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Record W3092372320 · doi:10.4414/smw.2020.20347

Long-term evaluation of the distal transverse plantar approach for Morton’s neuroma excision

2020· article· en· W3092372320 on OpenAlexaboutno aff
Trieu Hoai Nam Ngo, Aurélien Traverso, Swati Chopra, Hassen Hassani, Xavier Crevoisier

Bibliographic record

VenueSwiss Medical Weekly · 2020
Typearticle
Languageen
FieldMedicine
TopicPeripheral Nerve Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineNeurectomySurgeryAnkleNeuromaDissection (medical)ForefootFoot (prosody)Foot and ankle surgeryRetrospective cohort studyComplication

Abstract

fetched live from OpenAlex

BACKGROUND: There is currently no consensus on the ideal approach for the operative treatment of Morton’s neuroma. The distal transverse plantar approach aims at optimal exposure without the scar complications associated with the longitudinal plantar approach. Long-term evaluation based on validated outcome instruments is lacking. The main purpose of this retrospective study was to evaluate the long-term clinical outcome of this approach using validated function and scar evaluation scores. METHODS: Forty-nine patients operated on at our institution were examined clinically by two independent observers using the Foot and Ankle Ability Measure (FAAM) and the Vancouver Scar Scale (VSS). Patients who underwent neurectomy alone and those who had additional foot surgery were compared. RESULTS: Assessment at a mean of 7.9 years (range 4–12) postoperatively revealed a mean FAAM score of 84.8 ± 25% and a mean VSS score of 1.57 ± 1.7. Patients who underwent neurectomy alone had higher FAAM scores at follow up. We observed no complication that required an additional procedure. CONCLUSIONS: The transverse plantar approach results in good objective outcome scores, including scar healing, in the long term. This is our preferred technique because, in our experience, it offers optimal visualisation of the nerve, does not require deep dissection and allows the exposure of two adjacent web spaces of the foot through a single incision.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.494
Threshold uncertainty score0.595

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0010.000

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 head0.062
GPT teacher head0.326
Teacher spread0.264 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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