverse effectIntensive careVentilation (architecture)PediatricsIntensive care medicineAnesthesiaPregnancyInternal medicine

Abstract

fetched live from OpenAlex

Unplanned extubations (UEs) are a common adverse event experienced by ventilated neonates in the Neonatal Intensive Care unit (NICU) and can lead to significant morbidity in an already vulnerable population. Despite the fact that UEs are increasingly recognized as an important quality of care metric, this adverse event was not being routinely reported at our institution. We sought to determine the rate of UEs in this NICU and identify risk factors to target future quality improvement interventions. 1. To determine the rate of UEs (# of UEs/100 ventilator days) in a level II/III NICU; 2. To identify risk factors associated with UEs. Institutional ethics approval was obtained prior to start of the study. A retrospective chart review was conducted for all intubated neonates admitted to a 34 bed level II/III NICU from January 1st, 2013 until December 31st, 2013. An UE was defined as any removal of an endotracheal tube not directly ordered or intended by a physician. For each UE event, the following data were collected: gestational age, birth weight, gender, weight at time of extubation, time at which event occurred, reason for extubation, and total number of ventilation days. UE rate was calculated by #UEs/100 ventilator days. Reasons for UEs were expressed by Pareto charting. Multivariate regression analysis was performed for gestational age, birth weight, and total ventilation time. Timing of event was categorized as either day or night shift and analyzed for significance using ANOVA. The UE rate was 3.28 UEs/100 ventilator days. Patient movement and adhesive failure accounted for over 50% of UEs. In 22.7% of cases, patients did not require re-intubation. Total ventilation time was the only statistically significant risk factor for UEs with a 7.3% increased risk per ventilation day past the mean. UEs were no more likely to occur on day versus night shift, nor were there any significant differences in the reasons for UE based on shift. The UE rate at this institution was higher than the suggested benchmark. More than 20% of patients did not require reintubation, reinforcing the need for more aggressive weaning protocols. Interestingly, night versus day shift was not found to be a significant risk factor. Total ventilation days independently predicted UE risk; pre-emptively identifying such patients is a potential avenue for future quality improvement interventions.

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)0.006
metaresearch head score (Gemma)0.026
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 score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.188
GPT teacher head0.455
Teacher spread0.267 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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