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Record W4295540479 · doi:10.7759/cureus.27781

Paramedic Endotracheal Intubation Success Rates Before and After an Intensive Airway Management Education Session

2022· article· en· W4295540479 on OpenAlexaff
Alix Carter, Jan L. Jensen, Mark Walker, Yves Leroux, Mikiko Terashima, Jennifer McVey

Bibliographic record

VenueCureus · 2022
Typearticle
Languageen
FieldMedicine
TopicAirway Management and Intubation Techniques
Canadian institutionsNova Scotia Health AuthorityDalhousie University
Fundersnot available
KeywordsMedicineIntubationAirway managementIntervention (counseling)AirwayEmergency medical servicesEndotracheal intubationEmergency medicineConfidence intervalAdvanced life supportPsychological interventionIntensive careMedical emergencyResuscitationIntensive care medicineNursingAnesthesiaCardiopulmonary resuscitation

Abstract

fetched live from OpenAlex

Introduction Advanced airway management by paramedics is potentially life-saving, but carries a significant risk to patient safety and can be associated with poor clinical outcome if performed incorrectly. Previously, our team had found that an intensive education intervention demonstrated an improvement in paramedic performance on a written exam and increased confidence in airway skills. This study measured intubation success and the number of attempts per patient before and after intensive paramedic airway management education intervention. Methods A 10-hour mandatory course was taken by all advanced life support (ALS) paramedics in a provincial system (2009/04-07, n=~395). The course was done during semi-annual continuing education Emergency Health Services (EHS) in-services. These day-long courses were held in person over four months. The electronic charting database was queried for intubation attempts and successful placements 12 months before the training, during the four months of training, and 12 months post-training. The primary outcome is the difference in success rates between the before (pre-intervention) and after (post-intervention) periods. The secondary outcome is the number of attempts per patient. Stationarity of success in pre- and post-periods was tested. The model was fit tested using Maximum Likelihood regression, and variables were tested using the Wald test. Results A sample size of 476 intubation attempts in each of the pre- and post-periods was required to detect a 10% improvement with the pre-intervention success of 60%. A total of 1421 intubation attempts occurred; 674 pre-intervention, 604 post-intervention, and 143 during teaching. Seven attempts were excluded (success unknown). Intubation success rates improved, from 0.68 (95% CI 0.64-0.71) to 0.75 (95% CI 0.72-0.78); a difference of 0.076 (95% CI 0.03-0.12) (p = 0.001). Intubation success rates in the pre-intervention and post-intervention periods were found to be static. A significant decrease was found in the number of attempts per patient in the post-period (p = 0.005). Conclusion Intubation success increased from 68% to 75% and was maintained over the 12-month post-period. There is a potential that judgment may also have improved, based on the decreased number of attempts per patient. Limitations include missing values, paramedics' self-reported number of attempts, and the definition of what is considered to be an attempt. In addition to previously demonstrated improvements in paramedic exam and scenario performance, this airway education intervention appears to have made a significant improvement to patient outcomes. These findings support the value of such education interventions to improve performance.

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)0.013
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 score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.011
GPT teacher head0.308
Teacher spread0.297 · 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".

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Citations1
Published2022
Admission routes1
Has abstractyes

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