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Record W2513971947 · doi:10.4236/ojts.2016.63005

Is VATS Bullectomy and Pleurectomy an Effective Method for the Management of Spontaneous Pneumothorax?

2016· article· en· W2513971947 on OpenAlexaff
Ramzi A. Addas, Farid M. Shamji, Sudhir Sundaresan, Patrick J. Villeneuve, Andrew Seely, Sébastien Gilbert, Donna E. Maziak

Bibliographic record

VenueOpen Journal of Thoracic Surgery · 2016
Typearticle
Languageen
FieldMedicine
TopicPleural and Pulmonary Diseases
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsPleurectomyMedicinePneumothoraxCardiothoracic surgerySurgeryGeneral surgeryPathology

Abstract

fetched live from OpenAlex

Spontaneous pneumothorax, primary or secondary, is a common medical emergency for which specific indications for surgical intervention are well defined in selected patients. The traditional surgical approach has been by limited thoracotomy using axillary or posterolateral incision. With the advent of video-assisted minimally invasive technique in the last 20 years the traditional approach is infrequently used. The definitive operation to prevent recurrent pneumothorax by surgical approach requires bullectomy and parietal pleurectomy. The recurrence rate after the traditional open surgical approach has been low at <2%. On the other hand, video-assisted thoracoscopic surgery, although better tolerated has a higher recurrence rate at 5% [1]. Information on post-operative morbidity and mortality are lacking. For this reason, we have reviewed our experience at one institution on the outcome of the VATS approach. We found that prolonged post- operative air leak is the most common complication and cigarette smoking remains an important associated factor.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.046
GPT teacher head0.381
Teacher spread0.335 · 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

Citations6
Published2016
Admission routes1
Has abstractyes

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