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Vitreoretinal Lymphoma

2013· article· en· W2168497916 on OpenAlexaffabout
Steve D. Levasseur, Leah A. Wittenberg, Valerie A. White

Bibliographic record

VenueJAMA Ophthalmology · 2013
Typearticle
Languageen
FieldMedicine
TopicCNS Lymphoma Diagnosis and Treatment
Canadian institutionsVancouver General HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineVitrectomyIncidence (geometry)LymphomaRetrospective cohort studyCohortIntraocular lymphomaSurgeryInternal medicineVisual acuity

Abstract

fetched live from OpenAlex

OBJECTIVES: To determine the incidence and clinical and cytologic diagnostic accuracy of vitreoretinal lymphoma (VRL) and to evaluate its clinical features, management, and outcomes in a cohort of patients who underwent diagnostic vitrectomy. METHODS: Retrospective medical record review of 463 diagnostic vitrectomy specimens from 430 patients collected from October 1, 1990, through December 31, 2010, from Vancouver General Hospital and the British Columbia Cancer Agency. RESULTS: A total of 22 patients were diagnosed as having VRL with a preoperative clinical diagnostic sensitivity of 77%, specificity of 73%, positive predictive value of 13%, and negative predictive value of 98%. The cytologic diagnostic sensitivity was 87% (27 of 31 specimens). The incidence of VRL in British Columbia doubled from 1990 to 2010, with a final incidence of 0.047 cases per 100 000 people per year. The mean age at diagnosis was 66 years. Seventeen patients (77%) were women. The initial diagnosis of lymphoma was VRL in 19 patients (86%), of whom 7 (37%) had concurrent central nervous system lymphoma. Recurrent disease was found in 11 patients. Large B-cell lymphoma was diagnosed in 20 patients (91%). The median progression-free survival was 11 months, and the median survival was 33 months from the initial diagnosis. CONCLUSIONS: Vitreoretinal lymphoma remains a clinical diagnostic challenge. Early clinical suspicion with subsequent diagnostic vitrectomy for cytologic analysis and collaboration with the oncology department is critical to appropriate and prompt staging and treatment. More interdisciplinary studies are required to further characterize VRL and maximize the therapeutic options, thus improving the morbidity and mortality associated with the disease.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.272
Teacher spread0.257 · 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

Citations121
Published2013
Admission routes2
Has abstractyes

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