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Record W2093767322 · doi:10.1097/sap.0b013e3181591e27

Long-Term Subjective and Objective Outcome After Primary Repair of Traumatic Facial Nerve Injuries

2008· article· en· W2093767322 on OpenAlexaff
Erik Frijters, Stefan O.P. Hofer, Marc A.M. Mureau

Bibliographic record

VenueAnnals of Plastic Surgery · 2008
Typearticle
Languageen
FieldMedicine
TopicFacial Nerve Paralysis Treatment and Research
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineFacial nerveFacial paralysisPhysical examinationGrading (engineering)Outpatient clinicPhysical therapyCranial nerve diseasePalsySurgeryPhysical medicine and rehabilitationEye disease

Abstract

fetched live from OpenAlex

Although traumatic facial nerve paralysis is a severe handicap, there are no follow-up studies evaluating outcome after primary repair of traumatic facial nerve injuries. From May 1988 to August 2005, 27 patients (mean age, 27 years) were operated for traumatic facial nerve lesions (mean number of affected branches, 2.2). End-to-end facial nerve repair was always performed. All patients were invited to our outpatient clinic for standardized questionnaires (Facial Disability Index, Short Form-36 Health Survey), physical examination (Sunnybrook Facial Grading System), and clinical photographs. Sixteen patients participated in the follow-up study (mean, 9.2 years). Mean Facial Disability Index Physical and Social scores were 86 and 81, respectively, indicating good subjective facial functioning. The mean Sunnybrook Facial Grading System score was 74 indicating adequate facial functioning. Mean physical and mental health scores (Short Form-36 Health Survey) were comparable with normative data. Primary end-to-end repair of traumatic facial nerve injuries results in good long-term objective and subjective functional and emotional outcome.

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)0.005
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 score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
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 head0.086
GPT teacher head0.346
Teacher spread0.260 · 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

Citations26
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueAnnals of Plastic SurgerySame topicFacial Nerve Paralysis Treatment and ResearchFrench-language works237,207