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Record W2580114867 · doi:10.6002/ect.2016.0053

Liver Transplant Can Resolve Severe Neuropsychiatric Manifestations of Wilson Disease: A Case Report.

2016· paratext· en· W2580114867 on OpenAlexaff
Gregory Walker, Trana Hussaini, Robert Stowe, Silke Appel‐Cresswell, Eric M. Yoshida

Bibliographic record

VenueExperimental and Clinical Transplantation · 2016
Typeparatext
Languageen
FieldNursing
TopicTrace Elements in Health
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineDysarthriaContraindicationSurgeryPediatricsPsychiatry

Abstract

fetched live from OpenAlex

Although liver transplant for decompensated cirrhosis secondary to Wilson disease is well accepted, the use of transplant for patients with severe neurologic manifestations of this condition remains controversial, and these can be perceived as a contraindication. Here, we describe a 45-year-old woman who presented with an incidental hepatocellular carcinoma at the time of transplant. The patient had severe neurologic manifestations of Wilson disease pretransplant, including dysarthria, hyperreflexia, asymmetrical ataxia, tremor, bradyphrenia, and shuffling gait. She underwent successful transplant from a hepatic and surgical standpoint, but her postoperative course was marked by protracted mutism, hypophonia, and fluctuating akinesia and immobility that did not respond promptly to withdrawal of calcineurin inhibitors or pramipexole but did respond robustly to amantadine. At 9 months posttransplant, there was marked neurologic improvement, and, at 18 months, she exhibited subtle memory and organizational difficulties but was fully ambulatory and otherwise completely functional. Our experience suggests that even patients with severe neurologic Wilson disease may recover after transplant, albeit slowly, demonstrating the need for a multidisciplinary approach, including pre- and posttransplant neurologic and neuropsychiatric consultations.

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 categoriesMeta-epidemiology (narrow)
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 score0.129
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.036
GPT teacher head0.378
Teacher spread0.342 · 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 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

Citations8
Published2016
Admission routes1
Has abstractyes

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