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Record W3035624424 · doi:10.1111/resp.13873

<scp>Multi‐institutional</scp> retrospective analysis of adverse events following rigid <scp>tracheobronchoscopy</scp>

2020· article· en· W3035624424 on OpenAlexaff
Marc Fortin, Lonny Yarmus, Erino Angelo Rendina, Samaan Rafeq, Rafael S. Andrade, Gaëtane Michaud, Jordan Kazakov, Sixto Arias, Anna Maria Ciccone, Ricardo O. Amador, Moïshe Liberman

Bibliographic record

VenueRespirology · 2020
Typearticle
Languageen
FieldMedicine
TopicTracheal and airway disorders
Canadian institutionsCentre Hospitalier de l’Université de MontréalInstitut Universitaire de Gériatrie de MontréalInstitut universitaire de cardiologie et de pneumologie de Québec
Fundersnot available
KeywordsMedicineAdverse effectRetrospective cohort studyComplicationMortality rateCohortEmergency medicineInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVE: Rigid tracheobronchoscopy (RTB) has seen an increasing interest over the last decades with the development of the field of IPM but no benchmark exists for complication rates in RTB. We aimed to establish benchmarks for complication rates in RTB. METHODS: A multicentric retrospective analysis of RTB performed between 2009 and 2015 in eight participating centres was performed. RESULTS: A total of 1546 RTB were performed over the study period. One hundred and thirty-one non-lethal complications occurred in 103 procedures (6.7%, 95% CI: 5.5-8.0%). The periprocedural mortality rate was 1.2% (95% CI: 0.6-1.8%). The 30-day mortality rate was 5.6% (95% CI: 4.5-6.8%). Complication rate increases further when procedures were performed in an emergency setting. Procedures in patients with MAO are associated with a higher 30-day mortality (8.1% vs 2.7%, P < 0.01) and a different complication profile when compared to procedures performed for BAS. CONCLUSION: RTB is associated with a 6.7% non-lethal complication rate, a 1.2% periprocedural mortality rate and a 5.6% 30-day mortality in a large multicentre cohort of patients with benign and malignant airway disease.

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 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)0.000
metaresearch head score (Gemma)0.002
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 score0.026
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.022
GPT teacher head0.289
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 teacher head, not a consensus.

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

Citations15
Published2020
Admission routes1
Has abstractyes

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