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Record W3165187115 · doi:10.1007/s40123-021-00352-3

Seeing Beyond Anatomy: Quality of Life with Geographic Atrophy

2021· article· en· W3165187115 on OpenAlexaff
Dolores Caswell, William Caswell, Jill Carlton

Bibliographic record

VenueOphthalmology and Therapy · 2021
Typearticle
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsCARE CanadaCanadian Patient Safety InstituteCNIB Foundation
FundersBoehringer Ingelheim
KeywordsQuality of life (healthcare)MedicineGeographic atrophyQualitative researchQuality (philosophy)DiseaseBlindnessGerontologyPsychologyInternet privacyMacular degenerationNursingOptometryPathologyPsychiatrySociologyComputer science

Abstract

fetched live from OpenAlex

Quality of life (QoL) is a complex idea without a clear consensus definition. Generally speaking, QoL refers to several subjective measures of wellbeing that vary by individual and circumstance. QoL can decline noticeably as a disease progresses. This is particularly true for geographic atrophy (GA), an advanced form of age-related macular degeneration. GA leads to vision loss for which there is no currently approved pharmacological treatment. There is a lack of qualitative, patient-driven research on QoL in GA. There is also limited information available to both patients and physicians about GA, existing support groups and available assistive technologies. To address this, we have collated the experiences of a person with GA and those of her partner and carer with the current literature on QoL in GA. We have also outlined some of the wide range of developing technologies available to help people with GA carry out daily tasks and hobbies. It is clear that support, whether through informal or structured care, is vital to the wellbeing of people with GA. Despite this, the general public are often unaware of care work, which may result in this integral role being undervalued and under acknowledged. Furthermore, it is apparent that the general public have fundamental misunderstandings around what vision loss entails and are unaware that blindness is a vast spectrum. This feeds into the seemingly paradoxical mix of isolation and dependence on others that often results from GA and vision loss. Through this qualitative examination of a patient’s experiences, we hope to inform and educate both patients and physicians about GA as well as precipitate discussion around the frameworks that should be in place to support both newly diagnosed and long-term patients with GA and other retinal diseases. Asking someone about their ‘quality of life’ is one way to understand their general wellbeing. Quality of life can mean different things to different people. For some people it may mean being able to do what they want to. For others it may include feelings such as happiness. Diseases that cause people to lose their vision can have a very big impact on quality of life. Geographic atrophy is an eye disease that leads to loss of vision and has no cure. In this article, Dolores, a person with geographic atrophy, Bill, her husband and carer, and Jill, a quality of life researcher, discuss how geographic atrophy can change quality of life. Vision loss often means that people are unable to keep up their hobbies and do daily tasks, like shopping or cooking. Learning to use smartphone apps and gadgets can help many people with their hobbies and tasks. Feeling alone also makes quality of life for people with geographic atrophy worse. The help and understanding of others—including friends, family and doctors—are very important. Treatment plans for patients with vision loss need to consider all parts of a patient’s life. Training for doctors should continue to emphasise that people with geographic atrophy are more than just eyes that cannot be treated.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.272

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 head0.331
Teacher spread0.305 · 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

Citations18
Published2021
Admission routes1
Has abstractyes

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