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Record W2579762161 · doi:10.2500/ar.2016.7.0171

Modified Endoscopic Medial Maxillectomy for Zygomatic Implant Salvage

2016· article· en· W2579762161 on OpenAlexaff
Joseph S. Schwartz, Bobby A. Tajudeen, Nithin D. Adappa, James N. Palmer

Bibliographic record

VenueAllergy & Rhinology · 2016
Typearticle
Languageen
FieldMedicine
TopicSinusitis and nasal conditions
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineContext (archaeology)SinusitisImplantMaxillary sinusDentistrySurgery

Abstract

fetched live from OpenAlex

OBJECTIVES: Odontogenic chronic rhinosinusitis (CRS) is an epidemiologically important disease process due, in part, to the increasingly commonplace use of dental restorative procedures such as zygomatic implantation. Traditional management of this clinical entity typically entails extraction of the infected hardware via an open or endoscopic approach. We describe a novel management strategy of odontogenic CRS following bilateral zygomatic implantation for oral rehabilitation that we surgically salvaged via a modified endoscopic medial maxillectomy. METHODS: We describe the presentation and management of a case of metachronous development of bilateral CRS subsequent to zygomatic implantation. RESULTS: The patient's postoperative course was characterized by marked endoscopic, radiologic, and symptomatic improvement as measured by the 22-item Sino-Nasal Outcome Test. CONCLUSION: We describe a novel treatment strategy for the management of odontogenic sinusitis resulting from erroneous zygomatic implant placement. Modified endoscopic medial maxillectomy in this clinical context facilitates mucosal normalization of the affected sinus, while permitting preservation of oral function through salvage of the displaced implant.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.025
GPT teacher head0.280
Teacher spread0.254 · 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 designCase report
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
Published2016
Admission routes1
Has abstractyes

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