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Record W4405356165 · doi:10.1007/s40123-024-01061-3

Global Insights from Patients, Providers, and Staff on Challenges and Solutions in Managing Neovascular Age-Related Macular Degeneration

2024· article· en· W4405356165 on OpenAlexaff
Anat Loewenstein, Michelle Sylvanowicz, Winfried M. K. Amoaku, Tariq Aslam, Chui Ming Gemmy Cheung, Bora Eldem, Robert P. Finger, Richard P. Gale, Laurent Kodjikian, Adrian Koh, Jean‐François Korobelnik, Xiaofeng Lin, Paul Mitchell, Moira Murphy, Mali Okada, Ian Pearce, Francisco J. Rodríguez, J Stern, James Talks, David T. Wong, Tien Yin Wong, Focke Ziemssen, Jane Barratt

Bibliographic record

VenueOphthalmology and Therapy · 2024
Typearticle
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsInternational Federation on AgeingUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMacular degenerationMedicineAttendanceReimbursementFamily medicineHealth careOphthalmology

Abstract

fetched live from OpenAlex

INTRODUCTION: Neovascular age-related macular degeneration is a global public-health concern, associated with a considerable burden to individuals, healthcare systems, and society. The objective of this study was to understand different perspectives on the challenges associated with the clinical management of neovascular age-related macular degeneration, which could elucidate measures to comprehensively improve clinical care and outcomes. METHODS: A survey was carried out of patients with neovascular age-related macular degeneration, their providers, and clinic staff in 77 clinics across 24 countries on six continents, from a diverse range of healthcare systems, settings, and reimbursement models. Surveys comprised a series of single/multiple-response questions completed anonymously. Data gathered included patient personal characteristics, appointment attendance challenges, treatment experiences, and opportunities to improve support. Provider and clinic staff surveys asked similar questions about their perspectives; clinic characteristics were also captured. RESULTS: There were 6425 responses; 4558 patients with neovascular age-related macular degeneration, 659 providers, and 1208 clinic staff. Challenges identified included concern about patient burden to family/friends, high frequency of treatment, difficulties in traveling to appointments, long waiting times, and insufficient comprehension of neovascular age-related macular degeneration. Participants identified logistical (improved financial assistance with treatment and out-of-pocket costs, and appointment reminders), operational (addressing clinic set up to reduce waiting times and improving the amount of time providers spend with patients), and educational (improving quality and provision of patient information and expectation-setting) opportunities to improve care. CONCLUSIONS: The wealth of data generated by this global survey highlights the breadth of challenges associated with clinical management of patients with neovascular age-related macular degeneration. Addressing the opportunities raised could improve patient adherence to treatment and potentially outcomes, reduce appointment burden, and increase clinic capacity.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.708
Threshold uncertainty score0.360

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.026
GPT teacher head0.277
Teacher spread0.252 · 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 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

Citations7
Published2024
Admission routes1
Has abstractyes

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