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Record W4401007515 · doi:10.1016/j.xops.2024.100577

Retinal Microstructural Changes Reflecting Treatment-Associated Cognitive Dysfunction in Patients with Lower-Grade Gliomas

2024· article· en· W4401007515 on OpenAlexaboutno aff
Arina Nisanova, Ashutosh Parajuli, Bhavna Antony, Orwa Aboud, Jinger Sun, Megan E. Daly, Rubén Fragoso, Glenn Yiu, Yin Liu

Bibliographic record

VenueOphthalmology Science · 2024
Typearticle
Languageen
FieldMedicine
TopicCancer-related cognitive impairment studies
Canadian institutionsnot available
FundersNational Eye InstituteUniversity of California Davis School of MedicineUniversity of California, Davis
KeywordsMedicineRetinalMontreal Cognitive AssessmentOphthalmologyGliomaVisual acuityNerve fiber layerApolipoprotein EInternal medicineCognitive impairment

Abstract

fetched live from OpenAlex

Purpose To determine whether microstructural retinal changes, tumor features, and Apolipoprotein E (APOE) ε4 polymorphism are correlated with clinically detectable treatment-associated cognitive dysfunction (TACD) in patients with lower-grade gliomas. Design Cohort study. Participants and Controls Sixteen lower-grade glioma patients at a U.S. academic Ophthalmology department between January 2021 and November 2023. Normal controls were recruited from convenient sampling. Methods Montreal Cognitive Assessment (MoCA) scores and retinal changes were assessed in 6-months intervals. APOE genotyping was performed, and tumor details were recorded. Partial least-squares discriminant (PLSD) model was established to evaluate the association between TACD with APOE genotype, ophthalmic, and tumor features. Main Outcome Measures The main outcome measure was cognitive status as measured by the MoCA score and analyzed in relation to ophthalmic measurements, tumor features, and APOE genotype. Results Median time to first eye exam was 34 months (2–266) from tumor diagnosis and 23 months (0–246) from radiation. Nine patients (56%) had abnormal cognition (MoCA <26/30). MoCA scores were significantly worse in patients with temporal (22±7.2) than frontal lobe tumors (26±3.1, p =0.02) and those with oligodendrogliomas (22±4.1) than astrocytomas (26±3.6, =0.02). Patients with TACD had significant radial peripapillary capillary density loss (45%±4.6) compared to those with normal cognition (49%±2.6, p =0.02). A PLSD model correlated MoCA scores with retinal nerve fiber thickness, intraocular pressure, foveal avascular zone, best-corrected visual acuity, months since first diagnosis, and tumor pathology (oligodendroglioma or not). Using these features, the model identified patients with TACD with 77% accuracy. APOE genotyping showed: two ε2/ε3 (13%), ten ε3/ε3 (63%) , and one ε3/ε4 (6%). Conclusion Retinal microstructural changes may serve as biomarkers for TACD in patients with lower-grade gliomas. Temporal lobe tumors and oligodendrogliomas may increase susceptibility to TACD. Utilization of retinal markers may enhance TACD diagnosis, progression monitoring, and inform management of lower-grade glioma patients. A larger study with serial eye exams is warranted to evaluate the role of APOE ε 4 and develop a predictive model.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.028
GPT teacher head0.334
Teacher spread0.306 · 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 designObservational
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

Citations1
Published2024
Admission routes1
Has abstractyes

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