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Record W4286742014 · doi:10.1007/s12663-022-01761-y

Management of Aesthetical and Functional Complications after Total Parotidectomy. First Long-Term Experiences with Dermal Matrix Surgimend ® in Patient Affected by Malignant Parotid Tumors

2022· article· en· W4286742014 on OpenAlexaboutno aff
Paola Bonavolontà, Giorgio İaconetta, Giovanni Improda, Cristiana Germano, Gerardo Borriello, Federica Goglia, Vincenzo Abbate, Pasquale Piombino, Luigi Califano, Giovanni Dell’Aversana Orabona

Bibliographic record

VenueJournal of Maxillofacial and Oral Surgery · 2022
Typearticle
Languageen
FieldMedicine
TopicSalivary Gland Tumors Diagnosis and Treatment
Canadian institutionsnot available
FundersUniversità degli Studi di Napoli Federico II
KeywordsMedicineParotidectomyVascularitySurgeryOtorhinolaryngologyIncidence (geometry)Retrospective cohort studyFacial nerve

Abstract

fetched live from OpenAlex

Background: This is an observational cohort study on patients affected by malignant parotid tumors treated with total parotidectomy. The aim of our work is to analyze and compare the effects and complications after parotidectomy, using or not SurgiMend ®. Methods: 40 patients were retrospectively enrolled between September 2014 and June 2020. Basing on the placement of SurgiMend ® for parotid lodge reconstruction, the samples were divided into two groups. Thus, the incidence rate of complications after the surgical procedure was analyzed between the two groups. Results: = 0.05) revealed a significant difference of Vancouver Scar Scale (VSS) between the two groups, representation as vascularity and pigmentation improvement, changing scar color, scar height reduction, and increased pliability. Conclusion: Although many techniques are available to fill the parotidectomy defect, improve facial contour and prevent Frey's syndrome, the use of SurgiMend ® matrix is one of most effective and reliable method to address these complications, with the advantage of decreased operative time due to not require an additional surgical donor site.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.419

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.012
GPT teacher head0.236
Teacher spread0.224 · 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 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

Citations3
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Maxillofacial and Oral SurgerySame topicSalivary Gland Tumors Diagnosis and TreatmentFrench-language works237,207