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Record W4285531495 · doi:10.21037/jtd-22-35

Transthoracic needle biopsy versus surgical diagnosis for solid pulmonary nodules

2022· article· en· W4285531495 on OpenAlexafffund
Valérie Roy, Paula A. Ugalde, Etienne Bourdages-Pageau, Yves Lacasse, Catherine Labbé

Bibliographic record

VenueJournal of Thoracic Disease · 2022
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsUniversité LavalInstitut Universitaire de Cardiologie et de Pneumologie de Québec
FundersInstitut universitaire de cardiologie et de pneumologie de Québec, Université LavalUniversité Laval
KeywordsMedicineMalignancyBiopsyRetrospective cohort studySurgeryCohortRadiologyInternal medicine

Abstract

fetched live from OpenAlex

Background: When investigating solitary pulmonary nodules (SPN), non-surgical [such as transthoracic needle biopsy (TTNB)] or surgical biopsies can be performed. There is a paucity of data comparing these two approaches. Methods: benign lesion), to evaluate the proportion of TTNB that would yield a benign diagnosis and permit to avoid surgery, to evaluate if delays to surgery were longer when preoperative TTNB was performed, and if operative times were longer with upfront surgery. Results: In our cohort, 87 patients (58%) underwent TTNB, while 62 (42%) had an upfront surgical procedure. One hundred and twenty-eight patients (86%) had a malignant diagnosis. Thirteen patients out of the 87 biopsied (15%) avoided surgery owing to a benign biopsy result, or a non-specific diagnosis and a physician reassured enough to decide for radiological surveillance, while 5/62 patients (8%) who underwent upfront surgery had a benign diagnosis. There was no significant difference in delays from imaging to surgery or in operative time between patients with or without prior TTNB. Conclusions: In this unicentric retrospective cohort of patients investigated for SPN, the malignancy rate was high (86%), which seemed to limit the applicability of prediction models. Adherence to guidelines for the investigation of SPN by physicians seemed suboptimal. More real-world prospective studies are needed to compare non-surgical and surgical biopsies. There is also a need for simpler nodule evaluation algorithms.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.510
Threshold uncertainty score0.790

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.376
Teacher spread0.343 · 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 designNot applicable
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
Published2022
Admission routes2
Has abstractyes

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