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Record W4414945371 · doi:10.1177/00912174251382653

Depression and Anxiety in Patients With Irreversible Vision Loss: Meta-Analysis and Systematic Review

2025· review· en· W4414945371 on OpenAlexafffund
Nirmit Shah, Edward Tran, Mohamed Aly, Vivian Phu, Ellie Laughlin, Monali S. Malvankar‐Mehta

Bibliographic record

VenueThe International Journal of Psychiatry in Medicine · 2025
Typereview
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsWestern University
FundersGlaucoma Research Society of Canada
KeywordsAnxietyDepression (economics)Quality of life (healthcare)Mental healthLow visionVisual impairment

Abstract

fetched live from OpenAlex

ObjectiveApproximately 295 million individuals globally live with moderate to severe irreversible vision loss, primarily due to conditions such as glaucoma, diabetic retinopathy, and age-related macular degeneration (AMD). Vision impairment diminishes quality of life leading to higher rates of depression and anxiety. This study investigated the prevalence of anxiety and depression in patients with irreversible vision loss, with a comparative analysis across the conditions of AMD, diabetic retinopathy, and glaucoma.MethodsA comprehensive literature search was conducted in Medline, Embase, CINAHL, and Cochrane databases, supplemented by manual searches of conference literature.ResultsThe prevalence of depression in patients with irreversible vision loss was found to be 21% (95% CI: 0.17-0.26) among 76 561 patients, with variations based on the cause: 27% (95% CI: 0.19-0.35) in AMD, 48% (95% CI: 0.32-0.64) in diabetic retinopathy, and 23% (95% CI: 0.16-0.29) in glaucoma. Anxiety prevalence was 22% (95% CI: 0.15-0.30) among 25 616 patients.ConclusionThe high prevalence of depression and anxiety underscores the need for comprehensive healthcare approaches that incorporate mental health support, including vision rehabilitation, psychotherapy, pharmacological interventions, and lifestyle modifications. Future research should explore factors that protect against anxiety and depression, as well as address the long-term effects of vision loss treatments on mental health outcomes.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.305
Threshold uncertainty score0.452

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
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)0.0000.000

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 head0.020
GPT teacher head0.369
Teacher spread0.349 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations4
Published2025
Admission routes2
Has abstractyes

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