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A case of end-stage renal disease initially manifested with visual loss caused by uremic optic neuropathy

2011· article· en· W1821724580 on OpenAlexvenueno aff
Jong Woo Seo, Dae‐Hong Jeon, Yeo‐Jin Kang, Dong Won Lee, Hyeon Jeong Lee, Woong Sun Yoo, Hyun‐Jung Kim, Se‐Ho Chang, Dong Jun Park

Bibliographic record

VenueHemodialysis International · 2011
Typearticle
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHemodialysisUremiaAzotemiaOptic nerveOptic neuropathyEnd stage renal diseaseKidney diseaseNephrologySurgeryVisual acuityOphthalmologyInternal medicineRenal function

Abstract

fetched live from OpenAlex

Uremic optic neuropathy (UON) is extremely rare, although sporadic cases have been reported. UON is sometimes regarded as a manifestation of uremic neuropathy. Here, we report a case of end-stage renal disease presenting as UON. A 22-year-old male was transferred to our nephrology department due to azotemia. Sudden deterioration of his vision occurred 3 days before his transfer. The patient's blood pressure was 150/90 mmHg, and he had no symptoms or signs of uremia, except for the visual disturbance. Blood tests showed an elevated serum creatinine of 6.0 mg/dL and serum BUN of 53.6 mg/dL. Both kidneys were decreased in size on ultrasound. His best-corrected vision was 20/62.5 in both the eyes. Ophthalmoscopy revealed hyperemia, swelling of both optic nerve heads, and blurred margins of both optic disks. These findings are compatible with UON. The patient's visual acuity and visual field improved following hemodialysis and corticosteroid treatment. The swelling of the patient's optic disks was also resolved. The patient is currently undergoing hemodialysis with the goal of vision restoration. Uremic optic neuropathy should be considered when patients with advanced chronic kidney disease complain of deterioration of their vision.

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)0.003
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 score0.004
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.024
GPT teacher head0.285
Teacher spread0.261 · 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

Citations9
Published2011
Admission routes1
Has abstractyes

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