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Record W2358718667 · doi:10.2310/6650.2005.00005.215

216 VIDEO-ASSISTED THORACOSCOPIC SURGERY VERSUS OPEN THORACOTOMY IN PAEDIATRIC SCOLIOSIS

2005· article· en· W2358718667 on OpenAlexaff
Gerard P. Slobogean, C. Reilly

Bibliographic record

VenueJournal of Investigative Medicine · 2005
Typearticle
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineScoliosisVideo-assisted thoracoscopic surgeryThoracotomySurgery

Abstract

fetched live from OpenAlex

Purpose To compare the perioperative variables and clinical outcomes of video-assisted thoracoscopic surgery (VATS) with the traditional open thoracotomy approach for anterior spinal release and posterior fusion in the treatment of paediatric scoliosis. Methods A retrospective chart review of nineteen consecutive patients treated with VATS anterior spinal release and posterior fusion was completed. An additional nineteen age- and disease-matched patients treated with open thoracotomy were also reviewed for comparison. Results VATS patients achieved a larger post-operative curve correction compared to those that underwent thoracotomy (p= .01). The VATS group also received less transfused blood during the procedure (p= .03). The open thoracotomy patients experienced less post-operative chest tube drainage (p= .02), and as a result had their chest tubes removed earlier (p= .01). There was no difference in operating time, total blood loss, length of ventilator use, length of ICU stay, or length of hospital stay. There were no major complications in either group. Conclusions Video-assisted thoracoscopic surgery continues to be a safe and successful approach for the treatment of paediatric scoliosis. This study shows that it is possible to achieve large post-operative curve corrections and reduce the amount of transfused blood needed using the VATS technique.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.169
GPT teacher head0.390
Teacher spread0.220 · 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 designNon-randomized trial
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

Citations0
Published2005
Admission routes1
Has abstractyes

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