MétaCan
Menu
Back to cohort
Record W2050392264 · doi:10.2176/nmc.43.120

Postoperative Infection After Duraplasty With Expanded Polytetrafluoroethylene Sheet.

2003· article· en· W2050392264 on OpenAlexaff
Setsuko Nakagawa, Takashi Hayashi, Shigetaka ANEGAWA, Susumu Nakashima, S Shimokawa, Yoshihiko Furukawa

Bibliographic record

VenueNeurologia medico-chirurgica · 2003
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Surgical Oncology
Canadian institutionsSt Mary's Hospital Centre
Fundersnot available
KeywordsMedicineSurgeryCranioplastyDura materDecompressive craniectomyEmpyemaCraniotomySkull

Abstract

fetched live from OpenAlex

Dural reconstruction is a significant problem in many cases of decompressive craniotomy and dural defect. Expanded polytetrafluoroethylene (ePTFE) sheet have been used as a dura mater substitute for duraplasty. The outcomes of 83 consecutive patients at our institution were reviewed who underwent external decompression and closure with the ePTFE sheet between August 1995 and December 2000. Eight cases of infection occurred. Seven patients had infection with subdural empyema after cranioplasty with autologous bone. Three patients improved after removal of only the infected bone. One patient improved after removal of the infected bone and ePTFE sheet. One patient experienced wound infection after the original operation. Four patients subsequently developed local and severe inflammation with skin erythema until the ePTFE sheet was removed. Four patients had severe recurrent infections which required subsequent therapy such as vascularized free rectus abdominis muscle flap transfer. Duraplasty with ePTFE sheet might promote infection and poor circulation in the skin flap. The ePTFE sheet should be removed at an early stage in a patient with infection.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.256
Teacher spread0.245 · 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

Citations63
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueNeurologia medico-chirurgicaSame topicHead and Neck Surgical OncologyFrench-language works237,207