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Record W4320483750 · doi:10.1186/s13104-023-06275-5

Risk of iatrogenic pneumothorax based on location of transbronchial biopsy: a retrospective cohort study

2023· article· en· W4320483750 on OpenAlexaff
Mina Ishak, Debarati Chakraborty, Shayan Kassirian, Inderdeep Dhaliwal, Michael A. Mitchell

Bibliographic record

VenueBMC Research Notes · 2023
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicinePneumothoraxRetrospective cohort studyLogistic regressionBronchoscopyRadiologyCohortRadiographySurgeryLungChest tubeInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Transbronchial lung biopsy (TBB) is a commonly performed procedure to obtain parenchymal lung tissue during bronchoscopy. Pneumothorax is among the most common serious complications of TBB. The objective of this study was to assess whether location of TBB correlated with development of post-procedural pneumothorax. We also sought to identify additional risk factors associated with pneumothorax development. This was a single-centre, retrospective cohort study. All TBB performed between 2010 and 2020 underwent subsequent chart review. The primary outcome was radiologist reported pneumothorax on post-procedure chest x-ray. Multivariable logistic regression model was created with included variables chosen a priori based on clinical significance. RESULTS: There were a total of 222 TBB performed that met inclusion criteria. Radiographic evidence of pneumothorax was reported in 38 patients (15.4%). Ten patients (4.1%) required a chest tube. In the multivariable analysis, risk of pneumothorax was significantly higher for biopsies obtained from the left upper lobe (OR 3.3; 95% CI 1.3-9.1). There was an increased risk of pneumothorax following TBB when obtained from the left upper lobe. Clinicians should be aware of the increased risk and should consider alternative locations in patients with diffuse lung 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.017
Threshold uncertainty score0.343

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.076
GPT teacher head0.414
Teacher spread0.338 · 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.

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

Citations4
Published2023
Admission routes1
Has abstractyes

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