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Record W4386171340 · doi:10.1016/j.jhsg.2023.07.008

Tremor Induced by Focal Peripheral Nerve Entrapment: A Case Series

2023· article· en· W4386171340 on OpenAlexaff
Bianief Tchiloemba, Min Cheol Chang, Benjamin Ferembach, Elisabet Hagert, Jean Paul Brutus

Bibliographic record

VenueJournal of Hand Surgery Global Online · 2023
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicinePeripheralEntrapmentEntrapment NeuropathyUlnar nerveSurgeryPeripheral nerveNerve compression syndromePeripheral neuropathyCubital tunnel syndromeCubital tunnelAnesthesiaCarpal tunnel syndromeAnatomyInternal medicineElbow

Abstract

fetched live from OpenAlex

Little is known about tremors caused by peripheral nerve entrapment. We report two cases of tremors caused by peripheral nerve compressions. Two patients presented with intentional tremors combined with peripheral nerve compression symptoms on their affected hand. Based on the clinical findings and evaluations, the first patient was diagnosed with double-crush compression of the ulnar nerve at the cubital tunnel and Guyon canal, and the second patient was diagnosed with lacertus syndrome. The first patient underwent surgical release of the cubital tunnel and Guyon canal in two stages. The second patient underwent release of the lacertus fibrosus. At the 1-month follow-up after surgery, the tremors had completely resolved, and neurological symptoms improved. Peripheral nerve entrapment should be considered a potential cause of tremors in patients with tremors combined with symptoms of peripheral neuropathy. Surgical release can be curative.

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)0.002
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: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.036
GPT teacher head0.301
Teacher spread0.266 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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