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Record W1995693659 · doi:10.1097/icb.0b013e3181babe5c

BRACHIAL PLEXUS NEUROPATHY SECONDARY TO POSTOPERATIVE PRONE POSITIONING FOR MACULAR HOLE SURGERY

2010· article· en· W1995693659 on OpenAlexaff
Delan Jinapriya, Jeffrey Gale

Bibliographic record

VenueRetinal Cases & Brief Reports · 2010
Typearticle
Languageen
FieldMedicine
TopicRetinal and Macular Surgery
Canadian institutionsKingston Health Sciences CentreQueen's University
Fundersnot available
KeywordsMedicineBrachial plexusProne positionWeaknessSurgeryPlexusBrachial plexus injury

Abstract

fetched live from OpenAlex

In Brief Purpose: To report a case of unilateral brachial plexus neuropathy after prone positioning for macular hole repair. Methods: Case report. Results: After 7 days of strict prone positioning post-macular hole surgery, a 60-year-old patient developed severe pain and weakness in the left arm. Neurologic examination, imaging, and electromyography showed that the patient developed a unilateral brachial plexus neuropathy. Her strength and pain quickly improved after hospitalization and treatment with intravenous solumedrol, pain control, and physiotherapy. Her best-corrected vision improved from 20/400 to 20/40, however, she was left with frozen shoulder syndrome. Conclusion: After macular hole surgery, prone positioning with persistent abduction of the shoulder such that the patient's hands rest above the head may put patients at risk for a brachial plexus neuropathy. However, this risk may be minimized by the use of positioning assistive devices, reducing the duration in the prone position, instituting frequent breaks, and warning patients to look for signs of neuropathy. After macular hole surgery, prone positioning with persistent abduction of the shoulder such that the patient's hands rest above the head may put patients at risk for a brachial plexus neuropathy. However, this risk may be minimized by the use of positioning assistive devices, reducing the duration in the prone position, instituting frequent breaks, and warning patients to look for signs of neuropathy.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.495
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.275
Teacher spread0.259 · 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.

Study designBench or experimental
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

Citations0
Published2010
Admission routes1
Has abstractyes

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